with both the NE2001 and the YMW16 models. It is in a 5.84 day binary system with an $M_c \gtrsim 0.21 M_\odot$ binary companion (Bassa et al. 2018). The timing solution used in the catalog is obtained from LOFAR timing observations covering a 2.8 yr timespan. Subsequently, a 5.2 yr solution using Jodrell Bank Observatory L-band observations confirmed the model.

The LOFAR data indicate a flux density of $5 \pm 2$ mJy at 150 MHz. An 1800 s Green Bank Telescope observation at 820 MHz, with 200 MHz bandwidth, yielded a $37.2\sigma$ detection. For two polarizations, gain $G = 2$ K Jy$^{-1}$, system temperature $T_{\text{sys}} = 29$ K, and a 12% duty cycle seen in both the 150 and 820 MHz profiles, we obtain a flux density of $260$ µJy, calculated using the PRESTO sum_profiles.py routine.

Analysis of 101 positive detections at 1400 MHz with the Lovell telescope at Jodrell Bank Observatory yields flux densities of $89 \pm 11$ and $10 \pm 3$ µJy for the main peak and interpulse, respectively. The uncertainties are statistical, and include variations due to interstellar scintillation. The total is $S_{1400} = 99 \pm 23$ µJy, having added the 20% systematic calibration uncertainty in quadrature. The spectral index obtained from these three measurements agrees well with the average value of 1.7 of the pulsar population.

The JBO ROACH timing data show no significant pulsar proper motion. We found $\text{PMDEC} = -1.5(2)$ and $\text{PMRA} = 0.5$ (1.8). The Doppler correction is hence $0.98 < (1 - \xi) < 1$, with $(1 - \xi) = \dot{E}^{\text{int}}/\dot{E}$, as in Section 4.3.

PSR J1023+0038: PSR J1023+0038 was the first transitional MSP to be discovered (Archibald et al. 2009), and it underwent a transition from a rotationally powered MSP state to an accretion-powered state in 2013 (Stappers et al. 2014). A faint source coincident with the pulsar was detected by the LAT in the pre-transition data (Nolan et al. 2012), and the flux from this source increased five-fold when accretion began (Stappers et al. 2014).

Using the radio timing ephemeris of Archibald et al. (2013), we folded the pre-transition data (from the beginning of the LAT data to 2013 June), discovering significant pulsations, with $H = 62$. This ephemeris contains a single orbital period derivative to account for long-term trends in the orbital period, but does not account for shorter-timescale orbital phase variations seen in radio timing observations. We refined this solution using an unbinned timing analysis on the LAT data, also using only one orbital period derivative, resulting in an increased $H = 92$.

We also folded the post-transition data using a timing model built from X-ray timing by Jaodand et al. (2016) and X-ray and optical timing from Illiano et al. (2023). We fit a polynomial function to the orbital phase deviations measured by Illiano et al. (2023), and folded the LAT data using this orbital model and the spindown model of Jaodand et al. (2016). No pulsations were detected. We also searched for pulsations with slightly different spin periods and spin-down rates, and with slight shifts in orbital phase, using a sliding window approach, but again did not detect any significant pulsations.

This nondetection implies that the flux increase due to accretion is not an enhancement of the pulsed flux (seen in other nonaccreting redbacks; e.g., An et al. 2020; Clark et al. 2021), but is instead an additional unpulsed component. If the five-fold increase in gamma-ray flux is indeed due to unpulsed emission from the accretion process, and the gamma-ray pulsations remain unaffected by the accretion, then the pulsed

fraction would be reduced to 20% of the pre-transition level, and this would leave the pulsations undetectable to our analysis. Like PSR J1227-4853 (Johnson et al. 2015), it therefore remains unclear whether or not this system emits gamma-ray pulsations in the accretion-powered state.

PSR J1827-0849: Applying the methods of Clark et al. (2017) and Section 3.4 to LAT data around the position of a steep-spectrum radio source coincident with unidentified LAT source 3FGL J1827.6-0846, found by Frail et al. (2016), we discovered gamma-ray pulsations with spin period 2.24 ms in 2016. The radio positional uncertainties of $\sim 2''$ have greatly reduced the computing cost and allowed us to increase our sliding coherence window length to $2^{23}$ s (or $\sim 97$ days) and still perform the search on the ATLAS cluster$^{127}$ in about 1 day per source.

The associated radio source has flux density $229.9 \pm 14.8$ mJy in the GMRT 150 MHz All-Sky Survey, and $777 \pm 126$ mJy in VLSS$_r$ at 74 MHz. NVSS has no detection, giving $S_{1400} < 0.8$ mJy per beam. Table 8 lists an insignificant proper-motion estimate from LAT timing as per Section 3.5. C.J. Clark and coworkers are studying other LAT unidentified sources colocated with steep-spectrum radio sources and will detail their methods and results in future work.

PSR J1833-3840: This 1.87 ms pulsar was discovered in 2015 by F. Camilo, in observations of unidentified LAT sources using the Parkes radio telescope, using the methods reported by Camilo et al. (2015). Later, Frail et al. (2018) independently highlighted it in a search for steep radio spectrum pulsar candidates in LAT unidentified sources using the GMRT 150 MHz all-sky survey (TGSS ADR1). Fewer than 10% of known pulsars have such high spindown power, $\dot{E} = 1.1 \times 10^{35}$ erg s$^{-1}$, in the Milky Way or in globular clusters. The orbital period is 0.9 day. In 2020, then-undergraduate Camryn Phillips phase-connected GBT timing observations during PINT code development she was conducting. We phase-folded the gamma-ray data using her ephemeris and obtained the pulsed detection reported here.

PSR J1852-1310: The $P = 4.31$ ms isolated pulsar PSR J1852-1310 was discovered in a 1900s pointing on MJD 57793 toward an LAT unidentified source with a pulsar-like spectrum, at 800 MHz using the GUPPI backend on the Green Bank Radio Telescope. It was initially named PSR J1852-13. Routine timing observations at 1400 MHz with the Lovell telescope at Jodrell Bank Observatory began on MJD 57818. As of MJD 59927, 124 arrival times have been acquired using ROACH, allowing a phase-connected rotation ephemeris. The spindown power is $\dot{E} = 4.95 \times 10^{33}$ erg s$^{-1}$. For $DM = 44.95 \pm 0.01$ pc cm$^{-3}$ in the direction of this pulsar, the YMW16 model gives a distance of $1.27 \pm 0.5$ kpc. The integral energy flux of colocated 4FGL J1852.2-1309 thus gives $L_{\gamma} = (5.8 \pm 1.0) \times 10^{32}$ erg s$^{-1}$, for a gamma-ray efficiency of 11%.

GBT timing observations at 1400 MHz between MJD 58698 and 59050 yielded 49 times of arrival. Combining these with the JBO data slightly improves the MSP's proper-motion measurement, and we obtain $\text{PMDEC} = -6.6 \pm 1.4$ and $\text{PMRA} = -1.84 \pm 0.25$. The Doppler correction is hence $(1 - \xi) = 0.91$, as defined in Section 4.3, such that $\dot{E}^{\text{int}} = (4.6 \pm 0.2) \times 10^{33}$ erg s$^{-1}$.

<footnote n="127">127 https://www.aei.mpg.de/atlas</footnote>
Gamma-ray phase folding 14.5 yr of data using the JBO timing model revealed pulsations with test statistic $H = 122$ using the simple weights parameter $\mu_w = 4.3$. Model weights increase this to $H = 133$. $H$ increases steadily for the 8.5 yr before the start of the timing model, indicating that the MSPs spindown rate is stable, well-described using only spin frequency and its first derivative. The radio source is bright ($250\sigma$ in the discovery observation), and the profile has sharp features; hence, this MSP may rate inclusion in gravitational wave searches.

**PSR J1857+0943:** This 5.36 ms pulsar has long been known for its stable rotation rate (Segelstein et al. 1986). Gamma-ray phase folding using the rotation ephemeris provided by Reardon et al. (2021) yielded $H$-test >30, using simple weights. Located in a high background region, $(l, b) = (42.2, 3.12)$ degrees, the gamma-ray profile is ill-defined but appears to be dominated by a single narrow peak. The timing parallax distance from Table 8 and the integral energy flux of the colocated LAT source 4FGL J1857.2+0941 give $L_{\gamma} = (1.27 \pm 0.31^{0.6}_{-0.9}) \times 10^{33} \text{ erg s}^{-1}$, where the first uncertainty comes from the flux measurement and the second from the distance, about 30% of the spindown power.

**PSR J1901-0125:** The same procedure as described for PSR J1827-0849, above, led to the 2016 discovery of 2.79 ms gamma-ray pulsations. F. Camilo then re-analyzed GBT radio data from previous observations of the LAT source position using the LAT rotation ephemeris and discovered radio pulsations and measured the DM. Table 3 lists $S_{1400} = 2.50$ mJy, extrapolated from the Frail et al. (2016) GMRT flux density of $362 \pm 15$ mJy at 150 MHz and radio spectral index -2.23. Table 8 lists a $2.4\sigma$ proper-motion measurement using

the methods of Section 3.5. Clark and co-workers are studying other LAT unidentified sources colocated with steep-spectrum radio sources and will detail their methods and results in future work.

**PSR J2256-1024:** Crowter et al. (2020) found $\mu = 9 \pm 3 \text{mas yr}^{-1}$ using GBT timing data. NRT has also monitored this pulsar, but with a substantial gap between the end of the GBT data and the beginning of the NRT observations. This gap and limited frequency coverage cause a strong degeneracy between the spindown parameters, time-varying DM, and orbital frequency evolution. We therefore perform a hybrid analysis, using the methods of Section 3.5, in which we use LAT data to determine the “long-term” parameters (F0, F1, FB0, FB1, and FB2). We then fix these parameters and fit for the astrometry using the radio data, finding a proper motion of $\text{PMRA} = 2.80 \pm 0.05$, $\text{PMDEC} = -5.30 \pm 0.11$ from which $\mu = 6.0 \pm 0.1 \text{ mas yr}^{-1}$. A systematic error comparable to or larger than the statistical uncertainty is likely, due to the inhomogeneous data used in the analysis.

# Appendix B

## Typical Gamma-Ray Spectral Energy Distributions

Figure B1 shows sample SEDs provided as part of 4FGL-DR3.<sup>128</sup> The figure set for this pulsar catalog includes a compilation of the SEDs of the gamma-ray pulsars. Additional material is available at https://fermi.gsfc.nasa.gov/ssc/data/access/lat/3rd_PSRoprCatalog/. This also includes the spectral parameters with their covariance matrices and the data points necessary to reproduce the SEDs, and a python script that performs the task.

<footnote n="128"><sup>128</sup> https://fermi.gsfc.nasa.gov/ssc/data/access/lat/12yr-prCatalog/</footnote>
Gamma-ray phase folding 14.5 yr of data using the JBO timing model revealed pulsations with test statistic $H = 122$ using the simple weights parameter $\mu_w = 4.3$. Model weights increase this to $H = 133$. $H$ increases steadily for the 8.5 yr before the start of the timing model, indicating that the MSPs spindown rate is stable, well-described using only spin frequency and its first derivative. The radio source is bright ($250\sigma$ in the discovery observation), and the profile has sharp features; hence, this MSP may rate inclusion in gravitational wave searches.

**PSR J1857+0943:** This 5.36 ms pulsar has long been known for its stable rotation rate (Segelstein et al. 1986). Gamma-ray phase folding using the rotation ephemeris provided by Reardon et al. (2021) yielded $H$-test >30, using simple weights. Located in a high background region, $(l, b) = (42.2, 3.12)$ degrees, the gamma-ray profile is ill-defined but appears to be dominated by a single narrow peak. The timing parallax distance from Table 8 and the integral energy flux of the colocated LAT source 4FGL J1857.2+0941 give $L_{\gamma} = (1.27 \pm 0.31_{-0.9}^{+0.6}) \times 10^{33} \text{ erg s}^{-1}$, where the first uncertainty comes from the flux measurement and the second from the distance, about 30% of the spindown power.

**PSR J1901-0125:** The same procedure as described for PSR J1827-0849, above, led to the 2016 discovery of 2.79 ms gamma-ray pulsations. F. Camilo then re-analyzed GBT radio data from previous observations of the LAT source position using the LAT rotation ephemeris and discovered radio pulsations and measured the DM. Table 3 lists $S_{1400} = 2.50$ mJy, extrapolated from the Frail et al. (2016) GMRT flux density of $362 \pm 15$ mJy at 150 MHz and radio spectral index -2.23. Table 8 lists a $2.4\sigma$ proper-motion measurement using

the methods of Section 3.5. Clark and co-workers are studying other LAT unidentified sources colocated with steep-spectrum radio sources and will detail their methods and results in future work.

**PSR J2256-1024:** Crowter et al. (2020) found $\mu = 9 \pm 3 \text{mas yr}^{-1}$ using GBT timing data. NRT has also monitored this pulsar, but with a substantial gap between the end of the GBT data and the beginning of the NRT observations. This gap and limited frequency coverage cause a strong degeneracy between the spindown parameters, time-varying DM, and orbital frequency evolution. We therefore perform a hybrid analysis, using the methods of Section 3.5, in which we use LAT data to determine the “long-term” parameters (F0, F1, FB0, FB1, and FB2). We then fix these parameters and fit for the astrometry using the radio data, finding a proper motion of $\text{PMRA} = 2.80 \pm 0.05$, $\text{PMDEC} = -5.30 \pm 0.11$ from which $\mu = 6.0 \pm 0.1 \text{ mas yr}^{-1}$. A systematic error comparable to or larger than the statistical uncertainty is likely, due to the inhomogeneous data used in the analysis.

# Appendix B

## Typical Gamma-Ray Spectral Energy Distributions

Figure B1 shows sample SEDs provided as part of 4FGL-DR3.<sup>128</sup> The figure set for this pulsar catalog includes a compilation of the SEDs of the gamma-ray pulsars. Additional material is available at https://fermi.gsfc.nasa.gov/ssc/data/access/lat/3rd_PSR catalogue/. This also includes the spectral parameters with their covariance matrices and the data points necessary to reproduce the SEDs, and a python script that performs the task.

<footnote n="128">128 https://fermi.gsfc.nasa.gov/ssc/data/access/lat/12yr catalogue/</footnote>
<figure><img src="image_31.png" /></figure>

**Figure B1.** Typical gamma-ray spectral energy distributions (SEDs). The plots were made using the python script `sed Plotter.py` and data files. The SEDs for all of the gamma-ray pulsars detected as point sources (TS > 25) are also available. Similar to those provided with 4FGL-DR3, they use the refits done for some pulsars, described in Section 6. When $b_{fr}$ exists, both $b_{23}$ and $b_{fr}$ fits are shown, with the $b_{fr}$ uncertainty envelope. The complete figure set (294 images) is available.
(The complete figure set (294 images) is available.)

# Appendix C

## Additional Notes on Spectral Analysis

We study here the distribution of the model parameters and derived physical quantities as they vary among the 116 pulsars, which have both *b*-free and *b* = 2/3 fits available. These results are presented in Figure C1. In brief, they are as follows:

1. $\Gamma$, the spectral index at the reference energy $E_0$, is stable, varying by <10% over the effective range in *b*.

2. The curvature at the reference energy, *d*, varies more than $\Gamma$, by up to ~50%. If considering *b* < 1, the total range is only about ±20%.

3. $\Gamma_{100}$ varies almost linearly with *b* before saturating at *b* = 1.2. The shift is up to 1 unit harder for pulsars with *b* near 0, and 0.5 units softer for (mostly) MSPs with $b \ge 1.2$. Thus, clearly, freeing *b* profoundly alters the inferred low-energy spectral index.

4. The curvature at the peak, $d_p$, is stable if the intrinsic value of $b > 0.5$. For pulsars with spectra more consistent with small *b*, the *b*-free pulsars become sharper, with a difference in log-width ranging up to 2×. It is not (yet) clear if this difference primarily “fixes” the true width of the peak or delivers a better low-energy index.

5. The peak energy $E_p$ varies by <10%–15% in the “core” *b* range and <25% overall. The largest deviations are for the MSPs with fit values $b > 1$, which move to higher $E_p$.

In summary, the physical properties measured at the peak, $d_p$ and $E_p$, are robustly measured in both *b*-free and *b* = 2/3 fits, and so we can make inferences on their distribution using the entire pulsar sample. On the other hand, the low-energy spectrum is unreliable, and values inferred from the $b = 2/3$ model could be very far from the true values.
<figure><img src="image_32.png" /></figure>

**Figure B1.** Typical gamma-ray spectral energy distributions (SEDs). The plots were made using the python script `sed Plotter.py` and data files. The SEDs for all of the gamma-ray pulsars detected as point sources (TS > 25) are also available. Similar to those provided with 4FGL-DR3, they use the refits done for some pulsars, described in Section 6. When $b_{fr}$ exists, both $b_{23}$ and $b_{fr}$ fits are shown, with the $b_{fr}$ uncertainty envelope. The complete figure set (294 images) is available.
(The complete figure set (294 images) is available.)

# Appendix C

## Additional Notes on Spectral Analysis

We study here the distribution of the model parameters and derived physical quantities as they vary among the 116 pulsars, which have both *b*-free and *b* = 2/3 fits available. These results are presented in Figure C1. In brief, they are as follows:

1. $\Gamma$, the spectral index at the reference energy $E_0$, is stable, varying by <10% over the effective range in *b*.

2. The curvature at the reference energy, *d*, varies more than $\Gamma$, by up to ~50%. If considering *b* < 1, the total range is only about ±20%.

3. $\Gamma_{100}$ varies almost linearly with *b* before saturating at *b* = 1.2. The shift is up to 1 unit harder for pulsars with *b* near 0, and 0.5 units softer for (mostly) MSPs with $b \ge 1.2$. Thus, clearly, freeing *b* profoundly alters the inferred low-energy spectral index.

4. The curvature at the peak, $d_p$, is stable if the intrinsic value of $b > 0.5$. For pulsars with spectra more consistent with small *b*, the *b*-free pulsars become sharper, with a difference in log-width ranging up to 2×. It is not (yet) clear if this difference primarily “fixes” the true width of the peak or delivers a better low-energy index.

5. The peak energy $E_p$ varies by <10%–15% in the “core” *b* range and <25% overall. The largest deviations are for the MSPs with fit values $b > 1$, which move to higher $E_p$.

In summary, the physical properties measured at the peak, $d_p$ and $E_p$, are robustly measured in both *b*-free and *b* = 2/3 fits, and so we can make inferences on their distribution using the entire pulsar sample. On the other hand, the low-energy spectrum is unreliable, and values inferred from the $b = 2/3$ model could be very far from the true values.
<figure><img src="image_32.png" /><figcaption>**Figure C1.** Comparisons of base and derived parameters between the *b* = 2/3 and *b*-free populations. See the main text for further discussion.</figcaption></figure>

## Appendix D
### Description of the Catalog Files

Supplementary material is available at https://fermi.gsfc.nasa.gov/ssc/data/access/lat/3rd_PSR catalogue/. Here we describe the files posted as of publication. Additional material may be added in the future. Static versions of some data used in this work are also available. The “xxx” in the file names is a multidigit time stamp of the file creation date. Contact the authors to request missing information.

3PC_Catalog+SEDs_xxx.fits, 3PC_Catalog_xxx.xls: The pulsar catalog “flat file,” in FITS and spreadsheet formats. Each has 294 rows, one for each gamma-ray pulsar. The 112 columns contain basic pulsar properties (name, position, spin parameters, distance, radio flux density, etc.) as well as the spectral and profile parameters described in this article. The

FITS version includes a subtable (“HDU”) with the detailed spectral fit parameters and covariance matrix needed to reproduce the SEDs, provided in 3PC_SEDs.tgz (individual plots) and 3PC_AllSEDs.pdf (all plots concatenated into a single file). 3PC_SEDPlotter.tgz contains a python script that reads 3PC_Catalog+SEDs_xxx.fits to generate the SED plots. Most Figures and Tables in this article were created from the FITS and spreadsheet files: the python script Example_3PC_CatalogReader.py is a simple example. README_3PC_Catalog+SEDs_xxx.txt provides more detail. These materials are available with the article in the datacat.tar.gz package.

3PC_ProfileData_xxx.tgz: Contains two files for each pulsar, one in FITS format and the other in simple text (ascii), containing the weighted gamma-ray phase histograms and, when they exist, the fit to the histogram and/or the radio
<figure><img src="image_33.png" /><figcaption>**Figure C1.** Comparisons of base and derived parameters between the *b* = 2/3 and *b*-free populations. See the main text for further discussion.</figcaption></figure>

## Appendix D
### Description of the Catalog Files

Supplementary material is available at https://fermi.gsfc.nasa.gov/ssc/data/access/lat/3rd_PSR catalogue/. Here we describe the files posted as of publication. Additional material may be added in the future. Static versions of some data used in this work are also available. The “xxx” in the file names is a multidigit time stamp of the file creation date. Contact the authors to request missing information.

3PC_Catalog+SEDs_xxx.fits, 3PC_Catalog_xxx.xls: The pulsar catalog “flat file,” in FITS and spreadsheet formats. Each has 294 rows, one for each gamma-ray pulsar. The 112 columns contain basic pulsar properties (name, position, spin parameters, distance, radio flux density, etc.) as well as the spectral and profile parameters described in this article. The

FITS version includes a subtable (“HDU”) with the detailed spectral fit parameters and covariance matrix needed to reproduce the SEDs, provided in 3PC_SEDs.tgz (individual plots) and 3PC_AllSEDs.pdf (all plots concatenated into a single file). 3PC_SEDPlotter.tgz contains a python script that reads 3PC_Catalog+SEDs_xxx.fits to generate the SED plots. Most Figures and Tables in this article were created from the FITS and spreadsheet files: the python script Example_3PC_CatalogReader.py is a simple example. README_3PC_Catalog+SEDs_xxx.txt provides more detail. These materials are available with the article in the datacat.tar.gz package.

3PC_ProfileData_xxx.tgz: Contains two files for each pulsar, one in FITS format and the other in simple text (ascii), containing the weighted gamma-ray phase histograms and, when they exist, the fit to the histogram and/or the radio
profile. The python script `Example_3PC_PlotProfile-Data.py` illustrates how to read the files to reproduce the plots provided in `3PC_ProfilePlotsPDF_xxx.tgz` and `3PC_ProfilePlotsPNG_xxx.tgz`. The plots of gamma-ray peak evolution with energy, as in Figure Set 12, are provided in `3PC_LC_Eres_pdf_xxx.tgz`, `3PC_LC_Eres_png_xxx.tgz`. `README_ProfileData.txt` provides details. These materials are available with the article in the `datapro.tar.gz` package.

**3PC_TimingModels_xxx.tgz:** A compressed archive of the 294 rotation ephemerides (".par files") used to calculate the gamma-ray rotational phases using software such as TEMPO2 or PINT. `README_3PC_TimingModels.txt` provides details. These materials are available with in the `datapar.tar.gz` package.

**Phased, weighted FT1 FITS files:** available at https://heasarc.gsfc.nasa.gov/FTP/fermi/data/lat/catalogs/3PC/photon/. Two subdirectories called `3deg_50MeV` and `15deg_20MeV` each contain one file for each gamma-ray pulsar, in the standard Fermi LAT data format, with additional columns `PHASE` and `MODEL_WEIGHT`. The 277 files in `3deg_50MeV` include photons with energies >50 MeV, within 3° of the pulsar position, and were used to create the gamma-ray phase histograms. They occupy roughly 30 GB of disk space, with a large variation in single file size depending on the background intensity (generally decreasing away from the Galactic plane) and pulsar intensity. The files in `15deg_20-MeV` are on average 15× larger, including photons with energies >20 MeV within 15° of the pulsar position. They are suitable for spectral analyses (e.g., using the `gtlike` Fermi tool) or to explore the lowest LAT photon energies. `README_3PC_PhotonData_.txt` describes the FT1 files in more detail.

**3PC_sensitivity_xxx.fits:** The all-sky Fermi LAT pulsar sensitivity, in FITS format, is useful for, e.g., population syntheses. Example_3PC_SensitivityMap_xxx.py is a python script that reads the FITS file and generates a plot as in Figure 25. `README_3PC_SensitivityMap_xxx.txt` provides details.

Finally, we provide HTML files for each pulsar, to allow for a visual summary of the information for each gamma-ray pulsar, named `3PC/J0007+7303_LAT.html` and so on.

*Note added in proof.* Perez et al. (2023) discovered a 2.11 ms pulsar at the position of 4FGL J0212.1+5321.

## ORCID iDs

D. A. Smith https://orcid.org/0000-0002-7833-0275

S. Abdollahi https://orcid.org/0000-0002-6803-3605

M. Ajello https://orcid.org/0000-0002-6584-1703

M. Bailes https://orcid.org/0000-0003-3294-3081

L. Baldini https://orcid.org/0000-0002-9785-7726

J. Ballet https://orcid.org/0000-0002-8784-2977

M. G. Baring https://orcid.org/0000-0003-4433-1365

J. Becerra Gonzalez https://orcid.org/0000-0002-6729-9022

R. Bellazzini https://orcid.org/0000-0002-2469-7063

A. Berretta https://orcid.org/0000-0001-8008-2920

B. Bhattacharyya https://orcid.org/0000-0002-6287-6900

E. Bissaldi https://orcid.org/0000-0001-9935-8106

R. Bonino https://orcid.org/0000-0002-4264-1215

J. Bregeon https://orcid.org/0000-0002-6790-5328

P. Bruel https://orcid.org/0000-0002-9032-7941

M. Burgay https://orcid.org/0000-0002-8265-4344

R. A. Cameron https://orcid.org/0000-0003-0942-2747

F. Camilo https://orcid.org/0000-0002-1873-3718

R. Caputo https://orcid.org/0000-0002-9280-836X

P. A. Caraveo https://orcid.org/0000-0003-2478-8018

S. Ciprini https://orcid.org/0000-0002-0712-2479

C. J. Clark https://orcid.org/0000-0003-4355-3572

I. Cognard https://orcid.org/0000-0002-1775-9692

A. Corongiu https://orcid.org/0000-0002-5924-3141

P. Cristarella Orestano https://orcid.org/0000-0003-3219-608X

M. Crnogorcevic https://orcid.org/0000-0002-7604-1779

A. Cuoco https://orcid.org/0000-0003-1504-894X

S. Cutini https://orcid.org/0000-0002-1271-2924

F. D'Ammando https://orcid.org/0000-0001-7618-7527

M. E. DeCesar https://orcid.org/0000-0002-2185-1790

S. De Gaetano https://orcid.org/0000-0002-3358-2559

R. de Menezes https://orcid.org/0000-0001-5489-4925

J. Deneva https://orcid.org/0000-0003-1226-0793

F. de Palma https://orcid.org/0000-0001-5898-2834

N. Di Lalla https://orcid.org/0000-0002-7574-1298

F. Dirirsa https://orcid.org/0000-0002-3909-6711

L. Di Venere https://orcid.org/0000-0003-0703-824X

A. Domínguez https://orcid.org/0000-0002-3433-4610

E. C. Ferrara https://orcid.org/0000-0001-7828-7708

A. Fiori https://orcid.org/0000-0003-3174-0688

H. Fleischhack https://orcid.org/0000-0002-0794-8780

C. Flynn https://orcid.org/0000-0003-1110-0712

A. Franckowiak https://orcid.org/0000-0002-5605-2219

P. C. C. Freire https://orcid.org/0000-0003-1307-9435

Y. Fukazawa https://orcid.org/0000-0002-0921-8837

P. Fusco https://orcid.org/0000-0002-9383-2425

G. Galanti https://orcid.org/0000-0001-7254-3029

V. Gammaldi https://orcid.org/0000-0003-1826-6117

F. Gargano https://orcid.org/0000-0002-5055-6395

D. Gasparrini https://orcid.org/0000-0002-5064-9495

F. Giacchino https://orcid.org/0000-0002-0247-6884

N. Giglietto https://orcid.org/0000-0002-9021-2888

M. Giroletti https://orcid.org/0000-0002-8657-8852

D. Green https://orcid.org/0000-0003-0768-2203

I. A. Grenier https://orcid.org/0000-0003-3274-674X

L. Guillemot https://orcid.org/0000-0002-9049-8716

S. Guiriec https://orcid.org/0000-0001-5780-8770

E. Hays https://orcid.org/0000-0002-8172-593X

J. W. Hewitt https://orcid.org/0000-0002-4064-6346

D. Horan https://orcid.org/0000-0001-5574-2579

X. Hou https://orcid.org/0000-0003-0933-6101

F. Jankowski https://orcid.org/0000-0002-6658-2811

R. P. Johnson https://orcid.org/0000-0002-7850-3711

J. Kataoka https://orcid.org/0000-0003-2819-6415

M. Kerr https://orcid.org/0000-0002-0893-4073

M. Kramer https://orcid.org/0000-0002-4175-2271

M. Kuss https://orcid.org/0000-0003-1212-9998

L. Latronico https://orcid.org/0000-0002-0984-1856

J. Li https://orcid.org/0000-0003-1720-9727

F. Longo https://orcid.org/0000-0003-2501-2270

F. Loparco https://orcid.org/0000-0002-1173-5673

L. Lorusso https://orcid.org/0000-0002-2549-4401

M. N. Lovellette https://orcid.org/0000-0002-0332-5113

M. Lower https://orcid.org/0000-0001-9208-0009
profile. The python script `Example_3PC_PlotProfile-Data.py` illustrates how to read the files to reproduce the plots provided in `3PC_ProfilePlotsPDF_xxx.tgz` and `3PC_ProfilePlotsPNG_xxx.tgz`. The plots of gamma-ray peak evolution with energy, as in Figure Set 12, are provided in `3PC_LC_Eres_pdf_xxx.tgz`, `3PC_LC_Eres_png_xxx.tgz`. `README_ProfileData.txt` provides details. These materials are available with the article in the `datapro.tar.gz` package.

**3PC_TimingModels_xxx.tgz:** A compressed archive of the 294 rotation ephemerides (".par files") used to calculate the gamma-ray rotational phases using software such as TEMPO2 or PINT. `README_3PC_TimingModels.txt` provides details. These materials are available with in the `datapar.tar.gz` package.

**Phased, weighted FT1 FITS files:** available at https://heasarc.gsfc.nasa.gov/FTP/fermi/data/lat/catalogs/3PC/photon/. Two subdirectories called `3deg_50MeV` and `15deg_20MeV` each contain one file for each gamma-ray pulsar, in the standard Fermi LAT data format, with additional columns `PHASE` and `MODEL_WEIGHT`. The 277 files in `3deg_50MeV` include photons with energies >50 MeV, within 3° of the pulsar position, and were used to create the gamma-ray phase histograms. They occupy roughly 30 GB of disk space, with a large variation in single file size depending on the background intensity (generally decreasing away from the Galactic plane) and pulsar intensity. The files in `15deg_20-MeV` are on average 15× larger, including photons with energies >20 MeV within 15° of the pulsar position. They are suitable for spectral analyses (e.g., using the `gtlike` Fermi tool) or to explore the lowest LAT photon energies. `README_3PC_PhotonData_.txt` describes the FT1 files in more detail.

**3PC_sensitivity_xxx.fits:** The all-sky Fermi LAT pulsar sensitivity, in FITS format, is useful for, e.g., population syntheses. Example_3PC_SensitivityMap_xxx.py is a python script that reads the FITS file and generates a plot as in Figure 25. `README_3PC_SensitivityMap_xxx.txt` provides details.

Finally, we provide HTML files for each pulsar, to allow for a visual summary of the information for each gamma-ray pulsar, named `3PC/J0007+7303_LAT.html` and so on.

*Note added in proof.* Perez et al. (2023) discovered a 2.11 ms pulsar at the position of 4FGL J0212.1+5321.

## ORCID iDs

D. A. Smith https://orcid.org/0000-0002-7833-0275

S. Abdollahi https://orcid.org/0000-0002-6803-3605

M. Ajello https://orcid.org/0000-0002-6584-1703

M. Bailes https://orcid.org/0000-0003-3294-3081

L. Baldini https://orcid.org/0000-0002-9785-7726

J. Ballet https://orcid.org/0000-0002-8784-2977

M. G. Baring https://orcid.org/0000-0003-4433-1365

J. Becerra Gonzalez https://orcid.org/0000-0002-6729-9022

R. Bellazzini https://orcid.org/0000-0002-2469-7063

A. Berretta https://orcid.org/0000-0001-8008-2920

B. Bhattacharyya https://orcid.org/0000-0002-6287-6900

E. Bissaldi https://orcid.org/0000-0001-9935-8106

R. Bonino https://orcid.org/0000-0002-4264-1215

J. Bregeon https://orcid.org/0000-0002-6790-5328

P. Bruel https://orcid.org/0000-0002-9032-7941

M. Burgay https://orcid.org/0000-0002-8265-4344

R. A. Cameron https://orcid.org/0000-0003-0942-2747

F. Camilo https://orcid.org/0000-0002-1873-3718

R. Caputo https://orcid.org/0000-0002-9280-836X

P. A. Caraveo https://orcid.org/0000-0003-2478-8018

S. Ciprini https://orcid.org/0000-0002-0712-2479

C. J. Clark https://orcid.org/0000-0003-4355-3572

I. Cognard https://orcid.org/0000-0002-1775-9692

A. Corongiu https://orcid.org/0000-0002-5924-3141

P. Cristarella Orestano https://orcid.org/0000-0003-3219-608X

M. Crnogorcevic https://orcid.org/0000-0002-7604-1779

A. Cuoco https://orcid.org/0000-0003-1504-894X

S. Cutini https://orcid.org/0000-0002-1271-2924

F. D'Ammando https://orcid.org/0000-0001-7618-7527

M. E. DeCesar https://orcid.org/0000-0002-2185-1790

S. De Gaetano https://orcid.org/0000-0002-3358-2559

R. de Menezes https://orcid.org/0000-0001-5489-4925

J. Deneva https://orcid.org/0000-0003-1226-0793

F. de Palma https://orcid.org/0000-0001-5898-2834

N. Di Lalla https://orcid.org/0000-0002-7574-1298

F. Dirirsa https://orcid.org/0000-0002-3909-6711

L. Di Venere https://orcid.org/0000-0003-0703-824X

A. Domínguez https://orcid.org/0000-0002-3433-4610

E. C. Ferrara https://orcid.org/0000-0001-7828-7708

A. Fiori https://orcid.org/0000-0003-3174-0688

H. Fleischhack https://orcid.org/0000-0002-0794-8780

C. Flynn https://orcid.org/0000-0003-1110-0712

A. Franckowiak https://orcid.org/0000-0002-5605-2219

P. C. C. Freire https://orcid.org/0000-0003-1307-9435

Y. Fukazawa https://orcid.org/0000-0002-0921-8837

P. Fusco https://orcid.org/0000-0002-9383-2425

G. Galanti https://orcid.org/0000-0001-7254-3029

V. Gammaldi https://orcid.org/0000-0003-1826-6117

F. Gargano https://orcid.org/0000-0002-5055-6395

D. Gasparrini https://orcid.org/0000-0002-5064-9495

F. Giacchino https://orcid.org/0000-0002-0247-6884

N. Giglietto https://orcid.org/0000-0002-9021-2888

M. Giroletti https://orcid.org/0000-0002-8657-8852

D. Green https://orcid.org/0000-0003-0768-2203

I. A. Grenier https://orcid.org/0000-0003-3274-674X

L. Guillemot https://orcid.org/0000-0002-9049-8716

S. Guiriec https://orcid.org/0000-0001-5780-8770

E. Hays https://orcid.org/0000-0002-8172-593X

J. W. Hewitt https://orcid.org/0000-0002-4064-6346

D. Horan https://orcid.org/0000-0001-5574-2579

X. Hou https://orcid.org/0000-0003-0933-6101

F. Jankowski https://orcid.org/0000-0002-6658-2811

R. P. Johnson https://orcid.org/0000-0002-7850-3711

J. Kataoka https://orcid.org/0000-0003-2819-6415

M. Kerr https://orcid.org/0000-0002-0893-4073

M. Kramer https://orcid.org/0000-0002-4175-2271

M. Kuss https://orcid.org/0000-0003-1212-9998

L. Latronico https://orcid.org/0000-0002-0984-1856

J. Li https://orcid.org/0000-0003-1720-9727

F. Longo https://orcid.org/0000-0003-2501-2270

F. Loparco https://orcid.org/0000-0002-1173-5673

L. Lorusso https://orcid.org/0000-0002-2549-4401

M. N. Lovellette https://orcid.org/0000-0002-0332-5113

M. Lower https://orcid.org/0000-0001-9208-0009
P. Lubrano https://orcid.org/0000-0003-0221-4806

S. Maldera https://orcid.org/0000-0002-0698-4421

R. N. Manchester https://orcid.org/0000-0001-9445-5732

A. Manfreda https://orcid.org/0000-0002-0998-4953

G. Martí-Devesa https://orcid.org/0000-0003-0766-6473

M. N. Mazziotta https://orcid.org/0000-0001-9325-4672

I. Mereu https://orcid.org/0000-0003-0219-4534

P. F. Michelson https://orcid.org/0000-0002-1321-5620

W. Mitthumsiri https://orcid.org/0000-0002-3776-072X

T. Mizuno https://orcid.org/0000-0001-7263-0296

A. A. Moiseev https://orcid.org/0000-0002-1273-9959

M. E. Monzani https://orcid.org/0000-0002-8254-5308

A. Morselli https://orcid.org/0000-0002-7704-9553

M. Negro https://orcid.org/0000-0002-6548-5622

R. Nemmen https://orcid.org/0000-0003-3956-0331

L. Nieder https://orcid.org/0000-0002-5775-8977

N. Omodei https://orcid.org/0000-0002-5448-7577

M. Orienti https://orcid.org/0000-0003-4470-7094

J. F. Ormeslo https://orcid.org/0000-0002-7220-6409

M. Palatiello https://orcid.org/0000-0002-4124-5747

G. Panzarini https://orcid.org/0000-0002-2586-1021

M. Persic https://orcid.org/0000-0003-1853-4900

M. Pesce-Rollins https://orcid.org/0000-0003-1790-8018

R. Pillera https://orcid.org/0000-0003-3808-963X

A. Possenti https://orcid.org/0000-0001-5902-3731

G. Principe https://orcid.org/0000-0003-0406-7387

S. Rainò https://orcid.org/0000-0002-9181-0345

R. Rando https://orcid.org/0000-0001-6992-818X

S. M. Ransom https://orcid.org/0000-0001-5799-9714

P. S. Ray https://orcid.org/0000-0002-5297-5278

M. Razzano https://orcid.org/0000-0003-4825-1629

S. Razzaque https://orcid.org/0000-0002-0130-2460

A. Reimer https://orcid.org/0000-0001-8604-7077

O. Reimer https://orcid.org/0000-0001-6953-1385

N. Renault-Tinacci https://orcid.org/0000-0001-8443-8007

R. W. Romani https://orcid.org/0000-0001-6711-3286

M. Sánchez-Conde https://orcid.org/0000-0002-3849-9164

L. Scotton https://orcid.org/0000-0002-0602-0235

D. Serini https://orcid.org/0000-0002-9754-6530

C. Sgrò https://orcid.org/0000-0001-5676-6214

V. Sharma https://orcid.org/0000-0002-4394-4138

E. J. Siskind https://orcid.org/0000-0002-2872-2553

G. Spandre https://orcid.org/0000-0003-0802-3453

D. J. Suson https://orcid.org/0000-0003-2911-2025

H. Tajima https://orcid.org/0000-0002-1721-7252

D. Tak https://orcid.org/0000-0002-9852-2469

D. J. Thompson https://orcid.org/0000-0001-5217-9135

D. F. Torres https://orcid.org/0000-0002-1522-9065

J. Valverde https://orcid.org/0000-0002-8090-6528

C. Venter https://orcid.org/0000-0002-2666-4812

Z. Wadiasingh https://orcid.org/0000-0002-9249-0515

N. Wang https://orcid.org/0000-0002-9786-8548

K. Wood https://orcid.org/0000-0002-7376-3151

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P. Lubrano https://orcid.org/0000-0003-0221-4806

S. Maldera https://orcid.org/0000-0002-0698-4421

R. N. Manchester https://orcid.org/0000-0001-9445-5732

A. Manfreda https://orcid.org/0000-0002-0998-4953

G. Martí-Devesa https://orcid.org/0000-0003-0766-6473

M. N. Mazziotta https://orcid.org/0000-0001-9325-4672

I. Mereu https://orcid.org/0000-0003-0219-4534

P. F. Michelson https://orcid.org/0000-0002-1321-5620

W. Mitthumsiri https://orcid.org/0000-0002-3776-072X

T. Mizuno https://orcid.org/0000-0001-7263-0296

A. A. Moiseev https://orcid.org/0000-0002-1273-9959

M. E. Monzani https://orcid.org/0000-0002-8254-5308

A. Morselli https://orcid.org/0000-0002-7704-9553

M. Negro https://orcid.org/0000-0002-6548-5622

R. Nemmen https://orcid.org/0000-0003-3956-0331

L. Nieder https://orcid.org/0000-0002-5775-8977

N. Omodei https://orcid.org/0000-0002-5448-7577

M. Orienti https://orcid.org/0000-0003-4470-7094

J. F. Ormeslo https://orcid.org/0000-0002-7220-6409

M. Palatiello https://orcid.org/0000-0002-4124-5747

G. Panzarini https://orcid.org/0000-0002-2586-1021

M. Persic https://orcid.org/0000-0003-1853-4900

M. Pesce-Rollins https://orcid.org/0000-0003-1790-8018

R. Pillera https://orcid.org/0000-0003-3808-963X

A. Possenti https://orcid.org/0000-0001-5902-3731

G. Principe https://orcid.org/0000-0003-0406-7387

S. Rainò https://orcid.org/0000-0002-9181-0345

R. Rando https://orcid.org/0000-0001-6992-818X

S. M. Ransom https://orcid.org/0000-0001-5799-9714

P. S. Ray https://orcid.org/0000-0002-5297-5278

M. Razzano https://orcid.org/0000-0003-4825-1629

S. Razzaque https://orcid.org/0000-0002-0130-2460

A. Reimer https://orcid.org/0000-0001-8604-7077

O. Reimer https://orcid.org/0000-0001-6953-1385

N. Renault-Tinacci https://orcid.org/0000-0001-8443-8007

R. W. Romani https://orcid.org/0000-0001-6711-3286

M. Sánchez-Conde https://orcid.org/0000-0002-3849-9164

L. Scotton https://orcid.org/0000-0002-0602-0235

D. Serini https://orcid.org/0000-0002-9754-6530

C. Sgrò https://orcid.org/0000-0001-5676-6214

V. Sharma https://orcid.org/0000-0002-4394-4138

E. J. Siskind https://orcid.org/0000-0002-2872-2553

G. Spandre https://orcid.org/0000-0003-0802-3453

D. J. Suson https://orcid.org/0000-0003-2911-2025

H. Tajima https://orcid.org/0000-0002-1721-7252

D. Tak https://orcid.org/0000-0002-9852-2469

D. J. Thompson https://orcid.org/0000-0001-5217-9135

D. F. Torres https://orcid.org/0000-0002-1522-9065

J. Valverde https://orcid.org/0000-0002-8090-6528

C. Venter https://orcid.org/0000-0002-2666-4812

Z. Wadiasingh https://orcid.org/0000-0002-9249-0515

N. Wang https://orcid.org/0000-0002-9786-8548

K. Wood https://orcid.org/0000-0002-7376-3151

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