adsabs/AstroCLIMB huggingface dataset:
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: The strength of a planet’s mass constraint is generally correlated with the planet’s minimum adjacent period ratio. Here, we present each planet’s TTV-derived upper bound on planet mass (parameterized by the 95th percentile of the posterior, M 95%) alongside the planet’s minimum adjacent period ratio. The 95th percentile of our planet mass prior is shown as a dashed horizontal 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: Every planet in our sample shows minimal planet–planet correlations for both the mass and longitude of periastron posteriors. We present the distribution of the Pearson correlation coefficient ﹩{ \mathcal R }﹩ between adjacent planets’ mass posteriors (left panel) and the correlation coefficient between adjacent planets’ longitudes of periastron (right panel). The planet–planet correlations for the near-resonant systems removed from our sample are shown as black vertical lines.
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 upper bounds on planet mass are consistent with RV-derived mass measurements. Here, we present the 95th percentile on planet mass from our methods against RV-derived masses for the 14 planets in our sample with RV masses. The vertical error bars show the 2σ uncertainties on the RV measurements.
Paper: Zwicky Transient Facility and Globular Clusters: The Period–Luminosity and Period–Wesenheit Relations for Type II Cepheids
Authors: Chow-Choong Ngeow, Anupam Bhardwaj, Jing-Yi Henderson, Matthew J. Graham, Russ R. Laher, Michael S. Medford, Josiah Purdum, Ben Rusholme
Figure caption: Left panel: PC relations for the M31 TIICs, where the colors of the TIICs have been reddening corrected (Kodric et al. 2018). The solid lines are the PC relations given in Table 5, together with the ±3σ boundaries shown as dashed lines. Right panel: the PW relation (top right panel) for the W ri   r  Wesenheit index, and the extinction-corrected ri-band PL relations (middle right and bottom right panels) for the M31 TIICs. Crosses represent the rejected TIICs as described in the text (see Section 6). Similar to the left panels, the solid lines are the PL/PW relations given in Tables 3 and 4, respectively, shifted vertically with the distance modulus (μ) of M31, and the dashed lines are the corresponding ±3σ boundaries. Black lines are the shifted PL/PW relations by adopting the same μ = 24.407 mag (Li et al. 2021). The red lines represent the PL/PW relations after shifting the μ determined from fitting the data to the PL/PW relations given in Tables 3 and 4. In both panels, error bars are omitted for clarity.
Paper: Zwicky Transient Facility and Globular Clusters: The Period–Luminosity and Period–Wesenheit Relations for Type II Cepheids
Authors: Chow-Choong Ngeow, Anupam Bhardwaj, Jing-Yi Henderson, Matthew J. Graham, Russ R. Laher, Michael S. Medford, Josiah Purdum, Ben Rusholme
Figure caption: The updated multiband PL relations, where the best-fit PL relations are shown in solid lines (see Table 3), and the dashed lines represent the ±3σ of the best-fit PL relations (hence, data points outside the ±3σ range are rejected in the fitting). The BVIJHK-band PL relations were updated from Bhardwaj (2022) by using the homogeneous distance from Baumgardt & Vasiliev (2021). The updated gri-band PL relations were derived from combining two samples of TIICs: those with ZTF data as listed in Table 1, and the TIICs from the B22 sample that are not included in Table 1 (after being transformed to the gri bands). See Section 4.2 for more details. Note that the error bars are smaller than the size of the symbols.
Paper: Zwicky Transient Facility and Globular Clusters: The Period–Luminosity and Period–Wesenheit Relations for Type II Cepheids
Authors: Chow-Choong Ngeow, Anupam Bhardwaj, Jing-Yi Henderson, Matthew J. Graham, Russ R. Laher, Michael S. Medford, Josiah Purdum, Ben Rusholme
Figure caption: Slopes of the fitted linear regressions, γ, from the plots for PL residuals vs. [Fe/H] as a function of filters. The red line indicates the case of γ = 0.
Paper: Zwicky Transient Facility and Globular Clusters: The Period–Luminosity and Period–Wesenheit Relations for Type II Cepheids
Authors: Chow-Choong Ngeow, Anupam Bhardwaj, Jing-Yi Henderson, Matthew J. Graham, Russ R. Laher, Michael S. Medford, Josiah Purdum, Ben Rusholme
Figure caption: Same as Figure 4, but for the reddening-corrected PC relations (top three panels) and the reddening-free PQ relation (bottom panels). Scales on the y-axis were intended to be the same in all panels, such that the PC/PQ relations can be compared.
Paper: Zwicky Transient Facility and Globular Clusters: The Period–Luminosity and Period–Wesenheit Relations for Type II Cepheids
Authors: Chow-Choong Ngeow, Anupam Bhardwaj, Jing-Yi Henderson, Matthew J. Graham, Russ R. Laher, Michael S. Medford, Josiah Purdum, Ben Rusholme
Figure caption: Same as Figure 4, but for the PW relations.
Paper: Mass Production of 2021 KMTNet Microlensing Planets. I
Authors: Yoon-Hyun Ryu, Youn Kil Jung, Hongjing Yang, Andrew Gould, Michael D. Albrow, Sun-Ju Chung, Cheongho Han, Kyu-Ha Hwang, In-Gu Shin, Yossi Shvartzvald, Jennifer C. Yee, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: Caustic structures for KMT-2021-BLG-1391 for the two “inner/outer” pairs of degenerate solutions, i.e., Locals 1 and 4 and Locals 2 and 3, respectively. The source size is to scale, and the epochs of the observations are shown, with red points from KMTC and green points from KMTA. In the first pair of solutions, the source diameter is slightly smaller than the caustic separation, giving rise to a “dimple” over the peak of the anomaly. See Figure 1. In the second, the source is much larger than the caustic separation. The two pairs of solutions predict very different proper motions and so can ultimately be distinguished by late-time AO imaging.
Paper: Mass Production of 2021 KMTNet Microlensing Planets. I
Authors: Yoon-Hyun Ryu, Youn Kil Jung, Hongjing Yang, Andrew Gould, Michael D. Albrow, Sun-Ju Chung, Cheongho Han, Kyu-Ha Hwang, In-Gu Shin, Yossi Shvartzvald, Jennifer C. Yee, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: Caustics for KMT-2021-BLG-1253. There are two pairs of solutions: in Locals 1 and 4 the flat-topped bump is explained by a source whose diameter is about equal to the separation between two caustic walls, whereas in Locals 1 and 3 it is explained by a source that is much larger than this separation (and the caustic is substantially smaller). Each pair constitutes a classic wide/close degeneracy. The different normalized source sizes (ρ ∼ 1.3 × 10−3 vs. ρ ∼ 2 × 10−3) lead to different Bayesian mass and distance estimates, but these will ultimately be resolved by AO follow-up observations. See Section 5.2.
Paper: Mass Production of 2021 KMTNet Microlensing Planets. I
Authors: Yoon-Hyun Ryu, Youn Kil Jung, Hongjing Yang, Andrew Gould, Michael D. Albrow, Sun-Ju Chung, Cheongho Han, Kyu-Ha Hwang, In-Gu Shin, Yossi Shvartzvald, Jennifer C. Yee, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: Top panel: light curve and model for KMT-2021-BLG-1391, color-coded by observatory. Bottom panels: zoom-ins of 0.35 days centered on the “bump” anomaly traced by six KMTC points. The small-ρ “double-peaked” Local 1 is preferred over either of the large-ρ models (Locals 2 and 3) by Δχ 2 = 5, mainly because it better accounts for the “flat top” or possible “dimple” in the bump. See Figure 2.(The data used to create this figure are available.)
Paper: Mass Production of 2021 KMTNet Microlensing Planets. I
Authors: Yoon-Hyun Ryu, Youn Kil Jung, Hongjing Yang, Andrew Gould, Michael D. Albrow, Sun-Ju Chung, Cheongho Han, Kyu-Ha Hwang, In-Gu Shin, Yossi Shvartzvald, Jennifer C. Yee, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge
Figure caption: Light curve and models for KMT-2021-BLG-1253. Despite good coverage of the “bump” anomaly, there are four models that fit the data almost equally well (residuals in lower panels). However, all four solutions have similar planet–host mass ratios q ∼ 2.4 × 10−4 and normalized planet–host separations s ∼ 1. Nevertheless, they have very different normalized source sizes. See Table 3 and Figure 4.(The data used to create this figure are available.)
Paper: Correcting Stellar Flare Frequency Distributions Detected by TESS and Kepler
Authors: Dong-Yang Gao, 东洋 高, Hui-Gen Liu, 慧根 刘, Ming Yang, 明 杨, Ji-Lin Zhou, 济林 周
Figure caption: Different flare catalogs of solar-type stars. (a) The histogram of 15,056 flares on 507 stars from Yang19 (solid blue), 989 superflares on 307 stars from Tu20 (solid green), and 502 flares on 107 stars from Gün20 (solid red). The blue, green, and red dashed lines are the cumulative distribution functions from Yang19, Tu20, and Gün20, respectively. N f is the number of flares. (b) The blue, green, and red dots are the FFDs from Yang19, Tu20, and Gün20, respectively. The blue, green, and red solid lines are the fitted power laws of the respective FFDs in the energy range 1034.5–1036.0 erg. The FFDs of different catalogs using are fitted the equation ﹩{{\rm{log}}}_{10}({dN}(E)/({dE}\,{dt}))=\alpha \,{{\rm{log}}}_{10}(E)+C﹩ (see Section 3.5). The text in the figure indicates the fitted parameter values and the errors of α.
Paper: Correcting Stellar Flare Frequency Distributions Detected by TESS and Kepler
Authors: Dong-Yang Gao, 东洋 高, Hui-Gen Liu, 慧根 刘, Ming Yang, 明 杨, Ji-Lin Zhou, 济林 周
Figure caption: (a) The histogram of 792 flare events we detected in Sample-2 (solid green) and 178 superflares in Tu et al. (2020; solid red). Note that the energy calculation is based on the blackbody assumption and is not corrected in panel (a). The dashed green and red lines are the CDFs of all flares we detected and those from Tu et al. (2020), respectively. (b) Similar to panel (a), the histogram of 178 superflares from Tu et al. (2020; solid red) and the histogram of 169 cross-matched flare events we detected in Sample-2 (solid green). Note the energy correction is added in panel (b) to compare with Tu20's results (see the text and Appendix B for detail).
Paper: Correcting Stellar Flare Frequency Distributions Detected by TESS and Kepler
Authors: Dong-Yang Gao, 东洋 高, Hui-Gen Liu, 慧根 刘, Ming Yang, 明 杨, Ji-Lin Zhou, 济林 周
Figure caption: The flares we found using our pipeline for TIC 206592394 in Sector 2 of the TESS mission. The red, green, and blue events show the flares we found. The green and blue events are the same as in the catalogs of Tu et al. (2020) and Günther et al. (2020) respectively. The number of flares we detected is greater than in previous works, and is annotated on the figure.
Paper: Correcting Stellar Flare Frequency Distributions Detected by TESS and Kepler
Authors: Dong-Yang Gao, 东洋 高, Hui-Gen Liu, 慧根 刘, Ming Yang, 明 杨, Ji-Lin Zhou, 济林 周
Figure caption: Scatter plot of the normalized flare amplitudes vs. different stellar parameters in Sample-2. The black dots mark each flare and the red squares mark the average values on each star.
Paper: Correcting Stellar Flare Frequency Distributions Detected by TESS and Kepler
Authors: Dong-Yang Gao, 东洋 高, Hui-Gen Liu, 慧根 刘, Ming Yang, 明 杨, Ji-Lin Zhou, 济林 周
Figure caption: The five procedures adopted in this paper. Note procedures (ii) and (iii) are based on the improved Python package AltaiPony (Davenport 2016; Ilin et al. 2021).
Paper: On Internal and External Alignment of Dust Grains in Protostellar Environments
Authors: Thiem Hoang, Le Ngoc Tram, Vo Hong Minh Phan, Nguyen Chau Giang, Nguyen Thi Phuong, Nguyen Duc Dieu
Figure caption: Illustration of torque-free motion of an oblate spheroidal grain with semimajor and semiminor axes of a and c. In the grain’s body frame, the angular momentum ( J ) and angular velocity (Ω) are both precessing around the axis of maximum moment of inertia ﹩{\hat{{\boldsymbol{a}}}}_{1}﹩ with an angular rate ω.
Paper: On Internal and External Alignment of Dust Grains in Protostellar Environments
Authors: Thiem Hoang, Le Ngoc Tram, Vo Hong Minh Phan, Nguyen Chau Giang, Nguyen Thi Phuong, Nguyen Duc Dieu
Figure caption: Illustration of the three effects of RATs by an anisotropic radiation field, including the spin-up, alignment, and precession around  k . The perfect internal alignment of the grain’s shortest axis, ﹩\hat{{\boldsymbol{a}}}﹩                      1, with  J  is assumed.
Paper: Inferring Exoplanet Disequilibria with Multivariate Information in Atmospheric Reaction Networks
Authors: Theresa Fisher, Hyunju Kim, Camerian Millsaps, Michael Line, Sara I. Walker
Figure caption: Predictive power of variables for the disequilibrium state of the atmospheric chemical reaction networks. Each panel of the plot shows the predicting accuracy of one individual variable denoted on the title (highlighted in blue) compared to the other 10 variables shown in other panels (colored in gray) for atmospheric networks associated with K zz = 0, 106, 108, and 1010 as a function of the mean temperature with uncertainty ±50 K (where gray lines show the predicting accuracy from the other variables on all plots for ease of comparison). The variables include G (Gibbs free energy); the abundances of chemical species NH3, CH4, CO, and H2O; and the average topological properties (see Table 1 and Section 2.2).
Paper: Inferring Exoplanet Disequilibria with Multivariate Information in Atmospheric Reaction Networks
Authors: Theresa Fisher, Hyunju Kim, Camerian Millsaps, Michael Line, Sara I. Walker
Figure caption:  T = 2000 K. Distributions of network topology, interpolated from a 10,000-point normal distribution of initial conditions centered on a mean temperature of 2000 K, at K zz values of 0 and 1010, and uncertainties in temperature of 50, 250, and 1000 K. Distributions with different K zz values are less distinguishable from each other, likely because the faster thermal kinetics forces the system back to equilibrium more rapidly than chemical species can be dredged up via vertical mixing. This is in line with previous observations that the effect of vertical mixing on the distance from equilibrium tends to weaken as temperatures increase (Mollière et al. 2015; Thorngren et al. 2019). The bimodal distributions seen in the ± 1000 K case are an artifact of adding noise to the data. For the description of the network measures in the figure, see Table 1 and Section 2.2.
Paper: Inferring Exoplanet Disequilibria with Multivariate Information in Atmospheric Reaction Networks
Authors: Theresa Fisher, Hyunju Kim, Camerian Millsaps, Michael Line, Sara I. Walker
Figure caption: Boosting up the predicting accuracy for the disequilibrium state of the atmospheric chemical reaction networks with multivariate information. Each panel of the plot shows the predicting accuracy of variables for atmospheric networks associated with K zz = 0, 106, 108, and 1010 at a given mean temperature between 500 and 1900 K with uncertainty ±50 K. The three variables with the highest predictive power at each mean temperature compared to other individual variables (in gray) are colored red. (for detailed information about topological variables used in this plot, see Table 1 and Section 2.2). T*, A*, and N* represent multidimensional variable sets composed of the three top predictors, the abundance of the four chemical species shown in this plot, and the six network topological measures represented in Figure 9, respectively. The three different multivariable sets demonstrated higher predicting accuracy than individual variables even in the cases where the highest predictors are not included.
Paper: Inferring Exoplanet Disequilibria with Multivariate Information in Atmospheric Reaction Networks
Authors: Theresa Fisher, Hyunju Kim, Camerian Millsaps, Michael Line, Sara I. Walker
Figure caption:  T = 1200 K. Distributions of network measures and thermodynamic parameters, interpolated from a 10,000-point normal distribution of initial conditions centered on a mean temperature of 1200 K, at K zz values of 0 and 1010, and uncertainties in temperature of 50, 250, and 1000 K. The distributions with different K zz values can be distinguished from each other for the network measures (especially average clustering coefficient and mean degree), even with uncertainties of ±250 K. Total available Gibbs free energy, however, does not appear to be useful for distinguishing between atmospheres at equilibrium and disequilibrium. The bimodal distributions seen in the ±1000 K case are an artifact of adding noise to the data. Appendix For the description of the network measures in the figure, see Table 1 and Section 2.2.
Paper: Inferring Exoplanet Disequilibria with Multivariate Information in Atmospheric Reaction Networks
Authors: Theresa Fisher, Hyunju Kim, Camerian Millsaps, Michael Line, Sara I. Walker
Figure caption: K-S metric values for the distributions of observable molecule abundance, and network topological measures. Distributions were calculated from a normal distribution of initial conditions, centered at 900 K, 50sol metallicity, and 100 mb. Values were calculated with respect to the distribution at equilibrium (K zz = 0). Uncertainty for the distributions was ±50 K. A K-S value of 0 indicates that the two distributions sampled are indistinguishable from each other; the closer the value is to 1, the more distinguishable the distributions are. For comparative values across K zz values, see Table A1. For the description of the network measures in the figure, see Table 1 and Section 2.2.
Paper: Inferring Exoplanet Disequilibria with Multivariate Information in Atmospheric Reaction Networks
Authors: Theresa Fisher, Hyunju Kim, Camerian Millsaps, Michael Line, Sara I. Walker
Figure caption: The abundance of CO as a function of temperature and K zz, at 0.1, 1, 10, and 100 times solar metallicity. The x-axis is temperature, y-axis is K zz, and color corresponds to the abundance of CO (see color bar for each individual plot for scale).
Paper: Inferring Exoplanet Disequilibria with Multivariate Information in Atmospheric Reaction Networks
Authors: Theresa Fisher, Hyunju Kim, Camerian Millsaps, Michael Line, Sara I. Walker
Figure caption: Robustness of network topology as predictions for the disequilibrium state of the atmospheric chemical reaction networks against perturbation. The predicting accuracy of topological variables and the set of them for K zz are measured where one of four chemical species—NH3, CH4, CO, and H2O—was knocked out. The uncertainty of temperature in the given data set is 50 K.
Paper: Inferring Exoplanet Disequilibria with Multivariate Information in Atmospheric Reaction Networks
Authors: Theresa Fisher, Hyunju Kim, Camerian Millsaps, Michael Line, Sara I. Walker
Figure caption:  T = 1200 K w/ perturbations w/ pathway removed, uncertainty ±50 K. Distributions of network measures when the CH4−CO quenching pathway is removed from the network (dashed line) vs. complete networks (solid line), at 1200 K and 1 solar metallicity: clustering coefficient and average neighbor degree allow distinction between the two. For the description of the network measures in the figure, see Table 1 and Section 2.2.
Paper: Inferring Exoplanet Disequilibria with Multivariate Information in Atmospheric Reaction Networks
Authors: Theresa Fisher, Hyunju Kim, Camerian Millsaps, Michael Line, Sara I. Walker
Figure caption: The abundance of CH4 as a function of temperature and K zz, at 0.1, 1, 10, and 100 times solar metallicity. The x-axis is temperature, y-axis is K zz, and color corresponds to the abundance of CH4 (see color bar for each individual plot for scale).
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: Removal of stellar variability signal for TOI 322. The top panel shows the normalized TESS photometry from sector 32 (black points) and the celerite fit to the out-of-transit variability (pink line). The bottom panel shows the flattened, transit light curve on the same scale.
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: Transit light curves for TOI 601—1740. The phase folded TESS photometry is shown as the blue circles and the best-fit EXOFAST transit model is shown as the solid black line.
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: Transit light curves for TOI 141—492. The phase folded TESS photometry is shown as the blue circles and the best-fit EXOFAST transit model is shown as the solid black line.
Paper: MOA-2019-BLG-008Lb: A New Microlensing Detection of an Object at the Planet/Brown Dwarf Boundary
Authors: E. Bachelet, Y. Tsapras, Andrew Gould, R. A. Street, David P. Bennett, M. P. G. Hundertmark, V. Bozza, D. M. Bramich, A. Cassan, M. Dominik, K. Horne, S. Mao, A. Saha, J. Wambsganss, Weicheng Zang, Fumio Abe, Richard Barry, David P. Bennett, Aparna Bhattacharya, Ian A. Bond, Akihiko Fukui, Hirosane Fujii, Yuki Hirao, Yoshitaka Itow, Rintaro Kirikawa, Iona Kondo, Naoki Koshimoto, Yutaka Matsubara, Sho Matsumoto, Shota Miyazaki, Yasushi Muraki, Greg Olmschenk, Clément Ranc, Arisa Okamura, Nicholas J. Rattenbury, Yuki Satoh, Takahiro Sumi, Daisuke Suzuki, Stela Ishitani Silva, Taiga Toda, Paul . J. Tristram, Aikaterini Vandorou, Hibiki Yama, Michael D. Albrow, Sun-Ju Chung, Cheongho Han, Kyu-Ha Hwang, Youn Kil Jung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Jennifer C. Yee, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge, Andrzej Udalski, Przemek Mróz, Radosław Poleski, Jan Skowron, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Krzysztof Ulaczyk, Krzysztof A. Rybicki, Patryk Iwanek, Marcin Wrona, Mariusz Gromadzki
Figure caption: Left: CMD of stars located 3′ around the event, from the Gaia EDR3 release (Gaia Collaboration et al. 2020). The blue star is a multiple object containing the source, the lens, and potentially additional blends. Right: proper motion of these stars in galactic coordinates. The blue star indicates the position of the object located at the coordinates of the event, while red and gray points and ellipses indicate the bulge and disk population, respectively.