adsabs/AstroCLIMB huggingface dataset:
Paper: Refractory and Volatile Species in the UV-to-IR Transmission Spectrum of Ultra-hot Jupiter WASP-178b with HST and JWST
Authors: Joshua D. Lothringer, Katherine A. Bennett, David K. Sing, Brian Kehoe-Seamons, Zafar Rustamkulov, Henrique Reggiani, Kevin C. Schlaufman, Patrick McCreery, Seti Norris, Peter Hauschildt, Ceiligh Cacho-Negrete, Amélie Gressier, Néstor Espinoza, Cyril Gapp, Thomas M. Evans-Soma, Kevin B. Stevenson, Hannah Wakeford, Neale Gibson, Jamie Wilson, Nikolay Nikolov
Figure caption: Two-dimensional spectroscopic light curves from JWST/NIRSpec G395H/NRS2.
Paper: Refractory and Volatile Species in the UV-to-IR Transmission Spectrum of Ultra-hot Jupiter WASP-178b with HST and JWST
Authors: Joshua D. Lothringer, Katherine A. Bennett, David K. Sing, Brian Kehoe-Seamons, Zafar Rustamkulov, Henrique Reggiani, Kevin C. Schlaufman, Patrick McCreery, Seti Norris, Peter Hauschildt, Ceiligh Cacho-Negrete, Amélie Gressier, Néstor Espinoza, Cyril Gapp, Thomas M. Evans-Soma, Kevin B. Stevenson, Hannah Wakeford, Neale Gibson, Jamie Wilson, Nikolay Nikolov
Figure caption: Retrieved posteriors for the full-spectrum HST+JWST isothermal chemical equilibrium retrieval using both the FIREFLy (blue, top titles) and transitspectroscopy (red, bottom titles) reductions.
Paper: Refractory and Volatile Species in the UV-to-IR Transmission Spectrum of Ultra-hot Jupiter WASP-178b with HST and JWST
Authors: Joshua D. Lothringer, Katherine A. Bennett, David K. Sing, Brian Kehoe-Seamons, Zafar Rustamkulov, Henrique Reggiani, Kevin C. Schlaufman, Patrick McCreery, Seti Norris, Peter Hauschildt, Ceiligh Cacho-Negrete, Amélie Gressier, Néstor Espinoza, Cyril Gapp, Thomas M. Evans-Soma, Kevin B. Stevenson, Hannah Wakeford, Neale Gibson, Jamie Wilson, Nikolay Nikolov
Figure caption: Posterior distribution for the petitRADTRANS retrieval on the full 0.2–5.1 μm spectrum, using free chemistry and the three-parameter TP parameterization from T. Guillot (2010).
Paper: Refractory and Volatile Species in the UV-to-IR Transmission Spectrum of Ultra-hot Jupiter WASP-178b with HST and JWST
Authors: Joshua D. Lothringer, Katherine A. Bennett, David K. Sing, Brian Kehoe-Seamons, Zafar Rustamkulov, Henrique Reggiani, Kevin C. Schlaufman, Patrick McCreery, Seti Norris, Peter Hauschildt, Ceiligh Cacho-Negrete, Amélie Gressier, Néstor Espinoza, Cyril Gapp, Thomas M. Evans-Soma, Kevin B. Stevenson, Hannah Wakeford, Neale Gibson, Jamie Wilson, Nikolay Nikolov
Figure caption: Posterior distribution for the petitRADTRANS retrieval on the full 0.2–5.1 μm spectrum, using free chemistry and an isothermal atmosphere.
Paper: A Moderate Albedo from Reflecting Aerosols on the Dayside of WASP-80 b Revealed by JWST/NIRISS Eclipse Spectroscopy
Authors: Kim Morel, Louis-Philippe Coulombe, Jason F. Rowe, David Lafrenière, Loïc Albert, Étienne Artigau, Nicolas B. Cowan, Lisa Dang, Michael Radica, Jake Taylor, Caroline Piaulet-Ghorayeb, Pierre-Alexis Roy, Björn Benneke, Antoine Darveau-Bernier, Stefan Pelletier, René Doyon, Doug Johnstone, Adam B. Langeveld, Romain Allart, Laura Flagg, Jake D. Turner
Figure caption: Left: order 2 white-light-curve fit (0.674–0.850 μm). Right: light-curve fit for a large bin of the order 1 trace spanning 0.850–1.500 μm. Both light curves show similar systematics, supporting the need to model the order 2 light curves like the order 1 light curves. Top: raw NIRISS/SOSS light curves (gray) and their temporally binned points with 1σ error bars (black). The best-fit models, including the eclipse and the systematics, are overlapped in red. The retrieved eclipse depth for the order 2 white-light curve (left) is ﹩2{6}_{-37}^{+27}﹩ ppm, and the one for the short-wavelength order 1 bin (right) is ﹩3{4}_{-28}^{+25}﹩ ppm. The latter measurement corresponds to a tentative detection of reflected light at short wavelengths. Middle: detrended light curves (gray, binned points in black) once systematics are removed, along with the eclipse models (red). In each case, the error bars on the binned points are computed from the best-fit scatter parameter on the unbinned points (left: σ = 194.9 ppm, right: σ = 110.0 ppm). Bottom: residuals to the best-fit models and their rms values (based on the gray unbinned points).
Paper: A Moderate Albedo from Reflecting Aerosols on the Dayside of WASP-80 b Revealed by JWST/NIRISS Eclipse Spectroscopy
Authors: Kim Morel, Louis-Philippe Coulombe, Jason F. Rowe, David Lafrenière, Loïc Albert, Étienne Artigau, Nicolas B. Cowan, Lisa Dang, Michael Radica, Jake Taylor, Caroline Piaulet-Ghorayeb, Pierre-Alexis Roy, Björn Benneke, Antoine Darveau-Bernier, Stefan Pelletier, René Doyon, Doug Johnstone, Adam B. Langeveld, Romain Allart, Laura Flagg, Jake D. Turner
Figure caption: Results from the principal component analysis of the calibrated data products (without considering the integrations before the tilt event). (a) Eigenvalue of the first principal component, which clearly contains the eclipse. (b) First principal component, i.e., the one with the highest variance in the time series. (c) Eigenvalue of the second principal component. (d) Second principal component. This component represents changes in the spatial direction of the traces, resulting in the trade of flux between the upper and lower parts of the traces. (e) Eigenvalue of the third principal component. This beating pattern is caused by temperature variations in the instrument electronics compartment. We use this component to detrend our light curves. (f) Third principal component. This component results in changes in the FWHM of the traces, as shown by the trade of flux between the wings and center of the traces.
Paper: A Moderate Albedo from Reflecting Aerosols on the Dayside of WASP-80 b Revealed by JWST/NIRISS Eclipse Spectroscopy
Authors: Kim Morel, Louis-Philippe Coulombe, Jason F. Rowe, David Lafrenière, Loïc Albert, Étienne Artigau, Nicolas B. Cowan, Lisa Dang, Michael Radica, Jake Taylor, Caroline Piaulet-Ghorayeb, Pierre-Alexis Roy, Björn Benneke, Antoine Darveau-Bernier, Stefan Pelletier, René Doyon, Doug Johnstone, Adam B. Langeveld, Romain Allart, Laura Flagg, Jake D. Turner
Figure caption: Top: cross section (column 1300) of the SOSS 2D image of the WASP-80 field. The photometric aperture used to extract the spectrum in the additional reduction of the first and second-order traces are highlighted by the light-red and orange boxes. The imaged field star is highlighted by the light-blue box. The red, orange, and blue lines show the PSF model used to model the distribution of starlight across the field. The PSF model was used to estimate photometric contamination inside the aperture of each trace and repeated for each column to construct a decontamination model to accurately measure eclipse depths in the additional reduction. Bottom: same as top panel, but for column 1575, which is the last column used in the extraction of order 2. The contamination from the imaged field star on the order 2 extracted flux is <1% at this column.
Paper: A Moderate Albedo from Reflecting Aerosols on the Dayside of WASP-80 b Revealed by JWST/NIRISS Eclipse Spectroscopy
Authors: Kim Morel, Louis-Philippe Coulombe, Jason F. Rowe, David Lafrenière, Loïc Albert, Étienne Artigau, Nicolas B. Cowan, Lisa Dang, Michael Radica, Jake Taylor, Caroline Piaulet-Ghorayeb, Pierre-Alexis Roy, Björn Benneke, Antoine Darveau-Bernier, Stefan Pelletier, René Doyon, Doug Johnstone, Adam B. Langeveld, Romain Allart, Laura Flagg, Jake D. Turner
Figure caption: Top: raw NIRISS/SOSS order 1 (0.85–2.83 μm) white-light curves with 1σ error bars for the supreme-SPOON reduction (red) and the additional one (blue) with their temporally binned points. Bottom: difference between the white-light curve from the additional reduction and the one from supreme-SPOON. The error bars on the residuals represent the maximum ones between the two reductions. In general, both white-light curves follow the same trends.
Paper: A Moderate Albedo from Reflecting Aerosols on the Dayside of WASP-80 b Revealed by JWST/NIRISS Eclipse Spectroscopy
Authors: Kim Morel, Louis-Philippe Coulombe, Jason F. Rowe, David Lafrenière, Loïc Albert, Étienne Artigau, Nicolas B. Cowan, Lisa Dang, Michael Radica, Jake Taylor, Caroline Piaulet-Ghorayeb, Pierre-Alexis Roy, Björn Benneke, Antoine Darveau-Bernier, Stefan Pelletier, René Doyon, Doug Johnstone, Adam B. Langeveld, Romain Allart, Laura Flagg, Jake D. Turner
Figure caption: rms of the residuals from the order 1 white-light-curve fit (black line) as a function of the bin size. The blue line shows the decrease in the rms for Poisson noise. Our residuals fall below this line, but they follow the Poisson law for bin sizes larger than ∼300 s, as shown by the red line. This can be explained by the presence of remaining correlated noise at bin sizes smaller than the frequencies that the GP removes. Pure photon noise is represented by the gray dashed line. Our noise level is ∼1.5× the photon noise.
Paper: A Moderate Albedo from Reflecting Aerosols on the Dayside of WASP-80 b Revealed by JWST/NIRISS Eclipse Spectroscopy
Authors: Kim Morel, Louis-Philippe Coulombe, Jason F. Rowe, David Lafrenière, Loïc Albert, Étienne Artigau, Nicolas B. Cowan, Lisa Dang, Michael Radica, Jake Taylor, Caroline Piaulet-Ghorayeb, Pierre-Alexis Roy, Björn Benneke, Antoine Darveau-Bernier, Stefan Pelletier, René Doyon, Doug Johnstone, Adam B. Langeveld, Romain Allart, Laura Flagg, Jake D. Turner
Figure caption: NIRISS/SOSS eclipse spectrum of WASP-80 b according to different modeling approaches. Each eclipse depth is shown with its 1σ error bars. The black points represent the reference spectrum used for the analysis. The purple points, shifted by -0.01 μm for clarity, show the spectrum obtained without using a GP model in the light-curve fitting. The inclusion of a GP in the light-curve fit produces more realistic error bars on the spectrum. The green spectrum, shifted by +0.01 μm, follows the same modeling approach as the reference spectrum, but the time of mid-eclipse was fixed to the best-fit value from the white-light-curve fit in which it was allowed to vary. This time is delayed by 12.8 minutes compared to the expected value.
Paper: A Moderate Albedo from Reflecting Aerosols on the Dayside of WASP-80 b Revealed by JWST/NIRISS Eclipse Spectroscopy
Authors: Kim Morel, Louis-Philippe Coulombe, Jason F. Rowe, David Lafrenière, Loïc Albert, Étienne Artigau, Nicolas B. Cowan, Lisa Dang, Michael Radica, Jake Taylor, Caroline Piaulet-Ghorayeb, Pierre-Alexis Roy, Björn Benneke, Antoine Darveau-Bernier, Stefan Pelletier, René Doyon, Doug Johnstone, Adam B. Langeveld, Romain Allart, Laura Flagg, Jake D. Turner
Figure caption: Corner plot of the parameters included in the chemical equilibrium retrieval, except for the 10 temperature–pressure profile parameters.
Paper: A Moderate Albedo from Reflecting Aerosols on the Dayside of WASP-80 b Revealed by JWST/NIRISS Eclipse Spectroscopy
Authors: Kim Morel, Louis-Philippe Coulombe, Jason F. Rowe, David Lafrenière, Loïc Albert, Étienne Artigau, Nicolas B. Cowan, Lisa Dang, Michael Radica, Jake Taylor, Caroline Piaulet-Ghorayeb, Pierre-Alexis Roy, Björn Benneke, Antoine Darveau-Bernier, Stefan Pelletier, René Doyon, Doug Johnstone, Adam B. Langeveld, Romain Allart, Laura Flagg, Jake D. Turner
Figure caption: Corner plot of the parameters included in the free chemistry retrieval, except for the 10 temperature–pressure profile parameters.
Paper: Water in Protoplanetary Disks with JWST-MIRI: Spectral Excitation Atlas and Radial Distribution from Temperature Diagnostic Diagrams and Doppler Mapping
Authors: Andrea Banzatti, Colette Salyk, Klaus M. Pontoppidan, John S. Carr, Ke Zhang, Nicole Arulanantham, Sebastiaan Krijt, Karin I. Öberg, L. Ilsedore Cleeves, Joan R. Najita, Ilaria Pascucci, Geoffrey A. Blake, Carlos E. Romero-Mirza, Edwin A. Bergin, Lucas A. Cieza, Paola Pinilla, Feng Long, Patrick Mallaney, Chengyan Xie, Abygail R. Waggoner, Till Kaeufer
Figure caption: Atlas of water emission in MIRI-MRS spectra (see Section 3), using CI Tau as an example (shown in black). Vertical lines mark transition wavelengths, color coded according to the upper-level energy Eu as shown in the color bar. Lines marked with a star (color coded in the same way) are from the list of single (unblended) transitions used in this work (Appendix C). Slab models (top-right inset; Appendix D) are added with dashed lines on top of the data. Their sum is shown as a gray shaded region. The rovibrational band at 5–8 μm is dominated by v = 1–0 lines (all lines unless labeled), but there are some prominent v = 2–1 lines that are detected (see Section 3).
Paper: Water in Protoplanetary Disks with JWST-MIRI: Spectral Excitation Atlas and Radial Distribution from Temperature Diagnostic Diagrams and Doppler Mapping
Authors: Andrea Banzatti, Colette Salyk, Klaus M. Pontoppidan, John S. Carr, Ke Zhang, Nicole Arulanantham, Sebastiaan Krijt, Karin I. Öberg, L. Ilsedore Cleeves, Joan R. Najita, Ilaria Pascucci, Geoffrey A. Blake, Carlos E. Romero-Mirza, Edwin A. Bergin, Lucas A. Cieza, Paola Pinilla, Feng Long, Patrick Mallaney, Chengyan Xie, Abygail R. Waggoner, Till Kaeufer
Figure caption: Atlas of water emission in MIRI-MRS spectra (continued from Figure 2): the rotational spectrum at intermediate wavelengths. The emission is dominated by v = 0–0 lines (unlabeled), but there are several prominent v = 1–1 lines (Section 3.1.4). Ortho-para line pairs are labeled “O-P” (see Section 3.1.3).
Paper: Water in Protoplanetary Disks with JWST-MIRI: Spectral Excitation Atlas and Radial Distribution from Temperature Diagnostic Diagrams and Doppler Mapping
Authors: Andrea Banzatti, Colette Salyk, Klaus M. Pontoppidan, John S. Carr, Ke Zhang, Nicole Arulanantham, Sebastiaan Krijt, Karin I. Öberg, L. Ilsedore Cleeves, Joan R. Najita, Ilaria Pascucci, Geoffrey A. Blake, Carlos E. Romero-Mirza, Edwin A. Bergin, Lucas A. Cieza, Paola Pinilla, Feng Long, Patrick Mallaney, Chengyan Xie, Abygail R. Waggoner, Till Kaeufer
Figure caption: Atlas of water emission in MIRI-MRS spectra (continued from Figure 1): the rotational spectrum at intermediate wavelengths. The emission is dominated by v = 0–0 lines (all lines unless labeled), but there are lines from the first vibrational state including several prominent v = 1–1 lines (Section 3.1.4). Ortho-para line pairs are labeled “O-P” (see Section 3.1.3).
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: Evolution of loss values during the training process. Panel (a) illustrates the loss values for E1, panel (b) illustrates the loss values for E2, and panel (c) illustrates the loss values for the MoE. These panels demonstrate that both the individual expert neural networks and the integrated MoE system achieve convergence within a span of tens to hundreds of epochs.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: This figure presents images corresponding to three distinct observation modes. From left to right, the images represent observations made in sidereal mode, tracking mode, and intersection mode. All images are captured under optimal observation conditions, characterized by a sky background of 16.9. For enhanced clarity and ease of identification, the FMCOs are highlighted with red bounding boxes in each image.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: The structure of the gating network.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: mAP, Precision, and Recall for each model under different observation modes.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: The PR curves for each model under different observation modes.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: PR curve for different detection algorithms in Test A with IoU of 0.5.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: mAP, Precision, and Recall for each model for Test A.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: PR curve for different detection algorithms in the validation set with IoU of 0.5.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: The structure of the neural network used in E2.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: The green box is the FMCOs, and the detection results are represented by the red box. From left to right, top to bottom, this figure shows the ground-truth value and the detection results of CenterNet, YOLOX, and the method in this paper. As shown in this figure, the method proposed in this paper could effectively detect FMCOs.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: PR curve for different detection algorithms in the real data with IoU of 0.5.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: PR curve for different detection algorithms in Test B with IoU of 0.5.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: mAP, Precision, and Recall for each model for Test B.
Paper: Adaptive Detection of Fast-moving Celestial Objects Using a Mixture-of-experts and Physical-inspired Neural Network
Authors: Peng Jia, Ge Li, Bafeng Cheng, Yushan Li, Rongyu Sun
Figure caption: Panel (a) shows the real data under Tracking Mode, while panel (b) shows the real data under Sidereal Mode.
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Galactic Cartesian coordinates for candidate members of the 32 Ori association (top). Candidates that have measurements of radial velocities are plotted in diagrams of XYZ and UVW (middle and bottom). Six of the candidates are rejected via their velocities in the bottom diagrams and other data (crosses; see Section 4). Modestly discrepant measurements of UVW among the remaining candidates are labeled with the source names.
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Top: ﹩{M}_{{G}_{\mathrm{RP}}}﹩ vs. G BP − G RP and G − G RP for previously proposed members of 32 Ori and 118 Tau that have RUWE < 1.6 (Mamajek 2016; Bell et al. 2017). The boundaries used for selecting candidate members of Sco-Cen by Luhman (2022a) are marked (red lines). Bottom: new kinematic candidate members that have RUWE < 1.6 and σ  π  < 1 mas (Section 2.1). For reference, the spectral types that correspond to the colors of young stars are indicated (Luhman 2022a).
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Proper motion offsets vs. parallactic distance for previously proposed members of the 32 Ori and 118 Tau associations (Mamajek 2016; Bell et al. 2017).
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Maps of previously proposed members of the 32 Ori and 118 Tau associations (left; Mamajek 2016; Bell et al. 2017) and the candidate members compiled in this work (right; Section 2). Six of the latter candidates are rejected via UVW velocities and other data (crosses; Section 4).
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption:  G RP − J vs. J − H and J − H vs. H − K  s  for candidate members of the 32 Ori association from Table 4. The intrinsic colors of young stars from B0 to M9 are indicated (red lines; Luhman 2022a).
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Proper motion offsets vs. celestial coordinates (top) and parallactic distance (bottom) for candidate members of the 32 Ori association based on kinematics and CMDs (Section 2.2). Six of the candidates are rejected via UVW velocities and other data (crosses; see Section 4).
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Proper motion offsets vs. parallactic distance for candidate members of 32 Ori-Columba from Lee & Song (2019) that have RUWE < 1.6. Only the candidates at >90 pc are among the candidate members of 32 Ori selected in this work.
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Examples of spectra of candidate members of the 32 Ori association, which are displayed at a resolution of R = 150.(The data used to create this figure are available.)
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Histograms of offsets in ﹩{M}_{{G}_{\mathrm{RP}}}﹩ from the median CMD sequence for UCL/LCC for candidate members of 32 Ori, UCL/LCC, and β Pic that have G BP − G RP = 1.4–2.8 (∼0.2–1 M ⊙, K5–M4). Negative values correspond to brighter magnitudes and younger ages.
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: IR colors vs. spectral type for candidate members of the 32 Ori association from Table 4. For stars that lack spectroscopy, spectral types have been estimated from photometry (Figure 8). In each diagram, the tight sequence of blue colors corresponds to stellar photospheres. The thresholds used for identifying color excesses from disks are indicated (red solid lines; Luhman 2022b).
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: IR color excesses for candidate members of the 32 Ori association. The boundaries used for assigning disk classes are shown in the bottom diagram (red solid lines).
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption:                       ﹩{M}_{{G}_{\mathrm{RP}}}﹩ vs. G BP − G RP and G − G RP for candidate members of the 32 Ori association from Table 4. The two stars that appear below the sequence in the left CMD are the disk-bearing stars mentioned in Section 2.2.
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Standard deviations of X, Y, and Z among candidate members of 32 Ori over the past 40 Myr based on their current UVW velocities and an epicyclic approximation of Galactic orbital motion.
Paper: A Census of the 32 Ori Association with Gaia 
Authors: K. L. Luhman
Figure caption: Histogram of spectral types for candidate members of the 32 Ori association from Table 4. For stars that lack spectroscopy, spectral types have been estimated from photometry (Figure 8).