adsabs/AstroCLIMB huggingface dataset:
Paper: Determining Which Binary Component Hosts the TESS Transiting Planet
Authors: Kathryn V. Lester, Steve B. Howell, David R. Ciardi, Rachel A. Matson
Figure caption: Stellar density vs. effective temperature plots for TOI 601—1740. The dervied value for the primary component is shown as the blue circle, the secondary component is shown as the green diamond, and any tertiary components are shown as red triangles. The solid purple line shows the model density- T eff relation built from the single TOI’s (purple points). The host probabilities of each component are also listed.
Paper: Determining Which Binary Component Hosts the TESS Transiting Planet
Authors: Kathryn V. Lester, Steve B. Howell, David R. Ciardi, Rachel A. Matson
Figure caption: Example density histograms for TOI 172 from 10,000 iterations. The histograms for the primary and secondary component are shown in blue and green, respectively. The Gaussian fits, used to determine the 1σ uncertainties, are shown in solid black.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlations between the noncorrected J-band imaging light curve and different atmospheric parameters.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Left: evolution of the calculated FWHM for the H-band 2D spectra with time. Right: evolution of the centroids of the H-band 2D spectra with time.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlation between the H-band target’s corrected light curve and the corrected calibration stars’ light curves.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlation between the CH4–H2O target’s corrected light curve and the corrected calibration stars’ light curves.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlation between the CH4–H2O target’s noncorrected light curve and the noncorrected calibration stars’ light curves.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Noncorrected (left) and corrected (right) H-band light curves of all stars and the target (black line).
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlation between the H-band target’s noncorrected light curve and the noncorrected calibration stars’ light curves.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlation between the FWHM of the 2D H-band spectra and the corrected and noncorrected H-band light curve.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlation between the centroids of the 2D H-band spectra and the noncorrected H-band light curve.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlations between the corrected J-band imaging light curve and different atmospheric parameters.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlations between the noncorrected CH4–H2O light curve and different atmospheric parameters.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlations between the noncorrected H-band light curve and different atmospheric parameters.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlations between the corrected CH4–H2O light curve and different atmospheric parameters.
Paper: Top-of-the-atmosphere and Vertical Cloud Structure of a Fast-rotating Late T Dwarf
Authors: Elena Manjavacas, Theodora Karalidi, Xianyu Tan, Johanna M. Vos, Ben W. P. Lew, Beth A. Biller, Natalia Oliveros-Gómez
Figure caption: Correlations between the corrected H-band light curve and different atmospheric parameters.
Paper: Analytic Light Curve for Mutual Transits of Two Bodies Across a Limb-darkened Star
Authors: Tyler A. Gordon, Eric Agol
Figure caption: Decision tree when the planet and moon overlap each other (b  pm  < r  p  + r  m ). Blue cells represent a test on the state of the system, the outcomes of which determine the cases represented by white boxes. The letters in the white boxes refer to the configurations shown in Figure 1, and the arcs to integrate and their integration limits for each case are listed in Table 1. The boxes labeled “No Flux” indicate cases where the star is completely obscured by one or both of the transiting bodies. These outcomes are only possible when either r  p , r  m , or both are greater than 1, and thus would likely only occur for eclipsing binary or triple-star systems.
Paper: Analytic Light Curve for Mutual Transits of Two Bodies Across a Limb-darkened Star
Authors: Tyler A. Gordon, Eric Agol
Figure caption: Derivatives of the simulated transit in Figure 2 with respect to all model parameters. In order from left to right, top to bottom, the parameters are the semimajor axis, epoch, eccentricity, period, longitude of periastron, and inclination of the planet, the semimajor axis, epoch, eccentricity, period, longitude of the ascending node, longitude of periastron, and inclination for the moon, the moon mass as a fraction of the planetary mass, the planetary radius, the moon’s radius, and the two limb-darkening parameters. The units along the y-axes are in units of flux per the relevant unit for the parameter in question. For example, if the semimajor axis of the planet is in terms of stellar radii then the units for the upper-left plot are flux per unit stellar radius. The lines are color-coded as follows: parameters related to the planet are shown in red, those related to the moon are shown in blue, and the limb-darkening parameters for the star are shown in yellow.
Paper: Analytic Light Curve for Mutual Transits of Two Bodies Across a Limb-darkened Star
Authors: Tyler A. Gordon, Eric Agol
Figure caption: A simulated exoplanet/exomoon transit in which the exomoon and exoplanet fully overlap while transiting the star. The snapshots across the top of the plot show the configuration of the system at the points in time indicated along the x-axis of the light-curve plot. The blue dashed line shows the transit of the moon as it would appear if it were the only transiting body, and the red dashed line shows the same for the planet.
Paper: Analytic Light Curve for Mutual Transits of Two Bodies Across a Limb-darkened Star
Authors: Tyler A. Gordon, Eric Agol
Figure caption: Representative examples of the different possible configurations of the planet–moon transit for the case where the planet and moon overlap each other. The letters in the top right of each box refer to the outcomes of the decision tree in Figure 4.
Paper: Analytic Light Curve for Mutual Transits of Two Bodies Across a Limb-darkened Star
Authors: Tyler A. Gordon, Eric Agol
Figure caption: An exposure-time integrated light curve. The left panel shows the full light curve with the dashed line being the unintegrated curve. The red line is the integrated curve produced by the trapezoidal rule and the blue line is the integrated curve produced by Simpson’s rule. On the right we have zoomed in to the part of the transit where the moon crosses the limb of the planet. At this point the flux changes sharply, which produces errors in the time integration that accounts for the difference between the trapezoidal curve and the Simpson’s curve. Simpson’s method is a higher-order method and is more accurate, especially at these contact points.
Paper: Analytic Light Curve for Mutual Transits of Two Bodies Across a Limb-darkened Star
Authors: Tyler A. Gordon, Eric Agol
Figure caption: A sample configuration of the transiting exoplanet (red circle) and exomoon (blue circle). We use the input coordinates {b  p , bpm , θ}. Each of these coordinates are independent of the other two and together with the radii r  p  and r  m  they completely define the state of the system.
Paper: Analytic Light Curve for Mutual Transits of Two Bodies Across a Limb-darkened Star
Authors: Tyler A. Gordon, Eric Agol
Figure caption: Geometry of the overlap between the star and a transiting planet or moon showing the angles κ and κ* defined in Equations (64) and (65). Here the filled yellow circle represents the star and the smaller unfilled circle represents either the planet or the moon. In the text κ and κ* are subscripted with m or p for the moon and planet, respectively.
Paper: Analytic Light Curve for Mutual Transits of Two Bodies Across a Limb-darkened Star
Authors: Tyler A. Gordon, Eric Agol
Figure caption: Geometry of the planet–moon overlap showing the angles ﹩{\phi }_{p}^{\pm }﹩ and ﹩{\phi }_{m}^{\pm }﹩ from Equations (57) and (58). The dashed lines show the triangle formed by the sides b  p , b  m , and b  pm .
Paper: Simulating Spectral Kurtosis Mitigation against Realistic Radio Frequency Interference Signals
Authors: E. Smith, Ryan S. Lynch, D. J. Pisano
Figure caption: A glance at some statistical properties of a BPSK signal. (a) Comparing μ 2 and σ 2 in the channel center of the RFI with the TPR rate. (b) Power distributions in the central channel for a range of duty cycles. (c) Power distributions in the central channel for two different data rates. The 100 ksps signal is undersampled. (d) Comparing μ 2 and σ 2 in the central channel for three different data rates. The vertical dashed lines mark where μ 2 and σ 2 cross each other for each data rate.
Paper: Simulating Spectral Kurtosis Mitigation against Realistic Radio Frequency Interference Signals
Authors: E. Smith, Ryan S. Lynch, D. J. Pisano
Figure caption: Scatter plots of BPSK signals at various duty cycles comparing average power to ﹩\widehat{{SK}}\,﹩ value in the center channel. The data is split into two separate graphs for readability: 10%–50% duty cycle on the left, and 60%–100% on the right. Note how the data lies above 1 for duty cycles less than 50%, approaches ﹩\widehat{{SK}}\,﹩ values of 1 as the duty cycle approaches 50%, and goes below 1 for higher duty cycles. ﹩\widehat{{SK}}\,﹩ thresholds are outlined in red.
Paper: Simulating Spectral Kurtosis Mitigation against Realistic Radio Frequency Interference Signals
Authors: E. Smith, Ryan S. Lynch, D. J. Pisano
Figure caption: Scatter plots of BASK signals at various duty cycles comparing average power to ﹩\widehat{{SK}}\,﹩ value in the center channel. The data is split into two separate graphs for readability: 10%–50% duty cycle on the left, and 60%–100% on the right. For these signals, a 100% intrinsic duty cycle acts as a 50% effective duty cycle, and does not get flagged. ﹩\widehat{{SK}}\,﹩ thresholds are outlined in red.
Paper: White Dwarf Binaries across the H-R Diagram
Authors: Borja Anguiano, Steven R. Majewski, Keivan G. Stassun, Carles Badenes, Christine Mazzola Daher, Don Dixon, Carlos Allende Prieto, Donald P. Schneider, Adrian M. Price-Whelan, Rachael L. Beaton
Figure caption: Left panel: same as Figure 12, but now divided into regions corresponding to principal stellar evolutionary phases: 1—upper RGB; 2—RC; 3—lower RGB; 4—MS; 5—MS binary sequence; and 6—SSGs. Right panel: the CDFs of both the WD temperature (top panel) and overall metallicity (bottom panel) for stars lying in the different regions of the CMD. The upper RGB shows a larger number of hotter WDs, and the metallicity distribution for these systems is clearly skewed to lower metallicities with respect to those in the other regions of the CMD, while the MS group of binary candidates shows the largest number of metal-rich objects.
Paper: White Dwarf Binaries across the H-R Diagram
Authors: Borja Anguiano, Steven R. Majewski, Keivan G. Stassun, Carles Badenes, Christine Mazzola Daher, Don Dixon, Carlos Allende Prieto, Donald P. Schneider, Adrian M. Price-Whelan, Rachael L. Beaton
Figure caption: Left panel: the CMD distribution of WD binaries having reliable, full orbital fits to the APOGEE multi-epoch RVs, color-coded by the derived orbital period. We divide the sample of 252 such systems into secondary-star evolutionary stages as follows: 1—upper RGB; 2—RC; 3—lower RGB; 4—MS; 5 MS binary sequence; and 6—SSGs. Right panel: cumulative fraction of the orbital period in days for the different CMD groupings. The RC, the MS binary sequence, and the SSGs have clearly a different period distribution with respect to the other CMD groups. The RC systems show the smallest number of short-period binaries, while the MS binary sequence and the SSGs are greatly skewed to having the largest number of short-period binaries.
Paper: White Dwarf Binaries across the H-R Diagram
Authors: Borja Anguiano, Steven R. Majewski, Keivan G. Stassun, Carles Badenes, Christine Mazzola Daher, Don Dixon, Carlos Allende Prieto, Donald P. Schneider, Adrian M. Price-Whelan, Rachael L. Beaton
Figure caption: Exploring potential SSG systems in our catalog. Superposed are evolutionary models from Leiner et al. (2017) of SSGs experiencing mass transfer. All models assume a 1.3 M ⊙ subgiant primary with a compact companion in a 1.0-day orbit. Mass of the companion for each system is indicated by color of the track: 1.1 M ⊙ (green), 0.7 M ⊙ (blue), and 0.3 M ⊙ (red). The Leiner et al. (2017) models have been arbitrarily shifted 200 K cooler to better match the observed span of the SSG+WD candidate systems we observe, suggesting that similar evolutionary configurations but with different initial conditions (e.g., different subgiant mass, etc.) could potentially explain the diversity of SSG+WD systems we have identified. We also show in yellow a 4.5 Gyr solar-metallicity isochrone (Bressan et al. 2012)
Paper: White Dwarf Binaries across the H-R Diagram
Authors: Borja Anguiano, Steven R. Majewski, Keivan G. Stassun, Carles Badenes, Christine Mazzola Daher, Don Dixon, Carlos Allende Prieto, Donald P. Schneider, Adrian M. Price-Whelan, Rachael L. Beaton
Figure caption: APOGEE-derived radii for the non-WD stars vs. the nominal WD radii inferred from SED fitting (Section 2.4) for SDSS optical WDMS candidates (sdss-wdms.org; top panel), our parent sample of WD binary candidates based on Figure 1 (middle panel), and chromospherically active stars from Boro Saikia et al. (2018; bottom panel). In each panel, the red line represents a criterion, guided by and separating the loci of most single stars, most chromospherically active stars, and almost all bona fide WD stars from SDSS; the best AGGC stars will lie below this line.
Paper: White Dwarf Binaries across the H-R Diagram
Authors: Borja Anguiano, Steven R. Majewski, Keivan G. Stassun, Carles Badenes, Christine Mazzola Daher, Don Dixon, Carlos Allende Prieto, Donald P. Schneider, Adrian M. Price-Whelan, Rachael L. Beaton
Figure caption: Left panel: APOGEE-derived effective temperature vs. UV color for the AGGC sample. The figure is color-coded by the estimated WD radii. The vast majority of objects with (FUV–NUV)◦ <  3.5 in the AGGC show a potential WD where the radii are R < 10 R ⊕. Right panel: the temperature–radius diagram, given by the derived radius of the secondary as a function of the difference between the WD effective temperature and the secondary. The figure is color-coded by the derived WD candidate radius.
Paper: White Dwarf Binaries across the H-R Diagram
Authors: Borja Anguiano, Steven R. Majewski, Keivan G. Stassun, Carles Badenes, Christine Mazzola Daher, Don Dixon, Carlos Allende Prieto, Donald P. Schneider, Adrian M. Price-Whelan, Rachael L. Beaton
Figure caption: Top left panel: T eff–﹩\mathrm{log}g﹩ diagram for the APOGEE DR17 control sample (blue) and the WD binary catalog (orange). The selection of cold MS, RGB, and RC is also shown. Top right panel, bottom left and right panels: ΔRVmax cumulative fraction histogram for the cold MS sample, RGB, and RC in the APOGEE (blue) and WD binary catalogs (orange), respectively. The cumulative fraction for the WD binaries is skewed toward larger ΔRVmax with respect to the APOGEE control sample for the three selected populations.
Paper: White Dwarf Binaries across the H-R Diagram
Authors: Borja Anguiano, Steven R. Majewski, Keivan G. Stassun, Carles Badenes, Christine Mazzola Daher, Don Dixon, Carlos Allende Prieto, Donald P. Schneider, Adrian M. Price-Whelan, Rachael L. Beaton
Figure caption: Overall metallicity from the APOGEE spectra CDF for objects with M H < −3.0. The black line is for a sample dominated by single stars, and the red line is for the WD binary sample discussed in this work. For the most luminous stars the MDF is clearly different for the binary and nonbinary samples.
Paper: White Dwarf Binaries across the H-R Diagram
Authors: Borja Anguiano, Steven R. Majewski, Keivan G. Stassun, Carles Badenes, Christine Mazzola Daher, Don Dixon, Carlos Allende Prieto, Donald P. Schneider, Adrian M. Price-Whelan, Rachael L. Beaton
Figure caption: H-R diagram for the AGGC, with APOGEE-derived temperatures and H-band luminosities from 2MASS photometry+Gaia parallaxes. Sources are color-coded by the inferred WD temperature from the SED fitting (Section 3).
Paper: White Dwarf Binaries across the H-R Diagram
Authors: Borja Anguiano, Steven R. Majewski, Keivan G. Stassun, Carles Badenes, Christine Mazzola Daher, Don Dixon, Carlos Allende Prieto, Donald P. Schneider, Adrian M. Price-Whelan, Rachael L. Beaton
Figure caption: Comparison between the WD temperature derived using SED fitting and the (FUV–NUV) GALEX color. The figure is also color-coded with the WD radii. Stars with R WD > 20 R ⊕ tend to have T eff < 104 K.
Paper: Mass Upper Bounds for Over 50 Kepler Planets Using Low-S/N Transit Timing Variations
Authors: Jared C. Siegel, Leslie A. Rogers
Figure caption: Masses derived from low-S/N TTVs offer valuable constraints on the demographics of Kepler planets. On the left, we present the 95th percentile on planet mass from low-S/N TTVs against the 95th percentile on planet mass from the joint mass–radius–period distribution of Neil & Rogers (2020); see Section 5.4 for discussion. Planets where the TTV-derived mass constraint is informative (i.e., M 95% < M Fe(R), and M 95% deviates from the prior on mass) are shaded light blue; planets with informative TTV mass constraints that are a factor of 2 lower than the 95th percentile constraint from Neil & Rogers (2020) are shaded dark blue. On the right, we present the difference in M 95% between our TTV-based method (solid blue points) and Neil & Rogers (2020; hollow blue points), for the planets where this change is greater than a factor of 2. To contextualize these changes, we present the mass–radius relations for pure iron (red), silicate (purple), and water-ice (green) compositions (Seager et al. 2007).
Paper: Mass Upper Bounds for Over 50 Kepler Planets Using Low-S/N Transit Timing Variations
Authors: Jared C. Siegel, Leslie A. Rogers
Figure caption: Low-S/N TTV-derived mass constraints are generally insensitive to the treatment of stellar noise V ⋆,i,j . Here, we present the upper bounds on planet mass M 95% using our standard V ⋆,i,j  treatment (i.e., assuming V ⋆,i,j  is uncorrelated between planets) against the upper bounds derived using our alternative V ⋆,i,j  treatment (i.e., assuming V ⋆,i,j  is identical for planets in a given system). Planets where our standard assumption yields informative mass constraints are highlighted in blue. The KOI-658 system, where the two treatments differ by more than a factor of 4 for the outer two planets, is highlighted in red.
Paper: Mass Upper Bounds for Over 50 Kepler Planets Using Low-S/N Transit Timing Variations
Authors: Jared C. Siegel, Leslie A. Rogers
Figure caption: Using low-S/N TTV data, our method successfully constrains the masses of KOI-245.01 and KOI-245.02 and agrees well with RV-derived mass measurements. On the top row, we present the posteriors on planet mass for KOI-245.02 (left) and KOI-245.01 (right). For reference, we also include the orbital period and radius. On the bottom row, we present the O – C time series for each KOI.
Paper: Mass Upper Bounds for Over 50 Kepler Planets Using Low-S/N Transit Timing Variations
Authors: Jared C. Siegel, Leslie A. Rogers
Figure caption: For >50 planets, our methods place informative constraints on planet mass (i.e., the 95th percentile on planet mass M 95% significantly deviates from the prior and yields a bulk density less than a pure iron composition). We present M 95% for each planet’s posterior against its radius (blue), alongside the mass–radius relation for a pure iron (red), silicate (purple), and water-ice (green) composition (Seager et al. 2007). The 95th percentile of our mass prior is shown as a dashed vertical black line.
Paper: Mass Upper Bounds for Over 50 Kepler Planets Using Low-S/N Transit Timing Variations
Authors: Jared C. Siegel, Leslie A. Rogers
Figure caption: Planets with low-S/N TTV-derived composition constraints are predominately larger than 2 R ⊕. Here, we present the planet radius distribution for our entire sample of planets (black), alongside the distributions for planets with informative mass constraints (red) and planets with informative mass constraints that are less dense than a pure silicate composition (purple). Planets with informative mass constraints that are less dense than a pure water-ice composition are presented as vertical green lines. For clarity, the radius distributions are limited to R < 4 R ⊕.
Paper: Mass Upper Bounds for Over 50 Kepler Planets Using Low-S/N Transit Timing Variations
Authors: Jared C. Siegel, Leslie A. Rogers
Figure caption: For the vast majority of synthetic systems from He et al. (2020), the TTV variance induced by nondetected planets is significantly lower than the excess noise inferred for the Kepler singles. Here, we present the difference in TTV variance for a synthetic Kepler sample between modeling the physical and observed systems from He et al. (2020); systems where only one mock planet is observed are shown in blue. For comparison, we present the excess noise component—characterized via hierarchical Bayesian modeling in Section 3.2—for the Kepler singles in black.