<table><caption>**Table 5**

Galactic Pulsars Colocated with LAT Sources</caption><thead><tr><th>PSR</th><th>4FGL</th><th>P (ms)</th><th>10<sup>-33</sup> Ė (erg s<sup>-1</sup>)</th><th>Dist (kpc)</th><th>ε = L<sub>γ</sub>/Ė</th><th>E<sub>peak</sub> (GeV)</th><th>f = Δθ/r<sub>95</sub></th><th>Association</th></tr></thead><tbody><tr><td>J0301+35*</td><td>J0300.4+3450</td><td>147.06</td><td>...</td><td>3.1</td><td></td><td>0.12</td><td>1.19</td><td></td></tr><tr><td>J0921-5202</td><td>J0924.1-5202c</td><td>9.68</td><td>0.734</td><td>0.4</td><td>0.51</td><td></td><td>0.66</td><td></td></tr><tr><td>J1054-5943*</td><td>J1054.0-5938</td><td>346.91</td><td>3.85</td><td>2.6</td><td>2.31</td><td>1.97</td><td>0.77</td><td></td></tr><tr><td>J1146-6610</td><td>J1147.7-6618</td><td>3.72</td><td>6.09</td><td>1.8</td><td>0.73</td><td>0.56</td><td>1.00</td><td></td></tr><tr><td>J1154-6250*</td><td>J1155.6-6245c</td><td>282.01</td><td>0.984</td><td>1.4</td><td>7.57</td><td>0.60</td><td>0.75</td><td>SNR G296.8-00.3</td></tr><tr><td>J1302-6350 V</td><td>J1302.9-6349</td><td>47.76</td><td>826.0</td><td>2.6</td><td>0.01</td><td>55.53</td><td>0.32</td><td>PSR B1259-63</td></tr><tr><td>J1306-4035*</td><td>J1306.8-4035</td><td>2.20</td><td>...</td><td>4.7</td><td></td><td>0.10</td><td>0.45</td><td>sic</td></tr><tr><td>J1332-03 *V</td><td>J1331.7-0343</td><td>1106.40</td><td>...</td><td>3.5</td><td></td><td>0.69</td><td>1.06</td><td>PKS 1328-034</td></tr><tr><td>J1430-6623</td><td>J1431.5-6627</td><td>785.44</td><td>0.226</td><td>1.3</td><td>8.44</td><td>0.47</td><td>0.78</td><td></td></tr><tr><td>J1439-5501</td><td>J1440.2-5505</td><td>28.64</td><td>0.235</td><td>0.7</td><td>3.01</td><td>0.31</td><td>0.35</td><td>sic</td></tr><tr><td>J1455-59</td><td>J1456.4-5923c</td><td>176.20</td><td>58.5</td><td>6.7</td><td>3.87</td><td></td><td>0.81</td><td>1RXS J145540.4-591320</td></tr><tr><td>J1535-5848*</td><td>J1534.7-5842</td><td>307.18</td><td>3.70</td><td>3.0</td><td>2.61</td><td>3.90</td><td>1.08</td><td></td></tr><tr><td>J1545-4550</td><td>J1545.2-4553</td><td>3.58</td><td>45.3</td><td>2.2</td><td>0.15</td><td>0.56</td><td>1.19</td><td></td></tr><tr><td>J1550-5418*</td><td>J1550.8-5424c</td><td>2069.83</td><td>103.0</td><td>4.0</td><td>0.46</td><td>1.38</td><td>0.89</td><td>SNR G327.2-00.1</td></tr><tr><td>J1604-44 *V</td><td>J1604.5-4441</td><td>1389.20</td><td>...</td><td>7.8</td><td></td><td></td><td>0.96</td><td>PMN J1604-4441</td></tr><tr><td>J1616-5017</td><td>J1616.6-5009</td><td>491.38</td><td>15.5</td><td>3.5</td><td>6.89</td><td>0.78</td><td>0.82</td><td></td></tr><tr><td>J1632-4818</td><td>J1631.7-4826c</td><td>813.68</td><td>47.6</td><td>5.3</td><td>4.22</td><td></td><td>1.18</td><td></td></tr><tr><td>J1731-1847</td><td>J1731.7-1850</td><td>2.34</td><td>77.8</td><td>4.8</td><td>0.57</td><td>0.65</td><td>0.81</td><td>sic</td></tr><tr><td>J1741-34*</td><td>J1740.6-3430</td><td>875.14</td><td>...</td><td>4.6</td><td></td><td>0.01</td><td>1.08</td><td></td></tr><tr><td>J1743-3153</td><td>J1743.0-3201</td><td>193.11</td><td>57.9</td><td>8.8</td><td>4.37</td><td>0.81</td><td>1.05</td><td></td></tr><tr><td>J1743-35*</td><td>J1743.9-3539</td><td>569.98</td><td>...</td><td>4.0</td><td></td><td>0.71</td><td>0.37</td><td></td></tr><tr><td>J1801-1417</td><td>J1801.6-1418</td><td>3.62</td><td>4.29</td><td>1.1</td><td>0.75</td><td>0.51</td><td>0.27</td><td>sic</td></tr><tr><td>J1806+2819</td><td>J1807.1+2822</td><td>15.08</td><td>0.431</td><td>1.3</td><td>3.59</td><td></td><td>0.83</td><td>sic</td></tr><tr><td>J1811-1925</td><td>J1811.5-1925</td><td>64.71</td><td>6334.0</td><td>5.0</td><td>0.01</td><td>8.94</td><td>0.26</td><td>sic</td></tr><tr><td>J1813-08*</td><td>J1812.2-0856</td><td>4.23</td><td>...</td><td>3.3</td><td></td><td>0.47</td><td>0.68</td><td></td></tr><tr><td>J1838-0549</td><td>J1838.4-0545</td><td>235.31</td><td>101.0</td><td>4.1</td><td>1.40</td><td>1.33</td><td>1.02</td><td></td></tr><tr><td>J1850-0026</td><td>J1850.3-0031</td><td>166.64</td><td>333.0</td><td>6.7</td><td>0.91</td><td>0.87</td><td>0.57</td><td>SNR G032.4+00.1</td></tr><tr><td>J1852+0158g*</td><td>J1852.6+0203</td><td>185.73</td><td>...</td><td>7.6</td><td></td><td>0.42</td><td>1.13</td><td></td></tr><tr><td>J1852-0002g*</td><td>J1851.8-0007c</td><td>245.10</td><td>...</td><td>5.6</td><td></td><td>0.80</td><td>0.49</td><td>SNR G032.8-00.1</td></tr><tr><td>J1855+0455g*</td><td>J1855.2+0456</td><td>101.01</td><td>...</td><td>10.2</td><td></td><td>0.00</td><td>0.25</td><td></td></tr><tr><td>J1858+0310g*</td><td>J1857.9+0313c</td><td>372.75</td><td>...</td><td>6.7</td><td></td><td>0.66</td><td>0.77</td><td>LQAC 284+003</td></tr><tr><td>J1859+0126g*</td><td>J1900.8+0118</td><td>957.70</td><td>...</td><td>9.6</td><td></td><td>0.60</td><td>1.20</td><td>NVSS J190146+011301</td></tr><tr><td>J1904+0603g*</td><td>J1904.7+0615</td><td>1974.93</td><td>...</td><td>6.1</td><td></td><td>0.66</td><td>0.72</td><td></td></tr><tr><td>J1906+0646g*</td><td>J1906.2+0631</td><td>355.52</td><td>...</td><td>5.3</td><td></td><td>0.65</td><td>0.80</td><td>SNR G040.5-00.5</td></tr><tr><td>J1907+0631</td><td>J1906.2+0631</td><td>323.65</td><td>526.0</td><td>3.4</td><td>0.11</td><td>0.65</td><td>0.66</td><td>SNR G040.5-00.5</td></tr><tr><td>J1908+0811g*</td><td>J1908.7+0812</td><td>181.64</td><td>...</td><td>5.6</td><td></td><td>0.58</td><td>0.36</td><td></td></tr><tr><td>J1911+1051</td><td>J1911.3+1055</td><td>190.87</td><td>69.1</td><td>10.1</td><td>5.02</td><td>0.57</td><td>0.43</td><td></td></tr><tr><td>J1915+1150</td><td>J1915.3+1149</td><td>100.04</td><td>539.0</td><td>14.0</td><td>3.15</td><td>0.63</td><td>0.25</td><td>TXS 1913+115</td></tr><tr><td>J1917+1121g*</td><td>J1916.3+1108</td><td>510.31</td><td>...</td><td>7.1</td><td></td><td>0.54</td><td>1.19</td><td>SNR G045.7-00.4</td></tr><tr><td>J1928+1725 V</td><td>J1929.0+1729</td><td>289.84</td><td>...</td><td>3.7</td><td></td><td>0.50</td><td>0.81</td><td></td></tr><tr><td>J1929+1731g *V</td><td>J1929.0+1729</td><td>3995.40</td><td>...</td><td>9.2</td><td></td><td>0.50</td><td>0.35</td><td></td></tr><tr><td>J1930+1852</td><td>J1930.5+1853</td><td>137.04</td><td>11528.0</td><td>7.0</td><td>0.01</td><td>10.46</td><td>0.57</td><td>PWN G54.1+0.3</td></tr><tr><td>J1950+2414</td><td>J1950.6+2416</td><td>4.30</td><td>9.29</td><td>7.3</td><td>17.09</td><td>0.70</td><td>0.25</td><td>sic</td></tr><tr><td>J1957+2516*</td><td>J1957.3+2517</td><td>3.96</td><td>17.4</td><td>2.7</td><td>0.61</td><td>1.03</td><td>0.46</td><td>sic</td></tr><tr><td>J2015+0756*</td><td>J2015.3+0758</td><td>4.33</td><td>...</td><td>2.1</td><td></td><td></td><td>0.91</td><td></td></tr><tr><td>J2051+4434g*</td><td>J2052.3+4437</td><td>1303.16</td><td>...</td><td>13.5</td><td></td><td>0.80</td><td>0.42</td><td></td></tr><tr><td>J2052+4421g*</td><td>J2052.3+4437</td><td>375.31</td><td>...</td><td>13.5</td><td></td><td>0.80</td><td>0.77</td><td></td></tr><tr><td>J2055+1545</td><td>J2055.8+1545</td><td>2.16</td><td>79.2</td><td>3.6</td><td>0.15</td><td>0.57</td><td>0.06</td><td>sic</td></tr><tr><td>J2327+62*</td><td>J2325.9+6206c</td><td>266.00</td><td>...</td><td>4.3</td><td></td><td></td><td>0.91</td><td>NVSS J232543+620829</td></tr></tbody></table>

Note. Colocation means that the pulsar is within $f = \Delta\theta/r_{95} < 1.2$ of a 4FGL-DR3 Source, and has efficiency $\epsilon=L_{\gamma}/E' < 10$, assuming the pulsar distance (73 matches were overluminous). For association classes “psr” or “msp,” we list the pulsar regardless of the efficiency. These pulsars show no gamma-ray pulsations, although many have not been gamma-ray folded, indicated by no $E'$ value or by * in the PSR column. $\Delta\theta$ is the angular separation between the pulsar and the source, and $r_{95}$ is the 95% confidence level semimajor axis of the LAT error ellipse. $E_{\text{peak}}$ is the peak of the 4FGL spectral energy distribution (SED) when the PLEC fit was reported in 4FGL-DR3. The last column lists the 4FGL-DR3 association for the LAT source; “sic” means that it matches the pulsar name. “V” indicates Variability Index > 24.7. Pulsars with a “g” suffix come from the FAST Galactic plane pulsar survey (GPPS; Han et al. 2021).

Radio telescope arrays can coherently combine data from multiple antennas to form tied array beams, which are typically much smaller than the primary beam. These also benefit from improved localization, since computational resources generally limit the number of synthesized beams that can be formed and searched.

### 3.2.2. Optical, X-Ray, and Radio Studies to Refine Targets

Fewer than 1% of known neutron stars pulse in the optical band, so optical observations of gamma-ray sources might seem unproductive. However, relative to pulsars discovered in radio surveys, the LAT pulsar sample includes many more
<table><caption>**Table 5**

Galactic Pulsars Colocated with LAT Sources</caption><thead><tr><th>PSR</th><th>4FGL</th><th>P (ms)</th><th>10<sup>-33</sup> Ė (erg s<sup>-1</sup>)</th><th>Dist (kpc)</th><th>ε = L<sub>γ</sub>/Ė</th><th>E<sub>peak</sub> (GeV)</th><th>f = Δθ/r<sub>95</sub></th><th>Association</th></tr></thead><tbody><tr><td>J0301+35*</td><td>J0300.4+3450</td><td>147.06</td><td>...</td><td>3.1</td><td></td><td>0.12</td><td>1.19</td><td></td></tr><tr><td>J0921-5202</td><td>J0924.1-5202c</td><td>9.68</td><td>0.734</td><td>0.4</td><td>0.51</td><td></td><td>0.66</td><td></td></tr><tr><td>J1054-5943*</td><td>J1054.0-5938</td><td>346.91</td><td>3.85</td><td>2.6</td><td>2.31</td><td>1.97</td><td>0.77</td><td></td></tr><tr><td>J1146-6610</td><td>J1147.7-6618</td><td>3.72</td><td>6.09</td><td>1.8</td><td>0.73</td><td>0.56</td><td>1.00</td><td></td></tr><tr><td>J1154-6250*</td><td>J1155.6-6245c</td><td>282.01</td><td>0.984</td><td>1.4</td><td>7.57</td><td>0.60</td><td>0.75</td><td>SNR G296.8-00.3</td></tr><tr><td>J1302-6350 V</td><td>J1302.9-6349</td><td>47.76</td><td>826.0</td><td>2.6</td><td>0.01</td><td>55.53</td><td>0.32</td><td>PSR B1259-63</td></tr><tr><td>J1306-4035*</td><td>J1306.8-4035</td><td>2.20</td><td>...</td><td>4.7</td><td></td><td>0.10</td><td>0.45</td><td>sic</td></tr><tr><td>J1332-03 *V</td><td>J1331.7-0343</td><td>1106.40</td><td>...</td><td>3.5</td><td></td><td>0.69</td><td>1.06</td><td>PKS 1328-034</td></tr><tr><td>J1430-6623</td><td>J1431.5-6627</td><td>785.44</td><td>0.226</td><td>1.3</td><td>8.44</td><td>0.47</td><td>0.78</td><td></td></tr><tr><td>J1439-5501</td><td>J1440.2-5505</td><td>28.64</td><td>0.235</td><td>0.7</td><td>3.01</td><td>0.31</td><td>0.35</td><td>sic</td></tr><tr><td>J1455-59</td><td>J1456.4-5923c</td><td>176.20</td><td>58.5</td><td>6.7</td><td>3.87</td><td></td><td>0.81</td><td>1RXS J145540.4-591320</td></tr><tr><td>J1535-5848*</td><td>J1534.7-5842</td><td>307.18</td><td>3.70</td><td>3.0</td><td>2.61</td><td>3.90</td><td>1.08</td><td></td></tr><tr><td>J1545-4550</td><td>J1545.2-4553</td><td>3.58</td><td>45.3</td><td>2.2</td><td>0.15</td><td>0.56</td><td>1.19</td><td></td></tr><tr><td>J1550-5418*</td><td>J1550.8-5424c</td><td>2069.83</td><td>103.0</td><td>4.0</td><td>0.46</td><td>1.38</td><td>0.89</td><td>SNR G327.2-00.1</td></tr><tr><td>J1604-44 *V</td><td>J1604.5-4441</td><td>1389.20</td><td>...</td><td>7.8</td><td></td><td></td><td>0.96</td><td>PMN J1604-4441</td></tr><tr><td>J1616-5017</td><td>J1616.6-5009</td><td>491.38</td><td>15.5</td><td>3.5</td><td>6.89</td><td>0.78</td><td>0.82</td><td></td></tr><tr><td>J1632-4818</td><td>J1631.7-4826c</td><td>813.68</td><td>47.6</td><td>5.3</td><td>4.22</td><td></td><td>1.18</td><td></td></tr><tr><td>J1731-1847</td><td>J1731.7-1850</td><td>2.34</td><td>77.8</td><td>4.8</td><td>0.57</td><td>0.65</td><td>0.81</td><td>sic</td></tr><tr><td>J1741-34*</td><td>J1740.6-3430</td><td>875.14</td><td>...</td><td>4.6</td><td></td><td>0.01</td><td>1.08</td><td></td></tr><tr><td>J1743-3153</td><td>J1743.0-3201</td><td>193.11</td><td>57.9</td><td>8.8</td><td>4.37</td><td>0.81</td><td>1.05</td><td></td></tr><tr><td>J1743-35*</td><td>J1743.9-3539</td><td>569.98</td><td>...</td><td>4.0</td><td></td><td>0.71</td><td>0.37</td><td></td></tr><tr><td>J1801-1417</td><td>J1801.6-1418</td><td>3.62</td><td>4.29</td><td>1.1</td><td>0.75</td><td>0.51</td><td>0.27</td><td>sic</td></tr><tr><td>J1806+2819</td><td>J1807.1+2822</td><td>15.08</td><td>0.431</td><td>1.3</td><td>3.59</td><td></td><td>0.83</td><td>sic</td></tr><tr><td>J1811-1925</td><td>J1811.5-1925</td><td>64.71</td><td>6334.0</td><td>5.0</td><td>0.01</td><td>8.94</td><td>0.26</td><td>sic</td></tr><tr><td>J1813-08*</td><td>J1812.2-0856</td><td>4.23</td><td>...</td><td>3.3</td><td></td><td>0.47</td><td>0.68</td><td></td></tr><tr><td>J1838-0549</td><td>J1838.4-0545</td><td>235.31</td><td>101.0</td><td>4.1</td><td>1.40</td><td>1.33</td><td>1.02</td><td></td></tr><tr><td>J1850-0026</td><td>J1850.3-0031</td><td>166.64</td><td>333.0</td><td>6.7</td><td>0.91</td><td>0.87</td><td>0.57</td><td>SNR G032.4+00.1</td></tr><tr><td>J1852+0158g*</td><td>J1852.6+0203</td><td>185.73</td><td>...</td><td>7.6</td><td></td><td>0.42</td><td>1.13</td><td></td></tr><tr><td>J1852-0002g*</td><td>J1851.8-0007c</td><td>245.10</td><td>...</td><td>5.6</td><td></td><td>0.80</td><td>0.49</td><td>SNR G032.8-00.1</td></tr><tr><td>J1855+0455g*</td><td>J1855.2+0456</td><td>101.01</td><td>...</td><td>10.2</td><td></td><td>0.00</td><td>0.25</td><td></td></tr><tr><td>J1858+0310g*</td><td>J1857.9+0313c</td><td>372.75</td><td>...</td><td>6.7</td><td></td><td>0.66</td><td>0.77</td><td>LQAC 284+003</td></tr><tr><td>J1859+0126g*</td><td>J1900.8+0118</td><td>957.70</td><td>...</td><td>9.6</td><td></td><td>0.60</td><td>1.20</td><td>NVSS J190146+011301</td></tr><tr><td>J1904+0603g*</td><td>J1904.7+0615</td><td>1974.93</td><td>...</td><td>6.1</td><td></td><td>0.66</td><td>0.72</td><td></td></tr><tr><td>J1906+0646g*</td><td>J1906.2+0631</td><td>355.52</td><td>...</td><td>5.3</td><td></td><td>0.65</td><td>0.80</td><td>SNR G040.5-00.5</td></tr><tr><td>J1907+0631</td><td>J1906.2+0631</td><td>323.65</td><td>526.0</td><td>3.4</td><td>0.11</td><td>0.65</td><td>0.66</td><td>SNR G040.5-00.5</td></tr><tr><td>J1908+0811g*</td><td>J1908.7+0812</td><td>181.64</td><td>...</td><td>5.6</td><td></td><td>0.58</td><td>0.36</td><td></td></tr><tr><td>J1911+1051</td><td>J1911.3+1055</td><td>190.87</td><td>69.1</td><td>10.1</td><td>5.02</td><td>0.57</td><td>0.43</td><td></td></tr><tr><td>J1915+1150</td><td>J1915.3+1149</td><td>100.04</td><td>539.0</td><td>14.0</td><td>3.15</td><td>0.63</td><td>0.25</td><td>TXS 1913+115</td></tr><tr><td>J1917+1121g*</td><td>J1916.3+1108</td><td>510.31</td><td>...</td><td>7.1</td><td></td><td>0.54</td><td>1.19</td><td>SNR G045.7-00.4</td></tr><tr><td>J1928+1725 V</td><td>J1929.0+1729</td><td>289.84</td><td>...</td><td>3.7</td><td></td><td>0.50</td><td>0.81</td><td></td></tr><tr><td>J1929+1731g *V</td><td>J1929.0+1729</td><td>3995.40</td><td>...</td><td>9.2</td><td></td><td>0.50</td><td>0.35</td><td></td></tr><tr><td>J1930+1852</td><td>J1930.5+1853</td><td>137.04</td><td>11528.0</td><td>7.0</td><td>0.01</td><td>10.46</td><td>0.57</td><td>PWN G54.1+0.3</td></tr><tr><td>J1950+2414</td><td>J1950.6+2416</td><td>4.30</td><td>9.29</td><td>7.3</td><td>17.09</td><td>0.70</td><td>0.25</td><td>sic</td></tr><tr><td>J1957+2516*</td><td>J1957.3+2517</td><td>3.96</td><td>17.4</td><td>2.7</td><td>0.61</td><td>1.03</td><td>0.46</td><td>sic</td></tr><tr><td>J2015+0756*</td><td>J2015.3+0758</td><td>4.33</td><td>...</td><td>2.1</td><td></td><td></td><td>0.91</td><td></td></tr><tr><td>J2051+4434g*</td><td>J2052.3+4437</td><td>1303.16</td><td>...</td><td>13.5</td><td></td><td>0.80</td><td>0.42</td><td></td></tr><tr><td>J2052+4421g*</td><td>J2052.3+4437</td><td>375.31</td><td>...</td><td>13.5</td><td></td><td>0.80</td><td>0.77</td><td></td></tr><tr><td>J2055+1545</td><td>J2055.8+1545</td><td>2.16</td><td>79.2</td><td>3.6</td><td>0.15</td><td>0.57</td><td>0.06</td><td>sic</td></tr><tr><td>J2327+62*</td><td>J2325.9+6206c</td><td>266.00</td><td>...</td><td>4.3</td><td></td><td></td><td>0.91</td><td>NVSS J232543+620829</td></tr></tbody></table>

Note. Colocation means that the pulsar is within $f = \Delta\theta/r_{95} < 1.2$ of a 4FGL-DR3 Source, and has efficiency $\epsilon = L_{\gamma}/E' < 10$, assuming the pulsar distance (73 matches were overluminous). For association classes “psr” or “msp,” we list the pulsar regardless of the efficiency. These pulsars show no gamma-ray pulsations, although many have not been gamma-ray folded, indicated by no $E'$ value or by * in the PSR column. $\Delta\theta$ is the angular separation between the pulsar and the source, and $r_{95}$ is the 95% confidence level semimajor axis of the LAT error ellipse. $E_{\text{peak}}$ is the peak of the 4FGL spectral energy distribution (SED) when the PLEC fit was reported in 4FGL-DR3. The last column lists the 4FGL-DR3 association for the LAT source; “sic” means that it matches the pulsar name. “V” indicates Variability Index > 24.7. Pulsars with a “g” suffix come from the FAST Galactic plane pulsar survey (GPPS; Han et al. 2021).

Radio telescope arrays can coherently combine data from multiple antennas to form tied array beams, which are typically much smaller than the primary beam. These also benefit from improved localization, since computational resources generally limit the number of synthesized beams that can be formed and searched.

### 3.2.2. Optical, X-Ray, and Radio Studies to Refine Targets

Fewer than 1% of known neutron stars pulse in the optical band, so optical observations of gamma-ray sources might seem unproductive. However, relative to pulsars discovered in radio surveys, the LAT pulsar sample includes many more
members of the subclass of interacting binaries—black widows, rebacks, transitional MSPs, and related systems. The companions in these systems can have relatively bright optical magnitudes and (importantly) often exhibit modulation at the orbital period in brightness, color, and radial velocity. Consequently, searches for periodic optical sources within LAT source error regions have identified many candidate gamma-ray pulsars. Some of these have been followed up with radio detections, while others have enabled direct gamma-ray periodicity detections by using the precise position and orbital parameters to reduce the vast parameter space to be searched, as detailed in Section 3.4. Others remain strong candidates that are likely powering the gamma-ray sources, but have yet to be confirmed as pulsars (see Section 7). Some examples of the power of optical studies of LAT source regions include:

1. Optical and X-ray studies strongly indicated that 1FGL J2339.7-0531 hosts a black-widow MSP (Romani & Shaw 2011; Kong et al. 2012). After LAT blind searches found no pulsar, Ray et al. (2020) discovered radio pulsations. PSR J2339-0533 turned out to be a reback with a companion mass outside the parameter space covered by the LAT searches. The resulting ephemeris yielded gamma-ray pulsations as well (Pletsch & Clark 2015).

2. Optical studies by Romani (2012) led to the first discovery of an MSP, PSR J1311-3430, in a blind search of LAT data (Pletsch et al. 2012c). Detection of radio pulsations followed shortly (Ray et al. 2013). Two further binary MSPs have been discovered in this way: the black-widow PSR J1653-0158 (Nieder et al. 2020a) from an optical candidate discovered by Romani et al. (2014) and Kong et al. (2014), and the reback PSR J2039-5617 (Clark et al. 2021) from an optical candidate discovered by Romani (2015) and Salvetti et al. (2015).

3. Four candidate gamma-ray rebacks identified in optical and X-ray searches were recently identified as radio MSPs by TRAPUM (Halpern et al. 2017; Li et al. 2018b; Swihart et al. 2020; Au et al. 2023), listed in Table 6.

4. Optical studies of an unidentified LAT source by Strader et al. (2015) revealed an accretion disk in a binary system with a 5.4 day period. Camilo et al. (2016) subsequently discovered PSR J1417-4402 using the Parkes radio telescope. First thought to be a reback, its orbit is wide, and the wind interactions differ from other spiders. Swihart et al. (2018) argued that it is a possible progenitor of normal field MSP binaries and dubbed it the “huntman,” as the archetype of an emerging class. Unfortunately, it is difficult to time, and a phase-connected ephemeris that would yield gamma-ray pulsations is not anticipated soon.

Neutron stars can also power X-ray emission either directly from their surfaces or magnetospheres, or via shock emission when the pulsar wind interacts with a companion or the interstellar medium (Gentile et al. 2014; Marelli et al. 2015; Coti Zelati et al. 2020). The nonthermal shock spectra, sometimes modulated at the orbital period, provide strong signatures. Consequently, X-ray surveys also provide valuable information as demonstrated by varied studies of the error ellipses of unidentified LAT sources. For example, the Swift XRT systematically studied a large number of LAT

unassociated source regions.<fnref n="116" /> This data set has been mined using machine-learning techniques to identify promising pulsar candidates for radio follow-up (Kaur et al. 2019; Kerby et al. 2021).

Pulsars are steep-spectrum radio point sources (Jankowski et al. 2018). This was used to identify the source (4C 21.53) that was later found to be the first millisecond pulsar (PSR B1937+21; Backer et al. 1982). The availability of radio surveys covering nearly the whole sky was recently harnessed to look for pulsar candidates associated with LAT source regions (Frail et al. 2016, 2018; Bruzewski et al. 2021; Ray et al. 2022). These candidate lists have high-precision positions from radio interferometric imaging and well-measured fluxes, enabling both gamma-ray blind searches with reduced parameter spaces and radio pulsation searches that discovered several new MSPs.

### 3.3. Targeted Radio Searches

Shortly after LAT operations began, the Fermi Pulsar Search Consortium (PSC) was organized, bringing together the LAT team and many international collaborators with pulsar searching expertise and access to the world's largest radio telescopes (Ray et al. 2012). The aim was to coordinate radio pulsation searches of LAT sources, and to see which pulsars found in gamma-ray blind searches are truly radio-quiet. The PSC has been exceptionally successful at efficiently discovering MSPs in searches of LAT sources. Beginning in 2010, the TRAPUM collaboration formed to exploit MeerKAT (Stappers & Kramer 2016). It is not formally part of the PSC but includes searches of LAT sources. The FAST radio telescope in China also joined the searches under a separate arrangement. Radio astronomers are provided with early access to LAT source lists as well as the parameters of new pulsars discovered in gamma-ray blind searches (see Section 3.4).

LAT gamma-ray source localizations are much better than was possible with EGRET, making it often possible to search an entire 95% confidence error region with a single radio telescope pointing. Of course, the primary beam of a radio telescope depends on the observation frequency and the dish diameter. Thus, radio astronomers could choose telescope/ frequency combinations optimized for the error regions being searched. Initially, the telescopes were all single-dish (Green Bank Telescope, GBT, Parkes, Effelsberg, Nançay Radio Telescope, NRT, Arecibo Telescope, and the Lovell Telescope at Jodrell Bank), but array telescopes were soon added, the first being the Giant Metrewave Radio Telescope (GMRT), followed by LOFAR and MeerKAT (see Table 4).

Array-based telescopes offer increasingly powerful and flexible methods for pulsar searches. Incoherently combining the beams allows for very efficient but less sensitive searches of large error boxes. Some modern arrays have backends powerful enough to search hundreds of coherent (tied-array) beams arranged to cover a large primary beam, enabling extremely efficient full sensitivity searches of large error boxes (Clark et al. 2023a). Gated imaging (Roy & Bhattacharyya 2013) or tied-array beamforming (Stappers & Kramer 2016; Sanidas et al. 2019) can localize newly discovered pulsars extremely well, without the need for long-term timing campaigns.

A key feature of radio pulsar searches, compared to LAT blind searches, is that it is computationally feasible to maintain

<footnote n="116">¹¹⁶ https://www.swift.psu.edu/unassociated/</footnote>
members of the subclass of interacting binaries—black widows, rebacks, transitional MSPs, and related systems. The companions in these systems can have relatively bright optical magnitudes and (importantly) often exhibit modulation at the orbital period in brightness, color, and radial velocity. Consequently, searches for periodic optical sources within LAT source error regions have identified many candidate gamma-ray pulsars. Some of these have been followed up with radio detections, while others have enabled direct gamma-ray periodicity detections by using the precise position and orbital parameters to reduce the vast parameter space to be searched, as detailed in Section 3.4. Others remain strong candidates that are likely powering the gamma-ray sources, but have yet to be confirmed as pulsars (see Section 7). Some examples of the power of optical studies of LAT source regions include:

1. Optical and X-ray studies strongly indicated that 1FGL J2339.7-0531 hosts a black-widow MSP (Romani & Shaw 2011; Kong et al. 2012). After LAT blind searches found no pulsar, Ray et al. (2020) discovered radio pulsations. PSR J2339-0533 turned out to be a redback with a companion mass outside the parameter space covered by the LAT searches. The resulting ephemeris yielded gamma-ray pulsations as well (Pletsch & Clark 2015).

2. Optical studies by Romani (2012) led to the first discovery of an MSP, PSR J1311-3430, in a blind search of LAT data (Pletsch et al. 2012c). Detection of radio pulsations followed shortly (Ray et al. 2013). Two further binary MSPs have been discovered in this way: the black-widow PSR J1653-0158 (Nieder et al. 2020a) from an optical candidate discovered by Romani et al. (2014) and Kong et al. (2014), and the redback PSR J2039-5617 (Clark et al. 2021) from an optical candidate discovered by Romani (2015) and Salvetti et al. (2015).

3. Four candidate gamma-ray rebacks identified in optical and X-ray searches were recently identified as radio MSPs by TRAPUM (Halpern et al. 2017; Li et al. 2018b; Swihart et al. 2020; Au et al. 2023), listed in Table 6.

4. Optical studies of an unidentified LAT source by Strader et al. (2015) revealed an accretion disk in a binary system with a 5.4 day period. Camilo et al. (2016) subsequently discovered PSR J1417-4402 using the Parkes radio telescope. First thought to be a redback, its orbit is wide, and the wind interactions differ from other spiders. Swihart et al. (2018) argued that it is a possible progenitor of normal field MSP binaries and dubbed it the “huntman,” as the archetype of an emerging class. Unfortunately, it is difficult to time, and a phase-connected ephemeris that would yield gamma-ray pulsations is not anticipated soon.

Neutron stars can also power X-ray emission either directly from their surfaces or magnetospheres, or via shock emission when the pulsar wind interacts with a companion or the interstellar medium (Gentile et al. 2014; Marelli et al. 2015; Coti Zelati et al. 2020). The nonthermal shock spectra, sometimes modulated at the orbital period, provide strong signatures. Consequently, X-ray surveys also provide valuable information as demonstrated by varied studies of the error ellipses of unidentified LAT sources. For example, the Swift XRT systematically studied a large number of LAT

unassociated source regions.<fnref n="116" /> This data set has been mined using machine-learning techniques to identify promising pulsar candidates for radio follow-up (Kaur et al. 2019; Kerby et al. 2021).

Pulsars are steep-spectrum radio point sources (Jankowski et al. 2018). This was used to identify the source (4C 21.53) that was later found to be the first millisecond pulsar (PSR B1937+21; Backer et al. 1982). The availability of radio surveys covering nearly the whole sky was recently harnessed to look for pulsar candidates associated with LAT source regions (Frail et al. 2016, 2018; Bruzewski et al. 2021; Ray et al. 2022). These candidate lists have high-precision positions from radio interferometric imaging and well-measured fluxes, enabling both gamma-ray blind searches with reduced parameter spaces and radio pulsation searches that discovered several new MSPs.

### 3.3. Targeted Radio Searches

Shortly after LAT operations began, the Fermi Pulsar Search Consortium (PSC) was organized, bringing together the LAT team and many international collaborators with pulsar searching expertise and access to the world's largest radio telescopes (Ray et al. 2012). The aim was to coordinate radio pulsation searches of LAT sources, and to see which pulsars found in gamma-ray blind searches are truly radio-quiet. The PSC has been exceptionally successful at efficiently discovering MSPs in searches of LAT sources. Beginning in 2010, the TRAPUM collaboration formed to exploit MeerKAT (Stappers & Kramer 2016). It is not formally part of the PSC but includes searches of LAT sources. The FAST radio telescope in China also joined the searches under a separate arrangement. Radio astronomers are provided with early access to LAT source lists as well as the parameters of new pulsars discovered in gamma-ray blind searches (see Section 3.4).

LAT gamma-ray source localizations are much better than was possible with EGRET, making it often possible to search an entire 95% confidence error region with a single radio telescope pointing. Of course, the primary beam of a radio telescope depends on the observation frequency and the dish diameter. Thus, radio astronomers could choose telescope/ frequency combinations optimized for the error regions being searched. Initially, the telescopes were all single-dish (Green Bank Telescope, GBT, Parkes, Effelsberg, Nançay Radio Telescope, NRT, Arecibo Telescope, and the Lovell Telescope at Jodrell Bank), but array telescopes were soon added, the first being the Giant Metrewave Radio Telescope (GMRT), followed by LOFAR and MeerKAT (see Table 4).

Array-based telescopes offer increasingly powerful and flexible methods for pulsar searches. Incoherently combining the beams allows for very efficient but less sensitive searches of large error boxes. Some modern arrays have backends powerful enough to search hundreds of coherent (tied-array) beams arranged to cover a large primary beam, enabling extremely efficient full sensitivity searches of large error boxes (Clark et al. 2023a). Gated imaging (Roy & Bhattacharyya 2013) or tied-array beamforming (Stappers & Kramer 2016; Sanidas et al. 2019) can localize newly discovered pulsars extremely well, without the need for long-term timing campaigns.

A key feature of radio pulsar searches, compared to LAT blind searches, is that it is computationally feasible to maintain

<footnote n="116">¹¹⁶ https://www.swift.psu.edu/unassociated/</footnote>
<table><caption>**Table 6**
Thirty-nine MSPs Discovered in Radio Searches of LAT Unidentified Sources, Yet to Show Gamma-Ray Pulsations</caption><thead><tr><th>PSR</th><th>4FGL</th><th>P<br>(ms)</th><th>Dist<br>(kpc)</th><th>10<sup>-33</sup>L<sub>γ</sub><br>(erg s<sup>-1</sup>)</th><th>Discovery</th><th>References</th></tr></thead><tbody><tr><td>J0329+50</td><td>J0330.1+5038</td><td>3.06</td><td>0.3</td><td>0.052</td><td>GBT 2019</td><td>Tabassum et al. (2021)</td></tr><tr><td>J0506+50</td><td>J0506.1+5028</td><td>3.39</td><td>1.4</td><td>0.510</td><td>FAST 2020</td><td>P. Wang et al. (2023, in preparation)</td></tr><tr><td>J0646-54</td><td>J0646.4-5455</td><td>2.51</td><td>0.4</td><td>0.039</td><td>PKS 2017</td><td>as in Camilo et al. (2015)</td></tr><tr><td>J0657-4657</td><td>J0657.4-4658</td><td>3.95</td><td>0.5</td><td>0.085</td><td>MKT 2022</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J0838-2827</td><td>J0838.7-2827</td><td>3.62</td><td>0.4</td><td>0.147</td><td>MKT 2021</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J0843+67</td><td>J0843.3+6712</td><td>2.84</td><td>1.6</td><td>1.13</td><td>GBT 2017</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1008-46</td><td>X<sup>a</sup></td><td>2.72</td><td>0.4</td><td>...</td><td>GMRT 2021</td><td>J. Roy et al. (2023, in preparation)</td></tr><tr><td>J1036-4353</td><td>J1036.6-4349</td><td>1.68</td><td>0.4</td><td>0.069</td><td>MKT 2021</td><td>Clark et al. (2023a)</td></tr><tr><td>J1102+02</td><td>J1102.4+0246</td><td>4.05</td><td>3.7</td><td>2.53</td><td>GBT 2019</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1103-5403</td><td>X</td><td>3.39</td><td>1.7</td><td>...</td><td>PKS 2009</td><td>Keith et al. (2011)</td></tr><tr><td>J1120-3618</td><td>X</td><td>5.55</td><td>1.0</td><td>...</td><td>GMRT 2011</td><td>Roy & Bhattacharyya (2013)</td></tr><tr><td>J1304+12</td><td>J1304.4+1203</td><td>4.18</td><td>1.4</td><td>0.442</td><td>AO 2017</td><td>Cromartie (2020)</td></tr><tr><td>J1346-2610</td><td>J1345.9-2612</td><td>2.77</td><td>1.2</td><td>0.452</td><td>MKT 2022</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J1356+0230</td><td>J1356.6+0234</td><td>2.83</td><td>1.8</td><td>0.757</td><td>MKT 2021</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J1417-4402</td><td>J1417.6-4403</td><td>2.66</td><td>4.4</td><td>18.4</td><td>PKS 2015</td><td>“Huntsman,” Swihart et al. (2018)</td></tr><tr><td>J1551-0658</td><td>X</td><td>7.09</td><td>1.3</td><td>...</td><td>GBT 2010</td><td>P. Bangale et al. (2023) in preparation</td></tr><tr><td>J1624-39</td><td>J1624.3-3952</td><td>2.96</td><td>2.6</td><td>6.42</td><td>GBT 2020</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1634+02</td><td>J1634.7+0235</td><td>2.12</td><td>0.9</td><td>0.094</td><td>AO 2020</td><td>S. Tabassum et al. (2023, in preparation)</td></tr><tr><td>J1646-2142</td><td>X</td><td>5.85</td><td>1.0</td><td>...</td><td>GMRT 2011</td><td>Roy & Bhattacharyya (2013)</td></tr><tr><td>J1709-0333</td><td>J1709.4-0328</td><td>3.52</td><td>1.0</td><td>0.902</td><td>MKT 2021</td><td>Clark et al. (2023a)</td></tr><tr><td>J1716+34</td><td>J1716.3+3434</td><td>2.11</td><td>2.5</td><td>0.520</td><td>AO 2021</td><td>S. Tabassum et al. (2023, in preparation)</td></tr><tr><td>J1727-1609</td><td>J1728.1-1610</td><td>2.45</td><td>3.7</td><td>6.07</td><td>GBT 2017</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1802-4718</td><td>J1802.8-4719</td><td>3.67</td><td>1.2</td><td>0.575</td><td>PKS 2016</td><td>as in Camilo et al. (2015)</td></tr><tr><td>J1803+1358</td><td>J1803.2+1402</td><td>1.52</td><td>4.6</td><td>8.44</td><td>AO 2017</td><td>Cromartie (2020)</td></tr><tr><td>J1814+31</td><td>J1814.4+3132</td><td>2.09</td><td>3.0</td><td>4.87</td><td>AO 2017</td><td>Cromartie (2020)</td></tr><tr><td>J1823+1208</td><td>J1823.2+1209</td><td>5.21</td><td>1.7</td><td>0.646</td><td>MKT 2021</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J1823-3543</td><td>J1823.8-3544</td><td>2.37</td><td>3.7</td><td>3.22</td><td>MKT 2020</td><td>Clark et al. (2023a)</td></tr><tr><td>J1828+0625</td><td>X</td><td>3.63</td><td>1.0</td><td>...</td><td>GMRT 2011</td><td>Roy & Bhattacharyya (2013)</td></tr><tr><td>J1831-6503</td><td>J1831.1-6503</td><td>1.85</td><td>1.0</td><td>0.451</td><td>MKT 2022</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J1845+0200</td><td>J1845.0+0159</td><td>4.31</td><td>1.7</td><td>0.977</td><td>AO 2016</td><td>Cromartie (2020)</td></tr><tr><td>J1904-11</td><td>J1904.4-1129</td><td>2.62</td><td>4.7</td><td>4.80</td><td>GBT 2020</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1906-1754</td><td>J1906.4-1757</td><td>2.88</td><td>6.8</td><td>18.4</td><td>MKT 2020</td><td>Clark et al. (2023a)</td></tr><tr><td>J1910-5320</td><td>J1910.7-5320</td><td>2.33</td><td>1.0</td><td>0.360</td><td>MKT 2022</td><td>Au et al. (2023); Dodge et al. (submitted)</td></tr><tr><td>J1919+23</td><td>J1919.1+2354</td><td>4.63</td><td>2.0</td><td>1.36</td><td>AO 2017</td><td>Cromartie (2020)</td></tr><tr><td>J1947-11</td><td>J1947.6-1121</td><td>2.24</td><td>3.1</td><td>3.76</td><td>GBT 2022</td><td>J. Strader et al. (2023, in preparation)</td></tr><tr><td>J2036-02</td><td>J2036.2-0207</td><td>1.91</td><td>7.7</td><td>10.9</td><td>GBT 2020</td><td>Tabassum et al. (2021)</td></tr><tr><td>J2045-6837</td><td>J2045.9-6835</td><td>2.96</td><td>1.3</td><td>0.421</td><td>PKS 2017</td><td>as in Camilo et al. (2015)</td></tr><tr><td>J2051+50</td><td></td><td>1.68</td><td>1.4</td><td>...</td><td>GBT 2020</td><td>Tabassum et al. (2021)</td></tr><tr><td>J2333-5526</td><td>J2333.1-5527</td><td>2.10</td><td>2.5</td><td>3.13</td><td>MKT 2021</td><td>TRAPUM collab. (2023, in preparation)</td></tr></tbody></table>

**Notes.** Six pulsars with “X” in the 4FGL column are unrelated to the gamma-ray source that guided the radio search. Localization of the two pulsars with no 4FGL name is as yet inadequate for source matching. Distances use DM and the YMW16 model (Yao et al. 2017). Three unpublished pulsars were found using methods as in Camilo et al. (2015). The Discovery column takes “Fermi” entries from http://astro.phys.wvu.edu/GalacticMSPs/GalacticMSPs.txt. See also http://www.trapum.org/discoveries/.

<footnote><sup>a</sup> Search targeted uncatalogued LAT source 605N-0275 (T. Burnett 2023, private communication).</footnote>
<table><caption>**Table 6**
Thirty-nine MSPs Discovered in Radio Searches of LAT Unidentified Sources, Yet to Show Gamma-Ray Pulsations</caption><thead><tr><th>PSR</th><th>4FGL</th><th>P<br>(ms)</th><th>Dist<br>(kpc)</th><th>10<sup>-33</sup>L<sub>γ</sub><br>(erg s<sup>-1</sup>)</th><th>Discovery</th><th>References</th></tr></thead><tbody><tr><td>J0329+50</td><td>J0330.1+5038</td><td>3.06</td><td>0.3</td><td>0.052</td><td>GBT 2019</td><td>Tabassum et al. (2021)</td></tr><tr><td>J0506+50</td><td>J0506.1+5028</td><td>3.39</td><td>1.4</td><td>0.510</td><td>FAST 2020</td><td>P. Wang et al. (2023, in preparation)</td></tr><tr><td>J0646-54</td><td>J0646.4-5455</td><td>2.51</td><td>0.4</td><td>0.039</td><td>PKS 2017</td><td>as in Camilo et al. (2015)</td></tr><tr><td>J0657-4657</td><td>J0657.4-4658</td><td>3.95</td><td>0.5</td><td>0.085</td><td>MKT 2022</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J0838-2827</td><td>J0838.7-2827</td><td>3.62</td><td>0.4</td><td>0.147</td><td>MKT 2021</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J0843+67</td><td>J0843.3+6712</td><td>2.84</td><td>1.6</td><td>1.13</td><td>GBT 2017</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1008-46</td><td>X<sup>a</sup></td><td>2.72</td><td>0.4</td><td>...</td><td>GMRT 2021</td><td>J. Roy et al. (2023, in preparation)</td></tr><tr><td>J1036-4353</td><td>J1036.6-4349</td><td>1.68</td><td>0.4</td><td>0.069</td><td>MKT 2021</td><td>Clark et al. (2023a)</td></tr><tr><td>J1102+02</td><td>J1102.4+0246</td><td>4.05</td><td>3.7</td><td>2.53</td><td>GBT 2019</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1103-5403</td><td>X</td><td>3.39</td><td>1.7</td><td>...</td><td>PKS 2009</td><td>Keith et al. (2011)</td></tr><tr><td>J1120-3618</td><td>X</td><td>5.55</td><td>1.0</td><td>...</td><td>GMRT 2011</td><td>Roy & Bhattacharyya (2013)</td></tr><tr><td>J1304+12</td><td>J1304.4+1203</td><td>4.18</td><td>1.4</td><td>0.442</td><td>AO 2017</td><td>Cromartie (2020)</td></tr><tr><td>J1346-2610</td><td>J1345.9-2612</td><td>2.77</td><td>1.2</td><td>0.452</td><td>MKT 2022</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J1356+0230</td><td>J1356.6+0234</td><td>2.83</td><td>1.8</td><td>0.757</td><td>MKT 2021</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J1417-4402</td><td>J1417.6-4403</td><td>2.66</td><td>4.4</td><td>18.4</td><td>PKS 2015</td><td>“Huntsman,” Swihart et al. (2018)</td></tr><tr><td>J1551-0658</td><td>X</td><td>7.09</td><td>1.3</td><td>...</td><td>GBT 2010</td><td>P. Bangale et al. (2023) in preparation</td></tr><tr><td>J1624-39</td><td>J1624.3-3952</td><td>2.96</td><td>2.6</td><td>6.42</td><td>GBT 2020</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1634+02</td><td>J1634.7+0235</td><td>2.12</td><td>0.9</td><td>0.094</td><td>AO 2020</td><td>S. Tabassum et al. (2023, in preparation)</td></tr><tr><td>J1646-2142</td><td>X</td><td>5.85</td><td>1.0</td><td>...</td><td>GMRT 2011</td><td>Roy & Bhattacharyya (2013)</td></tr><tr><td>J1709-0333</td><td>J1709.4-0328</td><td>3.52</td><td>1.0</td><td>0.902</td><td>MKT 2021</td><td>Clark et al. (2023a)</td></tr><tr><td>J1716+34</td><td>J1716.3+3434</td><td>2.11</td><td>2.5</td><td>0.520</td><td>AO 2021</td><td>S. Tabassum et al. (2023, in preparation)</td></tr><tr><td>J1727-1609</td><td>J1728.1-1610</td><td>2.45</td><td>3.7</td><td>6.07</td><td>GBT 2017</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1802-4718</td><td>J1802.8-4719</td><td>3.67</td><td>1.2</td><td>0.575</td><td>PKS 2016</td><td>as in Camilo et al. (2015)</td></tr><tr><td>J1803+1358</td><td>J1803.2+1402</td><td>1.52</td><td>4.6</td><td>8.44</td><td>AO 2017</td><td>Cromartie (2020)</td></tr><tr><td>J1814+31</td><td>J1814.4+3132</td><td>2.09</td><td>3.0</td><td>4.87</td><td>AO 2017</td><td>Cromartie (2020)</td></tr><tr><td>J1823+1208</td><td>J1823.2+1209</td><td>5.21</td><td>1.7</td><td>0.646</td><td>MKT 2021</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J1823-3543</td><td>J1823.8-3544</td><td>2.37</td><td>3.7</td><td>3.22</td><td>MKT 2020</td><td>Clark et al. (2023a)</td></tr><tr><td>J1828+0625</td><td>X</td><td>3.63</td><td>1.0</td><td>...</td><td>GMRT 2011</td><td>Roy & Bhattacharyya (2013)</td></tr><tr><td>J1831-6503</td><td>J1831.1-6503</td><td>1.85</td><td>1.0</td><td>0.451</td><td>MKT 2022</td><td>TRAPUM collab. (2023, in preparation)</td></tr><tr><td>J1845+0200</td><td>J1845.0+0159</td><td>4.31</td><td>1.7</td><td>0.977</td><td>AO 2016</td><td>Cromartie (2020)</td></tr><tr><td>J1904-11</td><td>J1904.4-1129</td><td>2.62</td><td>4.7</td><td>4.80</td><td>GBT 2020</td><td>Tabassum et al. (2021)</td></tr><tr><td>J1906-1754</td><td>J1906.4-1757</td><td>2.88</td><td>6.8</td><td>18.4</td><td>MKT 2020</td><td>Clark et al. (2023a)</td></tr><tr><td>J1910-5320</td><td>J1910.7-5320</td><td>2.33</td><td>1.0</td><td>0.360</td><td>MKT 2022</td><td>Au et al. (2023); Dodge et al. (submitted)</td></tr><tr><td>J1919+23</td><td>J1919.1+2354</td><td>4.63</td><td>2.0</td><td>1.36</td><td>AO 2017</td><td>Cromartie (2020)</td></tr><tr><td>J1947-11</td><td>J1947.6-1121</td><td>2.24</td><td>3.1</td><td>3.76</td><td>GBT 2022</td><td>J. Strader et al. (2023, in preparation)</td></tr><tr><td>J2036-02</td><td>J2036.2-0207</td><td>1.91</td><td>7.7</td><td>10.9</td><td>GBT 2020</td><td>Tabassum et al. (2021)</td></tr><tr><td>J2045-6837</td><td>J2045.9-6835</td><td>2.96</td><td>1.3</td><td>0.421</td><td>PKS 2017</td><td>as in Camilo et al. (2015)</td></tr><tr><td>J2051+50</td><td></td><td>1.68</td><td>1.4</td><td>...</td><td>GBT 2020</td><td>Tabassum et al. (2021)</td></tr><tr><td>J2333-5526</td><td>J2333.1-5527</td><td>2.10</td><td>2.5</td><td>3.13</td><td>MKT 2021</td><td>TRAPUM collab. (2023, in preparation)</td></tr></tbody></table>

**Notes.** Six pulsars with “X” in the 4FGL column are unrelated to the gamma-ray source that guided the radio search. Localization of the two pulsars with no 4FGL name is as yet inadequate for source matching. Distances use DM and the YMW16 model (Yao et al. 2017). Three unpublished pulsars were found using methods as in Camilo et al. (2015). The Discovery column takes “Fermi” entries from http://astro.phys.wvu.edu/GalacticMSPs/GalacticMSPs.txt. See also http://www.trapum.org/discoveries/.

<footnote><sup>a</sup> Search targeted uncatalogued LAT source 605N-0275 (T. Burnett 2023, private communication).</footnote>
sensitivity to short-period binary pulsars even when none of the system parameters are known (as described in Section 3.4, binary MSPs can be found in gamma-ray blind searches when approximate orbital parameters are known from optical studies). Because the observation durations are generally short compared to the orbital period, this can be done through Fourier search techniques that assume a constant acceleration (Ransom et al. 2002), or a constant jerk (Andersen & Ransom 2018). Recently, an analysis of PSC search data using the jerk search method resulted in the discovery of 11 new MSPs, at least one of which would likely have been missed in a standard acceleration search (Tabassum et al. 2021).

At least 110 new pulsars have been discovered in the radio searches targeting LAT unassociated sources. All except eight are MSPs—MSPs dominate the high Galactic latitudes where radio surveys have been less thorough. At present, only one of the slow pulsars has been confirmed as a gamma-ray pulsar (PSR J2030+3641; Camilo et al. 2012). Given the many observations, some chance coincidences are expected, especially for telescopes with wide fields of view (particularly arrays of smaller telescopes combined incoherently, like the GMRT; e.g., Bhattacharyya et al. 2022). Table 6 lists 39 MSPs found in the targeted radio searches for which gamma-ray pulsations have not yet been detected. An “X” indicates six, where it has been concluded that the MSP is not associated with the target source. Most of the others were discovered after 2016, so the lack of gamma-ray pulsations from these sources is likely due to the lag in obtaining a rotation ephemeris with which to fold LAT data.

Developing such an ephemeris is an involved process, as the timing model must extrapolate well over the long span of LAT data required for the accumulated signal to become significant. Especially if the position is not well constrained by radio imaging or an X-ray or optical counterpart, then the radio campaign requires a dense set of observations to measure the spin period well and longer intervals (0.5–1.0 yr) to measure the position and $\dot{P}$. Pulsars with orbital period variability may require years of monitoring. Such follow-up campaigns can require multiple proposal cycles.

In most cases, after getting a good timing solution, LAT pulsations have been detected from the MSPs. If pulsations are detected in a fraction of the LAT data, the solution can often be extended to cover the full mission using LAT timing methods (see Section 3.5). We expect that a large fraction of the recent MSPs in Table 6 will be identified as gamma-ray pulsars in the future. Some of the pulsars in Table 5 may also someday reveal gamma-ray pulsations.

### 3.4. Blind Periodicity Searches

In addition to the detection of gamma-ray pulsations from known radio or X-ray pulsars via folding, the LAT data also allow for the discovery of entirely new pulsars through direct searches for their gamma-ray pulsations, without prior knowledge of their spin periods or spin-down rates. These searches complement and contrast the efforts described above in Sections 3.1 and 3.3, providing access to a population of otherwise undetectable pulsars. However, these searches are less sensitive than following-up a known radio or X-ray pulsar, and are extremely computationally demanding: searching for isolated young pulsars/MSPs in a single Fermi-LAT source typically takes a few days/weeks, respectively, using tens of

thousands of CPU cores, while a search for a single binary MSP can run for months on thousands of GPUs.

Of the pulsars in this catalog, 81 were first discovered in the LAT data, compared to 36 in 2PC. The majority are young pulsars, located near the Galactic plane. Notably, this includes 10 LAT-discovered MSPs of which three are in binary systems, whereas 2PC contained just one such object. That the discovery rate from direct gamma-ray pulsation searches has not fallen off is perhaps surprising when one considers how the computational cost and sensitivity of these searches increases with the data duration.

The computational cost depends on the dimensionality and volume of the parameter space that must be searched, and the required density of search points covering this volume. At minimum, these searches are two-dimensional, covering the range of spin frequencies (or periods) and spin-down rates spanned by the known pulsar population. A subarcsecond precision position—much better than can be provided by the LAT—is required to correct for the Earth’s orbital Römer delay. Unless one is available from multiwavelength observations, an additional two-dimensional grid of sky locations covering the localization region must be searched. The required positional precision in each dimension is proportional to the spin frequency, $f$. This would make searches for MSPs thousands of times more costly than searching for young pulsars, were this not partially mitigated by the far smaller range of spin-down rate $\dot{f}$ over which MSPs are found.

When searching for pulsars in circular binaries, at least three further parameters are required (the orbital period, phase, and radius), with two additional parameters required for eccentric systems. The search grid density in all binary parameters depends on $f$, again making rapidly spinning MSPs substantially more costly to find. The binary search parameter space is in fact so large that entirely uninformed searches are as yet infeasible, with searches only becoming possible when a candidate binary system is identified and its orbital parameters constrained via multiwavelength observations.

The required search-grid density in most dimensions depends on the duration $T_{\text{obs}}$ of the data over which the signal is integrated (Pletsch & Clark 2014). In $f$, and $\dot{f}$, the number of grid points scales linearly and quadratically, respectively, with $T_{\text{obs}}$. For $T_{\text{obs}} < 1$ yr, the number of sky positions that must be searched scales quadratically with $T_{\text{obs}}$, but this saturates at longer timescales. For binary pulsar searches, the required density of orbital period search points also scales linearly with $T_{\text{obs}}$ (Nieder et al. 2020a). The result is that the computing cost scales with at least $T_{\text{obs}}^3$ for isolated pulsars and $T_{\text{obs}}^4$ for binaries. This rapid scaling leads to fully coherent searches of data lasting more than a few months being entirely infeasible.

A compromise is achieved using “semicoherent” search methods, where the signal powers from many shorter windows (of duration $T_{\text{coh}}$, typically a few weeks long) are combined incoherently (Atwood et al. 2006; Pletsch et al. 2012a). For a semicoherent search, the numbers of grid points in the frequency and spindown dimensions are each reduced by a factor of $T_{\text{obs}}/T_{\text{coh}}$, while the number of sky positions that must be searched is reduced by a factor of $(1 \text{ yr})^2/T_{\text{coh}}^2$ (assuming $T_{\text{coh}} < 1 \text{ yr} < T_{\text{obs}}$). This semicoherent search is performed as an initial scan over the entire parameter space, with more sensitive fully coherent stages being used to “follow-up” a smaller number of semicoherent candidates to increase their significance.
sensitivity to short-period binary pulsars even when none of the system parameters are known (as described in Section 3.4, binary MSPs can be found in gamma-ray blind searches when approximate orbital parameters are known from optical studies). Because the observation durations are generally short compared to the orbital period, this can be done through Fourier search techniques that assume a constant acceleration (Ransom et al. 2002), or a constant jerk (Andersen & Ransom 2018). Recently, an analysis of PSC search data using the jerk search method resulted in the discovery of 11 new MSPs, at least one of which would likely have been missed in a standard acceleration search (Tabassum et al. 2021).

At least 110 new pulsars have been discovered in the radio searches targeting LAT unassociated sources. All except eight are MSPs—MSPs dominate the high Galactic latitudes where radio surveys have been less thorough. At present, only one of the slow pulsars has been confirmed as a gamma-ray pulsar (PSR J2030+3641; Camilo et al. 2012). Given the many observations, some chance coincidences are expected, especially for telescopes with wide fields of view (particularly arrays of smaller telescopes combined incoherently, like the GMRT; e.g., Bhattacharyya et al. 2022). Table 6 lists 39 MSPs found in the targeted radio searches for which gamma-ray pulsations have not yet been detected. An “X” indicates six, where it has been concluded that the MSP is not associated with the target source. Most of the others were discovered after 2016, so the lack of gamma-ray pulsations from these sources is likely due to the lag in obtaining a rotation ephemeris with which to fold LAT data.

Developing such an ephemeris is an involved process, as the timing model must extrapolate well over the long span of LAT data required for the accumulated signal to become significant. Especially if the position is not well constrained by radio imaging or an X-ray or optical counterpart, then the radio campaign requires a dense set of observations to measure the spin period well and longer intervals (0.5–1.0 yr) to measure the position and $\dot{P}$. Pulsars with orbital period variability may require years of monitoring. Such follow-up campaigns can require multiple proposal cycles.

In most cases, after getting a good timing solution, LAT pulsations have been detected from the MSPs. If pulsations are detected in a fraction of the LAT data, the solution can often be extended to cover the full mission using LAT timing methods (see Section 3.5). We expect that a large fraction of the recent MSPs in Table 6 will be identified as gamma-ray pulsars in the future. Some of the pulsars in Table 5 may also someday reveal gamma-ray pulsations.

### 3.4. Blind Periodicity Searches

In addition to the detection of gamma-ray pulsations from known radio or X-ray pulsars via folding, the LAT data also allow for the discovery of entirely new pulsars through direct searches for their gamma-ray pulsations, without prior knowledge of their spin periods or spin-down rates. These searches complement and contrast the efforts described above in Sections 3.1 and 3.3, providing access to a population of otherwise undetectable pulsars. However, these searches are less sensitive than following-up a known radio or X-ray pulsar, and are extremely computationally demanding: searching for isolated young pulsars/MSPs in a single Fermi-LAT source typically takes a few days/weeks, respectively, using tens of

thousands of CPU cores, while a search for a single binary MSP can run for months on thousands of GPUs.

Of the pulsars in this catalog, 81 were first discovered in the LAT data, compared to 36 in 2PC. The majority are young pulsars, located near the Galactic plane. Notably, this includes 10 LAT-discovered MSPs of which three are in binary systems, whereas 2PC contained just one such object. That the discovery rate from direct gamma-ray pulsation searches has not fallen off is perhaps surprising when one considers how the computational cost and sensitivity of these searches increases with the data duration.

The computational cost depends on the dimensionality and volume of the parameter space that must be searched, and the required density of search points covering this volume. At minimum, these searches are two-dimensional, covering the range of spin frequencies (or periods) and spin-down rates spanned by the known pulsar population. A subarcsecond precision position—much better than can be provided by the LAT—is required to correct for the Earth’s orbital Römer delay. Unless one is available from multiwavelength observations, an additional two-dimensional grid of sky locations covering the localization region must be searched. The required positional precision in each dimension is proportional to the spin frequency, $f$. This would make searches for MSPs thousands of times more costly than searching for young pulsars, were this not partially mitigated by the far smaller range of spin-down rate $\dot{f}$ over which MSPs are found.

When searching for pulsars in circular binaries, at least three further parameters are required (the orbital period, phase, and radius), with two additional parameters required for eccentric systems. The search grid density in all binary parameters depends on $f$, again making rapidly spinning MSPs substantially more costly to find. The binary search parameter space is in fact so large that entirely uninformed searches are as yet infeasible, with searches only becoming possible when a candidate binary system is identified and its orbital parameters constrained via multiwavelength observations.

The required search-grid density in most dimensions depends on the duration $T_{\text{obs}}$ of the data over which the signal is integrated (Pletsch & Clark 2014). In $f$, and $\dot{f}$, the number of grid points scales linearly and quadratically, respectively, with $T_{\text{obs}}$. For $T_{\text{obs}} < 1$ yr, the number of sky positions that must be searched scales quadratically with $T_{\text{obs}}$, but this saturates at longer timescales. For binary pulsar searches, the required density of orbital period search points also scales linearly with $T_{\text{obs}}$ (Nieder et al. 2020a). The result is that the computing cost scales with at least $T_{\text{obs}}^3$ for isolated pulsars and $T_{\text{obs}}^4$ for binaries. This rapid scaling leads to fully coherent searches of data lasting more than a few months being entirely infeasible.

A compromise is achieved using “semicoherent” search methods, where the signal powers from many shorter windows (of duration $T_{\text{coh}}$, typically a few weeks long) are combined incoherently (Atwood et al. 2006; Pletsch et al. 2012a). For a semicoherent search, the numbers of grid points in the frequency and spindown dimensions are each reduced by a factor of $T_{\text{obs}}/T_{\text{coh}}$, while the number of sky positions that must be searched is reduced by a factor of $(1 \text{ yr})^2/T_{\text{coh}}^2$ (assuming $T_{\text{coh}} < 1 \text{ yr} < T_{\text{obs}}$). This semicoherent search is performed as an initial scan over the entire parameter space, with more sensitive fully coherent stages being used to “follow-up” a smaller number of semicoherent candidates to increase their significance.
<figure><img src="image_7.png" /><figcaption>**Figure 6.** The radio flux density at 1400 MHz vs. the integral energy flux above 100 MeV. Gamma-ray and radio fluxes are essentially uncorrelated. Dark borders on the triangle symbols indicate MSPs discovered in deep radio searches of previously unidentified LAT sources by the PSC (see Section 3.3). The horizontal line at 30 µJy shows our convention to distinguish radio “loud” from radio “quiet” pulsars.</figcaption></figure>

The compromise is that the sensitivity of a semicoherent search is far worse than that of a fully coherent search (e.g., for pulsations from a known pulsar). When folding with a known ephemeris, the S/N is proportional to $T_{\text{obs}}^{1/2}$. In a semicoherent search, this scaling becomes $(T_{\text{coh}} T_{\text{obs}})^{1/4}$. Combining this with the computing cost scaling, we see that the recovered S/N (a proxy for sensitivity) increases very slowly as the computing cost, $C(T_{\text{obs}}, T_{\text{coh}})$, increases. For fixed $T_{\text{obs}} > 1$ yr, S/N $\propto C(T_{\text{coh}})^a$, where $a = 1/8$ if positional information is available, or $a = 1/16$ otherwise. For fixed $T_{\text{coh}} < 1$ yr, S/N $\propto C(T_{\text{obs}})^b$ where $b = 1/4$ for isolated pulsars, and $b = 1/8$ for binary pulsars.

Two additional effects further limit this sensitivity. First, the vast parameter space that must be searched over introduces a large “trials” factor, meaning that pulsed signals need to be detected with far higher test statistic values in order to be statistically significant. Where pulsars can be found in single-trial ephemeris folding searches at $H = 25$, the associated trials factor of a semicoherent search raises this significance threshold. To be statistically significant, these searches require the coherent power at the fundamental frequency to be $P_1 \gtrsim 120$. For typical gamma-ray pulse profile shapes, this corresponds to $H \gtrsim 200$. $T_{\text{coh}}$ can be chosen such that signals above this level will be detectable in the initial semicoherent stage.

Second, the accumulation of a pulsed signal can be disrupted by more complex timing behavior such as timing noise, glitching, or orbital period variations in the case of redback binary systems. However, statistical noise still accumulates over the full data duration. For timing behavior that results in a signal being “well behaved” only over a timescale $\tau$, this means that the S/N is further reduced by a factor of $\sqrt{\tau/T_{\text{obs}}}$. This latter effect does not occur in isolated MSPs, whose spindown rates are extremely stable over time, whereas energetic young pulsars, which tend to exhibit the most timing noise and glitches, will be the worst affected. Clark et al. (2017) predicted

that the detection rates of isolated MSPs would likely increase relative to those of young pulsars as a result.

In summary, as the LAT data duration increases, these searches become more expensive, and the minimum detectable flux density decreases more slowly than that of an ephemeris-folding search. The ratio between these sensitivities depends on the background photon flux, and hence on the location of the targeted source in the sky, but varies between a factor of ~3 and 4 for the ongoing *Einstein@Home* pulsar surveys (with $T_{\text{obs}} = 10$ yr, $T_{\text{coh}} = 2^{22}$ s). The difference in sensitivities between these two methods is emphasized by the difference in the gamma-ray fluxes of the radio-loud and radio-quiet populations shown in Figure 6.

To tackle these growing challenges, search efforts require increasing computing resources and methodological developments to increase efficiency and sensitivity. Fortunately, the available computing power does increase over time as technology progresses, and as search efforts have shifted to larger computing systems. The first successful searches in the early Fermi mission either searched the center of the localization region for each source, or targeted the location of a plausible X-ray counterpart (Abdo et al. 2009b; Saz Parkinson et al. 2010). After the first 2 yr of the Fermi mission, these discoveries became less frequent. Newer searches (Pletsch et al. 2012a, 2012b) mitigated dependence on event selection criteria and source localization by weighting events and shifting to large computing clusters to enable searching over a grid of positions. These searches were later migrated to the *Einstein@Home* distributed volunteer computing system, allowing for longer $T_{\text{coh}}$ and hence more sensitivity (Pletsch et al. 2013; Clark et al. 2015, 2016, 2017, 2018).

Additional sensitivity can be gained not just through computing power, but also through careful study. While semicoherent search methods were developed prior to Fermi's launch (Atwood et al. 2006), improvements to their sensitivity and efficiency have been made throughout the LAT mission (Pletsch & Clark 2014; Nieder et al. 2020a). Improvements to
<figure><img src="image_8.png" /><figcaption>**Figure 6.** The radio flux density at 1400 MHz vs. the integral energy flux above 100 MeV. Gamma-ray and radio fluxes are essentially uncorrelated. Dark borders on the triangle symbols indicate MSPs discovered in deep radio searches of previously unidentified LAT sources by the PSC (see Section 3.3). The horizontal line at 30 µJy shows our convention to distinguish radio “loud” from radio “quiet” pulsars.</figcaption></figure>

The compromise is that the sensitivity of a semicoherent search is far worse than that of a fully coherent search (e.g., for pulsations from a known pulsar). When folding with a known ephemeris, the S/N is proportional to $T_{\text{obs}}^{1/2}$. In a semicoherent search, this scaling becomes $(T_{\text{coh}} T_{\text{obs}})^{1/4}$. Combining this with the computing cost scaling, we see that the recovered S/N (a proxy for sensitivity) increases very slowly as the computing cost, $C(T_{\text{obs}}, T_{\text{coh}})$, increases. For fixed $T_{\text{obs}} > 1$ yr, S/N $\propto C(T_{\text{coh}})^a$, where $a = 1/8$ if positional information is available, or $a = 1/16$ otherwise. For fixed $T_{\text{coh}} < 1$ yr, S/N $\propto C(T_{\text{obs}})^b$ where $b = 1/4$ for isolated pulsars, and $b = 1/8$ for binary pulsars.

Two additional effects further limit this sensitivity. First, the vast parameter space that must be searched over introduces a large “trials” factor, meaning that pulsed signals need to be detected with far higher test statistic values in order to be statistically significant. Where pulsars can be found in single-trial ephemeris folding searches at $H = 25$, the associated trials factor of a semicoherent search raises this significance threshold. To be statistically significant, these searches require the coherent power at the fundamental frequency to be $P_1 \gtrsim 120$. For typical gamma-ray pulse profile shapes, this corresponds to $H \gtrsim 200$. $T_{\text{coh}}$ can be chosen such that signals above this level will be detectable in the initial semicoherent stage.

Second, the accumulation of a pulsed signal can be disrupted by more complex timing behavior such as timing noise, glitching, or orbital period variations in the case of redback binary systems. However, statistical noise still accumulates over the full data duration. For timing behavior that results in a signal being “well behaved” only over a timescale $\tau$, this means that the S/N is further reduced by a factor of $\sqrt{\tau/T_{\text{obs}}}$. This latter effect does not occur in isolated MSPs, whose spindown rates are extremely stable over time, whereas energetic young pulsars, which tend to exhibit the most timing noise and glitches, will be the worst affected. Clark et al. (2017) predicted

that the detection rates of isolated MSPs would likely increase relative to those of young pulsars as a result.

In summary, as the LAT data duration increases, these searches become more expensive, and the minimum detectable flux density decreases more slowly than that of an ephemeris-folding search. The ratio between these sensitivities depends on the background photon flux, and hence on the location of the targeted source in the sky, but varies between a factor of ~3 and 4 for the ongoing *Einstein@Home* pulsar surveys (with $T_{\text{obs}} = 10$ yr, $T_{\text{coh}} = 2^{22}$ s). The difference in sensitivities between these two methods is emphasized by the difference in the gamma-ray fluxes of the radio-loud and radio-quiet populations shown in Figure 6.

To tackle these growing challenges, search efforts require increasing computing resources and methodological developments to increase efficiency and sensitivity. Fortunately, the available computing power does increase over time as technology progresses, and as search efforts have shifted to larger computing systems. The first successful searches in the early Fermi mission either searched the center of the localization region for each source, or targeted the location of a plausible X-ray counterpart (Abdo et al. 2009b; Saz Parkinson et al. 2010). After the first 2 yr of the Fermi mission, these discoveries became less frequent. Newer searches (Pletsch et al. 2012a, 2012b) mitigated dependence on event selection criteria and source localization by weighting events and shifting to large computing clusters to enable searching over a grid of positions. These searches were later migrated to the *Einstein@Home* distributed volunteer computing system, allowing for longer $T_{\text{coh}}$ and hence more sensitivity (Pletsch et al. 2013; Clark et al. 2015, 2016, 2017, 2018).

Additional sensitivity can be gained not just through computing power, but also through careful study. While semicoherent search methods were developed prior to Fermi's launch (Atwood et al. 2006), improvements to their sensitivity and efficiency have been made throughout the LAT mission (Pletsch & Clark 2014; Nieder et al. 2020a). Improvements to
<figure><img src="image_8.png" /><figcaption>**Figure 7.** Radio flux density at 1400 MHz vs. pulsar distance. The horizontal line at 30 µJy shows our convention to distinguish radio "loud" from radio "quiet" pulsars. The diagonal line shows a threshold in pseudo-luminosity of 100 µJy-kpc². The pulsars at the lower-right are assigned distance limits along the Milky Way's rim in Figure 8. DMs for the pulsars on the line at 25 kpc saturate the YMW16 model.</figcaption></figure>

the LAT event reconstruction and background rejection increase the recoverable signal strengths (Atwood et al. 2013; Bruel et al. 2018), as do higher-level processing developments such as photon weighting (Kerr 2011; Bruel 2019). An unbinned likelihood method improved LAT's sensitivity at all time scales, useful for a broad range of astrophysical targets in addition to pulsars (Kerr 2019).

Extensive multiwavelength searches for possible counterparts at which to target pulsation searches continue to lead to new discoveries. To give some recent examples: targeted searches of X-ray sources discovered energetic gamma-ray pulsars within two supernova remnants (PSRs J1111–6039 and J1714–3830), and searches targeting steep-spectrum radio sources associated with LAT sources discovered two isolated MSPs (Frail et al. 2018).

Searches for periodic optical and X-ray counterparts to pulsar-like LAT sources have identified several promising black-widow and redback candidates, detailed in Section 7. The precise orbital constraints from long-term optical observations are key inputs for binary searches, although they remain the most computationally demanding projects. Nevertheless, the development of efficient search grid designs (Nieder et al. 2020a) and a GPU-accelerated<sup>117</sup> search algorithm deployed on *Einstein@Home* has resulted in two binary MSP discoveries (Nieder et al. 2020b; Clark et al. 2021), in addition to PSR J1311–3430 (Pletsch et al. 2012a), which was included in 2PC.

The complementary nature of the blind-search and ephe-
meris-folding populations is highlighted by the number of radio
detections of blind-search pulsars. In 2PC, there were radio
detections of just four pulsars discovered in gamma-ray
searches. This fraction remains small in this catalog: only 11
radio detections for 81 gamma-ray blind-search pulsars, despite
deep radio follow-ups. Of those detected, most have radio flux
densities lying below typical radio survey detection thresholds,

which are above the 30 µJy limit we use to define “radio-
quiet,” shown in Figures 6 and 7. This is perhaps unsurprising:
most pulsars discovered in gamma-ray searches are young
pulsars located in the Galactic plane, which has been
extensively surveyed by radio telescopes, and therefore we
would expect most radio-loud pulsars in this region to be
known. Most gamma-ray pulsars found off the Galactic plane
are MSPs, of which most are found in binary systems, and
therefore inaccessible to gamma-ray pulsation searches unless
orbital constraints from an optical counterpart can be derived.
A notable addition since 2PC is the six MSPs that remain
undetected in radio observations, including the black-widow
PSR J1653-0158 (Nieder et al. 2020b). In such spider binaries,
the dense ionized wind can obscure the pulsed radio signal for
much, or at times all, of the orbit, hindering radio detection.

3.5. *Timing Pulsars Using LAT Data*

The timing validity range of a recently discovered radio or
X-ray pulsar will likely not cover the entire LAT data set,
limiting the statistics available for profile characterization, and
limiting the discovery potential for glitches, profile changes,
spin-ups (Marshall et al. 2015), or other rare behavior. Often,
pulsar timing using LAT data allows for an accurate phase-
connected ephemeris covering the entire mission duration.

LAT pulsar timing has significantly improved, with new
techniques to handle timing noise and faint pulsars developed
by Ray et al. (2011) and Kerr et al. (2015). They use pulse ToA
estimation and time-domain models of timing noise. For faint
pulsars, ToA estimates for short data segments are not possible,
and we adopted the unbinned methods used in Ajello et al.
(2022). They optimize the timing model by maximizing the
likelihood, using PINT (Luo et al. 2021) to compute the
rotational phase for each photon. Parameter uncertainties are
derived from the likelihood curvature near the optimum.
Particularly useful for MSPs, we have been able to estimate
some precise proper motions directly from LAT data, necessary
for the Doppler corrections presented in Section 4.3.

<footnote n="117">¹¹⁷ Graphic Processor Unit.</footnote>
<figure><img src="image_9.png" /><figcaption>**Figure 7.** Radio flux density at 1400 MHz vs. pulsar distance. The horizontal line at 30 µJy shows our convention to distinguish radio "loud" from radio "quiet" pulsars. The diagonal line shows a threshold in pseudo-luminosity of 100 µJy-kpc². The pulsars at the lower-right are assigned distance limits along the Milky Way's rim in Figure 8. DMs for the pulsars on the line at 25 kpc saturate the YMW16 model.</figcaption></figure>

the LAT event reconstruction and background rejection increase the recoverable signal strengths (Atwood et al. 2013; Bruel et al. 2018), as do higher-level processing developments such as photon weighting (Kerr 2011; Bruel 2019). An unbinned likelihood method improved LAT's sensitivity at all time scales, useful for a broad range of astrophysical targets in addition to pulsars (Kerr 2019).

Extensive multiwavelength searches for possible counterparts at which to target pulsation searches continue to lead to new discoveries. To give some recent examples: targeted searches of X-ray sources discovered energetic gamma-ray pulsars within two supernova remnants (PSRs J1111–6039 and J1714–3830), and searches targeting steep-spectrum radio sources associated with LAT sources discovered two isolated MSPs (Frail et al. 2018).

Searches for periodic optical and X-ray counterparts to pulsar-like LAT sources have identified several promising black-widow and redback candidates, detailed in Section 7. The precise orbital constraints from long-term optical observations are key inputs for binary searches, although they remain the most computationally demanding projects. Nevertheless, the development of efficient search grid designs (Nieder et al. 2020a) and a GPU-accelerated<sup>117</sup> search algorithm deployed on *Einstein@Home* has resulted in two binary MSP discoveries (Nieder et al. 2020b; Clark et al. 2021), in addition to PSR J1311–3430 (Pletsch et al. 2012a), which was included in 2PC.

The complementary nature of the blind-search and ephe-
meris-folding populations is highlighted by the number of radio
detections of blind-search pulsars. In 2PC, there were radio
detections of just four pulsars discovered in gamma-ray
searches. This fraction remains small in this catalog: only 11
radio detections for 81 gamma-ray blind-search pulsars, despite
deep radio follow-ups. Of those detected, most have radio flux
densities lying below typical radio survey detection thresholds,

which are above the 30 µJy limit we use to define “radio-
quiet,” shown in Figures 6 and 7. This is perhaps unsurprising:
most pulsars discovered in gamma-ray searches are young
pulsars located in the Galactic plane, which has been
extensively surveyed by radio telescopes, and therefore we
would expect most radio-loud pulsars in this region to be
known. Most gamma-ray pulsars found off the Galactic plane
are MSPs, of which most are found in binary systems, and
therefore inaccessible to gamma-ray pulsation searches unless
orbital constraints from an optical counterpart can be derived.
A notable addition since 2PC is the six MSPs that remain
undetected in radio observations, including the black-widow
PSR J1653-0158 (Nieder et al. 2020b). In such spider binaries,
the dense ionized wind can obscure the pulsed radio signal for
much, or at times all, of the orbit, hindering radio detection.

3.5. *Timing Pulsars Using LAT Data*

The timing validity range of a recently discovered radio or
X-ray pulsar will likely not cover the entire LAT data set,
limiting the statistics available for profile characterization, and
limiting the discovery potential for glitches, profile changes,
spin-ups (Marshall et al. 2015), or other rare behavior. Often,
pulsar timing using LAT data allows for an accurate phase-
connected ephemeris covering the entire mission duration.

LAT pulsar timing has significantly improved, with new
techniques to handle timing noise and faint pulsars developed
by Ray et al. (2011) and Kerr et al. (2015). They use pulse ToA
estimation and time-domain models of timing noise. For faint
pulsars, ToA estimates for short data segments are not possible,
and we adopted the unbinned methods used in Ajello et al.
(2022). They optimize the timing model by maximizing the
likelihood, using PINT (Luo et al. 2021) to compute the
rotational phase for each photon. Parameter uncertainties are
derived from the likelihood curvature near the optimum.
Particularly useful for MSPs, we have been able to estimate
some precise proper motions directly from LAT data, necessary
for the Doppler corrections presented in Section 4.3.

<footnote n="117">¹¹⁷ Graphic Processor Unit.</footnote>
When both radio and LAT timing of comparable quality are available, we use the radio ephemeris. LAT timing was used for 142 of the pulsars in this catalog. Two-thirds of those were made with the ToA method. The fraction of timing solutions using the unbinned method is increasing, as analysts adopt the tool, as more difficult pulsars are added to the sample, and as the data sets lengthen. The ephemerides we used to fold the 294 pulsars are included in the supplementary data, at https://fermi.gsfc.nasa.gov/ssc/data/access/lat/3rd_PSR catalogue/, and at https://fermi.gsfc.nasa.gov/ssc/data/access/lat/ephems/. See Appendix D.

# 4. The Gamma-Ray Pulsars

The search methods yielded gamma-ray pulsations for 294 pulsars. Table 1 breaks down the numbers by different types. Here we compile their radio fluxes, distances, and, for the MSPs, their proper motions, used to Doppler-correct their spindown properties (Shklovskii 1970). Figure 3 shows the sky distribution of the Fermi pulsars. The LAT’s uniform sky coverage is important for detecting MSPs, as these relatively nearby sources are approximately uniformly distributed in Galactic latitude.

## 4.1. Radio Intensities

We tabulate measured or derived 1400 MHz flux density values ($S_{1400}$) in Tables 2 and 3. ATNF psrcat provides flux densities $S_ν$ from among 27 different radio frequencies $ν$; thus, as a starting point, we used psrqpy (Pitkin 2018) to extract all $S_ν$ values from psrcat, as well as the radio spectral index, SPINDX. When available, we use $S_{1400}$. Otherwise, we calculate $S_{1400} = S_ν (\frac{1400}{ν})^α$ with $α = SPINDX$ when present, and $α = -1.7$ otherwise. We use the $S_ν$ value corresponding to the frequency $ν$ closest to 1400 MHz. We used $α = -1.7$ in 2PC, a compromise among published values: -1.6 from Lorimer et al. (1995), -1.8 ± 0.2 from Maron et al. (2000), and -1.60 ± 0.03 from Jankowski et al. (2018). For MSPs, Spiewak et al. (2022) found -1.92 ± 0.06 with a standard deviation of 0.6, and Dai et al. (2015) found -1.81 ± 0.01. The small formal uncertainties are potentially misleading: for example, the value from Jankowski et al. (2018) is for a sample of 400 pulsars with a log-normal distribution of standard deviation 0.54, the distribution being sensitive to, e.g., the frequency range used, yielding the spread in average indices. Using multiple $S_ν$ values to fit a power law gives $S_{1400}$ values generally compatible with those found above, and possibly more accurate in some cases. However, discrepant $S_ν$ values lead to unrealistic results in some cases; hence, we use the simple prescription described above.

The psrcat $S_ν$ values have accumulated over decades, using a variety of instruments and analysis conventions. Frequency extrapolation introduces additional biases. Fortunately, v1.68 psrcat includes $S_{1400}$ values from two recent studies. Spiewak et al. (2022) used MeerKAT to obtain $S_{1400}$ for 189 MSPs,<fnref n="118" /> and Parent et al. (2022) analyzed Arecibo data from the PALFA survey for 93 MSPs. We also replace the Hessels et al. (2011) values with the updated results reported by Bangale et al. (2023). For a small number of pulsars, we obtained as-yet-unpublished $S_ν$ measurements, noted in the Tables.

In addition to pulsars that are well characterized from radio surveys, those discovered in blind searches are typically searched deeply for radio pulsations (Camilo et al. 2009; Abdo et al. 2010d; Saz Parkinson et al. 2010; Ray et al. 2011, 2012; Pletsch et al. 2012a; Nieder et al. 2020b). The 81 blind discoveries were followed by 11 radio detections, six of which qualify as “radio-loud,” with $S_{1400} > 30$ µJy (see below). Radio measurements are not yet available for recently discovered LAT pulsars.

Figure 6 shows that radio flux densities are essentially uncorrelated with the integrated gamma-ray energy fluxes, $G_{100}$. Population studies aim to constrain a power-law model of radio luminosity in which $L_r ∝ Ė^s$. Johnston & Karastergiou (2017) favored $s = 1/4$ but recognized that a range of $s$ values match observations, because of the large dispersion. Posselt et al. (2023) found an even smaller index. Since $L_γ ∝ \sqrt{Ē}$ (see Figure 23), flux correlation between the two wavelengths is naturally expected. However, the fraction of neutron star spindown power carried off by radio waves is thousands of times lower, or more, than that of gamma-rays, and radio emission is so weakly connected to the braking mechanism that the correlation is invisible.

Figure 7 shows how the radio flux densities of the gamma-ray pulsars compare with the overall pulsar population, as well as their lack of distance dependence. As in 2PC, we define a pulsar as “radio-loud” if $S_{1400} > 30$ µJy, and “radio-quiet” if the measured flux density is lower. The horizontal lines in Figures 6 and 7 show the threshold. Also as in 2PC, the diagonal line in Figure 7 shows an alternate threshold at pseudo-luminosity $100$ µJy-kpc².

Whether a radio or a gamma-ray beam (or both) sweeps through our line of sight from Earth depends on the beam shapes and orientations. Sieber et al. (1975) already showed that radio beam size often increases with decreasing frequency. Grießmeier et al. (2021) searched 27 radio-quiet northern gamma-ray pulsars at 150 MHz but obtained no new detections. This result is compatible with the current understanding of these pulsars’ orientations based on their emission geometries, which are derived from LAT light curves and plotted in Johnston et al. (2020), Grießmeier et al. (2021), and which are consistent with the radio beam not crossing the Earth’s line of sight.

## 4.2. Distances

Converting integrated energy fluxes $G_{100}$ to emitted luminosities $L_γ = 4πd^2f_ΩG_{100}$ requires the source distances $d$. (We set the beaming fraction $f_Ω = 1$; see Section 6.7.) Knowing pulsar distances also allows us to map neutron star distributions relative to the Galaxy’s spiral arms, as in Figure 8, and evaluate their scale height above the plane. The various methods to estimate pulsar distances offer widely differing accuracies. Tables 7 and 8 list the distances that we use, the estimation methods, and the references.

DM is the column density of free electrons along the path from Earth to the pulsar, in units of pc cm⁻³. The electrons delay the radio pulse arrival by $Δt = DM(pν^2)^{-1}$ where $ν$ is the observation frequency in megahertz and $p = 2.410 × 10^{-4}$ MHz⁻² pc cm⁻³ s⁻¹. Given a model for the electron density $n_e$ in the various structures of our Galaxy, integrating DM = $\int_0^d n_e dl$ along the line of sight $dl$ yields the distance $d$ for which DM matches the radio measurement. We

<footnote n="118">¹¹⁸ We thank R. Spiewak, M. Bailes et al. for sharing their results before publication.</footnote>
When both radio and LAT timing of comparable quality are available, we use the radio ephemeris. LAT timing was used for 142 of the pulsars in this catalog. Two-thirds of those were made with the ToA method. The fraction of timing solutions using the unbinned method is increasing, as analysts adopt the tool, as more difficult pulsars are added to the sample, and as the data sets lengthen. The ephemerides we used to fold the 294 pulsars are included in the supplementary data, at https://fermi.gsfc.nasa.gov/ssc/data/access/lat/3rd_PSR catalogue/, and at https://fermi.gsfc.nasa.gov/ssc/data/access/lat/ephems/. See Appendix D.

# 4. The Gamma-Ray Pulsars

The search methods yielded gamma-ray pulsations for 294 pulsars. Table 1 breaks down the numbers by different types. Here we compile their radio fluxes, distances, and, for the MSPs, their proper motions, used to Doppler-correct their spindown properties (Shklovskii 1970). Figure 3 shows the sky distribution of the Fermi pulsars. The LAT’s uniform sky coverage is important for detecting MSPs, as these relatively nearby sources are approximately uniformly distributed in Galactic latitude.

## 4.1. Radio Intensities

We tabulate measured or derived 1400 MHz flux density values ($S_{1400}$) in Tables 2 and 3. ATNF psrcat provides flux densities $S_ν$ from among 27 different radio frequencies $ν$; thus, as a starting point, we used psrqpy (Pitkin 2018) to extract all $S_ν$ values from psrcat, as well as the radio spectral index, SPINDX. When available, we use $S_{1400}$. Otherwise, we calculate $S_{1400} = S_ν (\frac{S_{1400}}{ν})^α$ with $α = SPINDX$ when present, and $α = -1.7$ otherwise. We use the $S_ν$ value corresponding to the frequency $ν$ closest to 1400 MHz. We used $α = -1.7$ in 2PC, a compromise among published values: -1.6 from Lorimer et al. (1995), -1.8 ± 0.2 from Maron et al. (2000), and -1.60 ± 0.03 from Jankowski et al. (2018). For MSPs, Spiewak et al. (2022) found -1.92 ± 0.06 with a standard deviation of 0.6, and Dai et al. (2015) found -1.81 ± 0.01. The small formal uncertainties are potentially misleading: for example, the value from Jankowski et al. (2018) is for a sample of 400 pulsars with a log-normal distribution of standard deviation 0.54, the distribution being sensitive to, e.g., the frequency range used, yielding the spread in average indices. Using multiple $S_ν$ values to fit a power law gives $S_{1400}$ values generally compatible with those found above, and possibly more accurate in some cases. However, discrepant $S_ν$ values lead to unrealistic results in some cases; hence, we use the simple prescription described above.

The psrcat $S_ν$ values have accumulated over decades, using a variety of instruments and analysis conventions. Frequency extrapolation introduces additional biases. Fortunately, v1.68 psrcat includes $S_{1400}$ values from two recent studies. Spiewak et al. (2022) used MeerKAT to obtain $S_{1400}$ for 189 MSPs,<fnref n="118" /> and Parent et al. (2022) analyzed Arecibo data from the PALFA survey for 93 MSPs. We also replace the Hessels et al. (2011) values with the updated results reported by Bangale et al. (2023). For a small number of pulsars, we obtained as-yet-unpublished $S_ν$ measurements, noted in the Tables.

In addition to pulsars that are well characterized from radio surveys, those discovered in blind searches are typically searched deeply for radio pulsations (Camilo et al. 2009; Abdo et al. 2010d; Saz Parkinson et al. 2010; Ray et al. 2011, 2012; Pletsch et al. 2012a; Nieder et al. 2020b). The 81 blind discoveries were followed by 11 radio detections, six of which qualify as “radio-loud,” with $S_{1400} > 30$ µJy (see below). Radio measurements are not yet available for recently discovered LAT pulsars.

Figure 6 shows that radio flux densities are essentially uncorrelated with the integrated gamma-ray energy fluxes, $G_{100}$. Population studies aim to constrain a power-law model of radio luminosity in which $L_r ∝ \dot{E}^s$. Johnston & Karastergiou (2017) favored $s = 1/4$ but recognized that a range of $s$ values match observations, because of the large dispersion. Posselt et al. (2023) found an even smaller index. Since $L_γ ∝ \sqrt{\dot{E}}$ (see Figure 23), flux correlation between the two wavelengths is naturally expected. However, the fraction of neutron star spindown power carried off by radio waves is thousands of times lower, or more, than that of gamma-rays, and radio emission is so weakly connected to the braking mechanism that the correlation is invisible.

Figure 7 shows how the radio flux densities of the gamma-ray pulsars compare with the overall pulsar population, as well as their lack of distance dependence. As in 2PC, we define a pulsar as “radio-loud” if $S_{1400} > 30$ µJy, and “radio-quiet” if the measured flux density is lower. The horizontal lines in Figures 6 and 7 show the threshold. Also as in 2PC, the diagonal line in Figure 7 shows an alternate threshold at pseudo-luminosity $100$ µJy-kpc$^2$.

Whether a radio or a gamma-ray beam (or both) sweeps through our line of sight from Earth depends on the beam shapes and orientations. Sieber et al. (1975) already showed that radio beam size often increases with decreasing frequency. Grießmeier et al. (2021) searched 27 radio-quiet northern gamma-ray pulsars at 150 MHz but obtained no new detections. This result is compatible with the current understanding of these pulsars’ orientations based on their emission geometries, which are derived from LAT light curves and plotted in Johnston et al. (2020), Grießmeier et al. (2021), and which are consistent with the radio beam not crossing the Earth’s line of sight.

## 4.2. Distances

Converting integrated energy fluxes $G_{100}$ to emitted luminosities $L_γ = 4πd^2f_ΩG_{100}$ requires the source distances $d$. (We set the beaming fraction $f_Ω = 1$; see Section 6.7.) Knowing pulsar distances also allows us to map neutron star distributions relative to the Galaxy’s spiral arms, as in Figure 8, and evaluate their scale height above the plane. The various methods to estimate pulsar distances offer widely differing accuracies. Tables 7 and 8 list the distances that we use, the estimation methods, and the references.

DM is the column density of free electrons along the path from Earth to the pulsar, in units of pc cm$^{-3}$. The electrons delay the radio pulse arrival by $Δt = DM(pν^2)^{-1}$ where $ν$ is the observation frequency in megahertz and $p = 2.410 × 10^{-4}$ MHz$^{-2}$ pc cm$^{-3}$ s$^{-1}$. Given a model for the electron density $n_e$ in the various structures of our Galaxy, integrating DM = $\int_0^d n_e dl$ along the line of sight $dl$ yields the distance $d$ for which DM matches the radio measurement. We

<footnote n="118">¹¹⁸ We thank R. Spiewak, M. Bailes et al. for sharing their results before publication.</footnote>
<figure><img src="image_9.png" /><figcaption>**Figure 8.** Gamma-ray pulsar positions projected onto the Milky Way model of Reid et al. (2009). The MSPs that appear coincident with the Galactic center, PSRs J1823−3021A and J1835−3259B in the globular clusters NGC 6624 and 6652, lie well above the Galactic plane. Distance uncertainties are not shown, but can be large for the more distant objects. The squares with arrows indicate the lines of sight toward pulsars for which no distance estimates exist, placed at the distances where 95% of the electron column density has been integrated in the YMW16 model. Other symbols are the same as in Figure 2.</figcaption></figure>

use mainly the YMW16 model (Yao et al. 2017), but often consult the NE2001 model when studying particular lines of sight (Cordes & Lazio 2002). Significant discrepancies between model and true distances occur along some lines of sight, more than three times the probable true distance in the worst cases. Examples are PSR J0614−3329 (Bassa et al. 2016a); PSR J2021+3651 (Abdo et al. 2009c); PSR J0248+6021 (Theureau et al. 2011); and PSR J0908−4913 (Johnston & Lower 2021). Figure 4 of Hou et al. (2014) illustrates one way to identify pulsar lines of sight that have DM model peculiarities.

Radio spectra can show Doppler-shifted neutral hydrogen (H I) absorption or emission lines due to clouds along the line of sight. A Galactic rotation model converts the Doppler-inferred radial velocity to a cloud distance estimate, and the pulsar distance is constrained if it appears to be in or between clouds. This “kinematic” method is tagged with a “K” in the tables. The “X” tag indicates cases where X-ray absorption below 1 keV yields a column density that can be compared with one obtained from 21 cm radio surveys.

To obtain the distances, we first query the ATNF psrcat DIST parameter, which is most often DIST_DM, the DM distance using YMW16. We adopt a 40% uncertainty on DIST_DM as per Figure 12 and Table 5 of Yao et al. (2017). When psrcat has a DIST_A value, obtained by another method, we use that instead and propagate the method and reference to our tables. The exception is that we exclude the distances deduced by Wang (2011) using the LAT G100 values and the

correlation between $L_γ$ and $\dot{E}$ shown in Section 6.7, since they would bias our attempts to better determine that correlation. If the psrcat parallax parameter PX is present, $DIST_A = 1/PX$, and we use the reference for PX. Parallax is measured only for relatively nearby pulsars, using X-ray or optical images, radio interferometric imaging, or accurate timing.<fnref n="119" /> When converting parallax measurements to distances, the Lutz–Kelker (LK) effect is an overestimate of parallax values, and hence an underestimate of distances, due to the larger volume of space traced by smaller parallax values (Lutz & Kelker 1973). We use the LK-corrected distance estimates determined by Verbiest et al. (2012). Good estimates of the distance to an optical companion in a binary system are more frequent than in 2PC because we have more spider MSPs than before, and because of the wealth of information provided by Gaia (Gaia Collab et al. 2018). For two of our MSPs, PSRs J1227−4853 and J1431−4715, Jennings et al. (2018) found distances using Gaia companion parallaxes. They used a spatial distribution prior specific to Galactic pulsars, i.e., not isotropic, which means that the LK-like correction brings some pulsars closer to Earth when they are toward the anticenter, as opposed to farther for standard LK. For these two MSPs, we simply use 1/PX, the same within uncertainties as the Jennings et al. (2018) distances.

For several pulsars, measured DM exceeds $DM_{max}$, the maximum modeled by Yao et al. (2017) for that line of sight,

<footnote n="119">¹¹⁹ http://hosting.astro.cornell.edu/research/parallax/ lists known pulsar parallaxes (Chatterjee et al. 2009).</footnote>
<figure><img src="image_10.png" /><figcaption>**Figure 8.** Gamma-ray pulsar positions projected onto the Milky Way model of Reid et al. (2009). The MSPs that appear coincident with the Galactic center, PSRs J1823−3021A and J1835−3259B in the globular clusters NGC 6624 and 6652, lie well above the Galactic plane. Distance uncertainties are not shown, but can be large for the more distant objects. The squares with arrows indicate the lines of sight toward pulsars for which no distance estimates exist, placed at the distances where 95% of the electron column density has been integrated in the YMW16 model. Other symbols are the same as in Figure 2.</figcaption></figure>

use mainly the YMW16 model (Yao et al. 2017), but often consult the NE2001 model when studying particular lines of sight (Cordes & Lazio 2002). Significant discrepancies between model and true distances occur along some lines of sight, more than three times the probable true distance in the worst cases. Examples are PSR J0614−3329 (Bassa et al. 2016a); PSR J2021+3651 (Abdo et al. 2009c); PSR J0248+6021 (Theureau et al. 2011); and PSR J0908−4913 (Johnston & Lower 2021). Figure 4 of Hou et al. (2014) illustrates one way to identify pulsar lines of sight that have DM model peculiarities.

Radio spectra can show Doppler-shifted neutral hydrogen (H I) absorption or emission lines due to clouds along the line of sight. A Galactic rotation model converts the Doppler-inferred radial velocity to a cloud distance estimate, and the pulsar distance is constrained if it appears to be in or between clouds. This “kinematic” method is tagged with a “K” in the tables. The “X” tag indicates cases where X-ray absorption below 1 keV yields a column density that can be compared with one obtained from 21 cm radio surveys.

To obtain the distances, we first query the ATNF psrcat DIST parameter, which is most often DIST_DM, the DM distance using YMW16. We adopt a 40% uncertainty on DIST_DM as per Figure 12 and Table 5 of Yao et al. (2017). When psrcat has a DIST_A value, obtained by another method, we use that instead and propagate the method and reference to our tables. The exception is that we exclude the distances deduced by Wang (2011) using the LAT G100 values and the

correlation between $L_γ$ and $\dot{E}$ shown in Section 6.7, since they would bias our attempts to better determine that correlation. If the psrcat parallax parameter PX is present, $DIST_A = 1/PX$, and we use the reference for PX. Parallax is measured only for relatively nearby pulsars, using X-ray or optical images, radio interferometric imaging, or accurate timing.<fnref n="119" /> When converting parallax measurements to distances, the Lutz–Kelker (LK) effect is an overestimate of parallax values, and hence an underestimate of distances, due to the larger volume of space traced by smaller parallax values (Lutz & Kelker 1973). We use the LK-corrected distance estimates determined by Verbiest et al. (2012). Good estimates of the distance to an optical companion in a binary system are more frequent than in 2PC because we have more spider MSPs than before, and because of the wealth of information provided by Gaia (Gaia Collab et al. 2018). For two of our MSPs, PSRs J1227−4853 and J1431−4715, Jennings et al. (2018) found distances using Gaia companion parallaxes. They used a spatial distribution prior specific to Galactic pulsars, i.e., not isotropic, which means that the LK-like correction brings some pulsars closer to Earth when they are toward the anticenter, as opposed to farther for standard LK. For these two MSPs, we simply use 1/PX, the same within uncertainties as the Jennings et al. (2018) distances.

For several pulsars, measured DM exceeds $DM_{max}$, the maximum modeled by Yao et al. (2017) for that line of sight,

<footnote n="119">¹¹⁹ http://hosting.astro.cornell.edu/research/parallax/ lists known pulsar parallaxes (Chatterjee et al. 2009).</footnote>
<table><caption>**Table 7**
Distance Estimates for Young LAT-detected Pulsars</caption><thead><tr><th>Pulsar Name</th><th>Distance (kpc)</th><th>Method</th><th>Reference</th></tr></thead><tbody><tr><td>J0002+6216</td><td>2.0 ± 0.4</td><td>O</td><td>Schinzel et al. (2019)</td></tr><tr><td>J0007+7303</td><td>1.4 ± 0.3</td><td>K</td><td>Pineault et al. (1993)</td></tr><tr><td>J0106+4855</td><td>3.1 ± 1.2</td><td>DM</td><td>Pletsch et al. (2012a)</td></tr><tr><td>J0117+5914</td><td>1.8 ± 0.7</td><td>DM</td><td>Bilous et al. (2016)</td></tr><tr><td>J0139+5814</td><td>2.6<sup>+0.3</sup><sub>-0.2</sub></td><td>P</td><td>Chatterjee et al. (2009)</td></tr><tr><td>J0205+6449</td><td>3.2 ± 0.2</td><td>K</td><td>Xu et al. (2006)</td></tr><tr><td>J0248+6021</td><td>2.0 ± 0.2</td><td>0</td><td>Theureau et al. (2011)</td></tr><tr><td>J0357+3205</td><td>&lt;7.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0359+5414</td><td>&lt;9.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0514-4408</td><td>1.0 ± 0.4</td><td>DM</td><td>Bhattacharyya et al. (2019)</td></tr><tr><td>J0534+2200</td><td>2.0<sup>+0.4</sup><sub>-0.3</sub></td><td>P</td><td>Brown et al. (2021)</td></tr><tr><td>J0540-6919</td><td>49.7 ± 1.1</td><td>O</td><td>Walker (2012)</td></tr><tr><td>J0554+3107</td><td>&lt;9.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0622+3749</td><td>&lt;8.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0631+0646</td><td>4.6 ± 1.8</td><td>DM</td><td>Wu et al. (2018)</td></tr><tr><td>J0631+1036</td><td>2.1 ± 0.8</td><td>DM</td><td>Weltevrede et al. (2010a)</td></tr><tr><td>J0633+0632</td><td>&lt;9.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0633+1746</td><td>0.2 ± 0.1</td><td>P</td><td>Caraveo et al. (1996)</td></tr><tr><td>J0659+1414</td><td>0.29<sup>+0.03</sup><sub>-0.03</sub></td><td>P</td><td>Brisken et al. (2003)</td></tr><tr><td>J0729-1448</td><td>2.7 ± 1.1</td><td>DM</td><td>McEwen et al. (2020)</td></tr><tr><td>J0729-1836</td><td>2.0<sup>+0.4</sup><sub>-0.3</sub></td><td>P</td><td>Deller et al. (2019)</td></tr><tr><td>J0734-1559</td><td>&lt;9.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0742-2822</td><td>2.0<sup>+1.0</sup><sub>-0.8</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J0744-2525</td><td>&lt;10.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0802-5613</td><td>&lt;11.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0834-4159</td><td>5.5 ± 2.2</td><td>DM</td><td>Kramer et al. (2003)</td></tr><tr><td>J0835-4510</td><td>0.28<sup>+0.10</sup><sub>-0.02</sub></td><td>P</td><td>Dodson et al. (2003)</td></tr><tr><td>J0908-4913</td><td>1.0<sup>+1.7</sup><sub>-0.7</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J0922+0638</td><td>1.1<sup>+0.2</sup><sub>-0.1</sub></td><td>P</td><td>Chatterjee et al. (2001)</td></tr><tr><td>J0940-5428</td><td>0.4 ± 0.2</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1016-5857</td><td>3.2 ± 1.3</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1019-5749</td><td>10.9 ± 4.4</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1023-5746</td><td>&lt;11.9</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1028-5819</td><td>1.4 ± 0.6</td><td>DM</td><td>Keith et al. (2008)</td></tr><tr><td>J1044-5737</td><td>&lt;11.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1048-5832</td><td>2.9<sup>+1.2</sup><sub>-0.7</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1055-6028</td><td>3.8 ± 1.5</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1057-5226</td><td>0.3 ± 0.2</td><td>O</td><td>Mignani et al. (2010)</td></tr><tr><td>J1057-5851</td><td>&lt;11.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1105-6037</td><td>&lt;12.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1105-6107</td><td>2.4 ± 0.9</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1111-6039</td><td>&lt;12.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1112-6103</td><td>4.5 ± 1.8</td><td>DM</td><td>Oswald et al. (2021)</td></tr><tr><td>J1119-6127</td><td>8.4 ± 0.4</td><td>K</td><td>Caswell et al. (2004)</td></tr><tr><td>J1124-5916</td><td>4.8<sup>+0.7</sup><sub>-1.2</sub></td><td>X</td><td>Gonzalez & Safi-Harb (2003)</td></tr><tr><td>J1135-6055</td><td>&lt;13.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1139-6247</td><td>&lt;14.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1151-6108</td><td>2.2 ± 0.9</td><td>DM</td><td>Serylak et al. (2021)</td></tr><tr><td>J1203-6242</td><td>&lt;15.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1208-6238</td><td>&lt;15.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1224-6407</td><td>4.0 ± 2.0</td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1231-5113</td><td>&lt;10.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1231-6511</td><td>&lt;17.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1253-5820</td><td>1.6 ± 0.7</td><td>DM</td><td>D'Amico et al. (1998)</td></tr><tr><td>J1341-6220</td><td>12.6 ± 5.0</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1350-6225</td><td>&lt;17.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1357-6429</td><td>3.1 ± 1.2</td><td>DM</td><td>Lorimer et al. (2006)</td></tr><tr><td>J1358-6025</td><td>&lt;16.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1410-6132</td><td>13.5 ± 5.4</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1413-6205</td><td>&lt;18.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1418-6058</td><td>1.6 ± 0.7</td><td>O</td><td>Yadigaroglu & Romani (1997)</td></tr><tr><td>J1420-6048</td><td>5.6 ± 2.3</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1422-6138</td><td>&lt;18.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr></tbody></table>

<table><caption>**Table 7**
(Continued)</caption><thead><tr><th>Pulsar Name</th><th>Distance (kpc)</th><th>Method</th><th>Reference</th></tr></thead><tbody><tr><td>J1429-5911</td><td>&lt;17.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1447-5757</td><td>&lt;18.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1459-6053</td><td>&lt;19.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1509-5850</td><td>3.4 ± 1.3</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1513-5908</td><td>4.4<sup>+1.3</sup><sub>-0.8</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1522-5735</td><td>&lt;19.3</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1528-5838</td><td>&lt;20.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1531-5610</td><td>2.8 ± 1.1</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1614-5048</td><td>5.1 ± 2.1</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1615-5137</td><td>&lt;18.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1620-4927</td><td>&lt;18.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1623-5005</td><td>&lt;18.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1624-4041</td><td>&lt;18.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1641-5317</td><td>&lt;22.3</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1646-4346</td><td>6.2 ± 2.5</td><td>DM</td><td>Hobbs et al. (2004a)</td></tr><tr><td>J1648-4611</td><td>4.5 ± 1.8</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1650-4601</td><td>&lt;22.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1702-4128</td><td>4.0 ± 1.6</td><td>DM</td><td>Oswald et al. (2021)</td></tr><tr><td>J1705-1906</td><td>0.7 ± 0.3</td><td>DM</td><td>Hobbs et al. (2004b)</td></tr><tr><td>J1709-4429</td><td>2.6<sup>+0.5</sup><sub>-0.6</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1714-3830</td><td>&lt;20.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1718-3825</td><td>3.5 ± 1.4</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1730-3350</td><td>3.5 ± 1.4</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1731-4744</td><td>0.7<sup>+0.1</sup><sub>-0.3</sub></td><td>O</td><td>Shternin et al. (2019)</td></tr><tr><td>J1732-3131</td><td>0.6 ± 0.3</td><td>DM</td><td>Maan et al. (2012, 2017)</td></tr><tr><td>J1736-3422</td><td>&lt;21.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1739-3023</td><td>3.1 ± 1.2</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1740+1000</td><td>1.2 ± 0.5</td><td>DM</td><td>Bilous et al. (2016)</td></tr><tr><td>J1741-2054</td><td>0.3<sup>+0.7</sup><sub>-0.1</sub></td><td>O</td><td>Brownsberger & Romani (2014)</td></tr><tr><td>J1742-3321</td><td>&lt;22.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1746-3239</td><td>&lt;22.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1747-2958</td><td>4.8 ± 0.8</td><td>X</td><td>Gaensler et al. (2004)</td></tr><tr><td>J1748-2815</td><td>&lt;20.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1757-2421</td><td>3.1 ± 1.2</td><td>DM</td><td>Hobbs et al. (2004b)</td></tr><tr><td>J1801-2451</td><td>3.8 ± 1.5</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1803-2149</td><td>&lt;21.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1809-2332</td><td>1.7 ± 1.0</td><td>K</td><td>Oka et al. (1999)</td></tr><tr><td>J1813-1246</td><td>&lt;22.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1816-0755</td><td>3.2 ± 1.3</td><td>DM</td><td>McEwen et al. (2020)</td></tr><tr><td>J1817-1742</td><td>&lt;22.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1826-1256</td><td>&lt;19.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1827-1446</td><td>&lt;22.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1828-1101</td><td>4.8 ± 1.9</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1831-0952</td><td>3.7 ± 1.5</td><td>DM</td><td>Lorimer et al. (2006)</td></tr><tr><td>J1833-1034</td><td>4.1 ± 0.3</td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1835-1106</td><td>3.2 ± 1.3</td><td>DM</td><td>D'Amico et al. (1998)</td></tr><tr><td>J1836+5925</td><td>0.5 ± 0.3</td><td>X</td><td>Halpern et al. (2002)</td></tr><tr><td>J1837-0604</td><td>4.8 ± 1.9</td><td>DM</td><td>Oswald et al. (2021)</td></tr><tr><td>J1838-0537</td><td>&lt;18.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1841-0524</td><td>4.1 ± 1.7</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1844-0346</td><td>&lt;17.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1846+0919</td><td>&lt;21.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1846-0258</td><td>5.8<sup>+0.5</sup><sub>-0.4</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1853-0004</td><td>5.3 ± 2.1</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1856+0113</td><td>3.3 ± 0.6</td><td>K</td><td>Caswell et al. (1975)</td></tr><tr><td>J1857+0143</td><td>4.6 ± 1.8</td><td>DM</td><td>Serylak et al. (2021)</td></tr><tr><td>J1906+0722</td><td>&lt;18.9</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1907+0602</td><td>2.6 ± 1.0</td><td>DM</td><td>Abdo et al. (2010d)</td></tr><tr><td>J1913+0904</td><td>3.0 ± 1.2</td><td>DM</td><td>Lorimer et al. (2006)</td></tr><tr><td>J1913+1011</td><td>4.6 ± 1.8</td><td>DM</td><td>Morris et al. (2002)</td></tr><tr><td>J1925+1720</td><td>5.0 ± 2.0</td><td>DM</td><td>Serylak et al. (2021)</td></tr><tr><td>J1928+1746</td><td>4.3 ± 1.7</td><td>DM</td><td>Nice et al. (2013)</td></tr><tr><td>J1932+1916</td><td>&lt;17.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr></tbody></table>
<table><caption>**Table 7**
Distance Estimates for Young LAT-detected Pulsars</caption><thead><tr><th>Pulsar Name</th><th>Distance (kpc)</th><th>Method</th><th>Reference</th></tr></thead><tbody><tr><td>J0002+6216</td><td>2.0 ± 0.4</td><td>O</td><td>Schinzel et al. (2019)</td></tr><tr><td>J0007+7303</td><td>1.4 ± 0.3</td><td>K</td><td>Pineault et al. (1993)</td></tr><tr><td>J0106+4855</td><td>3.1 ± 1.2</td><td>DM</td><td>Pletsch et al. (2012a)</td></tr><tr><td>J0117+5914</td><td>1.8 ± 0.7</td><td>DM</td><td>Bilous et al. (2016)</td></tr><tr><td>J0139+5814</td><td>2.6<sup>+0.3</sup><sub>-0.2</sub></td><td>P</td><td>Chatterjee et al. (2009)</td></tr><tr><td>J0205+6449</td><td>3.2 ± 0.2</td><td>K</td><td>Xu et al. (2006)</td></tr><tr><td>J0248+6021</td><td>2.0 ± 0.2</td><td>0</td><td>Theureau et al. (2011)</td></tr><tr><td>J0357+3205</td><td>&lt;7.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0359+5414</td><td>&lt;9.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0514-4408</td><td>1.0 ± 0.4</td><td>DM</td><td>Bhattacharyya et al. (2019)</td></tr><tr><td>J0534+2200</td><td>2.0<sup>+0.4</sup><sub>-0.3</sub></td><td>P</td><td>Brown et al. (2021)</td></tr><tr><td>J0540-6919</td><td>49.7 ± 1.1</td><td>O</td><td>Walker (2012)</td></tr><tr><td>J0554+3107</td><td>&lt;9.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0622+3749</td><td>&lt;8.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0631+0646</td><td>4.6 ± 1.8</td><td>DM</td><td>Wu et al. (2018)</td></tr><tr><td>J0631+1036</td><td>2.1 ± 0.8</td><td>DM</td><td>Weltevrede et al. (2010a)</td></tr><tr><td>J0633+0632</td><td>&lt;9.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0633+1746</td><td>0.2 ± 0.1</td><td>P</td><td>Caraveo et al. (1996)</td></tr><tr><td>J0659+1414</td><td>0.29<sup>+0.03</sup><sub>-0.03</sub></td><td>P</td><td>Brisken et al. (2003)</td></tr><tr><td>J0729-1448</td><td>2.7 ± 1.1</td><td>DM</td><td>McEwen et al. (2020)</td></tr><tr><td>J0729-1836</td><td>2.0<sup>+0.4</sup><sub>-0.3</sub></td><td>P</td><td>Deller et al. (2019)</td></tr><tr><td>J0734-1559</td><td>&lt;9.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0742-2822</td><td>2.0<sup>+1.0</sup><sub>-0.8</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J0744-2525</td><td>&lt;10.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0802-5613</td><td>&lt;11.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J0834-4159</td><td>5.5 ± 2.2</td><td>DM</td><td>Kramer et al. (2003)</td></tr><tr><td>J0835-4510</td><td>0.28<sup>+0.10</sup><sub>-0.02</sub></td><td>P</td><td>Dodson et al. (2003)</td></tr><tr><td>J0908-4913</td><td>1.0<sup>+1.7</sup><sub>-0.7</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J0922+0638</td><td>1.1<sup>+0.2</sup><sub>-0.1</sub></td><td>P</td><td>Chatterjee et al. (2001)</td></tr><tr><td>J0940-5428</td><td>0.4 ± 0.2</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1016-5857</td><td>3.2 ± 1.3</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1019-5749</td><td>10.9 ± 4.4</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1023-5746</td><td>&lt;11.9</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1028-5819</td><td>1.4 ± 0.6</td><td>DM</td><td>Keith et al. (2008)</td></tr><tr><td>J1044-5737</td><td>&lt;11.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1048-5832</td><td>2.9<sup>+1.2</sup><sub>-0.7</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1055-6028</td><td>3.8 ± 1.5</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1057-5226</td><td>0.3 ± 0.2</td><td>O</td><td>Mignani et al. (2010)</td></tr><tr><td>J1057-5851</td><td>&lt;11.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1105-6037</td><td>&lt;12.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1105-6107</td><td>2.4 ± 0.9</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1111-6039</td><td>&lt;12.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1112-6103</td><td>4.5 ± 1.8</td><td>DM</td><td>Oswald et al. (2021)</td></tr><tr><td>J1119-6127</td><td>8.4 ± 0.4</td><td>K</td><td>Caswell et al. (2004)</td></tr><tr><td>J1124-5916</td><td>4.8<sup>+0.7</sup><sub>-1.2</sub></td><td>X</td><td>Gonzalez &amp; Safi-Harb (2003)</td></tr><tr><td>J1135-6055</td><td>&lt;13.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1139-6247</td><td>&lt;14.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1151-6108</td><td>2.2 ± 0.9</td><td>DM</td><td>Serylak et al. (2021)</td></tr><tr><td>J1203-6242</td><td>&lt;15.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1208-6238</td><td>&lt;15.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1224-6407</td><td>4.0 ± 2.0</td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1231-5113</td><td>&lt;10.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1231-6511</td><td>&lt;17.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1253-5820</td><td>1.6 ± 0.7</td><td>DM</td><td>D'Amico et al. (1998)</td></tr><tr><td>J1341-6220</td><td>12.6 ± 5.0</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1350-6225</td><td>&lt;17.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1357-6429</td><td>3.1 ± 1.2</td><td>DM</td><td>Lorimer et al. (2006)</td></tr><tr><td>J1358-6025</td><td>&lt;16.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1410-6132</td><td>13.5 ± 5.4</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1413-6205</td><td>&lt;18.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1418-6058</td><td>1.6 ± 0.7</td><td>O</td><td>Yadigaroglu &amp; Romani (1997)</td></tr><tr><td>J1420-6048</td><td>5.6 ± 2.3</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1422-6138</td><td>&lt;18.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr></tbody></table>

<table><caption>**Table 7**
(Continued)</caption><thead><tr><th>Pulsar Name</th><th>Distance (kpc)</th><th>Method</th><th>Reference</th></tr></thead><tbody><tr><td>J1429-5911</td><td>&lt;17.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1447-5757</td><td>&lt;18.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1459-6053</td><td>&lt;19.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1509-5850</td><td>3.4 ± 1.3</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1513-5908</td><td>4.4<sup>+1.3</sup><sub>-0.8</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1522-5735</td><td>&lt;19.3</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1528-5838</td><td>&lt;20.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1531-5610</td><td>2.8 ± 1.1</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1614-5048</td><td>5.1 ± 2.1</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1615-5137</td><td>&lt;18.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1620-4927</td><td>&lt;18.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1623-5005</td><td>&lt;18.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1624-4041</td><td>&lt;18.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1641-5317</td><td>&lt;22.3</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1646-4346</td><td>6.2 ± 2.5</td><td>DM</td><td>Hobbs et al. (2004a)</td></tr><tr><td>J1648-4611</td><td>4.5 ± 1.8</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1650-4601</td><td>&lt;22.6</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1702-4128</td><td>4.0 ± 1.6</td><td>DM</td><td>Oswald et al. (2021)</td></tr><tr><td>J1705-1906</td><td>0.7 ± 0.3</td><td>DM</td><td>Hobbs et al. (2004b)</td></tr><tr><td>J1709-4429</td><td>2.6<sup>+0.5</sup><sub>-0.6</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1714-3830</td><td>&lt;20.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1718-3825</td><td>3.5 ± 1.4</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1730-3350</td><td>3.5 ± 1.4</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1731-4744</td><td>0.7<sup>+0.1</sup><sub>-0.3</sub></td><td>O</td><td>Shternin et al. (2019)</td></tr><tr><td>J1732-3131</td><td>0.6 ± 0.3</td><td>DM</td><td>Maan et al. (2012, 2017)</td></tr><tr><td>J1736-3422</td><td>&lt;21.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1739-3023</td><td>3.1 ± 1.2</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1740+1000</td><td>1.2 ± 0.5</td><td>DM</td><td>Bilous et al. (2016)</td></tr><tr><td>J1741-2054</td><td>0.3<sup>+0.7</sup><sub>-0.1</sub></td><td>O</td><td>Brownsberger &amp; Romani (2014)</td></tr><tr><td>J1742-3321</td><td>&lt;22.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1746-3239</td><td>&lt;22.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1747-2958</td><td>4.8 ± 0.8</td><td>X</td><td>Gaensler et al. (2004)</td></tr><tr><td>J1748-2815</td><td>&lt;20.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1757-2421</td><td>3.1 ± 1.2</td><td>DM</td><td>Hobbs et al. (2004b)</td></tr><tr><td>J1801-2451</td><td>3.8 ± 1.5</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1803-2149</td><td>&lt;21.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1809-2332</td><td>1.7 ± 1.0</td><td>K</td><td>Oka et al. (1999)</td></tr><tr><td>J1813-1246</td><td>&lt;22.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1816-0755</td><td>3.2 ± 1.3</td><td>DM</td><td>McEwen et al. (2020)</td></tr><tr><td>J1817-1742</td><td>&lt;22.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1826-1256</td><td>&lt;19.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1827-1446</td><td>&lt;22.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1828-1101</td><td>4.8 ± 1.9</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1831-0952</td><td>3.7 ± 1.5</td><td>DM</td><td>Lorimer et al. (2006)</td></tr><tr><td>J1833-1034</td><td>4.1 ± 0.3</td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1835-1106</td><td>3.2 ± 1.3</td><td>DM</td><td>D'Amico et al. (1998)</td></tr><tr><td>J1836+5925</td><td>0.5 ± 0.3</td><td>X</td><td>Halpern et al. (2002)</td></tr><tr><td>J1837-0604</td><td>4.8 ± 1.9</td><td>DM</td><td>Oswald et al. (2021)</td></tr><tr><td>J1838-0537</td><td>&lt;18.2</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1841-0524</td><td>4.1 ± 1.7</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1844-0346</td><td>&lt;17.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1846+0919</td><td>&lt;21.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1846-0258</td><td>5.8<sup>+0.5</sup><sub>-0.4</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1853-0004</td><td>5.3 ± 2.1</td><td>DM</td><td>Petroff et al. (2013)</td></tr><tr><td>J1856+0113</td><td>3.3 ± 0.6</td><td>K</td><td>Caswell et al. (1975)</td></tr><tr><td>J1857+0143</td><td>4.6 ± 1.8</td><td>DM</td><td>Serylak et al. (2021)</td></tr><tr><td>J1906+0722</td><td>&lt;18.9</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1907+0602</td><td>2.6 ± 1.0</td><td>DM</td><td>Abdo et al. (2010d)</td></tr><tr><td>J1913+0904</td><td>3.0 ± 1.2</td><td>DM</td><td>Lorimer et al. (2006)</td></tr><tr><td>J1913+1011</td><td>4.6 ± 1.8</td><td>DM</td><td>Morris et al. (2002)</td></tr><tr><td>J1925+1720</td><td>5.0 ± 2.0</td><td>DM</td><td>Serylak et al. (2021)</td></tr><tr><td>J1928+1746</td><td>4.3 ± 1.7</td><td>DM</td><td>Nice et al. (2013)</td></tr><tr><td>J1932+1916</td><td>&lt;17.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr></tbody></table>
<table><caption>**Table 7**
(Continued)</caption><thead><tr><th>Pulsar Name</th><th>Distance (kpc)</th><th>Method</th><th>Reference</th></tr></thead><tbody><tr><td>J1932+2220</td><td>10.9<sup>+1.3</sup><sub>-0.8</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1935+2025</td><td>4.6 ± 1.8</td><td>DM</td><td>Lorimer et al. (2013)</td></tr><tr><td>J1952+3252</td><td>3.0 ± 2.0</td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1954+2836</td><td>&lt;16.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1954+3852</td><td>4.7 ± 1.9</td><td>DM</td><td>McEwen et al. (2020)</td></tr><tr><td>J1957+5033</td><td>&lt;14.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1958+2846</td><td>&lt;16.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2006+3102</td><td>6.0 ± 2.4</td><td>DM</td><td>Nice et al. (2013)</td></tr><tr><td>J2017+3625</td><td>&lt;15.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2021+3651</td><td>1.8<sup>+1.7</sup><sub>-1.4</sub></td><td>atnfA</td><td>Kirichenko et al. (2015)</td></tr><tr><td>J2021+4026</td><td>1.5 ± 0.4</td><td>K</td><td>Landecker et al. (1980)</td></tr><tr><td>J2022+3842</td><td>10.0<sup>+4.0</sup><sub>-2.0</sub></td><td>O</td><td>Arzoumanian et al. (2011)</td></tr><tr><td>J2028+3332</td><td>&lt;14.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2030+3641</td><td>3.0 ± 1.0</td><td>O</td><td>Camilo et al. (2012)</td></tr><tr><td>J2030+4415</td><td>0.5<sup>+0.3</sup><sub>-0.2</sub></td><td>O</td><td>de Vries & Romani (2022)</td></tr><tr><td>J2032+4127</td><td>1.8 ± 0.1</td><td>P</td><td>Brown et al. (2021)</td></tr><tr><td>J2043+2740</td><td>1.5 ± 0.6</td><td>DM</td><td>Bilous et al. (2016)</td></tr><tr><td>J2055+2539</td><td>&lt;10.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2111+4606</td><td>&lt;12.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2139+4716</td><td>&lt;12.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2208+4056</td><td>0.8 ± 0.3</td><td>DM</td><td>Lynch et al. (2018)</td></tr><tr><td>J2229+6114</td><td>3.0 ± 1.2</td><td>X</td><td>Halpern et al. (2001)</td></tr><tr><td>J2238+5903</td><td>&lt;11.3</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2240+5832</td><td>7.3 ± 2.9</td><td>DM</td><td>Theureau et al. (2011)</td></tr></tbody></table>

**Note.** The best known distances of the 150 young pulsars detected by the Fermi LAT. For the DM method, the reference is for the dispersion measurement, and the distance was obtained with the YMW16 model for the Galactic electron density (Yao et al. 2017). “DMM” is the distance at which the YMW16 DM reaches 95% of its maximum value for that line of sight. Method “P” is parallax, “K” is kinetic (H I absorption), “KPLK” combines the two and corrects for Lutz-Kelker bias (Verbiest et al. 2012), “X” indicates an X-ray measurement of the hydrogen column density, and “O” englobes optical and other methods.

by between 1% and 50%. The YMW16 model therefore returns the distance to the Galaxy’s edge. Modeled DM saturates much closer to Earth, increasing slowly thereafter. For example, toward PSR J1327−0755, 95% of DMmax occurs at 3.7 kpc, compared to 25 kpc returned by the code, and in better agreement with the 1.7 kpc NE2001 distance. Therefore, for pulsars with DM > DMmax, we use the YMW16 distance for 95% of DMmax. Other pulsars cited in this catalog for which this occurs are PSR J1102+02 (Table 6), and PSRs J1302−03, J2051+4434g and J2052+4421G (Table 5).

For 63 pulsars we have no DM measurement or other distance estimator. We again calculate the YMW16 distance for 95% of DMmax, but use it as an upper limit. The method is “DMM” in Tables 7 and 8, and these radio-quiet pulsars are illustrated in Figure 8.

Both Espinoza et al. (2013) and 2PC discussed the problem of PSR J0610−2100 having gamma-ray efficiency $η = L_γ/\dot{E} > 1$, using the DM distances of 3.3 and 4 kpc. van der Wateren et al. (2022) used LOFAR timing and optical modeling for this system to find $d = 2.2 \pm 0.7$ kpc. Espinoza et al. (2013) pointed out that the line of sight to the pulsar grazes the electron overdensities bordering the Local Bubble, in both electron models. A slight extension of the modeled bubble

yields the increase in modeled DM needed to reconcile the distances. The closer distance for PSR J0610−2100 leads to $η \approx 50\%$. It also reduces the pulsar’s transverse velocity to $v_T \approx 220$ km s$^{-1}$, so that this MSP is no longer among the fastest known.

### 4.3. Doppler Corrections

Many pulsar characteristics depend on the intrinsic spin period $P^{\text{int}}$ and spindown rate $\dot{P}^{\text{int}}$. The Doppler shift of the observed period is $P = (1 + v_R/c)P^{\text{int}}$, where $v_R$ is the pulsar’s radial velocity along the unit vector $\mathbf{n}$ from the solar system. The Doppler correction to $\dot{P}$ is obtained by differentiating the equation and separating the effects of the system’s proper motion (Shklovskii 1970) from the acceleration due to Galactic rotation (the treatment by Damour & Taylor 1991 is particularly clear). The result is

$$ \dot{P}^{\text{int}} = \dot{P} - \dot{P}^{\text{shk}} - \dot{P}^{\text{gal}} \quad (3) $$

with

$$ \begin{aligned} \dot{P}^{\text{shk}} &= \frac{1}{c} \mu^2 d P \\ &= k \left( \frac{\mu}{\text{mas yr}^{-1}} \right)^2 \left( \frac{d}{\text{kpc}} \right) \left( \frac{P}{\text{s}} \right) \end{aligned} \quad (4) $$

and

$$ \dot{P}^{\text{gal}} = \frac{1}{c} \mathbf{n} \cdot (\mathbf{a}_1 - \mathbf{a}_0) P \quad (5) $$

where $k = 2.43 \times 10^{-21}$ for pulsar distance $d$ and proper-motion transverse to the line of sight $\mu$. In 2PC, we obtained the accelerations $\mathbf{a}_1$ of the pulsar and $\mathbf{a}_0$ of the Sun using the Galactic potential model of Carlberg & Innanen (1987) and Kuijken & Gilmore (1989). Here, we instead use GalPot$^{120}$ with the PJM17_best.Tpot parameter set (McMillan 2017).

The corrections are negligible for the young gamma-ray pulsars, which all have $\dot{P} > 10^{-17}$. However, for MSPs $\dot{P}^{\text{int}}$ can differ noticeably from observed $\dot{P}$. Expressing the correction magnitude as

$$ \xi = (\dot{P}^{\text{shk}} + \dot{P}^{\text{gal}})/\dot{P} = (\dot{P} - \dot{P}^{\text{int}})/\dot{P} \quad (6) $$

leads to $\dot{E}^{\text{int}} = \dot{E} (1 - \xi)$. For $\mu \lesssim 10$ mas yr$^{-1}$ and $d \lesssim 1$ kpc, $\dot{P}^{\text{shk}}$ and $\dot{P}^{\text{gal}}$ have comparable magnitudes and opposite signs. For larger $\mu^2 d$, $\dot{P}^{\text{shk}}$ dominates.

Table 8 lists $d$, $\mu$, their uncertainties $\delta d$, $\delta\mu$, and the resulting corrections. When we have no $\mu$ measurement and only a limit for $d$, we leave the last columns empty. Parentheses around the $\mu \pm \delta\mu$ value indicate that the measurement is insignificant, $\delta\mu/\mu > 3$, and we express the remaining columns as limits calculated using $\mu_{\text{max}} < \mu + 2\delta\mu$. In parentheses in the $\dot{P}^{\text{gal}}$ column are shown the minimum and maximum values for that direction for distances from 500 pc to the limit. Given a distance but no proper-motion value, we calculate $\dot{P}^{\text{gal}}$ and limits on $\xi$, using $\dot{P}^{\text{shk}} \ge 0$. There are eight such MSPs, of which PSR J0605+3757 is listed first. In the same spirit, e.g., PSR J1335−5656 has measured proper motion but unknown distance, and we combine the limit for $\dot{P}^{\text{shk}}$ with the extremum from the $\dot{P}^{\text{gal}}$ range.

<footnote>$^{120}$ https://github.com/PaulMcMillan-Astro/GalPot</footnote>
<table><caption>**Table 7**
(Continued)</caption><thead><tr><th>Pulsar Name</th><th>Distance (kpc)</th><th>Method</th><th>Reference</th></tr></thead><tbody><tr><td>J1932+2220</td><td>10.9<sup>+1.3</sup><sub>-0.8</sub></td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1935+2025</td><td>4.6 ± 1.8</td><td>DM</td><td>Lorimer et al. (2013)</td></tr><tr><td>J1952+3252</td><td>3.0 ± 2.0</td><td>KPLK</td><td>Verbiest et al. (2012)</td></tr><tr><td>J1954+2836</td><td>&lt;16.4</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1954+3852</td><td>4.7 ± 1.9</td><td>DM</td><td>McEwen et al. (2020)</td></tr><tr><td>J1957+5033</td><td>&lt;14.7</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J1958+2846</td><td>&lt;16.1</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2006+3102</td><td>6.0 ± 2.4</td><td>DM</td><td>Nice et al. (2013)</td></tr><tr><td>J2017+3625</td><td>&lt;15.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2021+3651</td><td>1.8<sup>+1.7</sup><sub>-1.4</sub></td><td>atnfA</td><td>Kirichenko et al. (2015)</td></tr><tr><td>J2021+4026</td><td>1.5 ± 0.4</td><td>K</td><td>Landecker et al. (1980)</td></tr><tr><td>J2022+3842</td><td>10.0<sup>+4.0</sup><sub>-2.0</sub></td><td>O</td><td>Arzoumanian et al. (2011)</td></tr><tr><td>J2028+3332</td><td>&lt;14.5</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2030+3641</td><td>3.0 ± 1.0</td><td>O</td><td>Camilo et al. (2012)</td></tr><tr><td>J2030+4415</td><td>0.5<sup>+0.3</sup><sub>-0.2</sub></td><td>O</td><td>de Vries & Romani (2022)</td></tr><tr><td>J2032+4127</td><td>1.8 ± 0.1</td><td>P</td><td>Brown et al. (2021)</td></tr><tr><td>J2043+2740</td><td>1.5 ± 0.6</td><td>DM</td><td>Bilous et al. (2016)</td></tr><tr><td>J2055+2539</td><td>&lt;10.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2111+4606</td><td>&lt;12.8</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2139+4716</td><td>&lt;12.0</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2208+4056</td><td>0.8 ± 0.3</td><td>DM</td><td>Lynch et al. (2018)</td></tr><tr><td>J2229+6114</td><td>3.0 ± 1.2</td><td>X</td><td>Halpern et al. (2001)</td></tr><tr><td>J2238+5903</td><td>&lt;11.3</td><td>DMM</td><td>Yao et al. (2017)</td></tr><tr><td>J2240+5832</td><td>7.3 ± 2.9</td><td>DM</td><td>Theureau et al. (2011)</td></tr></tbody></table>

**Note.** The best known distances of the 150 young pulsars detected by the Fermi LAT. For the DM method, the reference is for the dispersion measurement, and the distance was obtained with the YMW16 model for the Galactic electron density (Yao et al. 2017). “DMM” is the distance at which the YMW16 DM reaches 95% of its maximum value for that line of sight. Method “P” is parallax, “K” is kinetic (H I absorption), “KPLK” combines the two and corrects for Lutz-Kelker bias (Verbiest et al. 2012), “X” indicates an X-ray measurement of the hydrogen column density, and “O” englobes optical and other methods.

by between 1% and 50%. The YMW16 model therefore returns the distance to the Galaxy’s edge. Modeled DM saturates much closer to Earth, increasing slowly thereafter. For example, toward PSR J1327−0755, 95% of DMmax occurs at 3.7 kpc, compared to 25 kpc returned by the code, and in better agreement with the 1.7 kpc NE2001 distance. Therefore, for pulsars with DM > DMmax, we use the YMW16 distance for 95% of DMmax. Other pulsars cited in this catalog for which this occurs are PSR J1102+02 (Table 6), and PSRs J1302−03, J2051+4434g and J2052+4421G (Table 5).

For 63 pulsars we have no DM measurement or other distance estimator. We again calculate the YMW16 distance for 95% of DMmax, but use it as an upper limit. The method is “DMM” in Tables 7 and 8, and these radio-quiet pulsars are illustrated in Figure 8.

Both Espinoza et al. (2013) and 2PC discussed the problem of PSR J0610−2100 having gamma-ray efficiency $\eta = L_{\gamma}/\dot{E} > 1$, using the DM distances of 3.3 and 4 kpc. van der Wateren et al. (2022) used LOFAR timing and optical modeling for this system to find $d = 2.2 \pm 0.7$ kpc. Espinoza et al. (2013) pointed out that the line of sight to the pulsar grazes the electron overdensities bordering the Local Bubble, in both electron models. A slight extension of the modeled bubble

yields the increase in modeled DM needed to reconcile the distances. The closer distance for PSR J0610−2100 leads to $\eta \approx 50\%$. It also reduces the pulsar’s transverse velocity to $v_T \approx 220$ km s$^{-1}$, so that this MSP is no longer among the fastest known.

### 4.3. Doppler Corrections

Many pulsar characteristics depend on the intrinsic spin period $P^{\text{int}}$ and spindown rate $\dot{P}^{\text{int}}$. The Doppler shift of the observed period is $P = (1 + v_R/c)P^{\text{int}}$, where $v_R$ is the pulsar’s radial velocity along the unit vector $\mathbf{n}$ from the solar system. The Doppler correction to $\dot{P}$ is obtained by differentiating the equation and separating the effects of the system’s proper motion (Shklovskii 1970) from the acceleration due to Galactic rotation (the treatment by Damour & Taylor 1991 is particularly clear). The result is

$$ \dot{P}^{\text{int}} = \dot{P} - \dot{P}^{\text{shk}} - \dot{P}^{\text{gal}} \quad (3) $$

with

$$ \begin{aligned} \dot{P}^{\text{shk}} &= \frac{1}{c} \mu^2 d P \\ &= k \left( \frac{\mu}{\text{mas yr}^{-1}} \right)^2 \left( \frac{d}{\text{kpc}} \right) \left( \frac{P}{\text{s}} \right) \end{aligned} \quad (4) $$

and

$$ \dot{P}^{\text{gal}} = \frac{1}{c} \mathbf{n} \cdot (\mathbf{a}_1 - \mathbf{a}_0) P \quad (5) $$

where $k = 2.43 \times 10^{-21}$ for pulsar distance $d$ and proper-motion transverse to the line of sight $\mu$. In 2PC, we obtained the accelerations $\mathbf{a}_1$ of the pulsar and $\mathbf{a}_0$ of the Sun using the Galactic potential model of Carlberg & Innanen (1987) and Kuijken & Gilmore (1989). Here, we instead use GalPot$^{120}$ with the PJM17_best.Tpot parameter set (McMillan 2017).

The corrections are negligible for the young gamma-ray pulsars, which all have $\dot{P} > 10^{-17}$. However, for MSPs $\dot{P}^{\text{int}}$ can differ noticeably from observed $\dot{P}$. Expressing the correction magnitude as

$$ \xi = (\dot{P}^{\text{shk}} + \dot{P}^{\text{gal}})/\dot{P} = (\dot{P} - \dot{P}^{\text{int}})/\dot{P} \quad (6) $$

leads to $\dot{E}^{\text{int}} = \dot{E} (1 - \xi)$. For $\mu \lesssim 10$ mas yr$^{-1}$ and $d \lesssim 1$ kpc, $\dot{P}^{\text{shk}}$ and $\dot{P}^{\text{gal}}$ have comparable magnitudes and opposite signs. For larger $\mu^2 d$, $\dot{P}^{\text{shk}}$ dominates.

Table 8 lists $d$, $\mu$, their uncertainties $\delta d$, $\delta\mu$, and the resulting corrections. When we have no $\mu$ measurement and only a limit for $d$, we leave the last columns empty. Parentheses around the $\mu \pm \delta\mu$ value indicate that the measurement is insignificant, $\delta\mu/\mu > 3$, and we express the remaining columns as limits calculated using $\mu_{\text{max}} < \mu + 2\delta\mu$. In parentheses in the $\dot{P}^{\text{gal}}$ column are shown the minimum and maximum values for that direction for distances from 500 pc to the limit. Given a distance but no proper-motion value, we calculate $\dot{P}^{\text{gal}}$ and limits on $\xi$, using $\dot{P}^{\text{shk}} \ge 0$. There are eight such MSPs, of which PSR J0605+3757 is listed first. In the same spirit, e.g., PSR J1335−5656 has measured proper motion but unknown distance, and we combine the limit for $\dot{P}^{\text{shk}}$ with the extremum from the $\dot{P}^{\text{gal}}$ range.

<footnote>$^{120}$ https://github.com/PaulMcMillan-Astro/GalPot</footnote>
<table><caption>Table 8
Millisecond Pulsar Distances and Spindown Doppler Corrections</caption><thead><tr><th>PSR</th><th>d<br>(pc)</th><th>Method</th><th>Reference</th><th>μ<br>(mas yr<sup>-1</sup>)</th><th>Reference</th><th>P<sup>shk</sup><br>(10<sup>-21</sup>)</th><th>P<sup>gal</sup><br>(10<sup>-21</sup>)</th><th>E<sup>int</sup><br>(10<sup>33</sup> erg s<sup>-1</sup>)</th><th>(1 − ξ)</th></tr></thead><tbody><tr><td>J0023+0923</td><td>1790<sup>+510</sup><sub>-320</sub></td><td>P</td><td>Alam et al. (2021)</td><td>13.9 ± 0.1</td><td>Same</td><td>2.57</td><td>-0.59</td><td>12.4<sup>+1.0</sup><sub>-0.7</sub></td><td>0.82</td></tr><tr><td>J0030+0451</td><td>320 ± 10</td><td>P</td><td>Alam et al. (2021)</td><td>6.4 ± 0.1</td><td>Same</td><td>0.15</td><td>-0.52</td><td>3.602 ± 0.003</td><td>1.0</td></tr><tr><td>J0034-0534</td><td>1340 ± 530</td><td>DM</td><td>Abdo et al. (2010e)</td><td>12.1 ± 0.5</td><td>Desvignes et al. (2016)</td><td>0.90</td><td>-0.40</td><td>26.6 ± 2.2</td><td>0.90</td></tr><tr><td>J0101-6422</td><td>1000 ± 400</td><td>DM</td><td>Spiewak et al. (2022)</td><td>17.3 ± 0.5</td><td>LAT</td><td>1.87</td><td>-0.51</td><td>8.0 ± 1.8</td><td>0.72</td></tr><tr><td>J0102+4839</td><td>2310 ± 920</td><td>DM</td><td>Hessels et al. (2011)</td><td>4.1 ± 0.3</td><td>NRT</td><td>0.28</td><td>-0.14</td><td>17.6 ± 0.2</td><td>0.99</td></tr><tr><td>J0154+1833</td><td>1620 ± 640</td><td>DM</td><td>Martinez et al. (2019)</td><td>13.6 ± 1.5</td><td>Same</td><td>1.72</td><td>-0.17</td><td>3.8 ± 2.4</td><td>0.45</td></tr><tr><td>J0218+4232</td><td>3150<sup>+850</sup><sub>-600</sub></td><td>PLK</td><td>Verbiest & Lorimer (2014)</td><td>6.5 ± 0.1</td><td>Du et al. (2014)</td><td>0.76</td><td>0.11</td><td>241.9<sup>+0.7</sup><sub>-0.5</sub></td><td>0.99</td></tr><tr><td>J0248+4230</td><td>1850 ± 740</td><td>DM</td><td>Bhattacharyya et al. (2021)</td><td>(6.0 ± 3.3)</td><td>Same</td><td>&lt;1.8</td><td>0.09</td><td>&gt;33</td><td>&gt;0.89</td></tr><tr><td>J0251+2606</td><td>1170 ± 460</td><td>DM</td><td>Deneva et al. (2021)</td><td>17.8 ± 3.6</td><td>LAT</td><td>2.30</td><td>-0.03</td><td>12.8 ± 3.2</td><td>0.70</td></tr><tr><td>J0307+7443</td><td>380 ± 150</td><td>DM</td><td>Hessels et al. (2011)</td><td>(2.6 ± 1.1)</td><td>LAT</td><td>&lt;0.1</td><td>-0.04</td><td>&gt;22</td><td>&gt;1.00</td></tr><tr><td>J0312-0921</td><td>810 ± 320</td><td>DM</td><td>Tabassum et al. (2021)</td><td>32.2 ± 0.6</td><td>LAT</td><td>7.62</td><td>-0.35</td><td>9.7 ± 2.4</td><td>0.63</td></tr><tr><td>J0318+0253</td><td>1320 ± 530</td><td>DM</td><td>Wang et al. (2021)</td><td>(10.3 ± 13.1)</td><td>LAT</td><td>&lt;22.4</td><td>-0.21</td><td>&gt; -1.3</td><td>&gt; -0.26</td></tr><tr><td>J0340+4130</td><td>1600 ± 640</td><td>DM</td><td>Arzoumanian et al. (2018)</td><td>3.4 ± 0.3</td><td>Same</td><td>0.15</td><td>0.22</td><td>6.1 ± 0.1</td><td>0.94</td></tr><tr><td>J0418+6635</td><td>2200 ± 880</td><td>DM</td><td>Tabassum et al. (2021)</td><td>(2.3 ± 1.0)</td><td>LAT</td><td>&lt;0.3</td><td>0.14</td><td>&gt;21</td><td>&gt;0.97</td></tr><tr><td>J0437-4715</td><td>150 ± 10</td><td>P</td><td>Reardon et al. (2016)</td><td>140.91 ± 0.00</td><td>Same</td><td>43.57</td><td>-0.28</td><td>2.9 ± 0.6</td><td>0.24</td></tr><tr><td>J0533+6759</td><td>2390 ± 950</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>(1.6 ± 0.7)</td><td>LAT</td><td>&lt;0.2</td><td>0.24</td><td>&gt;5.7</td><td>&gt;0.96</td></tr><tr><td>J0605+3757</td><td>210 ± 80</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td></td><td></td><td></td><td>0.04</td><td>≤9.1</td><td>≤0.99</td></tr><tr><td>J0610-2100</td><td>2200 ± 700</td><td>P</td><td>van der Wateren et al. (2022)</td><td>18.80 ± 0.03</td><td>Same</td><td>7.29</td><td>-0.07</td><td>3.5 ± 1.6</td><td>0.41</td></tr><tr><td>J0613-0200</td><td>780 ± 70</td><td>P</td><td>Desvignes et al. (2016)</td><td>10.51 ± 0.01</td><td>Reardon et al. (2021)</td><td>0.64</td><td>0.07</td><td>12.2 ± 0.1</td><td>0.93</td></tr><tr><td>J0614-3329</td><td>630 ± 100</td><td>O</td><td>Bassa et al. (2016a)</td><td>2.0 ± 0.1</td><td>Guillemot et al. (2016)</td><td>0.02</td><td>-0.18</td><td>22.69 ± 0.02</td><td>1.0</td></tr><tr><td>J0621+2514</td><td>1640 ± 650</td><td>DM</td><td>Spiewak et al. (2022)</td><td>(10.9 ± 52.0)</td><td>LAT</td><td>&lt;142.9</td><td>0.32</td><td>&gt; -232</td><td>&gt; -4.76</td></tr><tr><td>J0636+5128</td><td>710<sup>+190</sup><sub>-120</sub></td><td>P</td><td>Alam et al. (2021)</td><td>3.63 ± 0.03</td><td>NRT</td><td>0.07</td><td>0.06</td><td>5.60<sup>+0.06</sup><sub>-0.04</sub></td><td>0.96</td></tr><tr><td>J0653+4706</td><td>910 ± 360</td><td>DM</td><td>Bassa et al. (2018)</td><td>(1.6 ± 2.0)</td><td>JBO</td><td>&lt;0.3</td><td>0.17</td><td>&gt;7.4</td><td>&gt;0.98</td></tr><tr><td>J0737-3039A</td><td>735 ± 60</td><td>P</td><td>Kramer et al. (2021)</td><td>3.31 ± 0.03</td><td>Same</td><td>0.44</td><td>-0.88</td><td>5.942 ± 0.001</td><td>1.0</td></tr><tr><td>J0740+6620</td><td>1150 ± 160</td><td>atnfA</td><td>Fonseca et al. (2021)</td><td>32.55 ± 0.04</td><td>Cromartie et al. (2020)</td><td>8.53</td><td>-0.04</td><td>6.1 ± 2.0</td><td>0.30</td></tr><tr><td>J0751+1807</td><td>1110 ± 200</td><td>P</td><td>Desvignes et al. (2016)</td><td>13.7 ± 0.3</td><td>Same</td><td>1.76</td><td>0.09</td><td>5.6 ± 0.3</td><td>0.76</td></tr><tr><td>J0931-1902</td><td>3720 ± 1480</td><td>DM</td><td>Spiewak et al. (2022)</td><td>5.0 ± 0.1</td><td>Alam et al. (2021)</td><td>1.04</td><td>-0.73</td><td>1.3 ± 0.2</td><td>0.92</td></tr><tr><td>J0952-0607</td><td>6260<sup>+300</sup><sub>-400</sub></td><td>O</td><td>Kandel & Romani (2022)</td><td></td><td></td><td></td><td>-0.14</td><td>≤68</td><td>≤1.03</td></tr><tr><td>J0955-3947</td><td>490 ± 190</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.10</td><td>≤179</td><td>≤1.00</td></tr><tr><td>J0955-6150</td><td>2170 ± 860</td><td>DM</td><td>Spiewak et al. (2022)</td><td>1.8 ± 0.3</td><td>LAT</td><td>0.03</td><td>-0.40</td><td>73.3 ± 0.8</td><td>1.0</td></tr><tr><td>J1012-4235</td><td>370 ± 140</td><td>DM</td><td>Spiewak et al. (2022)</td><td>6.7 ± 1.0</td><td>LAT</td><td>0.13</td><td>-0.12</td><td>8.7 ± 0.1</td><td>1.00</td></tr><tr><td>J1023+0038</td><td>1360 ± 40</td><td>P</td><td>Brown et al. (2021)</td><td>17.98 ± 0.04</td><td>Deller et al. (2012)</td><td>1.82</td><td>-0.24</td><td>42.8 ± 0.4</td><td>0.77</td></tr><tr><td>J1024-0719</td><td>1220 ± 160</td><td>P</td><td>Bassa et al. (2016b)</td><td>59.76 ± 0.03</td><td>Reardon et al. (2021)</td><td>54.63</td><td>-0.74</td><td>-10.2 ± 2.1</td><td>-1.9</td></tr><tr><td>J1035-6720</td><td>1460 ± 580</td><td>DM</td><td>Spiewak et al. (2022)</td><td>11.0 ± 1.4</td><td>LAT</td><td>1.22</td><td>-0.37</td><td>76.2 ± 1.0</td><td>0.98</td></tr><tr><td>J1036-8317</td><td>2160<sup>+650</sup><sub>-270</sub></td><td>P</td><td>Brown et al. (2021)</td><td>11.7 ± 0.2</td><td>Gaia Collab. et al. (2021)</td><td>2.44</td><td>-0.78</td><td>28.8<sup>+0.8</sup><sub>-0.3</sub></td><td>0.95</td></tr><tr><td>J1048+2339</td><td>1320<sup>+560</sup><sub>-230</sub></td><td>P</td><td>Brown et al. (2021)</td><td>19.3 ± 0.3</td><td>Gaia Collab. et al. (2021)</td><td>5.60</td><td>-0.63</td><td>9.7<sup>+0.9</sup><sub>-0.4</sub></td><td>0.83</td></tr><tr><td>J1124-3653</td><td>990 ± 390</td><td>DM</td><td>Hessels et al. (2011)</td><td>5.0 ± 0.5</td><td>Bangale et al. (2023)</td><td>0.14</td><td>-0.30</td><td>16.7 ± 0.3</td><td>1.0</td></tr><tr><td>J1125-5825</td><td>1740 ± 690</td><td>DM</td><td>Spiewak et al. (2022)</td><td>10.3 ± 0.3</td><td>Ng et al. (2014)</td><td>1.39</td><td>-0.43</td><td>79.5 ± 0.8</td><td>0.98</td></tr><tr><td>J1125-6014</td><td>980 ± 390</td><td>DM</td><td>Spiewak et al. (2022)</td><td>17.13 ± 0.01</td><td>Reardon et al. (2021)</td><td>1.85</td><td>-0.19</td><td>4.5 ± 1.6</td><td>0.55</td></tr><tr><td>J1137+7528</td><td>3830 ± 1530</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td></td><td></td><td></td><td>-0.16</td><td>≤8.4</td><td>≤1.05</td></tr><tr><td>J1142+0119</td><td>2160 ± 860</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>(105.0 ± 62.0)</td><td>Same</td><td>&lt;1404.1</td><td>-1.26</td><td>&gt; -418</td><td>&gt; -92.52</td></tr><tr><td>J1207-5050</td><td>1260 ± 500</td><td>DM</td><td>Spiewak et al. (2022)</td><td>7.0 ± 0.5</td><td>Bhattacharyya et al. (2021)</td><td>0.73</td><td>-0.52</td><td>2.0 ± 0.1</td><td>0.97</td></tr><tr><td>J1221-0633</td><td>1250 ± 500</td><td>DM</td><td>McEwen et al. (2020)</td><td>(44.2 ± 20.0)</td><td>LAT</td><td>&lt;41.5</td><td>-0.41</td><td>&gt; -165</td><td>&gt; -2.79</td></tr><tr><td>J1227-4853</td><td>1750<sup>+490</sup><sub>-200</sub></td><td>P</td><td>Brown et al. (2021)</td><td>20.1 ± 0.2</td><td>Jennings et al. (2018)</td><td>2.92</td><td>-0.26</td><td>87.3<sup>+6.7</sup><sub>-2.8</sub></td><td>0.80</td></tr><tr><td>J1231-1411</td><td>420 ± 100</td><td>O</td><td>Testa et al. (2015)</td><td>62.0 ± 0.1</td><td>NRT</td><td>14.41</td><td>-0.39</td><td>5.7 ± 2.7</td><td>0.34</td></tr><tr><td>J1259-8148</td><td>1420 ± 560</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.28</td><td>≤16</td><td>≤1.08</td></tr></tbody></table>
<table><caption>Table 8
Millisecond Pulsar Distances and Spindown Doppler Corrections</caption><thead><tr><th>PSR</th><th>d<br>(pc)</th><th>Method</th><th>Reference</th><th>μ<br>(mas yr<sup>-1</sup>)</th><th>Reference</th><th>P<sup>shk</sup><br>(10<sup>-21</sup>)</th><th>P<sup>gal</sup><br>(10<sup>-21</sup>)</th><th>E<sup>int</sup><br>(10<sup>33</sup> erg s<sup>-1</sup>)</th><th>(1 - ξ)</th></tr></thead><tbody><tr><td>J0023+0923</td><td>1790<sup>+510</sup><sub>-320</sub></td><td>P</td><td>Alam et al. (2021)</td><td>13.9 ± 0.1</td><td>Same</td><td>2.57</td><td>-0.59</td><td>12.4<sup>+1.0</sup><sub>-0.7</sub></td><td>0.82</td></tr><tr><td>J0030+0451</td><td>320 ± 10</td><td>P</td><td>Alam et al. (2021)</td><td>6.4 ± 0.1</td><td>Same</td><td>0.15</td><td>-0.52</td><td>3.602 ± 0.003</td><td>1.0</td></tr><tr><td>J0034-0534</td><td>1340 ± 530</td><td>DM</td><td>Abdo et al. (2010e)</td><td>12.1 ± 0.5</td><td>Desvignes et al. (2016)</td><td>0.90</td><td>-0.40</td><td>26.6 ± 2.2</td><td>0.90</td></tr><tr><td>J0101-6422</td><td>1000 ± 400</td><td>DM</td><td>Spiewak et al. (2022)</td><td>17.3 ± 0.5</td><td>LAT</td><td>1.87</td><td>-0.51</td><td>8.0 ± 1.8</td><td>0.72</td></tr><tr><td>J0102+4839</td><td>2310 ± 920</td><td>DM</td><td>Hessels et al. (2011)</td><td>4.1 ± 0.3</td><td>NRT</td><td>0.28</td><td>-0.14</td><td>17.6 ± 0.2</td><td>0.99</td></tr><tr><td>J0154+1833</td><td>1620 ± 640</td><td>DM</td><td>Martinez et al. (2019)</td><td>13.6 ± 1.5</td><td>Same</td><td>1.72</td><td>-0.17</td><td>3.8 ± 2.4</td><td>0.45</td></tr><tr><td>J0218+4232</td><td>3150<sup>+850</sup><sub>-600</sub></td><td>PLK</td><td>Verbiest & Lorimer (2014)</td><td>6.5 ± 0.1</td><td>Du et al. (2014)</td><td>0.76</td><td>0.11</td><td>241.9<sup>+0.7</sup><sub>-0.5</sub></td><td>0.99</td></tr><tr><td>J0248+4230</td><td>1850 ± 740</td><td>DM</td><td>Bhattacharyya et al. (2021)</td><td>(6.0 ± 3.3)</td><td>Same</td><td>&lt;1.8</td><td>0.09</td><td>&gt;33</td><td>&gt;0.89</td></tr><tr><td>J0251+2606</td><td>1170 ± 460</td><td>DM</td><td>Deneva et al. (2021)</td><td>17.8 ± 3.6</td><td>LAT</td><td>2.30</td><td>-0.03</td><td>12.8 ± 3.2</td><td>0.70</td></tr><tr><td>J0307+7443</td><td>380 ± 150</td><td>DM</td><td>Hessels et al. (2011)</td><td>(2.6 ± 1.1)</td><td>LAT</td><td>&lt;0.1</td><td>-0.04</td><td>&gt;22</td><td>&gt;1.00</td></tr><tr><td>J0312-0921</td><td>810 ± 320</td><td>DM</td><td>Tabassum et al. (2021)</td><td>32.2 ± 0.6</td><td>LAT</td><td>7.62</td><td>-0.35</td><td>9.7 ± 2.4</td><td>0.63</td></tr><tr><td>J0318+0253</td><td>1320 ± 530</td><td>DM</td><td>Wang et al. (2021)</td><td>(10.3 ± 13.1)</td><td>LAT</td><td>&lt;22.4</td><td>-0.21</td><td>&gt; -1.3</td><td>&gt; -0.26</td></tr><tr><td>J0340+4130</td><td>1600 ± 640</td><td>DM</td><td>Arzoumanian et al. (2018)</td><td>3.4 ± 0.3</td><td>Same</td><td>0.15</td><td>0.22</td><td>6.1 ± 0.1</td><td>0.94</td></tr><tr><td>J0418+6635</td><td>2200 ± 880</td><td>DM</td><td>Tabassum et al. (2021)</td><td>(2.3 ± 1.0)</td><td>LAT</td><td>&lt;0.3</td><td>0.14</td><td>&gt;21</td><td>&gt;0.97</td></tr><tr><td>J0437-4715</td><td>150 ± 10</td><td>P</td><td>Reardon et al. (2016)</td><td>140.91 ± 0.00</td><td>Same</td><td>43.57</td><td>-0.28</td><td>2.9 ± 0.6</td><td>0.24</td></tr><tr><td>J0533+6759</td><td>2390 ± 950</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>(1.6 ± 0.7)</td><td>LAT</td><td>&lt;0.2</td><td>0.24</td><td>&gt;5.7</td><td>&gt;0.96</td></tr><tr><td>J0605+3757</td><td>210 ± 80</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td></td><td></td><td></td><td>0.04</td><td>&le;9.1</td><td>&le;0.99</td></tr><tr><td>J0610-2100</td><td>2200 ± 700</td><td>P</td><td>van der Wateren et al. (2022)</td><td>18.80 ± 0.03</td><td>Same</td><td>7.29</td><td>-0.07</td><td>3.5 ± 1.6</td><td>0.41</td></tr><tr><td>J0613-0200</td><td>780 ± 70</td><td>P</td><td>Desvignes et al. (2016)</td><td>10.51 ± 0.01</td><td>Reardon et al. (2021)</td><td>0.64</td><td>0.07</td><td>12.2 ± 0.1</td><td>0.93</td></tr><tr><td>J0614-3329</td><td>630 ± 100</td><td>O</td><td>Bassa et al. (2016a)</td><td>2.0 ± 0.1</td><td>Guillemot et al. (2016)</td><td>0.02</td><td>-0.18</td><td>22.69 ± 0.02</td><td>1.0</td></tr><tr><td>J0621+2514</td><td>1640 ± 650</td><td>DM</td><td>Spiewak et al. (2022)</td><td>(10.9 ± 52.0)</td><td>LAT</td><td>&lt;142.9</td><td>0.32</td><td>&gt; -232</td><td>&gt; -4.76</td></tr><tr><td>J0636+5128</td><td>710<sup>+190</sup><sub>-120</sub></td><td>P</td><td>Alam et al. (2021)</td><td>3.63 ± 0.03</td><td>NRT</td><td>0.07</td><td>0.06</td><td>5.60<sup>+0.06</sup><sub>-0.04</sub></td><td>0.96</td></tr><tr><td>J0653+4706</td><td>910 ± 360</td><td>DM</td><td>Bassa et al. (2018)</td><td>(1.6 ± 2.0)</td><td>JBO</td><td>&lt;0.3</td><td>0.17</td><td>&gt;7.4</td><td>&gt;0.98</td></tr><tr><td>J0737-3039A</td><td>735 ± 60</td><td>P</td><td>Kramer et al. (2021)</td><td>3.31 ± 0.03</td><td>Same</td><td>0.44</td><td>-0.88</td><td>5.942 ± 0.001</td><td>1.0</td></tr><tr><td>J0740+6620</td><td>1150 ± 160</td><td>atnfA</td><td>Fonseca et al. (2021)</td><td>32.55 ± 0.04</td><td>Cromartie et al. (2020)</td><td>8.53</td><td>-0.04</td><td>6.1 ± 2.0</td><td>0.30</td></tr><tr><td>J0751+1807</td><td>1110 ± 200</td><td>P</td><td>Desvignes et al. (2016)</td><td>13.7 ± 0.3</td><td>Same</td><td>1.76</td><td>0.09</td><td>5.6 ± 0.3</td><td>0.76</td></tr><tr><td>J0931-1902</td><td>3720 ± 1480</td><td>DM</td><td>Spiewak et al. (2022)</td><td>5.0 ± 0.1</td><td>Alam et al. (2021)</td><td>1.04</td><td>-0.73</td><td>1.3 ± 0.2</td><td>0.92</td></tr><tr><td>J0952-0607</td><td>6260<sup>+300</sup><sub>-400</sub></td><td>O</td><td>Kandel & Romani (2022)</td><td></td><td></td><td></td><td>-0.14</td><td>&le;68</td><td>&le;1.03</td></tr><tr><td>J0955-3947</td><td>490 ± 190</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.10</td><td>&le;179</td><td>&le;1.00</td></tr><tr><td>J0955-6150</td><td>2170 ± 860</td><td>DM</td><td>Spiewak et al. (2022)</td><td>1.8 ± 0.3</td><td>LAT</td><td>0.03</td><td>-0.40</td><td>73.3 ± 0.8</td><td>1.0</td></tr><tr><td>J1012-4235</td><td>370 ± 140</td><td>DM</td><td>Spiewak et al. (2022)</td><td>6.7 ± 1.0</td><td>LAT</td><td>0.13</td><td>-0.12</td><td>8.7 ± 0.1</td><td>1.00</td></tr><tr><td>J1023+0038</td><td>1360 ± 40</td><td>P</td><td>Brown et al. (2021)</td><td>17.98 ± 0.04</td><td>Deller et al. (2012)</td><td>1.82</td><td>-0.24</td><td>42.8 ± 0.4</td><td>0.77</td></tr><tr><td>J1024-0719</td><td>1220 ± 160</td><td>P</td><td>Bassa et al. (2016b)</td><td>59.76 ± 0.03</td><td>Reardon et al. (2021)</td><td>54.63</td><td>-0.74</td><td>-10.2 ± 2.1</td><td>-1.9</td></tr><tr><td>J1035-6720</td><td>1460 ± 580</td><td>DM</td><td>Spiewak et al. (2022)</td><td>11.0 ± 1.4</td><td>LAT</td><td>1.22</td><td>-0.37</td><td>76.2 ± 1.0</td><td>0.98</td></tr><tr><td>J1036-8317</td><td>2160<sup>+650</sup><sub>-270</sub></td><td>P</td><td>Brown et al. (2021)</td><td>11.7 ± 0.2</td><td>Gaia Collab. et al. (2021)</td><td>2.44</td><td>-0.78</td><td>28.8<sup>+0.8</sup><sub>-0.3</sub></td><td>0.95</td></tr><tr><td>J1048+2339</td><td>1320<sup>+560</sup><sub>-230</sub></td><td>P</td><td>Brown et al. (2021)</td><td>19.3 ± 0.3</td><td>Gaia Collab. et al. (2021)</td><td>5.60</td><td>-0.63</td><td>9.7<sup>+0.9</sup><sub>-0.4</sub></td><td>0.83</td></tr><tr><td>J1124-3653</td><td>990 ± 390</td><td>DM</td><td>Hessels et al. (2011)</td><td>5.0 ± 0.5</td><td>Bangale et al. (2023)</td><td>0.14</td><td>-0.30</td><td>16.7 ± 0.3</td><td>1.0</td></tr><tr><td>J1125-5825</td><td>1740 ± 690</td><td>DM</td><td>Spiewak et al. (2022)</td><td>10.3 ± 0.3</td><td>Ng et al. (2014)</td><td>1.39</td><td>-0.43</td><td>79.5 ± 0.8</td><td>0.98</td></tr><tr><td>J1125-6014</td><td>980 ± 390</td><td>DM</td><td>Spiewak et al. (2022)</td><td>17.13 ± 0.01</td><td>Reardon et al. (2021)</td><td>1.85</td><td>-0.19</td><td>4.5 ± 1.6</td><td>0.55</td></tr><tr><td>J1137+7528</td><td>3830 ± 1530</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td></td><td></td><td></td><td>-0.16</td><td>&le;8.4</td><td>&le;1.05</td></tr><tr><td>J1142+0119</td><td>2160 ± 860</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>(105.0 ± 62.0)</td><td>Same</td><td>&lt;1404.1</td><td>-1.26</td><td>&gt; -418</td><td>&gt; -92.52</td></tr><tr><td>J1207-5050</td><td>1260 ± 500</td><td>DM</td><td>Spiewak et al. (2022)</td><td>7.0 ± 0.5</td><td>Bhattacharyya et al. (2021)</td><td>0.73</td><td>-0.52</td><td>2.0 ± 0.1</td><td>0.97</td></tr><tr><td>J1221-0633</td><td>1250 ± 500</td><td>DM</td><td>McEwen et al. (2020)</td><td>(44.2 ± 20.0)</td><td>LAT</td><td>&lt;41.5</td><td>-0.41</td><td>&gt; -165</td><td>&gt; -2.79</td></tr><tr><td>J1227-4853</td><td>1750<sup>+490</sup><sub>-200</sub></td><td>P</td><td>Brown et al. (2021)</td><td>20.1 ± 0.2</td><td>Jennings et al. (2018)</td><td>2.92</td><td>-0.26</td><td>87.3<sup>+6.7</sup><sub>-2.8</sub></td><td>0.80</td></tr><tr><td>J1231-1411</td><td>420 ± 100</td><td>O</td><td>Testa et al. (2015)</td><td>62.0 ± 0.1</td><td>NRT</td><td>14.41</td><td>-0.39</td><td>5.7 ± 2.7</td><td>0.34</td></tr><tr><td>J1259-8148</td><td>1420 ± 560</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.28</td><td>&le;16</td><td>&le;1.08</td></tr></tbody></table>
<table><caption>Table 8
(Continued)</caption><thead><tr><th>PSR</th><th>d<br>(pc)</th><th>Method</th><th>Reference</th><th>μ<br>(mas yr<sup>-1</sup>)</th><th>Reference</th><th>ρ<sup>shk</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>gal</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>int</sup><br>(10<sup>33</sup> erg s<sup>-1</sup>)</th><th>(1 - ξ)</th></tr></thead><tbody><tr><td>J1301+0833</td><td>1770 ± 110</td><td>O</td><td>Kandel & Romani (2022)</td><td>22.8 ± 3.5</td><td>LAT</td><td>4.11</td><td>-0.50</td><td>43.7 ± 8.2</td><td>0.66</td></tr><tr><td>J1302-3258</td><td>1430 ± 570</td><td>DM</td><td>Spiewak et al. (2022)</td><td>13.2 ± 0.7</td><td>NRT</td><td>2.28</td><td>-0.63</td><td>3.6 ± 0.7</td><td>0.75</td></tr><tr><td>J1306-6043</td><td>1310 ± 520</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.35</td><td>≤6.7</td><td>≤1.01</td></tr><tr><td>J1311-3430</td><td>1580<sup>+970</sup><sub>-350</sub></td><td>P</td><td>Brown et al. (2021)</td><td>9.1 ± 0.3</td><td>LAT</td><td>0.82</td><td>-0.43</td><td>48.3<sup>+1.3</sup><sub>-0.5</sub></td><td>0.98</td></tr><tr><td>J1312+0051</td><td>1470 ± 580</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>25.0 ± 0.9</td><td>Same</td><td>9.45</td><td>-1.05</td><td>4.5 ± 2.0</td><td>0.51</td></tr><tr><td>J1327-0755</td><td>3700 ± 1480</td><td>DM</td><td>Boyles et al. (2013)</td><td>(6.4 ± 4.2)</td><td>NRT</td><td>&lt;5.3</td><td>-1.15</td><td>&gt; -4.9</td><td>&gt; -1.31</td></tr><tr><td>J1335-5656</td><td>&lt;15040</td><td>DMM</td><td>Yao et al. (2017)</td><td>5.5 ± 1.2</td><td>C. J. Clark et al. (2023, in preparation)</td><td>&lt;3.5</td><td>(-2.9, -0.0)</td><td>&gt;4.0</td><td>&gt;0.71</td></tr><tr><td>J1400-1431</td><td>270<sup>+120</sup><sub>-60</sub></td><td>P</td><td>Swiggum et al. (2017)</td><td>42.9 ± 2.2</td><td>NRT</td><td>3.82</td><td>-0.20</td><td>4.9<sup>+2.3</sup><sub>-3.3</sub></td><td>0.50</td></tr><tr><td>J1402+1306</td><td>690 ± 270</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-1.00</td><td>≤2.8</td><td>≤1.07</td></tr><tr><td>J1431-4715</td><td>1770<sup>+530</sup><sub>-210</sub></td><td>P</td><td>Brown et al. (2021)</td><td>18.8 ± 0.3</td><td>Jennings et al. (2018)</td><td>3.06</td><td>-0.10</td><td>54.3<sup>+4.5</sup><sub>-1.8</sub></td><td>0.79</td></tr><tr><td>J1446-4701</td><td>1560 ± 620</td><td>DM</td><td>Spiewak et al. (2022)</td><td>5.3 ± 0.1</td><td>Reardon et al. (2021)</td><td>0.24</td><td>-0.06</td><td>36.2 ± 0.4</td><td>0.98</td></tr><tr><td>J1455-3330</td><td>680 ± 270</td><td>DM</td><td>Spiewak et al. (2022)</td><td>8.2 ± 0.1</td><td>Alam et al. (2021)</td><td>0.88</td><td>-0.23</td><td>1.83 ± 0.03</td><td>0.97</td></tr><tr><td>J1513-2550</td><td>3960 ± 1580</td><td>DM</td><td>Spiewak et al. (2022)</td><td>7.2 ± 0.2</td><td>NRT</td><td>1.06</td><td>-0.51</td><td>86.8<sup>+2.7</sup><sub>-2.1</sub></td><td>0.97</td></tr><tr><td>J1514-4946</td><td>900 ± 360</td><td>DM</td><td>Spiewak et al. (2022)</td><td>14.0 ± 0.7</td><td>LAT</td><td>1.55</td><td>0.05</td><td>14.6 ± 0.5</td><td>0.91</td></tr><tr><td>J1526-2744</td><td>1320 ± 520</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.08</td><td>≤9.2</td><td>≤1.02</td></tr><tr><td>J1536-4948</td><td>970 ± 390</td><td>DM</td><td>Bhattacharyya et al. (2021)</td><td>7.8 ± 0.3</td><td>Same</td><td>0.45</td><td>0.09</td><td>27.9 ± 0.2</td><td>0.97</td></tr><tr><td>J1543-5149</td><td>1140 ± 450</td><td>DM</td><td>Spiewak et al. (2022)</td><td>4.3 ± 0.5</td><td>PKS</td><td>0.11</td><td>0.07</td><td>72.2 ± 0.2</td><td>0.99</td></tr><tr><td>J1544+4937</td><td>2990<sup>+2000</sup><sub>-990</sub></td><td>O</td><td>Tang et al. (2014)</td><td>10.3 ± 0.3</td><td>NRT</td><td>1.66</td><td>-0.68</td><td>8.4<sup>+4.4</sup><sub>-2.2</sub></td><td>0.69</td></tr><tr><td>J1552+5437</td><td>2630 ± 1050</td><td>DM</td><td>Pleunis et al. (2017)</td><td>(3.4 ± 2.3)</td><td>LAT</td><td>&lt;1.0</td><td>-0.68</td><td>&gt;6.9</td><td>&gt;0.88</td></tr><tr><td>J1555-2908</td><td>5100<sup>+500</sup><sub>-700</sub></td><td>O</td><td>Kennedy et al. (2022)</td><td>(1.1 ± 1.9)</td><td>LAT</td><td>&lt;0.5</td><td>-0.28</td><td>&gt;306</td><td>&gt;0.99</td></tr><tr><td>J1600-3053</td><td>1920<sup>+360</sup><sub>-260</sub></td><td>P</td><td>Alam et al. (2021)</td><td>7.03 ± 0.03</td><td>Reardon et al. (2021)</td><td>0.83</td><td>0.15</td><td>7.21<sup>+0.13</sup><sub>-0.10</sub></td><td>0.90</td></tr><tr><td>J1614-2230</td><td>700 ± 300</td><td>P</td><td>Matthews et al. (2016)</td><td>32.4 ± 0.6</td><td>Alam et al. (2021)</td><td>5.62</td><td>0.018</td><td>5.0 ± 3.1</td><td>0.41</td></tr><tr><td>J1622-0315</td><td>1230<sup>+540</sup><sub>-180</sub></td><td>P</td><td>Brown et al. (2021)</td><td>13.4 ± 0.3</td><td>Gaia Collab. et al. (2021)</td><td>2.06</td><td>-0.24</td><td>6.6<sup>+0.6</sup><sub>-0.2</sub></td><td>0.84</td></tr><tr><td>J1623-6936</td><td>1290 ± 510</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.10</td><td>≤26</td><td>≤1.01</td></tr><tr><td>J1625-0021</td><td>950 ± 380</td><td>DM</td><td>Deneva et al. (2021)</td><td>(4.0 ± 1.8)</td><td>LAT</td><td>&lt;0.4</td><td>-0.18</td><td>&gt;37</td><td>&gt;0.99</td></tr><tr><td>J1627+3219</td><td>4470 ± 1780</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-1.04</td><td>≤25</td><td>≤1.19</td></tr><tr><td>J1628-3205</td><td>1190<sup>+620</sup><sub>-190</sub></td><td>P</td><td>Brown et al. (2021)</td><td>22.3 ± 0.4</td><td>Gaia Collab. et al. (2021)</td><td>4.62</td><td>0.20</td><td>11.9<sup>+2.9</sup><sub>-0.9</sub></td><td>0.67</td></tr><tr><td>J1630+3734</td><td>1180 ± 470</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>18.5 ± 0.2</td><td>JBO</td><td>3.28</td><td>-0.62</td><td>8.7 ± 1.4</td><td>0.75</td></tr><tr><td>J1640+2224</td><td>1510<sup>+170</sup><sub>-140</sub></td><td>P</td><td>Vigeland et al. (2018)</td><td>11.53 ± 0.02</td><td>Arzoumanian et al. (2018)</td><td>1.55</td><td>-0.57</td><td>2.3 ± 0.2</td><td>0.65</td></tr><tr><td>J1641+8049</td><td>3030 ± 1210</td><td>DM</td><td>Lynch et al. (2018)</td><td>(0.6 ± 1.0)</td><td>LAT</td><td>&lt;0.1</td><td>-0.28</td><td>&gt;48</td><td>&gt;1.02</td></tr><tr><td>J1649-3012</td><td>&lt;15820</td><td>DMM</td><td>Yao et al. (2017)</td><td>(10.1 ± 11.4)</td><td>LAT</td><td></td><td>(-6.3, 1.3)</td><td></td><td></td></tr><tr><td>J1653-0158</td><td>740<sup>+1560</sup><sub>-60</sub></td><td>P</td><td>Brown et al. (2021)</td><td>17.6 ± 0.9</td><td>Gaia Collab. et al. (2021)</td><td>1.10</td><td>-0.05</td><td>7.0<sup>+12.0</sup><sub>-0.8</sub></td><td>0.56</td></tr><tr><td>J1658-5324</td><td>880 ± 350</td><td>DM</td><td>Spiewak et al. (2022)</td><td>4.9 ± 0.3</td><td>Camilo et al. (2015)</td><td>0.13</td><td>0.10</td><td>29.3 ± 0.2</td><td>0.98</td></tr><tr><td>J1713+0747</td><td>1310 ± 30</td><td>P</td><td>Reardon et al. (2021)</td><td>6.29 ± 0.00</td><td>Same</td><td>0.58</td><td>-0.29</td><td>3.41 ± 0.01</td><td>0.97</td></tr><tr><td>J1730-2304</td><td>620<sup>+150</sup><sub>-100</sub></td><td>P</td><td>Reardon et al. (2016)</td><td>20.3 ± 0.4</td><td>Reardon et al. (2021)</td><td>5.04</td><td>0.41</td><td>1.1 ± 0.1</td><td>0.73</td></tr><tr><td>J1732-5049</td><td>1870 ± 740</td><td>DM</td><td>Spiewak et al. (2022)</td><td>9.9 ± 0.2</td><td>Reardon et al. (2021)</td><td>2.36</td><td>0.45</td><td>3.0 ± 0.3</td><td>0.80</td></tr><tr><td>J1741+1351</td><td>2180<sup>+650</sup><sub>-400</sub></td><td>P</td><td>Alam et al. (2021)</td><td>11.64 ± 0.02</td><td>Arzoumanian et al. (2018)</td><td>2.69</td><td>-0.49</td><td>21.0<sup>+0.6</sup><sub>-0.4</sub></td><td>0.93</td></tr><tr><td>J1744-1134</td><td>390<sup>+100</sup><sub>-10</sub></td><td>P</td><td>Reardon et al. (2016)</td><td>21.03 ± 0.01</td><td>Reardon et al. (2021)</td><td>1.73</td><td>0.09</td><td>4.16<sup>+0.26</sup><sub>-0.03</sub></td><td>0.80</td></tr><tr><td>J1744-7619</td><td>&lt;1500</td><td>O</td><td>Clark et al. (2018)</td><td>18.7 ± 1.2</td><td>LAT</td><td>&lt;6.0</td><td>(-0.4, -0.2)</td><td>&gt;2.2</td><td>&gt;0.40</td></tr><tr><td>J1745+1017</td><td>1210 ± 480</td><td>DM</td><td>Spiewak et al. (2022)</td><td>8.7 ± 0.2</td><td>NRT</td><td>0.59</td><td>-0.12</td><td>4.4 ± 0.5</td><td>0.81</td></tr><tr><td>J1747-4036</td><td>7140 ± 2850</td><td>DM</td><td>Spiewak et al. (2022)</td><td>2.7 ± 0.5</td><td>Alam et al. (2021)</td><td>0.21</td><td>0.12</td><td>114.0<sup>+29.3</sup><sub>-4.6</sub></td><td>0.98</td></tr><tr><td>J1757-6032</td><td>3490 ± 1390</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.30</td><td>≤5.2</td><td>≤1.10</td></tr><tr><td>J1803-6707</td><td>1840<sup>+820</sup><sub>-290</sub></td><td>P</td><td>Brown et al. (2021)</td><td>10.6 ± 0.2</td><td>Gaia Collab. et al. (2021)</td><td>1.08</td><td>-0.16</td><td>71.7<sup>+2.0</sup><sub>-0.7</sub></td><td>0.95</td></tr><tr><td>J1805+0615</td><td>3880 ± 1550</td><td>DM</td><td>Deneva et al. (2021)</td><td>15.0 ± 3.0</td><td>Same</td><td>4.52</td><td>-0.35</td><td>75.9 ± 10.5</td><td>0.82</td></tr><tr><td>J1810+1744</td><td>1870<sup>+1120</sup><sub>-380</sub></td><td>P</td><td>Brown et al. (2021)</td><td>8.7 ± 0.4</td><td>LAT</td><td>0.57</td><td>-0.18</td><td>36.6<sup>+3.3</sup><sub>-1.2</sub></td><td>0.92</td></tr></tbody></table>
<table><caption>Table 8
(Continued)</caption><thead><tr><th>PSR</th><th>d<br>(pc)</th><th>Method</th><th>Reference</th><th>μ<br>(mas yr<sup>-1</sup>)</th><th>Reference</th><th>ρ<sup>shk</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>gal</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>int</sup><br>(10<sup>33</sup> erg s<sup>-1</sup>)</th><th>(1 - ξ)</th></tr></thead><tbody><tr><td>J1301+0833</td><td>1770 ± 110</td><td>O</td><td>Kandel & Romani (2022)</td><td>22.8 ± 3.5</td><td>LAT</td><td>4.11</td><td>-0.50</td><td>43.7 ± 8.2</td><td>0.66</td></tr><tr><td>J1302-3258</td><td>1430 ± 570</td><td>DM</td><td>Spiewak et al. (2022)</td><td>13.2 ± 0.7</td><td>NRT</td><td>2.28</td><td>-0.63</td><td>3.6 ± 0.7</td><td>0.75</td></tr><tr><td>J1306-6043</td><td>1310 ± 520</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.35</td><td>≤6.7</td><td>≤1.01</td></tr><tr><td>J1311-3430</td><td>1580<sup>+970</sup><sub>-350</sub></td><td>P</td><td>Brown et al. (2021)</td><td>9.1 ± 0.3</td><td>LAT</td><td>0.82</td><td>-0.43</td><td>48.3<sup>+1.3</sup><sub>-0.5</sub></td><td>0.98</td></tr><tr><td>J1312+0051</td><td>1470 ± 580</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>25.0 ± 0.9</td><td>Same</td><td>9.45</td><td>-1.05</td><td>4.5 ± 2.0</td><td>0.51</td></tr><tr><td>J1327-0755</td><td>3700 ± 1480</td><td>DM</td><td>Boyles et al. (2013)</td><td>(6.4 ± 4.2)</td><td>NRT</td><td>&lt;5.3</td><td>-1.15</td><td>&gt; -4.9</td><td>&gt; -1.31</td></tr><tr><td>J1335-5656</td><td>&lt;15040</td><td>DMM</td><td>Yao et al. (2017)</td><td>5.5 ± 1.2</td><td>C. J. Clark et al. (2023, in preparation)</td><td>&lt;3.5</td><td>(-2.9, -0.0)</td><td>&gt;4.0</td><td>&gt;0.71</td></tr><tr><td>J1400-1431</td><td>270<sup>+120</sup><sub>-60</sub></td><td>P</td><td>Swiggum et al. (2017)</td><td>42.9 ± 2.2</td><td>NRT</td><td>3.82</td><td>-0.20</td><td>4.9<sup>+2.3</sup><sub>-3.3</sub></td><td>0.50</td></tr><tr><td>J1402+1306</td><td>690 ± 270</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-1.00</td><td>≤2.8</td><td>≤1.07</td></tr><tr><td>J1431-4715</td><td>1770<sup>+530</sup><sub>-210</sub></td><td>P</td><td>Brown et al. (2021)</td><td>18.8 ± 0.3</td><td>Jennings et al. (2018)</td><td>3.06</td><td>-0.10</td><td>54.3<sup>+4.5</sup><sub>-1.8</sub></td><td>0.79</td></tr><tr><td>J1446-4701</td><td>1560 ± 620</td><td>DM</td><td>Spiewak et al. (2022)</td><td>5.3 ± 0.1</td><td>Reardon et al. (2021)</td><td>0.24</td><td>-0.06</td><td>36.2 ± 0.4</td><td>0.98</td></tr><tr><td>J1455-3330</td><td>680 ± 270</td><td>DM</td><td>Spiewak et al. (2022)</td><td>8.2 ± 0.1</td><td>Alam et al. (2021)</td><td>0.88</td><td>-0.23</td><td>1.83 ± 0.03</td><td>0.97</td></tr><tr><td>J1513-2550</td><td>3960 ± 1580</td><td>DM</td><td>Spiewak et al. (2022)</td><td>7.2 ± 0.2</td><td>NRT</td><td>1.06</td><td>-0.51</td><td>86.8<sup>+2.7</sup><sub>-2.1</sub></td><td>0.97</td></tr><tr><td>J1514-4946</td><td>900 ± 360</td><td>DM</td><td>Spiewak et al. (2022)</td><td>14.0 ± 0.7</td><td>LAT</td><td>1.55</td><td>0.05</td><td>14.6 ± 0.5</td><td>0.91</td></tr><tr><td>J1526-2744</td><td>1320 ± 520</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.08</td><td>≤9.2</td><td>≤1.02</td></tr><tr><td>J1536-4948</td><td>970 ± 390</td><td>DM</td><td>Bhattacharyya et al. (2021)</td><td>7.8 ± 0.3</td><td>Same</td><td>0.45</td><td>0.09</td><td>27.9 ± 0.2</td><td>0.97</td></tr><tr><td>J1543-5149</td><td>1140 ± 450</td><td>DM</td><td>Spiewak et al. (2022)</td><td>4.3 ± 0.5</td><td>PKS</td><td>0.11</td><td>0.07</td><td>72.2 ± 0.2</td><td>0.99</td></tr><tr><td>J1544+4937</td><td>2990<sup>+2000</sup><sub>-990</sub></td><td>O</td><td>Tang et al. (2014)</td><td>10.3 ± 0.3</td><td>NRT</td><td>1.66</td><td>-0.68</td><td>8.4<sup>+4.4</sup><sub>-2.2</sub></td><td>0.69</td></tr><tr><td>J1552+5437</td><td>2630 ± 1050</td><td>DM</td><td>Pleunis et al. (2017)</td><td>(3.4 ± 2.3)</td><td>LAT</td><td>&lt;1.0</td><td>-0.68</td><td>&gt;6.9</td><td>&gt;0.88</td></tr><tr><td>J1555-2908</td><td>5100<sup>+500</sup><sub>-700</sub></td><td>O</td><td>Kennedy et al. (2022)</td><td>(1.1 ± 1.9)</td><td>LAT</td><td>&lt;0.5</td><td>-0.28</td><td>&gt;306</td><td>&gt;0.99</td></tr><tr><td>J1600-3053</td><td>1920<sup>+360</sup><sub>-260</sub></td><td>P</td><td>Alam et al. (2021)</td><td>7.03 ± 0.03</td><td>Reardon et al. (2021)</td><td>0.83</td><td>0.15</td><td>7.21<sup>+0.13</sup><sub>-0.10</sub></td><td>0.90</td></tr><tr><td>J1614-2230</td><td>700 ± 300</td><td>P</td><td>Matthews et al. (2016)</td><td>32.4 ± 0.6</td><td>Alam et al. (2021)</td><td>5.62</td><td>0.018</td><td>5.0 ± 3.1</td><td>0.41</td></tr><tr><td>J1622-0315</td><td>1230<sup>+540</sup><sub>-180</sub></td><td>P</td><td>Brown et al. (2021)</td><td>13.4 ± 0.3</td><td>Gaia Collab. et al. (2021)</td><td>2.06</td><td>-0.24</td><td>6.6<sup>+0.6</sup><sub>-0.2</sub></td><td>0.84</td></tr><tr><td>J1623-6936</td><td>1290 ± 510</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.10</td><td>≤26</td><td>≤1.01</td></tr><tr><td>J1625-0021</td><td>950 ± 380</td><td>DM</td><td>Deneva et al. (2021)</td><td>(4.0 ± 1.8)</td><td>LAT</td><td>&lt;0.4</td><td>-0.18</td><td>&gt;37</td><td>&gt;0.99</td></tr><tr><td>J1627+3219</td><td>4470 ± 1780</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-1.04</td><td>≤25</td><td>≤1.19</td></tr><tr><td>J1628-3205</td><td>1190<sup>+620</sup><sub>-190</sub></td><td>P</td><td>Brown et al. (2021)</td><td>22.3 ± 0.4</td><td>Gaia Collab. et al. (2021)</td><td>4.62</td><td>0.20</td><td>11.9<sup>+2.9</sup><sub>-0.9</sub></td><td>0.67</td></tr><tr><td>J1630+3734</td><td>1180 ± 470</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>18.5 ± 0.2</td><td>JBO</td><td>3.28</td><td>-0.62</td><td>8.7 ± 1.4</td><td>0.75</td></tr><tr><td>J1640+2224</td><td>1510<sup>+170</sup><sub>-140</sub></td><td>P</td><td>Vigeland et al. (2018)</td><td>11.53 ± 0.02</td><td>Arzoumanian et al. (2018)</td><td>1.55</td><td>-0.57</td><td>2.3 ± 0.2</td><td>0.65</td></tr><tr><td>J1641+8049</td><td>3030 ± 1210</td><td>DM</td><td>Lynch et al. (2018)</td><td>(0.6 ± 1.0)</td><td>LAT</td><td>&lt;0.1</td><td>-0.28</td><td>&gt;48</td><td>&gt;1.02</td></tr><tr><td>J1649-3012</td><td>&lt;15820</td><td>DMM</td><td>Yao et al. (2017)</td><td>(10.1 ± 11.4)</td><td>LAT</td><td></td><td>(-6.3, 1.3)</td><td></td><td></td></tr><tr><td>J1653-0158</td><td>740<sup>+1560</sup><sub>-60</sub></td><td>P</td><td>Brown et al. (2021)</td><td>17.6 ± 0.9</td><td>Gaia Collab. et al. (2021)</td><td>1.10</td><td>-0.05</td><td>7.0<sup>+12.0</sup><sub>-0.8</sub></td><td>0.56</td></tr><tr><td>J1658-5324</td><td>880 ± 350</td><td>DM</td><td>Spiewak et al. (2022)</td><td>4.9 ± 0.3</td><td>Camilo et al. (2015)</td><td>0.13</td><td>0.10</td><td>29.3 ± 0.2</td><td>0.98</td></tr><tr><td>J1713+0747</td><td>1310 ± 30</td><td>P</td><td>Reardon et al. (2021)</td><td>6.29 ± 0.00</td><td>Same</td><td>0.58</td><td>-0.29</td><td>3.41 ± 0.01</td><td>0.97</td></tr><tr><td>J1730-2304</td><td>620<sup>+150</sup><sub>-100</sub></td><td>P</td><td>Reardon et al. (2016)</td><td>20.3 ± 0.4</td><td>Reardon et al. (2021)</td><td>5.04</td><td>0.41</td><td>1.1 ± 0.1</td><td>0.73</td></tr><tr><td>J1732-5049</td><td>1870 ± 740</td><td>DM</td><td>Spiewak et al. (2022)</td><td>9.9 ± 0.2</td><td>Reardon et al. (2021)</td><td>2.36</td><td>0.45</td><td>3.0 ± 0.3</td><td>0.80</td></tr><tr><td>J1741+1351</td><td>2180<sup>+650</sup><sub>-400</sub></td><td>P</td><td>Alam et al. (2021)</td><td>11.64 ± 0.02</td><td>Arzoumanian et al. (2018)</td><td>2.69</td><td>-0.49</td><td>21.0<sup>+0.6</sup><sub>-0.4</sub></td><td>0.93</td></tr><tr><td>J1744-1134</td><td>390<sup>+100</sup><sub>-10</sub></td><td>P</td><td>Reardon et al. (2016)</td><td>21.03 ± 0.01</td><td>Reardon et al. (2021)</td><td>1.73</td><td>0.09</td><td>4.16<sup>+0.26</sup><sub>-0.03</sub></td><td>0.80</td></tr><tr><td>J1744-7619</td><td>&lt;1500</td><td>O</td><td>Clark et al. (2018)</td><td>18.7 ± 1.2</td><td>LAT</td><td>&lt;6.0</td><td>(-0.4, -0.2)</td><td>&gt;2.2</td><td>&gt;0.40</td></tr><tr><td>J1745+1017</td><td>1210 ± 480</td><td>DM</td><td>Spiewak et al. (2022)</td><td>8.7 ± 0.2</td><td>NRT</td><td>0.59</td><td>-0.12</td><td>4.4 ± 0.5</td><td>0.81</td></tr><tr><td>J1747-4036</td><td>7140 ± 2850</td><td>DM</td><td>Spiewak et al. (2022)</td><td>2.7 ± 0.5</td><td>Alam et al. (2021)</td><td>0.21</td><td>0.12</td><td>114.0<sup>+29.3</sup><sub>-4.6</sub></td><td>0.98</td></tr><tr><td>J1757-6032</td><td>3490 ± 1390</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.30</td><td>≤5.2</td><td>≤1.10</td></tr><tr><td>J1803-6707</td><td>1840<sup>+820</sup><sub>-290</sub></td><td>P</td><td>Brown et al. (2021)</td><td>10.6 ± 0.2</td><td>Gaia Collab. et al. (2021)</td><td>1.08</td><td>-0.16</td><td>71.7<sup>+2.0</sup><sub>-0.7</sub></td><td>0.95</td></tr><tr><td>J1805+0615</td><td>3880 ± 1550</td><td>DM</td><td>Deneva et al. (2021)</td><td>15.0 ± 3.0</td><td>Same</td><td>4.52</td><td>-0.35</td><td>75.9 ± 10.5</td><td>0.82</td></tr><tr><td>J1810+1744</td><td>1870<sup>+1120</sup><sub>-380</sub></td><td>P</td><td>Brown et al. (2021)</td><td>8.7 ± 0.4</td><td>LAT</td><td>0.57</td><td>-0.18</td><td>36.6<sup>+3.3</sup><sub>-1.2</sub></td><td>0.92</td></tr></tbody></table>
<table><caption>Table 8
(Continued)</caption><thead><tr><th>PSR</th><th>d<br>(pc)</th><th>Method</th><th>Reference</th><th>μ<br>(mas yr<sup>-1</sup>)</th><th>Reference</th><th>ρ<sup>shk</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>gal</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>int</sup><br>(10<sup>33</sup> erg s<sup>-1</sup>)</th><th>(1 - ξ)</th></tr></thead><tbody><tr><td>J1811-2405</td><td>1830 ± 730</td><td>DM</td><td>Spiewak et al. (2022)</td><td>0.5 ± 0.1</td><td>Ng et al. (2020)</td><td>0.00</td><td>0.47</td><td>27.1 ± 0.5</td><td>0.96</td></tr><tr><td>J1816+4510</td><td>3430<sup>+1210</sup><sub>-480</sub></td><td>P</td><td>Brown et al. (2021)</td><td>4.4 ± 0.1</td><td>Gaia Collab. et al. (2021)</td><td>0.51</td><td>-1.12</td><td>53.1<sup>+0.4</sup><sub>-0.2</sub></td><td>1.0</td></tr><tr><td>J1823-3021A</td><td>7600 ± 400</td><td>O</td><td>Kuulkers et al. (2003)</td><td>6.94 ± 0.03</td><td>Vasiliev & Baumgardt (2021)</td><td>4.84</td><td>-0.54</td><td>826.9<sup>+0.8</sup><sub>-0.6</sub></td><td>1.00</td></tr><tr><td>J1824+1014</td><td>2900 ± 1160</td><td>DM</td><td>Deneva et al. (2021)</td><td></td><td></td><td></td><td>-0.44</td><td>≤3.5</td><td>≤1.08</td></tr><tr><td>J1824-0621</td><td>3530 ± 1410</td><td>DM</td><td>Miao et al. (2023)</td><td></td><td></td><td></td><td>0.47</td><td>≤10</td><td>≤0.95</td></tr><tr><td>J1824-2452A</td><td>5370 ± 100</td><td>O</td><td>Baumgardt & Vasiliev (2021)</td><td>8.93 ± 0.03</td><td>Vasiliev & Baumgardt (2021)</td><td>3.18</td><td>1.79</td><td>2236.2 ± 0.1</td><td>1.00</td></tr><tr><td>J1827-0849</td><td>&lt;22290</td><td>DMM</td><td>Appendix A</td><td>(1.8 ± 3.9)</td><td>LAT</td><td></td><td></td><td></td><td></td></tr><tr><td>J1832-0836</td><td>2030<sup>+650</sup><sub>-390</sub></td><td>P</td><td>Alam et al. (2021)</td><td>22.9 ± 0.1</td><td>Same</td><td>7.04</td><td>0.33</td><td>1.8<sup>+4.5</sup><sub>-1.6</sub></td><td>0.11</td></tr><tr><td>J1833-3840</td><td>4640 ± 1850</td><td>DM</td><td>Appendix A</td><td></td><td></td><td></td><td>0.43</td><td>≤105</td><td>≤0.98</td></tr><tr><td>J1835-3259B</td><td>8400<sup>+940</sup><sub>-770</sub></td><td>P</td><td>Brown et al. (2021)</td><td>6.95 ± 0.03</td><td>Vasiliev & Baumgardt (2021)</td><td>1.80</td><td>-2.26</td><td>282.5<sup>+6.3</sup><sub>-8.8</sub></td><td>1.0</td></tr><tr><td>J1843-1113</td><td>1260 ± 500</td><td>P</td><td>Desvignes et al. (2016)</td><td>3.7 ± 0.3</td><td>Same</td><td>0.08</td><td>0.14</td><td>58.2 ± 0.4</td><td>0.98</td></tr><tr><td>J1852-1310</td><td>1270 ± 500</td><td>DM</td><td>Yao et al. (2017)</td><td>6.8 ± 1.3</td><td>JBO</td><td>0.62</td><td>0.31</td><td>4.6 ± 0.2</td><td>0.91</td></tr><tr><td>J1855-1436</td><td>5120 ± 2050</td><td>DM</td><td>Spiewak et al. (2022)</td><td></td><td></td><td></td><td>0.24</td><td>≤9.1</td><td>≤0.98</td></tr><tr><td>J1857+0943</td><td>1200 ± 350</td><td>P</td><td>Desvignes et al. (2016)</td><td>6.03 ± 0.02</td><td>Reardon et al. (2021)</td><td>0.57</td><td>-0.03</td><td>4.44 ± 0.04</td><td>0.97</td></tr><tr><td>J1858-2216</td><td>920 ± 360</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>6.9 ± 0.4</td><td>LAT</td><td>0.26</td><td>0.11</td><td>10.3 ± 0.3</td><td>0.91</td></tr><tr><td>J1858-5422</td><td>1210 ± 480</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.05</td><td>≤13</td><td>≤1.01</td></tr><tr><td>J1901-0125</td><td>2360 ± 940</td><td>DM</td><td>Appendix A</td><td>(5.8 ± 2.4)</td><td>LAT</td><td>&lt;1.8</td><td>0.11</td><td>&gt;61</td><td>&gt;0.95</td></tr><tr><td>J1902-5105</td><td>1640 ± 650</td><td>DM</td><td>Spiewak et al. (2022)</td><td>8.0 ± 0.5</td><td>LAT</td><td>0.44</td><td>-0.02</td><td>64.3 ± 1.4</td><td>0.95</td></tr><tr><td>J1903-7051</td><td>930 ± 370</td><td>DM</td><td>Spiewak et al. (2022)</td><td>18.3 ± 2.0</td><td>Camilo et al. (2015)</td><td>2.72</td><td>-0.26</td><td>6.7 ± 1.1</td><td>0.76</td></tr><tr><td>J1908+2105</td><td>2600 ± 1040</td><td>DM</td><td>Deneva et al. (2021)</td><td>8.3 ± 2.4</td><td>Gaia Collab. et al. (2021)</td><td>1.13</td><td>-0.44</td><td>30.9 ± 1.9</td><td>0.95</td></tr><tr><td>J1909-3744</td><td>1140 ± 10</td><td>P</td><td>Reardon et al. (2016)</td><td>37.02 ± 0.00</td><td>Reardon et al. (2021)</td><td>11.20</td><td>0.06</td><td>4.3 ± 0.2</td><td>0.20</td></tr><tr><td>J1921+0137</td><td>5080 ± 2030</td><td>DM</td><td>Spiewak et al. (2022)</td><td>4.3 ± 1.4</td><td>LAT</td><td>0.57</td><td>-0.82</td><td>48.1<sup>+2.8</sup><sub>-2.0</sub></td><td>1.0</td></tr><tr><td>J1921+1929</td><td>2430 ± 970</td><td>DM</td><td>Parent et al. (2019)</td><td>11.5 ± 1.0</td><td>Same</td><td>2.07</td><td>-0.38</td><td>77.4 ± 2.0</td><td>0.96</td></tr><tr><td>J1939+2134</td><td>3060<sup>+500</sup><sub>-380</sub></td><td>P</td><td>Alam et al. (2021)</td><td>0.41 ± 0.00</td><td>Reardon et al. (2021)</td><td>0.00</td><td>-0.35</td><td>109.7 ± 1</td><td>1.0</td></tr><tr><td>J1946+3417</td><td>6940 ± 2770</td><td>DM</td><td>Alam et al. (2021)</td><td>8.9 ± 0.1</td><td>Same</td><td>4.27</td><td>-1.81</td><td>0.9<sup>+2.1</sup><sub>-0.8</sub></td><td>0.22</td></tr><tr><td>J1946-5403</td><td>1150 ± 460</td><td>DM</td><td>Spiewak et al. (2022)</td><td>(2.8 ± 2.1)</td><td>LAT</td><td>&lt;0.4</td><td>-0.17</td><td>&gt;5.0</td><td>&gt;0.93</td></tr><tr><td>J1959+2048</td><td>1270<sup>+750</sup><sub>-270</sub></td><td>P</td><td>Brown et al. (2021)</td><td>30.4 ± 0.6</td><td>Arzoumanian et al. (1994)</td><td>4.59</td><td>-0.12</td><td>117<sup>+26</sup><sub>-10</sub></td><td>0.73</td></tr><tr><td>J2006+0148</td><td>2430 ± 970</td><td>DM</td><td>Deneva et al. (2021)</td><td>(3.0 ± 2.5)</td><td>LAT</td><td>&lt;0.8</td><td>-0.31</td><td>&gt;11</td><td>&gt;0.85</td></tr><tr><td>J2017+0603</td><td>1390<sup>+1470</sup><sub>-140</sub></td><td>O</td><td>Testa et al. (2015)</td><td>2.2 ± 0.1</td><td>Arzoumanian et al. (2018)</td><td>0.05</td><td>-0.26</td><td>13.8<sup>+0.2</sup><sub>-0.1</sub></td><td>1.0</td></tr><tr><td>J2017-1614</td><td>1440 ± 570</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>(11.0 ± 12.8)</td><td>LAT</td><td>&lt;10.9</td><td>-0.18</td><td>&gt; -26</td><td>&gt; -3.44</td></tr><tr><td>J2029-4239</td><td>640 ± 250</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.35</td><td>≤2.6</td><td>≤1.04</td></tr><tr><td>J2034+3632</td><td>&lt;14110</td><td>DMM</td><td>Yao et al. (2017)</td><td>14.2 ± 0.7</td><td>Ajello et al. (2022)</td><td>&lt;25.2</td><td>(-1.9, -0.1)</td><td>&gt;20.3</td><td>&gt;13.56</td></tr><tr><td>J2039-3616</td><td>1700 ± 680</td><td>DM</td><td>Spiewak et al. (2022)</td><td>13.6 ± 0.4</td><td>Swiggum et al. (2023)</td><td>2.52</td><td>-0.43</td><td>7.2 ± 1.2</td><td>0.75</td></tr><tr><td>J2039-5617</td><td>1680<sup>+550</sup><sub>-220</sub></td><td>P</td><td>Brown et al. (2021)</td><td>15.5 ± 0.3</td><td>Clark et al. (2021)</td><td>2.60</td><td>-0.40</td><td>25.4<sup>+1.8</sup><sub>-0.8</sub></td><td>0.84</td></tr><tr><td>J2042+0246</td><td>640 ± 250</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>6.9 ± 0.9</td><td>LAT</td><td>0.34</td><td>-0.29</td><td>6.0 ± 0.1</td><td>1.00</td></tr><tr><td>J2043+1711</td><td>1380<sup>+140</sup><sub>-120</sub></td><td>P</td><td>Alam et al. (2021)</td><td>12.25 ± 0.02</td><td>Same</td><td>1.21</td><td>-0.31</td><td>14.1<sup>+0.4</sup><sub>-0.3</sub></td><td>0.84</td></tr><tr><td>J2047+1053</td><td>2790 ± 1110</td><td>DM</td><td>Ray et al. (2012)</td><td>17.1 ± 1.5</td><td>JBO</td><td>8.52</td><td>-1.19</td><td>6.8 ± 1.9</td><td>0.65</td></tr><tr><td>J2051-0827</td><td>1460 ± 580</td><td>DM</td><td>Shaifullah et al. (2016)</td><td>6.1 ± 0.1</td><td>Same</td><td>0.60</td><td>-0.64</td><td>5.5 ± 0.1</td><td>1.0</td></tr><tr><td>J2052+1219</td><td>5570<sup>+470</sup><sub>-550</sub></td><td>O</td><td>Kandel & Romani (2022)</td><td>14.6 ± 0.6</td><td>Deneva et al. (2021)</td><td>5.74</td><td>-1.11</td><td>10.5 ± 3.7</td><td>0.31</td></tr><tr><td>J2115+5448</td><td>3100 ± 1240</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>17.5 ± 0.3</td><td>NRT</td><td>6.04</td><td>-0.56</td><td>154.2 ± 5.4</td><td>0.93</td></tr><tr><td>J2116+1345</td><td>2730 ± 1090</td><td>DM</td><td>Yao et al. (2017)</td><td>11 ± 3</td><td>Lewis et al. (2023)</td><td>1.8</td><td>-0.6</td><td>5.4 ± 3.2</td><td>0.56</td></tr><tr><td>J2124-3358</td><td>410<sup>+100</sup><sub>-50</sub></td><td>P</td><td>Reardon et al. (2016)</td><td>52.28 ± 0.04</td><td>Reardon et al. (2021)</td><td>13.42</td><td>-0.42</td><td>2.5<sup>+1.1</sup><sub>-0.5</sub></td><td>0.37</td></tr><tr><td>J2129-0429</td><td>1830 ± 110</td><td>O</td><td>Bellem et al. (2016)</td><td>16.0 ± 0.1</td><td>Jennings et al. (2018)</td><td>8.66</td><td>-1.75</td><td>20.61 ± 0.05</td><td>0.97</td></tr><tr><td>J2205+6012</td><td>3530 ± 1410</td><td>DM</td><td>Desvignes et al. (2022)</td><td>3.78 ± 0.01</td><td>Same</td><td>0.30</td><td>-0.42</td><td>56.2 ± 0.4</td><td>1.0</td></tr><tr><td>J2214+3000</td><td>600 ± 310</td><td>P</td><td>Guillemot et al. (2016)</td><td>21.0 ± 0.1</td><td>Alam et al. (2021)</td><td>2.01</td><td>-0.27</td><td>17.2 ± 1.4</td><td>0.88</td></tr></tbody></table>
<table><caption>Table 8
(Continued)</caption><thead><tr><th>PSR</th><th>d<br>(pc)</th><th>Method</th><th>Reference</th><th>μ<br>(mas yr<sup>-1</sup>)</th><th>Reference</th><th>ρ<sup>shk</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>gal</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>int</sup><br>(10<sup>33</sup> erg s<sup>-1</sup>)</th><th>(1 - ξ)</th></tr></thead><tbody><tr><td>J1811-2405</td><td>1830 ± 730</td><td>DM</td><td>Spiewak et al. (2022)</td><td>0.5 ± 0.1</td><td>Ng et al. (2020)</td><td>0.00</td><td>0.47</td><td>27.1 ± 0.5</td><td>0.96</td></tr><tr><td>J1816+4510</td><td>3430<sup>+1210</sup><sub>-480</sub></td><td>P</td><td>Brown et al. (2021)</td><td>4.4 ± 0.1</td><td>Gaia Collab. et al. (2021)</td><td>0.51</td><td>-1.12</td><td>53.1<sup>+0.4</sup><sub>-0.2</sub></td><td>1.0</td></tr><tr><td>J1823-3021A</td><td>7600 ± 400</td><td>O</td><td>Kuulkers et al. (2003)</td><td>6.94 ± 0.03</td><td>Vasiliev & Baumgardt (2021)</td><td>4.84</td><td>-0.54</td><td>826.9<sup>+0.8</sup><sub>-0.6</sub></td><td>1.00</td></tr><tr><td>J1824+1014</td><td>2900 ± 1160</td><td>DM</td><td>Deneva et al. (2021)</td><td></td><td></td><td></td><td>-0.44</td><td>≤3.5</td><td>≤1.08</td></tr><tr><td>J1824-0621</td><td>3530 ± 1410</td><td>DM</td><td>Miao et al. (2023)</td><td></td><td></td><td></td><td>0.47</td><td>≤10</td><td>≤0.95</td></tr><tr><td>J1824-2452A</td><td>5370 ± 100</td><td>O</td><td>Baumgardt & Vasiliev (2021)</td><td>8.93 ± 0.03</td><td>Vasiliev & Baumgardt (2021)</td><td>3.18</td><td>1.79</td><td>2236.2 ± 0.1</td><td>1.00</td></tr><tr><td>J1827-0849</td><td>&lt;22290</td><td>DMM</td><td>Appendix A</td><td>(1.8 ± 3.9)</td><td>LAT</td><td></td><td></td><td></td><td></td></tr><tr><td>J1832-0836</td><td>2030<sup>+650</sup><sub>-390</sub></td><td>P</td><td>Alam et al. (2021)</td><td>22.9 ± 0.1</td><td>Same</td><td>7.04</td><td>0.33</td><td>1.8<sup>+4.5</sup><sub>-1.6</sub></td><td>0.11</td></tr><tr><td>J1833-3840</td><td>4640 ± 1850</td><td>DM</td><td>Appendix A</td><td></td><td></td><td></td><td>0.43</td><td>≤105</td><td>≤0.98</td></tr><tr><td>J1835-3259B</td><td>8400<sup>+940</sup><sub>-770</sub></td><td>P</td><td>Brown et al. (2021)</td><td>6.95 ± 0.03</td><td>Vasiliev & Baumgardt (2021)</td><td>1.80</td><td>-2.26</td><td>282.5<sup>+6.3</sup><sub>-8.8</sub></td><td>1.0</td></tr><tr><td>J1843-1113</td><td>1260 ± 500</td><td>P</td><td>Desvignes et al. (2016)</td><td>3.7 ± 0.3</td><td>Same</td><td>0.08</td><td>0.14</td><td>58.2 ± 0.4</td><td>0.98</td></tr><tr><td>J1852-1310</td><td>1270 ± 500</td><td>DM</td><td>Yao et al. (2017)</td><td>6.8 ± 1.3</td><td>JBO</td><td>0.62</td><td>0.31</td><td>4.6 ± 0.2</td><td>0.91</td></tr><tr><td>J1855-1436</td><td>5120 ± 2050</td><td>DM</td><td>Spiewak et al. (2022)</td><td></td><td></td><td></td><td>0.24</td><td>≤9.1</td><td>≤0.98</td></tr><tr><td>J1857+0943</td><td>1200 ± 350</td><td>P</td><td>Desvignes et al. (2016)</td><td>6.03 ± 0.02</td><td>Reardon et al. (2021)</td><td>0.57</td><td>-0.03</td><td>4.44 ± 0.04</td><td>0.97</td></tr><tr><td>J1858-2216</td><td>920 ± 360</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>6.9 ± 0.4</td><td>LAT</td><td>0.26</td><td>0.11</td><td>10.3 ± 0.3</td><td>0.91</td></tr><tr><td>J1858-5422</td><td>1210 ± 480</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.05</td><td>≤13</td><td>≤1.01</td></tr><tr><td>J1901-0125</td><td>2360 ± 940</td><td>DM</td><td>Appendix A</td><td>(5.8 ± 2.4)</td><td>LAT</td><td>&lt;1.8</td><td>0.11</td><td>&gt;61</td><td>&gt;0.95</td></tr><tr><td>J1902-5105</td><td>1640 ± 650</td><td>DM</td><td>Spiewak et al. (2022)</td><td>8.0 ± 0.5</td><td>LAT</td><td>0.44</td><td>-0.02</td><td>64.3 ± 1.4</td><td>0.95</td></tr><tr><td>J1903-7051</td><td>930 ± 370</td><td>DM</td><td>Spiewak et al. (2022)</td><td>18.3 ± 2.0</td><td>Camilo et al. (2015)</td><td>2.72</td><td>-0.26</td><td>6.7 ± 1.1</td><td>0.76</td></tr><tr><td>J1908+2105</td><td>2600 ± 1040</td><td>DM</td><td>Deneva et al. (2021)</td><td>8.3 ± 2.4</td><td>Gaia Collab. et al. (2021)</td><td>1.13</td><td>-0.44</td><td>30.9 ± 1.9</td><td>0.95</td></tr><tr><td>J1909-3744</td><td>1140 ± 10</td><td>P</td><td>Reardon et al. (2016)</td><td>37.02 ± 0.00</td><td>Reardon et al. (2021)</td><td>11.20</td><td>0.06</td><td>4.3 ± 0.2</td><td>0.20</td></tr><tr><td>J1921+0137</td><td>5080 ± 2030</td><td>DM</td><td>Spiewak et al. (2022)</td><td>4.3 ± 1.4</td><td>LAT</td><td>0.57</td><td>-0.82</td><td>48.1<sup>+2.8</sup><sub>-2.0</sub></td><td>1.0</td></tr><tr><td>J1921+1929</td><td>2430 ± 970</td><td>DM</td><td>Parent et al. (2019)</td><td>11.5 ± 1.0</td><td>Same</td><td>2.07</td><td>-0.38</td><td>77.4 ± 2.0</td><td>0.96</td></tr><tr><td>J1939+2134</td><td>3060<sup>+500</sup><sub>-380</sub></td><td>P</td><td>Alam et al. (2021)</td><td>0.41 ± 0.00</td><td>Reardon et al. (2021)</td><td>0.00</td><td>-0.35</td><td>109.7 ± 1</td><td>1.0</td></tr><tr><td>J1946+3417</td><td>6940 ± 2770</td><td>DM</td><td>Alam et al. (2021)</td><td>8.9 ± 0.1</td><td>Same</td><td>4.27</td><td>-1.81</td><td>0.9<sup>+2.1</sup><sub>-0.8</sub></td><td>0.22</td></tr><tr><td>J1946-5403</td><td>1150 ± 460</td><td>DM</td><td>Spiewak et al. (2022)</td><td>(2.8 ± 2.1)</td><td>LAT</td><td>&lt;0.4</td><td>-0.17</td><td>&gt;5.0</td><td>&gt;0.93</td></tr><tr><td>J1959+2048</td><td>1270<sup>+750</sup><sub>-270</sub></td><td>P</td><td>Brown et al. (2021)</td><td>30.4 ± 0.6</td><td>Arzoumanian et al. (1994)</td><td>4.59</td><td>-0.12</td><td>117<sup>+26</sup><sub>-10</sub></td><td>0.73</td></tr><tr><td>J2006+0148</td><td>2430 ± 970</td><td>DM</td><td>Deneva et al. (2021)</td><td>(3.0 ± 2.5)</td><td>LAT</td><td>&lt;0.8</td><td>-0.31</td><td>&gt;11</td><td>&gt;0.85</td></tr><tr><td>J2017+0603</td><td>1390<sup>+470</sup><sub>-140</sub></td><td>O</td><td>Testa et al. (2015)</td><td>2.2 ± 0.1</td><td>Arzoumanian et al. (2018)</td><td>0.05</td><td>-0.26</td><td>13.8<sup>+0.2</sup><sub>-0.1</sub></td><td>1.0</td></tr><tr><td>J2017-1614</td><td>1440 ± 570</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>(11.0 ± 12.8)</td><td>LAT</td><td>&lt;10.9</td><td>-0.18</td><td>&gt; -26</td><td>&gt; -3.44</td></tr><tr><td>J2029-4239</td><td>640 ± 250</td><td>DM</td><td>Yao et al. (2017)</td><td></td><td></td><td></td><td>-0.35</td><td>≤2.6</td><td>≤1.04</td></tr><tr><td>J2034+3632</td><td>&lt;14110</td><td>DMM</td><td>Yao et al. (2017)</td><td>14.2 ± 0.7</td><td>Ajello et al. (2022)</td><td>&lt;25.2</td><td>(-1.9, -0.1)</td><td>&gt;20.3</td><td>&gt;13.56</td></tr><tr><td>J2039-3616</td><td>1700 ± 680</td><td>DM</td><td>Spiewak et al. (2022)</td><td>13.6 ± 0.4</td><td>Swiggum et al. (2023)</td><td>2.52</td><td>-0.43</td><td>7.2 ± 1.2</td><td>0.75</td></tr><tr><td>J2039-5617</td><td>1680<sup>+550</sup><sub>-220</sub></td><td>P</td><td>Brown et al. (2021)</td><td>15.5 ± 0.3</td><td>Clark et al. (2021)</td><td>2.60</td><td>-0.40</td><td>25.4<sup>+1.8</sup><sub>-0.8</sub></td><td>0.84</td></tr><tr><td>J2042+0246</td><td>640 ± 250</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>6.9 ± 0.9</td><td>LAT</td><td>0.34</td><td>-0.29</td><td>6.0 ± 0.1</td><td>1.00</td></tr><tr><td>J2043+1711</td><td>1380<sup>+140</sup><sub>-120</sub></td><td>P</td><td>Alam et al. (2021)</td><td>12.25 ± 0.02</td><td>Same</td><td>1.21</td><td>-0.31</td><td>14.1<sup>+0.4</sup><sub>-0.3</sub></td><td>0.84</td></tr><tr><td>J2047+1053</td><td>2790 ± 1110</td><td>DM</td><td>Ray et al. (2012)</td><td>17.1 ± 1.5</td><td>JBO</td><td>8.52</td><td>-1.19</td><td>6.8 ± 1.9</td><td>0.65</td></tr><tr><td>J2051-0827</td><td>1460 ± 580</td><td>DM</td><td>Shaifullah et al. (2016)</td><td>6.1 ± 0.1</td><td>Same</td><td>0.60</td><td>-0.64</td><td>5.5 ± 0.1</td><td>1.0</td></tr><tr><td>J2052+1219</td><td>5570<sup>+470</sup><sub>-550</sub></td><td>O</td><td>Kandel & Romani (2022)</td><td>14.6 ± 0.6</td><td>Deneva et al. (2021)</td><td>5.74</td><td>-1.11</td><td>10.5 ± 3.7</td><td>0.31</td></tr><tr><td>J2115+5448</td><td>3100 ± 1240</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td>17.5 ± 0.3</td><td>NRT</td><td>6.04</td><td>-0.56</td><td>154.2 ± 5.4</td><td>0.93</td></tr><tr><td>J2116+1345</td><td>2730 ± 1090</td><td>DM</td><td>Yao et al. (2017)</td><td>11 ± 3</td><td>Lewis et al. (2023)</td><td>1.8</td><td>-0.6</td><td>5.4 ± 3.2</td><td>0.56</td></tr><tr><td>J2124-3358</td><td>410<sup>+100</sup><sub>-50</sub></td><td>P</td><td>Reardon et al. (2016)</td><td>52.28 ± 0.04</td><td>Reardon et al. (2021)</td><td>13.42</td><td>-0.42</td><td>2.5<sup>+1.1</sup><sub>-0.5</sub></td><td>0.37</td></tr><tr><td>J2129-0429</td><td>1830 ± 110</td><td>O</td><td>Bellem et al. (2016)</td><td>16.0 ± 0.1</td><td>Jennings et al. (2018)</td><td>8.66</td><td>-1.75</td><td>20.61 ± 0.05</td><td>0.97</td></tr><tr><td>J2205+6012</td><td>3530 ± 1410</td><td>DM</td><td>Desvignes et al. (2022)</td><td>3.78 ± 0.01</td><td>Same</td><td>0.30</td><td>-0.42</td><td>56.2 ± 0.4</td><td>1.0</td></tr><tr><td>J2214+3000</td><td>600 ± 310</td><td>P</td><td>Guillemot et al. (2016)</td><td>21.0 ± 0.1</td><td>Alam et al. (2021)</td><td>2.01</td><td>-0.27</td><td>17.2 ± 1.4</td><td>0.88</td></tr></tbody></table>
<table><caption>**Table 8**
(Continued)</caption><thead><tr><th>PSR</th><th>d<br>(pc)</th><th>Method</th><th>Reference</th><th>μ<br>(mas yr<sup>-1</sup>)</th><th>Reference</th><th>ṁ<sup>shk</sup><br>(10<sup>-21</sup>)</th><th>ṁ<sup>gal</sup><br>(10<sup>-21</sup>)</th><th>ṁ<sup>int</sup><br>(10<sup>33</sup> erg s<sup>-1</sup>)</th><th>(1 − ξ)</th></tr></thead><tbody><tr><td>J2215+5135</td><td>2660<sup>+1450</sup><sub>-470</sub></td><td>P</td><td>Brown et al. (2021)</td><td>2.2 ± 0.2</td><td>Gaia Collab. et al. (2021)</td><td>0.08</td><td>-0.45</td><td>52.7<sup>+0.3</sup><sub>-0.1</sub></td><td>1.0</td></tr><tr><td>J2234+0944</td><td>1420<sup>+1070</sup><sub>-420</sub></td><td>P</td><td>Alam et al. (2021)</td><td>32.9 ± 0.2</td><td>Same</td><td>13.60</td><td>-0.79</td><td>5.6<sup>+8.4</sup><sub>-3.4</sub></td><td>0.35</td></tr><tr><td>J2241-5236</td><td>1040 ± 40</td><td>P</td><td>Reardon et al. (2021)</td><td>19.61 ± 0.01</td><td>Same</td><td>2.13</td><td>-0.42</td><td>26.3 ± 0.3</td><td>0.80</td></tr><tr><td>J2256-1024</td><td>2080<sup>+940</sup><sub>-490</sub></td><td>P</td><td>Crowter et al. (2020)</td><td>6.0 ± 0.1</td><td>GBT</td><td>0.42</td><td>-0.70</td><td>38.3<sup>+0.8</sup><sub>-0.4</sub></td><td>1.0</td></tr><tr><td>J2302+4442</td><td>860 ± 340</td><td>DM</td><td>Alam et al. (2021)</td><td>5.8 ± 0.1</td><td>Same</td><td>0.37</td><td>-0.42</td><td>3.8 ± 0.1</td><td>1.0</td></tr><tr><td>J2310-0555</td><td>1550 ± 620</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td></td><td></td><td></td><td>-0.67</td><td>≤12</td><td>≤1.14</td></tr><tr><td>J2317+1439</td><td>1700<sup>+250</sup><sub>-190</sub></td><td>P</td><td>Alam et al. (2021)</td><td>3.69 ± 0.03</td><td>Same</td><td>0.19</td><td>-0.76</td><td>2.89 ± 0.06</td><td>1.2</td></tr><tr><td>J2339-0533</td><td>1300<sup>+350</sup><sub>-160</sub></td><td>P</td><td>Brown et al. (2021)</td><td>11.1 ± 0.4</td><td>Jennings et al. (2018)</td><td>1.12</td><td>-0.67</td><td>22.5<sup>+0.5</sup><sub>-0.3</sub></td><td>0.97</td></tr></tbody></table>

**Note.** Columns 2 and 3 give the distances for the 144 MSPs detected with the Fermi LAT, and the method used to find them: P—parallax; LK—corrected for the Lutz–Kelker effect; DM—from dispersion measure (DM) using the YMW16 model (Yao et al. 2017); O—optical and other methods. For DM, the references in Column 4 give the dispersion measurement. “DMM” is a limit on the pulsar distance, corresponding to 95% of the maximum YMW16 DM for that line of sight. Proper-motion measurements μ are listed in Column 5, taken from the references in Column 6, often the “same” as in Column 4. “LAT” refers to gamma-ray timing, described in Section 3.5. “NRT,” “JBO,” “PKS,” and “GBT” indicate that the measurements were made for this work using data from the Nançay, Lovell, Parkes, and Green Bank radio telescopes. Columns 7 and 8 list the contributions of the Shklovskii effect Ṁ<sup>shk</sup> and of acceleration due to the Galactic rotation, Ṁ<sup>gal</sup> to the intrinsic spindown rate Ṁ<sup>int</sup>. The last columns list the intrinsic spindown power Ḕ<sup>int</sup> = Ḕ(1 − ξ). See the text for how cases with a missing or insignificant μ measurement, or a distance limit, are handled.
<table><caption>**Table 8**
(Continued)</caption><thead><tr><th>PSR</th><th>d<br>(pc)</th><th>Method</th><th>Reference</th><th>μ<br>(mas yr<sup>-1</sup>)</th><th>Reference</th><th>ρ<sup>shk</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>gal</sup><br>(10<sup>-21</sup>)</th><th>ρ<sup>int</sup><br>(10<sup>33</sup> erg s<sup>-1</sup>)</th><th>(1 - ξ)</th></tr></thead><tbody><tr><td>J2215+5135</td><td>2660<sup>+1450</sup><sub>-470</sub></td><td>P</td><td>Brown et al. (2021)</td><td>2.2 ± 0.2</td><td>Gaia Collab. et al. (2021)</td><td>0.08</td><td>-0.45</td><td>52.7<sup>+0.3</sup><sub>-0.1</sub></td><td>1.0</td></tr><tr><td>J2234+0944</td><td>1420<sup>+1070</sup><sub>-420</sub></td><td>P</td><td>Alam et al. (2021)</td><td>32.9 ± 0.2</td><td>Same</td><td>13.60</td><td>-0.79</td><td>5.6<sup>+8.4</sup><sub>-3.4</sub></td><td>0.35</td></tr><tr><td>J2241-5236</td><td>1040 ± 40</td><td>P</td><td>Reardon et al. (2021)</td><td>19.61 ± 0.01</td><td>Same</td><td>2.13</td><td>-0.42</td><td>26.3 ± 0.3</td><td>0.80</td></tr><tr><td>J2256-1024</td><td>2080<sup>+940</sup><sub>-490</sub></td><td>P</td><td>Crowter et al. (2020)</td><td>6.0 ± 0.1</td><td>GBT</td><td>0.42</td><td>-0.70</td><td>38.3<sup>+0.8</sup><sub>-0.4</sub></td><td>1.0</td></tr><tr><td>J2302+4442</td><td>860 ± 340</td><td>DM</td><td>Alam et al. (2021)</td><td>5.8 ± 0.1</td><td>Same</td><td>0.37</td><td>-0.42</td><td>3.8 ± 0.1</td><td>1.0</td></tr><tr><td>J2310-0555</td><td>1550 ± 620</td><td>DM</td><td>Sanpa-Arsa (2016)</td><td></td><td></td><td></td><td>-0.67</td><td>≤12</td><td>≤1.14</td></tr><tr><td>J2317+1439</td><td>1700<sup>+250</sup><sub>-190</sub></td><td>P</td><td>Alam et al. (2021)</td><td>3.69 ± 0.03</td><td>Same</td><td>0.19</td><td>-0.76</td><td>2.89 ± 0.06</td><td>1.2</td></tr><tr><td>J2339-0533</td><td>1300<sup>+350</sup><sub>-160</sub></td><td>P</td><td>Brown et al. (2021)</td><td>11.1 ± 0.4</td><td>Jennings et al. (2018)</td><td>1.12</td><td>-0.67</td><td>22.5<sup>+0.5</sup><sub>-0.3</sub></td><td>0.97</td></tr></tbody></table>

**Note.** Columns 2 and 3 give the distances for the 144 MSPs detected with the Fermi LAT, and the method used to find them: P—parallax; LK—corrected for the Lutz-Kelker effect; DM—from dispersion measure (DM) using the YMW16 model (Yao et al. 2017); O—optical and other methods. For DM, the references in Column 4 give the dispersion measurement. “DMM” is a limit on the pulsar distance, corresponding to 95% of the maximum YMW16 DM for that line of sight. Proper-motion measurements μ are listed in Column 5, taken from the references in Column 6, often the “same” as in Column 4. “LAT” refers to gamma-ray timing, described in Section 3.5. “NRT,” “JBO,” “PKS,” and “GBT” indicate that the measurements were made for this work using data from the Nançay, Lovell, Parkes, and Green Bank radio telescopes. Columns 7 and 8 list the contributions of the Shklovskii effect ρ<sup>shk</sup> and of acceleration due to the Galactic rotation, ρ<sup>gal</sup> to the intrinsic spindown rate ρ<sup>int</sup>. The last columns list the intrinsic spindown power ρ<sup>int</sup> = ρ<sup>int</sup>(1 - ξ). See the text for how cases with a missing or insignificant μ measurement, or a distance limit, are handled.