adsabs/AstroCLIMB huggingface dataset:
Paper: The Comprehensive Archive of Substellar and Planetary Accretion Rates
Authors: S. K. Betti, K. B. Follette, K. Ward-Duong, A. E. Peck, Y. Aoyama, J. Bary, B. Dacus, S. Edwards, G.-D. Marleau, K. Mohamed, J. Palmo, C. Plunkett, C. Robinson, H. Wang
Figure caption: CASPAR ﹩\dot{M}\mbox{--}M﹩ best-fit relations for stars (black circles), BDs (cyan diamonds), and PMCs (magenta squares). The solid lines and bands show the best linear fit and 1σ  standard deviation of the fit for each mass population, while the dashed lines show extrapolations beyond the bounds of the fit regions. The bottom panel shows the residuals for each best fit. Downward arrows indicate accretion-rate upper limits.
Paper: The Comprehensive Archive of Substellar and Planetary Accretion Rates
Authors: S. K. Betti, K. B. Follette, K. Ward-Duong, A. E. Peck, Y. Aoyama, J. Bary, B. Dacus, S. Edwards, G.-D. Marleau, K. Mohamed, J. Palmo, C. Plunkett, C. Robinson, H. Wang
Figure caption: Best-fit ﹩\mathrm{log}\dot{M}﹩ as a function of age at the HBL (M = 0.075 M ⊙; solid line and filled markers) and at the DBL (M = 0.012 M ⊙; dashed line and open markers) for stars (black circles) and BDs (cyan diamonds) from Figure 16. We show the best exponential fits for each population and find that the BD accretion rates decrease at a faster rate compared to the stellar rates.
Paper: The Comprehensive Archive of Substellar and Planetary Accretion Rates
Authors: S. K. Betti, K. B. Follette, K. Ward-Duong, A. E. Peck, Y. Aoyama, J. Bary, B. Dacus, S. Edwards, G.-D. Marleau, K. Mohamed, J. Palmo, C. Plunkett, C. Robinson, H. Wang
Figure caption: Accretion rate vs. mass for ρ Ophiuchus (left), Taurus (center), and Upper Scorpius (right). Colors and markers are as in Figure 15. The best linear fits (solid lines) and 1σ  scatters (bands) are shown for the star (black) and BD (cyan) populations. The dashed lines show the extrapolation into the planetary regime.
Paper: The Comprehensive Archive of Substellar and Planetary Accretion Rates
Authors: S. K. Betti, K. B. Follette, K. Ward-Duong, A. E. Peck, Y. Aoyama, J. Bary, B. Dacus, S. Edwards, G.-D. Marleau, K. Mohamed, J. Palmo, C. Plunkett, C. Robinson, H. Wang
Figure caption: CASPAR accretion rate vs. mass with linear best fits from different linear regression algorithms. linmix takes into account all parameters, while the others take into account some parameters, as listed in Table 9.
Paper: The Eclipse-mapping Null Space: Comparing Theoretical Predictions with Observed Maps
Authors: Ryan C. Challener, Emily Rauscher
Figure caption: Design matrices for the eclipse observation of WASP-18b presented in Coulombe et al. (2023), shown out to sixth-degree harmonics, for a perfectly edge-on (top) and inclined (bottom) orbit. Each column shows the contribution from a given spherical harmonic mode at each time (or orbital phase) in the observation. Multiplying a row by harmonic weights  y , summing, and adding the uniform component gives the planetary light curve at that time (Equation (3)). The vertical black lines separate the harmonic degrees. Red and blue indicate positive and negative contributions to the light curve, respectively. The white regions show times where a harmonic contributes zero flux (i.e., that harmonic is unobservable at that time). The green inset zooms in on examples of the spherical harmonic signals generated in the eclipse ingress.
Paper: The Eclipse-mapping Null Space: Comparing Theoretical Predictions with Observed Maps
Authors: Ryan C. Challener, Emily Rauscher
Figure caption: Size of the null space vs. exposure time (top) and impact parameter (bottom). The sampling rates range from one to 64 exposures over the eclipse ingress. The 64-sample case roughly matches the observation in Coulombe et al. (2023). The impact parameters range from zero to 1. In general, as long as there are ≥16 exposures during eclipse ingress/egress (which will be standard for JWST), the sampling rate does not affect the size of the null space. Similarly, the size of the null space does not change with impact parameter as long as the impact parameter is nonzero and the orbit is nongrazing.
Paper: The Eclipse-mapping Null Space: Comparing Theoretical Predictions with Observed Maps
Authors: Ryan C. Challener, Emily Rauscher
Figure caption: Nullity (how much spatial information is unmappable) for a rotational vs. an eclipsing light curve. We assume that the inclined eclipsed object has an orbital inclination of 89° to break the degeneracies of the latitudinally symmetric spherical harmonic modes. The eclipse gives the observation access to significantly more brightness patterns on the planet than for a noneclipsing planet, particularly if the orbit is inclined. However, many patterns remain unobservable, especially at high spatial resolution (high spherical harmonic degree). In all cases, the planet-to-star radius ratio is 0.1, the mass ratio is 0.001, the orbital period is 1 day, and the full planet orbit is sampled 100,000 times such that the sampling rate does not impact the nullity at these spatial resolutions. See later sections for further discussion of the effects of orbital parameters and sampling rate. We make no assumption about the S/N of the observation, as it has no effect on the nullity.
Paper: The Eclipse-mapping Null Space: Comparing Theoretical Predictions with Observed Maps
Authors: Ryan C. Challener, Emily Rauscher
Figure caption: Spherical harmonic design matrix ﹩\pmb{\mathscr{A}}﹩ (top, same as the bottom panel of Figure 1) and eigencurve design matrix ﹩{\pmb{\mathscr{A}}}_{{\rm{E}}}﹩ (bottom) for a JWST eclipse observation of WASP-18b (Coulombe et al. 2023). The ﹩{\pmb{\mathscr{A}}}_{{\rm{E}}}﹩ is the result of orthogonalizing the light curves (columns) in ﹩\pmb{\mathscr{A}}﹩ and is the basis set of light-curve components used in eigenmapping fits. Both matrices have ranks of 43 (43 nondegenerate components), which is clear for ﹩{\pmb{\mathscr{A}}}_{{\rm{E}}}﹩, where the orthogonalization has separated the zero and nonzero components.
Paper: The Eclipse-mapping Null Space: Comparing Theoretical Predictions with Observed Maps
Authors: Ryan C. Challener, Emily Rauscher
Figure caption: Decomposition of a GCM flux map into the observable and null-space modes. The fourth column is a restriction of the full null space (third column) to only spherical harmonics of degree 5 or less, which shows the data-limited null space. Note that the light curves for the truth and observable components are identical, and the light curves from the null-space maps are flat, showing that they are not observable. The GCM is the 0 G (no magnetic field) RM-GCM WASP-18b model from Coulombe et al. (2023).
Paper: The Eclipse-mapping Null Space: Comparing Theoretical Predictions with Observed Maps
Authors: Ryan C. Challener, Emily Rauscher
Figure caption: Flux (units arbitrary) eigenmaps corresponding to the eigencurves in a design matrix ﹩{\pmb{\mathscr{A}}}_{{\rm{E}}}﹩ for 0 < l < 6 for the eclipse observation of WASP-18b in Coulombe et al. (2023). These eigenmaps are ranked, from top left to bottom right, by the variance in their light curves. The final five maps generate light curves that are zero at all times during the observation and thus are in the null space.
Paper: The Eclipse-mapping Null Space: Comparing Theoretical Predictions with Observed Maps
Authors: Ryan C. Challener, Emily Rauscher
Figure caption: Observable (left) and null (right) modes for an eclipse of a land map of Earth (top) with a range of impact parameters. As expected, the edge-on (b = 0) and grazing (b = 1) have significant unobservable structures, and fine structures outside approximately −90° and 90° longitude are washed out. However, varying b between these edge cases also changes the shape of the null space.
Paper: The Impact of the Free-floating Planet Mass Function on the Event Rate for Accurate Microlensing Parallax Determination: Application to Euclid and Roman Parallax Observation
Authors: M. Ban
Figure caption: Map of the ratio of the chi-square values for the different effective temperatures of a source and an impact parameter (see Equation (10)). The limb-darkening coefficients are referred to by Claret et al. (2012) and Claret (2017). The finite-source effects are simulated with the mean angular radii of the source derived from the Besançon Galactic model catalogs assuming FFP lenses. The cross marker represents the weighted mean and 1σ distribution of T eff and u 0 of our sample events. Note that uniform brightness was assumed for the sample drawing, and these sample events survived our detectability criteria (see Section 2.3).
Paper: The Impact of the Free-floating Planet Mass Function on the Event Rate for Accurate Microlensing Parallax Determination: Application to Euclid and Roman Parallax Observation
Authors: M. Ban
Figure caption: Event rate [event/year/deg2] for accurately measured microlensing parallax for different FFP mass functions. The FFP mass on the x-axis is binned by ﹩d{\mathrm{log}}_{10}{M}_{\mathrm{FFP}}\sim 0.1﹩. The least acceptable discrepancy is assumed as <100%, which corresponds to a factor of 2 uncertainty. The limitations of the finite-source effect are ρ/u 0 < 0.5 in solid and <1.0 in dashed curves. Two solutions of the microlensing parallax are not considered in this plot and the δ u 0 is taken from a typical subtraction formula
Paper: The Impact of the Free-floating Planet Mass Function on the Event Rate for Accurate Microlensing Parallax Determination: Application to Euclid and Roman Parallax Observation
Authors: M. Ban
Figure caption: Three different FFP mass functions in the solid curves and the slope of the population factor as a power law (β) in Equation (18) in the dashed curves. The left y-axis corresponds to the mass function values, and the right y-axis corresponds to the β value.
Paper: The Impact of the Free-floating Planet Mass Function on the Event Rate for Accurate Microlensing Parallax Determination: Application to Euclid and Roman Parallax Observation
Authors: M. Ban
Figure caption: Example of the photometric data observed by Euclid and Roman in simultaneous parallax generated by our microlensing simulator.
Paper: The Comprehensive Archive of Substellar and Planetary Accretion Rates
Authors: S. K. Betti, K. B. Follette, K. Ward-Duong, A. E. Peck, Y. Aoyama, J. Bary, B. Dacus, S. Edwards, G.-D. Marleau, K. Mohamed, J. Palmo, C. Plunkett, C. Robinson, H. Wang
Figure caption: Accretion rate vs. mass for a range of accretion-tracing lines, namely: (a) optical Hydrogen Balmer series lines; (b) NIR Hydrogen Paschen, Brackett, and Pfund series lines; (c) Helium I emission lines; and (d) Calcium II emission lines. The gray line shows the best linear ﹩\dot{M}\mbox{--}M﹩ fit to the overall CASPAR database, while the colored lines show the best linear fit for each emission line. The histograms show the posterior distributions for the masses (top), accretion rates (top right), and accretion-rate residuals (bottom right) for each panel. We find that the NIR line flux fit shows the most deviation in best fit; it is offset by 0.9 dex compared to the best linear fit at the DBL (compared to <0.4 in the other lines).
Paper: The Comprehensive Archive of Substellar and Planetary Accretion Rates
Authors: S. K. Betti, K. B. Follette, K. Ward-Duong, A. E. Peck, Y. Aoyama, J. Bary, B. Dacus, S. Edwards, G.-D. Marleau, K. Mohamed, J. Palmo, C. Plunkett, C. Robinson, H. Wang
Figure caption: (a) Accretion rate vs. mass for individual accretion diagnostics, colored as in Figure 4. The large markers indicate the binned accretion rates by mass. (b) Residuals between binned accretion rates and CASPAR continuum excess fit. The line luminosities (including Hα photometric) show (significant) deviation from the continuum excess with decreasing mass. The Hα photometric luminosities appear significantly offset from the CASPAR continuum excess best fit; however, the majority of the stellar accretion rates are from objects with ages <1 Myr, which biases the high-mass results (see Section 6.1).
Paper: The Comprehensive Archive of Substellar and Planetary Accretion Rates
Authors: S. K. Betti, K. B. Follette, K. Ward-Duong, A. E. Peck, Y. Aoyama, J. Bary, B. Dacus, S. Edwards, G.-D. Marleau, K. Mohamed, J. Palmo, C. Plunkett, C. Robinson, H. Wang
Figure caption: Range of measured accretion rates for objects in CASPAR with (a) multiepoch/multiaccretion tracer measurements, (b) all accretion rates measured for all emission lines in one epoch, and (c) all accretion rates in all epochs for individual emission lines. In panels (a) and (b), the ranges are colored by stellar/substellar populations. In panel (c), the ranges are colored by the individual line tracers. The right panels shows the PDFs for each population. Overall, we find increased variability in the substellar regime (1.33 dex), but consistent 0.8 dex variability with population for emission lines and epochs.
Paper: The Comprehensive Archive of Substellar and Planetary Accretion Rates
Authors: S. K. Betti, K. B. Follette, K. Ward-Duong, A. E. Peck, Y. Aoyama, J. Bary, B. Dacus, S. Edwards, G.-D. Marleau, K. Mohamed, J. Palmo, C. Plunkett, C. Robinson, H. Wang
Figure caption: Top: CASPAR accretion rate vs. mass, colored by age: ≤1 Myr (gold circles), (1–3] Myr (orange stars), (3–8] Myr (magenta squares), and >8 Myr (purple triangles). The solid lines are the best linear fits to each age population with a fixed constant slope of 2.02. We find a 1 dex decrease in the best-fit intercept with increasing age. Bottom: residuals for the best linear fit for each age population.
Paper: The Comprehensive Archive of Substellar and Planetary Accretion Rates
Authors: S. K. Betti, K. B. Follette, K. Ward-Duong, A. E. Peck, Y. Aoyama, J. Bary, B. Dacus, S. Edwards, G.-D. Marleau, K. Mohamed, J. Palmo, C. Plunkett, C. Robinson, H. Wang
Figure caption: Left: the CASPAR ﹩\dot{M}\mbox{--}M﹩ best-fit relation for overall CASPAR (black solid line), CASPAR stars only (black dashed dot line), Zhou et al. (2014; gray dotted line), and Hartmann et al. (2016; brown solid line). The 1σ scatter is shown by the shaded regions for each fit. The residuals between each linear fit and CASPAR are shown below. Right: histogram of residuals for each population. The thin gray lines show the mean of each distribution. Markers and colors are as in Figure 7.