adsabs/AstroCLIMB huggingface dataset:
Paper: Demonstrating Photon Ring Existence with Single-baseline Polarimetry
Authors: Daniel C. M. Palumbo, George N. Wong, Andrew Chael, Michael D. Johnson
Figure caption: Spiral quotient phase (bottom row) for snapshots of the same GRMHD fluid frame at four different frequencies, ray traced with M87* parameters. The dashed green circle shows Earth-diameter baselines at each frequency. At higher frequencies, the direct image becomes relatively fainter compared to the indirect image, causing the crossing point between n = 0 and n = 1 to move inward to shorter baselines just in reach of Earth-based VLBI; at 345 GHz, Earth-space VLBI appears viable for finding the photon ring phase change.
Paper: Demonstrating Photon Ring Existence with Single-baseline Polarimetry
Authors: Daniel C. M. Palumbo, George N. Wong, Andrew Chael, Michael D. Johnson
Figure caption: Maximum permissible thermal noise on individual visibility measurements allowed for robust spiral quotient phase signal in snapshot detections as given by Equation (20), averaged at each point over one thousand gravitational times for M87* (left) and Sgr A* (right), plotted alongside the refractive scattering noise on each axis in dashed lines for Sgr A*. Differences between sampling along u and v reflect intrinsic source structure caused by nonzero inclination, as well as scattering anisotropy in the case of Sgr A*. The sensitivity required to recover the phase in Sgr A* with Earth-diameter interferometry (lime green) stays approximately constant in frequency, though the phase is dominated by refractive substructure at the lower frequencies.
Paper: Demonstrating Photon Ring Existence with Single-baseline Polarimetry
Authors: Daniel C. M. Palumbo, George N. Wong, Andrew Chael, Michael D. Johnson
Figure caption: Left: plots of the Bessel functions J 0 and J 2 corresponding to the interferometric response to rotationally symmetric Stokes I and Q + iU images, respectively, assuming d = 40 μas. Right: relative sign of the two functions, which is constant after the first null of J 0 except for an asymptotically shrinking region between the nulls of J 0 and J 2.
Paper: Demonstrating Photon Ring Existence with Single-baseline Polarimetry
Authors: Daniel C. M. Palumbo, George N. Wong, Andrew Chael, Michael D. Johnson
Figure caption: Spiral quotient phase (bottom row) for a time-averaged MAD simulation with spin a * = 0.5 and R high = 80, ray traced at 230 GHz and decomposed into the direct (n = 0), indirect (n = 1) and full (all n) images (top row). In the bottom right panel, the n = 0 phase dominates on short baselines until the direct image thickness is resolved, at which point the n = 1 phase dominates the combined signal. The dashed green circle shows Earth-diameter baselines, which never reach the n = 1 dominated regime at 230 GHz.
Paper: Demonstrating Photon Ring Existence with Single-baseline Polarimetry
Authors: Daniel C. M. Palumbo, George N. Wong, Andrew Chael, Michael D. Johnson
Figure caption: Top left: (u, v) coverage from ALMA, GLT, and SMA at 230, 345, and 690 GHz. Top right: distributions of ﹩\angle {\breve{\beta }}_{2}﹩ at each (u, v) point over the duration of the M87* simulation. Bottom row: same as top row, but for Sgr A*, using ALMA, SPT, and SMA. Observations are computed assuming a perfect, noiseless instrument observing every 20 minutes. The temporal variation is increased when the visibility response to a ∼40 μas ring passes through nulls, as well as when the n = 0 and n = 1 contributions are comparable (around 15 Gλ). However, the longest baselines at 690 GHz still have a mean value that is clearly distinguishable in sign from the short-baseline average. Moreover, the spiral quotient itself permits coherent averaging over long timescales, critical to the success of the experiment.
Paper: Disk Galaxies Are Self-similar: The Universality of the H I-to-Halo Mass Ratio for Isolated Disks
Authors: Marie Korsaga, Benoit Famaey, Jonathan Freundlich, Lorenzo Posti, Rodrigo Ibata, Christian Boily, Katarina Kraljic, D. Esparza-Arredondo, C. Ramos Almeida, Jean Koulidiati
Figure caption: Left panel: H I mass vs. halo mass for ∼2.1 × 104 central galaxies (irrespective of morphology) in Illustris-TNG50 (green) and for 3180 isolated disk galaxies in SIMBA with M 200 ≥ 109 M ⊙ and v/σ≥0.8 (gray). The lines represent the median of the binned data, and the 1σ band around the median is represented by the green and gray bands, respectively. Right panel: H I mass to halo mass ratio vs. stellar mass. The 1σ band around the median is represented by the green and gray bands. Green: ∼2.1 × 104 centrals in TNG50. Red dots: simulated galaxies with M ⋆ > 5 × 1010  M ⊙ in TNG50 and with the fractional mass of stars with a stellar circularity ϵ > 0.7 larger than 30%, hence disk galaxies in TNG50. Gray: 3180 isolated disk galaxies in SIMBA, with M 200 ≥ 109  M ⊙ and v/σ ≥ 0.8.
Paper: Disk Galaxies Are Self-similar: The Universality of the H I-to-Halo Mass Ratio for Isolated Disks
Authors: Marie Korsaga, Benoit Famaey, Jonathan Freundlich, Lorenzo Posti, Rodrigo Ibata, Christian Boily, Katarina Kraljic, D. Esparza-Arredondo, C. Ramos Almeida, Jean Koulidiati
Figure caption: Top left: H I-mass vs. halo mass for the 150 rotation curve fits with DZ profiles (magenta dots). The black line corresponds to the relation ﹩{M}_{\mathrm{HI}}=\mathrm{log}(\mathrm{median}({M}_{\mathrm{HI}}/{M}_{200}))\times {M}_{200}﹩. Top right: H I-to-halo-mass ratio vs. stellar mass for the same sample (magenta dots with their associated error bars): the magenta line corresponds to the median value, and the band corresponds to the 1σ zone (scatter = 0.37 dex; intrinsic scatter = 0.31 dex). Blue squares depict galaxies hosting an AGN. The gray band indicates the 1σ band from isolated disks in SIMBA as a comparison. Bottom left: H I-to-halo-mass ratio for the DZ fits of the SPARC galaxies as a function of disk central surface brightness at 3.6 μm. Bottom right: same as a function of bulge-to-disk-luminosity ratio for 31 galaxies with bulge.
Paper: Disk Galaxies Are Self-similar: The Universality of the H I-to-Halo Mass Ratio for Isolated Disks
Authors: Marie Korsaga, Benoit Famaey, Jonathan Freundlich, Lorenzo Posti, Rodrigo Ibata, Christian Boily, Katarina Kraljic, D. Esparza-Arredondo, C. Ramos Almeida, Jean Koulidiati
Figure caption: Left panel: H I mass as a function of stellar mass. The individual measurements for the 150 galaxies are presented as magenta dots. The contours correspond to the 9153 H ı-selected ALFALFA galaxies from Maddox et al. (2015; see that paper for details). The green and gray lines (bands) represent the median (1σ scatter) of the binned data of central galaxies in Illustris-TNG50 and isolated disk galaxies in SIMBA, respectively. The diagonal dashed line marks the one-to-one relation of equal H I and stellar masses. Right panel: H I-to-Halo-mass ratio vs. stellar mass for the 150 galaxies with blue circles indicating the median and scatter in each bin. The two simulated disk galaxies in both Illustris-TNG50 and SIMBA having M ⋆/M ⊙ > 1011 and the highest M HI/M 200 are represented as red squares and green stars, respectively.
Paper: Disk Galaxies Are Self-similar: The Universality of the H I-to-Halo Mass Ratio for Isolated Disks
Authors: Marie Korsaga, Benoit Famaey, Jonathan Freundlich, Lorenzo Posti, Rodrigo Ibata, Christian Boily, Katarina Kraljic, D. Esparza-Arredondo, C. Ramos Almeida, Jean Koulidiati
Figure caption: Galaxy F568-1. Top row: NFW; left panels: posterior distributions and mass model in right panel. Bottom row: DZ; left panels: posterior distributions and mass model in right panel.
Paper: AT 2023clx: The Faintest and Closest Optical Tidal Disruption Event Discovered in Nearby Star-forming Galaxy NGC 3799
Authors: Jiazheng Zhu, Ning Jiang, Tinggui Wang, Shifeng Huang, Zheyu Lin, Yibo Wang, Jian-Guo Wang
Figure caption: Top left: LCOGT g-band image, which was taken on 2023 February 26 UT. Top middle: PanSTARRS g-band stack image of the host galaxy. Top right: difference image of AT 2023clx. Middle: host-galaxy-subtracted light curves of AT 2023clx in the UV and optical bands. The triangles represent the upper limits, and the dashed curve shows the power-law profile fit to the AT 2023clx g-band curve (red line for rise and black t −5/3 line for decline). Bottom: the Swift/XRT light curve of AT 2023clx. The triangles represent the upper limits. AT 2023clx was non-detected in 0.3–10 keV in any single observation, or even in the stacked image. The stacked X-ray upper limit is shown as the black horizontal line with an arrow. (The data used to create this figure are available.)
Paper: AT 2023clx: The Faintest and Closest Optical Tidal Disruption Event Discovered in Nearby Star-forming Galaxy NGC 3799
Authors: Jiazheng Zhu, Ning Jiang, Tinggui Wang, Shifeng Huang, Zheyu Lin, Yibo Wang, Jian-Guo Wang
Figure caption: Evolution of the luminosity compared with iPTF16fnl (Blagorodnova et al. 2017), AT 2019qiz (Nicholl et al. 2020), and AT 2020wey (Charalampopoulos et al. 2023) (top panel), temperature (middle panel), and blackbody radius (bottom panel) of AT 2023clx. The dashed curve shows the ﹩{(t-{t}_{0})}^{-5/3}﹩ power law (t 0 = MJD 59,978 ± 4 days) fit to the AT 2023clx bolometric light curves after the peak, and the reference epoch is set to be the g-band peak at MJD = 60000.0.
Paper: AT 2023clx: The Faintest and Closest Optical Tidal Disruption Event Discovered in Nearby Star-forming Galaxy NGC 3799
Authors: Jiazheng Zhu, Ning Jiang, Tinggui Wang, Shifeng Huang, Zheyu Lin, Yibo Wang, Jian-Guo Wang
Figure caption: Distribution of galaxies in the SFR vs. the M stellar of galaxies from Chang et al. (2015). The SF sequence is shown in orange where the dashed lines show the 1σ scatter. The gray scale represents the number of galaxies after weighting by 1/﹩{V}_{\max }﹩. The red star symbol marks the NGC 3799, which is well located on the SF sequence region.
Paper: AT 2023clx: The Faintest and Closest Optical Tidal Disruption Event Discovered in Nearby Star-forming Galaxy NGC 3799
Authors: Jiazheng Zhu, Ning Jiang, Tinggui Wang, Shifeng Huang, Zheyu Lin, Yibo Wang, Jian-Guo Wang
Figure caption: The comparison of optical spectra between AT 2023clx and some other low-luminosity TDEs at similar phases, including iPTF16fnl (Blagorodnova et al. 2017), AT 2019qiz (Nicholl et al. 2020), and AT 2020wey (Charalampopoulos et al. 2023). Their spectroscopic evolution is nearly identical.
Paper: AT 2023clx: The Faintest and Closest Optical Tidal Disruption Event Discovered in Nearby Star-forming Galaxy NGC 3799
Authors: Jiazheng Zhu, Ning Jiang, Tinggui Wang, Shifeng Huang, Zheyu Lin, Yibo Wang, Jian-Guo Wang
Figure caption: Our estimated volumetric rate using AT 2020wey and AT 2023clx is marked by red point; compare with the TDE LF from van Velzen (2018), Lin et al. (2022b), Charalampopoulos et al. (2023), and Yao et al. (2023).
Paper: AT 2023clx: The Faintest and Closest Optical Tidal Disruption Event Discovered in Nearby Star-forming Galaxy NGC 3799
Authors: Jiazheng Zhu, Ning Jiang, Tinggui Wang, Shifeng Huang, Zheyu Lin, Yibo Wang, Jian-Guo Wang
Figure caption: The spectra acquired for AT 2023clx. The identified H and He lines are labeled at the top (red for helium and black for hydrogen).(The data used to create this figure are available.)
Paper: Implications of Atmospheric Nondetections for Trappist-1 Inner Planets on Atmospheric Retention Prospects for Outer Planets
Authors: Joshua Krissansen-Totton
Figure caption: Complete atmosphere erosion on Trappist-1b is unsurprising given the potential for continuous hydrodynamic escape until virtually all water is lost. All Trappist-1b evolutionary model outputs consistent with the absence of substantial surface volatiles today (<1 bar). Subplots denote (a) the evolution of mantle (blue) and surface temperature (red), (b) the solidification radius as it moves from the core–mantle boundary to the surface, (c) atmospheric abundances of water (red), oxygen (blue), and carbon dioxide (black), (d) the planetary energy budget including absorbed shortwave radiation (ASR; red), outgoing longwave radiation (OLR; blue), and interior heat flow (black), (e) carbon dioxide fluxes including magmatic outgassing (red), thermal escape (cyan), nonthermal escape (magenta), and weathering (black), and (f) oxygen fluxes including net oxygen gain via hydrogen escape (black), nonthermal O2 loss (red), and O2 consumption by crustal sinks (cyan). Shaded regions denote 95% confidence intervals across all model outputs consistent with the hypothetical lack of an atmosphere.
Paper: Implications of Atmospheric Nondetections for Trappist-1 Inner Planets on Atmospheric Retention Prospects for Outer Planets
Authors: Joshua Krissansen-Totton
Figure caption: Initial volatile inventories for Trappist-1b consistent with the absence of a substantial modern atmosphere. Magenta distributions show initial volatile compositions from all Trappist-1b evolutionary calculations. Cyan and dotted distributions show initial volatile distributions that result in modern surface pressures <10 and <1 bar, respectively. Forward modeling with the PACMAN geochemical model (Figure 1) shows that initial water inventories (left) must have been <∼100 Earth oceans to permit complete atmospheric erosion within the ∼8 Gyr lifetime of the planet. Similarly, initial CO2 inventories (right) must have been less than ∼1021.7 kg to permit complete atmospheric erosion. The black dotted (<1 bar) distributions are resampled as the assumed initial volatile inventories for Trappist-1e and f above to represent an endmember case whereby initial volatile endowments within the planetary system are highly correlated.
Paper: Implications of Atmospheric Nondetections for Trappist-1 Inner Planets on Atmospheric Retention Prospects for Outer Planets
Authors: Joshua Krissansen-Totton
Figure caption: All Trappist-1e model outputs consistent with an airless Trappist-1b and c, and with initial volatile endowments constrained by the airlessness of the inner planets. Since Trappist-1e orbits beyond the runaway greenhouse limit during the main-sequence evolution of Trappist-1, the potential for substantial atmospheric erosion is limited, as most model runs in Monte Carlo simulations retain substantial surface volatile inventories.
Paper: Implications of Atmospheric Nondetections for Trappist-1 Inner Planets on Atmospheric Retention Prospects for Outer Planets
Authors: Joshua Krissansen-Totton
Figure caption: Trappist-1e and f initial volatile inventories are unconstrained by an airless 1b and c, but would be tightly constrained if e or f were found to be devoid of surface volatiles. Comparison of initial volatile inventories for Trappist-1e (left) and f (right) assumed Monte Carlo range (“Prior”), implied by an airless Trappist-1b and c (“Posterior”), as well as the distributions required to produce an airless e and f. Top panels denote initial water inventories, whereas bottom panels denote initial CO2 inventories.
Paper: The NANOGrav 15 yr Data Set: Bayesian Limits on Gravitational Waves from Individual Supermassive Black Hole Binaries
Authors: Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, Paul T. Baker, Bence Bécsy, Laura Blecha, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, Robin Case, J. Andrew Casey-Clyde, Maria Charisi, Shami Chatterjee, Tyler Cohen, James M. Cordes, Neil J. Cornish, Fronefield Crawford, H. Thankful Cromartie, Kathryn Crowter, Megan E. DeCesar, Paul B. Demorest, Matthew C. Digman, Timothy Dolch, Brendan Drachler, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Nate Garver-Daniels, Peter A. Gentile, Joseph Glaser, Deborah C. Good, Kayhan Gültekin, Jeffrey S. Hazboun, Sophie Hourihane, Ross J. Jennings, Aaron D. Johnson, Megan L. Jones, Andrew R. Kaiser, David L. Kaplan, Luke Zoltan Kelley, Matthew Kerr, Joey S. Key, Nima Laal, Michael T. Lam, William G. Lamb, T. Joseph W. Lazio, Natalia Lewandowska, Tingting Liu, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Chung-Pei Ma, Dustin R. Madison, Alexander McEwen, James W. McKee, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Patrick M. Meyers, Chiara M. F. Mingarelli, Andrea Mitridate, Cherry Ng, David J. Nice, Stella Koch Ocker, Ken D. Olum, Timothy T. Pennucci, Benetge B. P. Perera, Polina Petrov, Nihan S. Pol, Henri A. Radovan, Scott M. Ransom, Paul S. Ray, Joseph D. Romano, Shashwat C. Sardesai, Ann Schmiedekamp, Carl Schmiedekamp, Kai Schmitz, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Magdalena S. Siwek, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Abhimanyu Susobhanan, Joseph K. Swiggum, Jacob Taylor, Stephen R. Taylor, Jacob E. Turner, Caner Unal, Michele Vallisneri, Rutger van Haasteren, Sarah J. Vigeland, Haley M. Wahl, Caitlin A. Witt, Olivia Young
Figure caption: Savage-Dickey Bayes factors for the CW+CURN model vs. the CURN model as a function of frequency (black). Also shown are Bayes factors when excluding PSR J1713+0747 (red); when advanced noise models are used for PSR J1713+0747 (blue); for PSRs J1713+0747, B1937+21, J1909−3744, and J1012+5307 (aqua); and for PSRs J1713+0747, B1937+21, J1909−3744, J1012+5307, J2317+1439, J1640+2224, J1741+1351, and J0613−0200 (purple). Shaded regions show the 1σ uncertainties.
Paper: The NANOGrav 15 yr Data Set: Bayesian Limits on Gravitational Waves from Individual Supermassive Black Hole Binaries
Authors: Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, Paul T. Baker, Bence Bécsy, Laura Blecha, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, Robin Case, J. Andrew Casey-Clyde, Maria Charisi, Shami Chatterjee, Tyler Cohen, James M. Cordes, Neil J. Cornish, Fronefield Crawford, H. Thankful Cromartie, Kathryn Crowter, Megan E. DeCesar, Paul B. Demorest, Matthew C. Digman, Timothy Dolch, Brendan Drachler, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Nate Garver-Daniels, Peter A. Gentile, Joseph Glaser, Deborah C. Good, Kayhan Gültekin, Jeffrey S. Hazboun, Sophie Hourihane, Ross J. Jennings, Aaron D. Johnson, Megan L. Jones, Andrew R. Kaiser, David L. Kaplan, Luke Zoltan Kelley, Matthew Kerr, Joey S. Key, Nima Laal, Michael T. Lam, William G. Lamb, T. Joseph W. Lazio, Natalia Lewandowska, Tingting Liu, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Chung-Pei Ma, Dustin R. Madison, Alexander McEwen, James W. McKee, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Patrick M. Meyers, Chiara M. F. Mingarelli, Andrea Mitridate, Cherry Ng, David J. Nice, Stella Koch Ocker, Ken D. Olum, Timothy T. Pennucci, Benetge B. P. Perera, Polina Petrov, Nihan S. Pol, Henri A. Radovan, Scott M. Ransom, Paul S. Ray, Joseph D. Romano, Shashwat C. Sardesai, Ann Schmiedekamp, Carl Schmiedekamp, Kai Schmitz, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Magdalena S. Siwek, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Abhimanyu Susobhanan, Joseph K. Swiggum, Jacob Taylor, Stephen R. Taylor, Jacob E. Turner, Caner Unal, Michele Vallisneri, Rutger van Haasteren, Sarah J. Vigeland, Haley M. Wahl, Caitlin A. Witt, Olivia Young
Figure caption: All-sky CW strain 95% upper limits from the NANOGrav 12.5 yr data set with QuickCW (purple). We also show the official 12.5 yr upper limits (blue), which, despite the different methodology, are consistent with the QuickCW results. Also shown for comparison is the 15 yr upper limit curve (red). We also analyzed the 12.5 yr slice of the 15 yr data set (brown), which gives results similar to the 12.5 yr data set at low and high frequencies, but follows the 15 yr results more closely at moderate frequencies.
Paper: The NANOGrav 15 yr Data Set: Bayesian Limits on Gravitational Waves from Individual Supermassive Black Hole Binaries
Authors: Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, Paul T. Baker, Bence Bécsy, Laura Blecha, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, Robin Case, J. Andrew Casey-Clyde, Maria Charisi, Shami Chatterjee, Tyler Cohen, James M. Cordes, Neil J. Cornish, Fronefield Crawford, H. Thankful Cromartie, Kathryn Crowter, Megan E. DeCesar, Paul B. Demorest, Matthew C. Digman, Timothy Dolch, Brendan Drachler, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Nate Garver-Daniels, Peter A. Gentile, Joseph Glaser, Deborah C. Good, Kayhan Gültekin, Jeffrey S. Hazboun, Sophie Hourihane, Ross J. Jennings, Aaron D. Johnson, Megan L. Jones, Andrew R. Kaiser, David L. Kaplan, Luke Zoltan Kelley, Matthew Kerr, Joey S. Key, Nima Laal, Michael T. Lam, William G. Lamb, T. Joseph W. Lazio, Natalia Lewandowska, Tingting Liu, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Chung-Pei Ma, Dustin R. Madison, Alexander McEwen, James W. McKee, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Patrick M. Meyers, Chiara M. F. Mingarelli, Andrea Mitridate, Cherry Ng, David J. Nice, Stella Koch Ocker, Ken D. Olum, Timothy T. Pennucci, Benetge B. P. Perera, Polina Petrov, Nihan S. Pol, Henri A. Radovan, Scott M. Ransom, Paul S. Ray, Joseph D. Romano, Shashwat C. Sardesai, Ann Schmiedekamp, Carl Schmiedekamp, Kai Schmitz, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Magdalena S. Siwek, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Abhimanyu Susobhanan, Joseph K. Swiggum, Jacob Taylor, Stephen R. Taylor, Jacob E. Turner, Caner Unal, Michele Vallisneri, Rutger van Haasteren, Sarah J. Vigeland, Haley M. Wahl, Caitlin A. Witt, Olivia Young
Figure caption: All-sky CW strain 95% upper limits using a uniform (red) and log-uniform (orange) prior on the amplitude. Dashed lines show the upper limits we get if we take HD correlations into account with re-weighing. These are only calculated over the range of frequencies where we had enough samples for the re-weighing. The blue marker indicates the frequency and the amplitude of the low-frequency candidate discussed in Section 3.1 with 68% credible intervals.
Paper: The NANOGrav 15 yr Data Set: Bayesian Limits on Gravitational Waves from Individual Supermassive Black Hole Binaries
Authors: Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, Paul T. Baker, Bence Bécsy, Laura Blecha, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, Robin Case, J. Andrew Casey-Clyde, Maria Charisi, Shami Chatterjee, Tyler Cohen, James M. Cordes, Neil J. Cornish, Fronefield Crawford, H. Thankful Cromartie, Kathryn Crowter, Megan E. DeCesar, Paul B. Demorest, Matthew C. Digman, Timothy Dolch, Brendan Drachler, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Nate Garver-Daniels, Peter A. Gentile, Joseph Glaser, Deborah C. Good, Kayhan Gültekin, Jeffrey S. Hazboun, Sophie Hourihane, Ross J. Jennings, Aaron D. Johnson, Megan L. Jones, Andrew R. Kaiser, David L. Kaplan, Luke Zoltan Kelley, Matthew Kerr, Joey S. Key, Nima Laal, Michael T. Lam, William G. Lamb, T. Joseph W. Lazio, Natalia Lewandowska, Tingting Liu, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Chung-Pei Ma, Dustin R. Madison, Alexander McEwen, James W. McKee, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Patrick M. Meyers, Chiara M. F. Mingarelli, Andrea Mitridate, Cherry Ng, David J. Nice, Stella Koch Ocker, Ken D. Olum, Timothy T. Pennucci, Benetge B. P. Perera, Polina Petrov, Nihan S. Pol, Henri A. Radovan, Scott M. Ransom, Paul S. Ray, Joseph D. Romano, Shashwat C. Sardesai, Ann Schmiedekamp, Carl Schmiedekamp, Kai Schmitz, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Magdalena S. Siwek, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Abhimanyu Susobhanan, Joseph K. Swiggum, Jacob Taylor, Stephen R. Taylor, Jacob E. Turner, Caner Unal, Michele Vallisneri, Rutger van Haasteren, Sarah J. Vigeland, Haley M. Wahl, Caitlin A. Witt, Olivia Young
Figure caption:  P–P plot showing unbiased recovery of binary parameters. Plotted for eight binary parameters is the cumulative fraction of realizations where the true value of the parameter was at a given percentile of the recovered posterior. The dashed diagonal line indicates perfect recovery, while the three shaded regions show 68.3%/95.5%/99.7% confidence intervals based on the number of realizations. All curves stay within these bands, demonstrating unbiased parameter recovery.