adsabs/AstroCLIMB huggingface dataset:
Paper: Simultaneous Six-way Observations from the Navy Precision Optical Interferometer
Authors: Ellyn K. Baines, Solvay Blomquist, James H. Clark III, Jim Gorney, Erin Maier, Jason Sanborn, Henrique R. Schmitt, Jordan M. Stone, Gerard T. van Belle, Kaspar von Braun
Figure caption: The NPOI configuration used for six-way observing. The squares show the locations of the siderostats as a function of distance from the center, the red lines show the baselines on spectrograph 1, and the blue lines show the baselines on spectrograph 2. The dashed line is the baseline that repeats on both spectrographs. Table 3 lists the lengths of the various baselines.
Paper: Simultaneous Six-way Observations from the Navy Precision Optical Interferometer
Authors: Ellyn K. Baines, Solvay Blomquist, James H. Clark III, Jim Gorney, Erin Maier, Jason Sanborn, Henrique R. Schmitt, Jordan M. Stone, Gerard T. van Belle, Kaspar von Braun
Figure caption: Angular diameter fits to measured visibilities. The solid red line represents the visibility curve for the best-fit θ LD, the open circles are the calibrated visibilities, and the vertical lines are the measurement uncertainties.
Paper: Simultaneous Six-way Observations from the Navy Precision Optical Interferometer
Authors: Ellyn K. Baines, Solvay Blomquist, James H. Clark III, Jim Gorney, Erin Maier, Jason Sanborn, Henrique R. Schmitt, Jordan M. Stone, Gerard T. van Belle, Kaspar von Braun
Figure caption: An example probability density solution for the diameter fit to HD 6168/ϵ Psc visibilities as described in Section 3.1.
Paper: A Lack of Variability between Repeated Spitzer Phase Curves of WASP-43b
Authors: Matthew M. Murphy, Thomas G. Beatty, Michael T. Roman, Isaac Malsky, Alex Wingate, Grace Ochs, L. Cinque, Hayley Beltz, Emily Rauscher, Eliza M.-R. Kempton, Kevin B. Stevenson
Figure caption: Reduced-χ 2 values between our observed phase curve data and each cloudy GCM phase curve. The dashed, dotted, and dotted–dashed lines show this comparison for the 2014, 2019a, and 2019b visits individually, respectively. The thick solid lines show this comparison for all three observing visits combined. Horizontal lines are drawn at reduced-χ 2 = 1 and 2 for visual reference. Our observations strongly reject the intermediate thickness models. We find that no model fits the data extremely well, as the minimum reduced-χ 2 = 1.3 for the seven scale height nucleation limited model. However, we find that our observations are reasonably consistent with both the thinnest models (of 1–2 scale height maximum thicknesses) and the thickest models (7–9 scale height layer maximum thicknesses).
Paper: A Lack of Variability between Repeated Spitzer Phase Curves of WASP-43b
Authors: Matthew M. Murphy, Thomas G. Beatty, Michael T. Roman, Isaac Malsky, Alex Wingate, Grace Ochs, L. Cinque, Hayley Beltz, Emily Rauscher, Eliza M.-R. Kempton, Kevin B. Stevenson
Figure caption: Pointing histograms for the 2014 visit (top), 2019a visit (middle), and 2019b visit (bottom). The 2014 visit shows considerable overlap, but there is a notable trend in centroids toward the lower right likely due to re-pointing inconsistency between its three AORs. The 2019a visit has full overlap between its two AORs. The 2019b visit has two distinct centroid regions. The top right region consists frames from the first AOR and the bottom left region consists of frames from the second AOR. This suggests the spacecraft was unable to return to its original pointing when starting the second AOR.
Paper: A Lack of Variability between Repeated Spitzer Phase Curves of WASP-43b
Authors: Matthew M. Murphy, Thomas G. Beatty, Michael T. Roman, Isaac Malsky, Alex Wingate, Grace Ochs, L. Cinque, Hayley Beltz, Emily Rauscher, Eliza M.-R. Kempton, Kevin B. Stevenson
Figure caption: Emission phase curve of WASP-43b at 4.5 μm, which is the fully shared fit in our analysis. The black data points are a combination of the data from the three visits analyzed in this work, binned in 10 minute intervals. This binning is only done for presentation purposes, and only unbinned data were used during the analysis. The bottom panel shows the full light curve, while the top panel highlights the phase curve.
Paper: A Lack of Variability between Repeated Spitzer Phase Curves of WASP-43b
Authors: Matthew M. Murphy, Thomas G. Beatty, Michael T. Roman, Isaac Malsky, Alex Wingate, Grace Ochs, L. Cinque, Hayley Beltz, Emily Rauscher, Eliza M.-R. Kempton, Kevin B. Stevenson
Figure caption: Overlays of the fitted phase curves from this work. Solid lines are the best fit, while the transparent lines represent the 1σ uncertainty associated with each curve. Top: the individually fit phase curves. Middle: the semi-shared fit phase curves overlayed with the individually fit phase curves. Bottom: all fit phase curves, including the fully shared fit phase curve which we deem representative of all three visits.
Paper: A Lack of Variability between Repeated Spitzer Phase Curves of WASP-43b
Authors: Matthew M. Murphy, Thomas G. Beatty, Michael T. Roman, Isaac Malsky, Alex Wingate, Grace Ochs, L. Cinque, Hayley Beltz, Emily Rauscher, Eliza M.-R. Kempton, Kevin B. Stevenson
Figure caption: A plot of all light curves fit as part of this work. Columns distinguish different fitting methods—leftmost are the individual fits, middle are the semi-shared fits, and rightmost are the fully shared fits. Rows distinguish different visits—top being 2014, middle being 2019a, and bottom being 2019b. Our BIC analysis preferred the fully shared fit, meaning all three visits are best fit by a single, shared light curve.
Paper: A Lack of Variability between Repeated Spitzer Phase Curves of WASP-43b
Authors: Matthew M. Murphy, Thomas G. Beatty, Michael T. Roman, Isaac Malsky, Alex Wingate, Grace Ochs, L. Cinque, Hayley Beltz, Emily Rauscher, Eliza M.-R. Kempton, Kevin B. Stevenson
Figure caption: Simulated cloudy phase curves from our GCM integrated over a 5–6 μm bandpass. The points are simulated observations in this bandpass by JWST/MIRI LRS, as a prediction for what the upcoming JWST Transiting Exoplanet Community ERS Program observations of WASP-43b (Bean et al. 2018) may achieve. Top: here, we focus only on the one and seven scale height models as these represent the two thickness regimes that our Spitzer observations could not distinguish. Assuming one of these models as truth, these MIRI LRS observations would be able to rule out the other model at very high significance. This suggests that MIRI LRS observations will be able to measure accurately WASP-43b’s nightside emission and approximate cloud thickness. Bottom: here, we show the 7–9 scale height models, since our Spitzer observations could not significantly rule out any of these models, thus placing an upper limit on the possible thickness variation. We find that, in this 5–6 μm bandpass, there is no significant difference between the three models at any phase. Therefore, repeated MIRI LRS observations would likely not be able to place an improved upper limit on the thickness variations.
Paper: A Lack of Variability between Repeated Spitzer Phase Curves of WASP-43b
Authors: Matthew M. Murphy, Thomas G. Beatty, Michael T. Roman, Isaac Malsky, Alex Wingate, Grace Ochs, L. Cinque, Hayley Beltz, Emily Rauscher, Eliza M.-R. Kempton, Kevin B. Stevenson
Figure caption: Plots of our full data sets along with each fitted model. The top three rows show the normalized, unbinned light curve of the 2014, 2019a, and 2019b visits, respectively. The normalization factor used for each is given in their corresponding legend. In these top three panels, the red line represents the full best-fit model including astrophysical and systematic components, the cyan line represents the best-fit linear ramp, and the lime line represents the best-fit astrophysical model. The bottom row plots the normalized, unbinned flux against the x- and y-FWHMs of WASP-43 on our images for each visit. The best-fit x-FWHM model is shown in cyan, and the best-fit y-FWHM model is shown in lime, for each visit. These best-fit models are all from our fully shared fit case, which provided the best fit.
Paper: A Lack of Variability between Repeated Spitzer Phase Curves of WASP-43b
Authors: Matthew M. Murphy, Thomas G. Beatty, Michael T. Roman, Isaac Malsky, Alex Wingate, Grace Ochs, L. Cinque, Hayley Beltz, Emily Rauscher, Eliza M.-R. Kempton, Kevin B. Stevenson
Figure caption: Plot of the standard deviations of the residuals as a function of bin size for each visit, after applying all components of our fully shared fit model. For each data set, the standard deviations decrease roughly as 1/﹩\sqrt{N}﹩ as the bin size is increased, suggesting there is not much excess red noise left over in the detrended data, and each visit’s plot looks nearly the same.
Paper: A Lack of Variability between Repeated Spitzer Phase Curves of WASP-43b
Authors: Matthew M. Murphy, Thomas G. Beatty, Michael T. Roman, Isaac Malsky, Alex Wingate, Grace Ochs, L. Cinque, Hayley Beltz, Emily Rauscher, Eliza M.-R. Kempton, Kevin B. Stevenson
Figure caption: Plot of the cloudy GCM phase curves that are consistent with our combined observations by ﹩{\chi }_{\mathrm{reduced}}^{2}\lt ﹩ 2.2. Models with all cloud species are shown as colored solid lines, while those with nucleation limited species are the colored dotted lines. Also shown are the detrended observed data, combined from the 2014, 2019a, and 2019b visits, as fit by our fully shared model. Points within transit and eclipse are removed. The solid black line is the fully shared fit phase curve, which was best fit to the data as described in Section 4.
Paper: On the Application of Bayesian Leave-one-out Cross-validation to Exoplanet Atmospheric Analysis
Authors: Luis Welbanks, Peter McGill, Michael Line, Nikku Madhusudhan
Figure caption: Retrieved transmission spectrum of HAT-P-41 b for the reference “minimal” model and HST UVIS G280 observations with systematic marginalization treatment, HST WFC3 G141, and Spitzer IRAC 3.6 μm and 4.5 μm observations from Wakeford et al. (2020) and Lewis et al. (2020). Data points are color-coded by the Δelpd score between the reference minimal model and the model without H− absorption. Redder data points (larger positive Δelpd score) are better explained by the reference model with H− absorption while the bluer points (larger negative Δelpd score) are better explained by the model without H− absorption. The orange arrow indicates the data point with the highest Δelpd score (3.6 μm), at a wavelength where bound-free H− absorption is not expected. The retrievals indicate a 2.7σ detection of H−, but removing the data point with the highest Δelpd score (i.e., Spitzer point at 3.6 μm) removes this preference.
Paper: On the Application of Bayesian Leave-one-out Cross-validation to Exoplanet Atmospheric Analysis
Authors: Luis Welbanks, Peter McGill, Michael Line, Nikku Madhusudhan
Figure caption: Comparison between the reference model (purple) and simpler models (green), with shaded regions showing their retrieved 2σ confidence intervals. The synthetic observations are color-coded by their Δelpd score following Equation (6), between the reference model and models without H2O (top left), Na (top right), K (bottom left), and inhomogeneous clouds and hazes (bottom right). Data points with larger positive Δelpd scores (redder points) indicate that the reference model is better at explaining them. H2O absorption preferentially explains data points at ∼1.1–1.7 μm, Na absorption at ∼0.6 μm, and K absorption at ∼0.8 μm, in agreement with expectations. The increase in the predictive performance of the model (the numerical scale of the color map) is largest due to H2O, followed by Na and K; the inclusion of inhomogeneous clouds and hazes in the model does not improve the predictive performance of the model for this input cloud-free atmosphere.
Paper: On the Application of Bayesian Leave-one-out Cross-validation to Exoplanet Atmospheric Analysis
Authors: Luis Welbanks, Peter McGill, Michael Line, Nikku Madhusudhan
Figure caption: Left: exact elpd terms (Equation (4)) against PSIS-approximated elpd terms (Equation (A5)) for the synthetic data scenario described in Section 5. The exact terms we calculated by refitting the model N (46) times with each data point left out in turn. One-to-one correspondence is shown as a dashed line. The PSIS-approximated elpd terms are in good agreement with the exact terms. Middle: Pareto k values for the PSIS approximation for each data point and for each model considered in Section 5. Reference model is shown in blue, while models without H2O, Na, K, or clouds are shown in orange, green, red, and purple, respectively. Data point number is ordered by increasing wavelength. Right: as middle panel but for the real data in Section 6 and the “minimal” model used as reference (green points), the model without H− absorption (orange points), and the model without H2O absorption (purple points). For the synthetic and real observations, all Pareto k values are <0.7, indicating that the PSIS approximation is reliable for all left out data points. This means all elpd terms were computed with PSIS and only one model fit had to be performed.
Paper: On the Application of Bayesian Leave-one-out Cross-validation to Exoplanet Atmospheric Analysis
Authors: Luis Welbanks, Peter McGill, Michael Line, Nikku Madhusudhan
Figure caption: Predictive model performance quantified by the sum of the Δelpd scores (Equation (6)) over the entire data set divided by their standard error (SE; Equation (8)); see Table 1. The Δelpd scores are computed by the difference in elpd score between the reference model and models without H2O (blue), Na (orange), K (green), and inhomogeneous clouds and hazes (red). Positive values indicate an increase in the predictive performance of the reference model due to the addition of the specific model component. On the other hand, negative values indicate a decreased predictive performance of the model due to the inclusion of the specific model component.
Paper: On the Application of Bayesian Leave-one-out Cross-validation to Exoplanet Atmospheric Analysis
Authors: Luis Welbanks, Peter McGill, Michael Line, Nikku Madhusudhan
Figure caption: As Figure 4 but for the Δelpd score between the reference “minimal” model and the model without H2O absorption. Redder data points are preferentially explained by H2O absorption. The data points with a larger Δelpd score (redder data points) indicate a preference for H2O absorption, and fall at wavelengths near the ∼1.4 μm H2O feature as expected.
Paper: On the Application of Bayesian Leave-one-out Cross-validation to Exoplanet Atmospheric Analysis
Authors: Luis Welbanks, Peter McGill, Michael Line, Nikku Madhusudhan
Figure caption: Δelpd scores (i.e., predictive model performance) divided by their standard error (SE) for the inclusion of H2O (blue) and H− (orange) absorption for the reference “minimal” model and HST WFC3/UVIS (systematic marginalization), HST WFC3 G141, and Spitzer IRAC observations. Adding H2O absorption into the reference model results in a larger increase in the predictive performance of the model than including H− absorption.
Paper: On the Application of Bayesian Leave-one-out Cross-validation to Exoplanet Atmospheric Analysis
Authors: Luis Welbanks, Peter McGill, Michael Line, Nikku Madhusudhan
Figure caption: Reference model fit and simulated data as described in Section 5. Each of the data points are colored by their PSIS-approximated elpd score (elpd i,Reference). Data points with a lighter (more yellow) color have a higher elpd score and are better predicted by the model when left out.
Paper: NICMOS Kernel-phase Interferometry. II. Demographics of Nearby Brown Dwarfs
Authors: Samuel M. Factor, Adam L. Kraus
Figure caption: Binary population as a function of projected separation. The blue histogram shows the detected companion separations and error bars calculated using Burgasser et al. (2003), with dashes below showing the unbinned values. Gray bars and error bars correspond to the Blake et al. (2010) measurement of tight separation binaries (﹩{2.5}_{-1.6}^{+8.6} \% ﹩ spread out evenly over ﹩\mathrm{log}(\rho )=-2﹩ to 0). Orange curves are 1000 companion probability densities drawn from the posterior distributions using the informed prior, while the solid black curve is drawn using the median parameters (﹩F={0.11}_{-0.03}^{+0.04}﹩, ﹩\overline{\mathrm{log}(\rho )}={0.34}_{-0.25}^{+0.19}﹩, ﹩{\sigma }_{\mathrm{log}(\rho )}={0.58}_{-0.13}^{+0.20}﹩, i.e., the top left panel of Figure 4 marginalized over q). The black dashed line shows the Malmquist-corrected distribution (see Section 3.2) and the dashed–dotted line shows the “observed” distribution (bottom center panel of Figure 4), calculated by multiplying the Malmquist-corrected binary-population distribution by our sensitivity (shown in Figure 2 or the top right panel of Figure 4). The black dotted line is the completeness fraction (right vertical axis), the ratio between the black dashed and dashed–dotted lines—or equivalently, the marginalized and normalized sensitivity.
Paper: NICMOS Kernel-phase Interferometry. II. Demographics of Nearby Brown Dwarfs
Authors: Samuel M. Factor, Adam L. Kraus
Figure caption: Empirical relations for converting 2MASS photometry to the corresponding HST–2MASS colors (left) and NICMOS photometry to bolometric luminosity (right) built using synthetic photometry of the sample of brown dwarfs in Filippazzo et al. (2015), shown as points and error bars. Equations for the HST–2MASS colors are given in Equations (1) and (2) and equations for HST absolute magnitude to logL are given in Equation (3) and coefficients in Table 2. Black lines are drawn using the median parameters, while colored lines are 100 samples drawn from the posterior distributions.
Paper: NICMOS Kernel-phase Interferometry. II. Demographics of Nearby Brown Dwarfs
Authors: Samuel M. Factor, Adam L. Kraus
Figure caption: Posteriors of the mass-function power-law index γ as a function of assumed field age. White points and black vertical lines correspond to median and ±1σ values.
Paper: NICMOS Kernel-phase Interferometry. II. Demographics of Nearby Brown Dwarfs
Authors: Samuel M. Factor, Adam L. Kraus
Figure caption: Binary demographic parameters as a function of stellar mass. Black points are taken from Table 1 of Sullivan & Kraus (2021), who compiled parameters from a variety of sources (Raghavan et al. 2010; Kraus & Hillenbrand 2012; De Rosa et al. 2014; Winters et al. 2019; Tokovinin 2020). The dark blue circle corresponds to the work of Fontanive et al. (2018; for T5–Y0), the gray X is from Reid et al. (2006), the orange square is from Allen (2007), and the light blue diamond is from Burgasser et al. (2007). Fits from this work are shown on a color scale from purple to yellow for different assumed field ages. Assumed age mainly affects the derived masses of the sources and γ, the mass-ratio power-law index, while having little to no effect on the three other parameters. Mass error bars show the central 68% interval. We use projected separation, ρ, and semimajor axis, a, interchangeably because the conversion between the two values is ∼1 (Dupuy & Liu 2011; see footnote 1).
Paper: The PEPSI Exoplanet Transit Survey (PETS). II. A Deep Search for Thermal Inversion Agents in KELT-20 b/MASCARA-2 b with Emission and Transmission Spectroscopy 
Authors: Marshall C. Johnson, Ji Wang, 王 吉, Anusha Pai Asnodkar, Aldo S. Bonomo, B. Scott Gaudi, Thomas Henning, Ilya Ilyin, Engin Keles, Luca Malavolta, Matthias Mallonn, Karan Molaverdikhani, Valerio Nascimbeni, Jennifer Patience, Katja Poppenhaeger, Gaetano Scandariato, Everett Schlawin, Evgenya Shkolnik, Daniela Sicilia, Alessandro Sozzetti, Klaus G. Strassmeier, Christian Veillet, Fei Yan
Figure caption: Model spectra generated with petitRADTRANS. The wavelength ranges covered by PEPSI CD III and V are shown in blue and red, respectively. The The top panel shows the emission spectrum of Fe I. The bottom panels show the emission (left) and transmission (right) spectra, respectively, of (top to bottom) TiO, VO, FeH, and CaH. The spectra shown for the molecular constituents are generated with the minimum VMR which would give a 4σ detection in our injection-recovery testing; see the main text for more details.
Paper: The PEPSI Exoplanet Transit Survey (PETS). II. A Deep Search for Thermal Inversion Agents in KELT-20 b/MASCARA-2 b with Emission and Transmission Spectroscopy 
Authors: Marshall C. Johnson, Ji Wang, 王 吉, Anusha Pai Asnodkar, Aldo S. Bonomo, B. Scott Gaudi, Thomas Henning, Ilya Ilyin, Engin Keles, Luca Malavolta, Matthias Mallonn, Karan Molaverdikhani, Valerio Nascimbeni, Jennifer Patience, Katja Poppenhaeger, Gaetano Scandariato, Everett Schlawin, Evgenya Shkolnik, Daniela Sicilia, Alessandro Sozzetti, Klaus G. Strassmeier, Christian Veillet, Fei Yan
Figure caption: Example PEPSI data displaying our procedure to telluric-correct the spectra. The figure shows one PEPSI spectrum from 2021-05-1 in black, with the blue and red arms in the top and bottom panels, respectively. The molecfit-corrected spectrum is shown in red for the red arm. For that arm we also highlight the wavelength regions fit by molecfit in gray, and those which we mask out when performing our analyses due to poor telluric correction in red.
Paper: The PEPSI Exoplanet Transit Survey (PETS). II. A Deep Search for Thermal Inversion Agents in KELT-20 b/MASCARA-2 b with Emission and Transmission Spectroscopy 
Authors: Marshall C. Johnson, Ji Wang, 王 吉, Anusha Pai Asnodkar, Aldo S. Bonomo, B. Scott Gaudi, Thomas Henning, Ilya Ilyin, Engin Keles, Luca Malavolta, Matthias Mallonn, Karan Molaverdikhani, Valerio Nascimbeni, Jennifer Patience, Katja Poppenhaeger, Gaetano Scandariato, Everett Schlawin, Evgenya Shkolnik, Daniela Sicilia, Alessandro Sozzetti, Klaus G. Strassmeier, Christian Veillet, Fei Yan
Figure caption: P-T profiles considered in this work. Our best P-T profile which we adopt is shown in red, along with the published P-T profiles retrieved by Yan et al. (2022b), Fu et al. (2022), Borsa et al. (2022), and Kasper et al. (2022).
Paper: The PEPSI Exoplanet Transit Survey (PETS). II. A Deep Search for Thermal Inversion Agents in KELT-20 b/MASCARA-2 b with Emission and Transmission Spectroscopy 
Authors: Marshall C. Johnson, Ji Wang, 王 吉, Anusha Pai Asnodkar, Aldo S. Bonomo, B. Scott Gaudi, Thomas Henning, Ilya Ilyin, Engin Keles, Luca Malavolta, Matthias Mallonn, Karan Molaverdikhani, Valerio Nascimbeni, Jennifer Patience, Katja Poppenhaeger, Gaetano Scandariato, Everett Schlawin, Evgenya Shkolnik, Daniela Sicilia, Alessandro Sozzetti, Klaus G. Strassmeier, Christian Veillet, Fei Yan
Figure caption: Graphic illustrating the phases at which our observations of KELT-20 b took place. Different nights are marked by different colors. The planetary orbit and the stellar surface are the large and small circles, respectively. The observer is viewing from the bottom, and the illustration is looking down on the north pole of the star, such that the planet moves in a counter-clockwise direction; transit occurs at the bottom, and secondary eclipse at the top. The dotted lines denote the edges of the secondary eclipse and the transit.
Paper: Exploring the Recycling Model of Phobos Formation: Rubble-pile Satellites 
Authors: Gustavo Madeira, Sébastien Charnoz, Yun Zhang, Ryuki Hyodo, Patrick Michel, Hidenori Genda, Silvia Giuliatti Winter
Figure caption: (a) Time span (left scale; solid line) and number of cycles (right scale; dotted line) to form a Phobos analog as a function of the particle size. (b) Mass of the largest satellite in the cycle relative to the initial disk mass in the same cycle, with different colors corresponding to different particle sizes. The open points in the panel correspond to the cycles that form a Phobos analog. (c) Average optical depth of the residual ring coexisting with Phobos as a function of the particle size. We set the initial disk mass as 1.1 × 104 M P and the friction angle equal to 40°. The annotations below and above the black curve give the ring mass and number of particles in the ring, respectively.