adsabs/AstroCLIMB huggingface dataset:
Paper: Structural Parameters of the Thin Disk Population from Evolved Stars in the Solar Neighborhood
Authors: Sedanur İyisan, Selçuk Bilir, Özgecan Önal Taş, Olcay Plevne
Figure caption: The positions of the PARSEC mass tracks of main-sequence stars of different masses on the CMD. The curves with different colors indicate different masses, and the dashed lines indicate the region where the evolved stars studied were located.
Paper: Structural Parameters of the Thin Disk Population from Evolved Stars in the Solar Neighborhood
Authors: Sedanur İyisan, Selçuk Bilir, Özgecan Önal Taş, Olcay Plevne
Figure caption: The variation in scale heights calculated for evolved stars concerning their absolute magnitudes across both Galactic hemispheres.
Paper: Structural Parameters of the Thin Disk Population from Evolved Stars in the Solar Neighborhood
Authors: Sedanur İyisan, Selçuk Bilir, Özgecan Önal Taş, Olcay Plevne
Figure caption: Spatial distributions of 671,600 evolved stars whose astrometric data were precisely selected from the Gaia DR3 catalog: Z × X (upper panel) and Y × X (bottom panel). The color scale indicates the density of the star count.
Paper: Structural Parameters of the Thin Disk Population from Evolved Stars in the Solar Neighborhood
Authors: Sedanur İyisan, Selçuk Bilir, Özgecan Önal Taş, Olcay Plevne
Figure caption: Heliocentric celestial sphere separated into 36-star fields based on the Galactic coordinates of evolved stars: (a) 0∘ < l ≤ 180∘ and (b) 180∘ < l ≤ 360∘.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Seeing variability of highly elongated stars in MUSE observations of 2I/Borisov on 2019 December 31. Stars A + B, as shown in the top two panels, are the calibration stars used by starkiller in this reduction, followed by their best-fitting Gaussian and data PSFs. The stars are highly elongated, with a fitted streak length of 98 spaxels. Over the course of this 600 s exposure, the star trails exhibit a nonuniform brightness profile along their major axis, which causes the stars to be poorly represented by a simple elongated Moffat or Gaussian profile. The bottom panel shows the normalized cross section along the major axis for stars A + B (blue and green solid lines, respectively), the best-fitting Gaussian PSF (red dashed–dotted line), and the data PSF (orange dashed line). The data PSF is able to capture some of the subtle structure imposed on the PSF from seeing variability, which leads to better subtractions.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Example of the three PSF models—Moffat, Gaussian, and data (top row)—alongside two field stars in a 2I/Borisov data cube observed on 2020 March 19 (left column), and their respective residuals (center). While each PSF appears similar, the subtle differences become clear in the fit residuals. Neither the Moffat or Gaussian profiles provide a reliable representations of the stars in this data cube, or in most other streaked MUSE data cubes. However, the data PSF is a much closer match, lacking the poor subtraction patterns of the Moffat and Gaussian. We attribute the complex PSF that significantly varies along the streak to atmospheric scintillation throughout the 600 s exposure. starkiller will begin modeling the PSF as either Gaussian or Moffat; however, if the initial model is significantly different from the data PSF, the data PSF is then used exclusively in spectra extraction and scene generation.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Left: reduced MUSE data cube at 7000 Å of 2I/Borisov at b = 26° on 2020 March 19, with position-corrected Gaia Data Release 3 (DR3) stars shown as orange stars. Middle: scene constructed by starkiller on Gaia-listed stars in the FOV. Right: the scene-subtracted cube at 7000 Å. Subtraction quality varies between sources, influenced primarily by the closeness of the model spectra and crowding. Sources that are not present in the Gaia DR3 catalog are not subtracted, and are therefore present unaltered in the subtracted scene.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Example spectral model match to two stellar spectra extracted from the trailed MUSE data cube in Figure 1. The MUSE spectra is shown by the solid blue line, and the best-fitting model's stellar spectra, which has been independently flux scaled by Gaia G-band photometry, is shown as an orange dashed line. The best-matching model is taken to be the model with the highest Pearson correlation coefficient (r), from a grid of spectra subject to a range of extinction values. An additional flux correction, discussed in Section 3.6, is also applied. The residuals of the model fits are shown in the lower panels.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Example spectral model match to two stellar spectra extracted from the MUSE data cube in Figure 10. The MUSE spectra is shown by the solid blue line, and the best-fitting model's stellar spectra, which has been independently flux scaled by Gaia G-band photometry, is shown as an orange dashed line (the same as in Figure 6). Both of these sources are from within the nebula. The spectral extraction and modeling is robust to narrow features from external emission, or instrument noise, resulting in high model correlations.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Doppler fits for Gaia 5856950561179332352 in the MUSE data cube of 2I/Borisov on 2020 March 19. starkiller provides a rough relative velocity for stars with spectral types A–K by fitting Gaussian models to prominent absorption lines in stellar spectra: Hβ, Hα, Na D, and the Ca II triplet. Each line in the Ca II triplet is modeled independently, and labeled as a, b, and c in increasing wavelength. In this example, the error-weighted average velocity is −46 ± 2 km s−1.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Ratio of the best-fitting stellar models through the ck+ method to the MUSE spectra for each of the calibration sources from the IFU. As each model spectrum is scaled by the catalog, in this case Gaia DR3 magnitudes, any differences between the models can be a result of poor template matching, or variations in flux calibration. Common trends that are present between the models (purple line) for the calibration sources are used to create a flux correction (orange dotted line). Every model spectrum is divided by the flux correction, to bring them into greater alignment with the observed spectra. As all variations occur close to 1, we can see that the flux calibration between Gaia and MUSE is consistent.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Comparison of the Gaia DR3 star position using the MUSE WCS (blue crosses), and the starkiller corrected positions (orange stars). Through the starkiller reduction process sources are realigned assuming a linear offset, plus rotation. In all instances sources are aligned to be at the center of their corresponding streaks. The alignment method used by starkiller has proven to be robust to source elongation and crowding.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Distribution of differences between the synthetic G-band AB magnitudes (GSyn) and the observed G-band Vega magnitudes (GObs) for DA white dwarf calibrators. The offset between the two magnitudes is primarily due to the differences in magnitude systems. There is also a small calibration offset, which is described in T. Axelrod et al. (2023).
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: The results of our second injection-recovery test. A planetary signal with a semi-amplitude 1 m s−1, period 28.5 days, and eccentricity 0.1 was injected into the raw MAROON-X RV data. The upper panel of this figure shows the GLS periodograms calculated for the residuals of the MAROON-X data after removing the contribution from the known eccentric planet. The bottom panel shows the phase-folded curve for the recovered planetary signal after performing a two-Keplerian fit with the offsets from Table 3.
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: The results of our first injection-recovery test. A planetary signal with a semi-amplitude 1 m s−1, period 9.5 days, and eccentricity 0.1 was injected into the raw MAROON-X RV data. The upper panel of this figure shows the GLS periodograms calculated for the residuals of the MAROON-X data after removing the contribution from the known eccentric planet. The bottom panel shows the phase-folded curve for the recovered planetary signal after performing a two-Keplerian fit with the offsets from Table 3.
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: Completeness plots for the HD 3651residuals. The left panel shows the completeness for the blue data, the middle panel shows the completeness for the red data, and the right panel shows completeness for the combined residuals.
Paper: Potential Subsurface Lava Tube Skylight on the Western Flank of Elysium Mons, Mars
Authors: Ravi Sharma, Chunyu Ding, Yan Su, Zhonghan Lei, Changzhi Jiang, Jiangwan Xu, YuXiao Zhi, Zihang Liang, Jiawei Li, Xiaohang Qiu, Haoyu Chen, S. N. A. Jaaffrey
Figure caption: Conceptual model illustrating the thermal and geological dynamics of a subsurface cavity on Mars, highlighting heat exchange processes and potential habitability. Surface heat transfer (Limiting Factor 1) is influenced by material properties, grain size, thermal conductivity, and thermal inertia, while subsurface heat retention (Limiting Factor 2) is governed by presence of subsurface materials, heat conduction, thermal depth penetration, volatiles, air circulation (AC), and emission through the skylight. Stratified geological layers (A–F) represent distinct deposition periods, preserving a record of Martian climatic and geological history. The cavity’s thermal environment is shaped by warm air trapped at higher elevations, cold air settling near the floor, and the presence of volatiles, such as water-equivalent hydrogen (H2O), which influence heat capacity and thermal dynamics. These processes underscore the potential of such cavities as exploration targets, offering insights into Martian volcanic and hydrological processes, resource availability, and the stability of subsurface environments for future missions.
Paper: Potential Subsurface Lava Tube Skylight on the Western Flank of Elysium Mons, Mars
Authors: Ravi Sharma, Chunyu Ding, Yan Su, Zhonghan Lei, Changzhi Jiang, Jiangwan Xu, YuXiao Zhi, Zihang Liang, Jiawei Li, Xiaohang Qiu, Haoyu Chen, S. N. A. Jaaffrey
Figure caption: Identification of a potential cave entrance within the PCC on the western flank of Elysium Mons using HiRISE imagery and DN value classification. (a) HiRISE image: ESP_042629_2090_RED highlights shadowed regions indicative of significant depth, with an arrow marking the potential cave entrance location. (b) DN value map from ESP_042629_2090_RED showing low DN zones (0–5 and 5–10) with distinct curved and linear patterns, with the potential entrance area indicated by an arrow. (c) HiRISE image: ESP_063477_2090_RED provides an additional view of the PCC, confirming shadowed regions consistent with subsurface voids, with the entrance location marked. (d) DN value map from ESP_063477_2090_RED reinforces the detection of organized low DN features, with the arrow pointing to a coherent linear pattern that strongly suggests a potential cave entrance. These findings emphasize the structural collapse of a skylight, marking it as a prime target for future subsurface exploration.
Paper: Potential Subsurface Lava Tube Skylight on the Western Flank of Elysium Mons, Mars
Authors: Ravi Sharma, Chunyu Ding, Yan Su, Zhonghan Lei, Changzhi Jiang, Jiangwan Xu, YuXiao Zhi, Zihang Liang, Jiawei Li, Xiaohang Qiu, Haoyu Chen, S. N. A. Jaaffrey
Figure caption: Thermal behavior of the PCC and surrounding terrain analyzed using IRPBT data from THEMIS, observed at different times of the Martian day during the summer season. (a) CTX image (M. C. Malin et al. 2007) providing morphological context; (b) i62531007PBT image (P. Christensen et al. 2002b, 2002c; P. R. Christensen et al. 2004) afternoon (∼2:03 pm) showing uniform temperature distribution; (c) i63298019PBT image (P. Christensen et al. 2002b, 2002c; P. R. Christensen et al. 2004) evening (∼6:52 pm) indicating initial thermal retention at the PCC; (d) i79701006PBT image (P. Christensen et al. 2002b, 2002c; P. R. Christensen et al. 2004) night (∼10:25 pm) displaying significant thermal anomaly at the PCC; (e) i55773011PBT image (P. Christensen et al. 2002b, 2002c; P. R. Christensen et al. 2004) midnight (∼3:39 am) showing maximum heat retention at the PCC; (f) i63292003PBT image (P. Christensen et al. 2002b, 2002c; P. R. Christensen et al. 2004) early morning (∼6:18 am) exhibiting comparable thermal patterns to the surrounding terrain. These observations highlight the PCC’s prolonged heat retention, suggesting an insulating subsurface void.
Paper: Potential Subsurface Lava Tube Skylight on the Western Flank of Elysium Mons, Mars
Authors: Ravi Sharma, Chunyu Ding, Yan Su, Zhonghan Lei, Changzhi Jiang, Jiangwan Xu, YuXiao Zhi, Zihang Liang, Jiawei Li, Xiaohang Qiu, Haoyu Chen, S. N. A. Jaaffrey
Figure caption: Contextual map of the study area on the western flank of Elysium Mons, highlighting the associated pit chain, and the PCC (small red arrow). The map illustrates partially collapsed pit chains and their spatial alignment, which are typical surface expressions of sequential collapses but lack thermal anomalies indicative of subsurface voids, as confirmed in Figure 6. The long red arrow extending westward indicates the inferred direction of subsurface volcanic flow, suggesting potential subsurface connectivity. This interpretation is based on CTX imagery and MOLA elevation data (D. E. Smith et al. 2001; D. Smith et al. 2003), providing critical geological context for the identified subsurface features.
Paper: Potential Subsurface Lava Tube Skylight on the Western Flank of Elysium Mons, Mars
Authors: Ravi Sharma, Chunyu Ding, Yan Su, Zhonghan Lei, Changzhi Jiang, Jiangwan Xu, YuXiao Zhi, Zihang Liang, Jiawei Li, Xiaohang Qiu, Haoyu Chen, S. N. A. Jaaffrey
Figure caption: CTX images (M. C. Malin et al. 2007) from different Sun incidence angles of the Special Pit candidate studied on the western flank of the Elysium Mons. The respective details of the images are tabulated in Table 1.
Paper: Potential Subsurface Lava Tube Skylight on the Western Flank of Elysium Mons, Mars
Authors: Ravi Sharma, Chunyu Ding, Yan Su, Zhonghan Lei, Changzhi Jiang, Jiangwan Xu, YuXiao Zhi, Zihang Liang, Jiawei Li, Xiaohang Qiu, Haoyu Chen, S. N. A. Jaaffrey
Figure caption: Diurnal temperature variations at the PCC during the Martian summer season. Based on THEMIS IRPBT data used in this study (P. Christensen et al. 2002b, 2002c; P. R. Christensen et al. 2004). The maximum temperature at the PCC (TmaxC, red circles), the minimum temperature in the surrounding surface region (TminS, blue circles), and the maximum temperature at nearby pit chains excluding the PCC (TmaxP, yellow triangles) are plotted across different times of day-afternoon, evening, night, midnight, and early morning. Solar longitude (Ls) values provide the seasonal context. The PCC exhibits notable thermal anomalies, maintaining higher temperatures compared to both the surrounding terrain and nearby pit chains, highlighting its distinct thermal behavior and subsurface implications.
Paper: What if we Find Nothing? Bayesian Analysis of the Statistical Information of Null Results in Future Exoplanet Habitability and Biosignature Surveys
Authors: Daniel Angerhausen, Amedeo Balbi, Andjelka B. Kovačević, Emily O. Garvin, Sascha P. Quanz
Figure caption: Final results for the case of a null-result survey of “perfect” observations. Left: best fit from Bayesian analysis for the fraction ηobs as a function of the number N of nondetections. The frequentist best fit corresponds to ﹩{\hat{\eta }}_{\mathrm{MLE}}=0﹩, and hence can not be represented in this plot. Right: 99.9% upper limits derived from the credible intervals of the posteriors for the different prior beliefs. Here we also compare Bayesian to Frequentist uncertainty assessments, by including both an exact binomial confidence interval, as well as a Wilson confidence interval based on a normal approximation. In order to exclude scenarios with ηobs > 0.2 and 0.1 with 99% belief, we would need more than ∼40 or 80 individual, “perfect” observations, respectively. As expected and discussed in Section 2.2, the “optimistic” priors produce posteriors with higher values, whereas the “pessimistic” priors are at the lower end of the spectrum.
Paper: What if we Find Nothing? Bayesian Analysis of the Statistical Information of Null Results in Future Exoplanet Habitability and Biosignature Surveys
Authors: Daniel Angerhausen, Amedeo Balbi, Andjelka B. Kovačević, Emily O. Garvin, Sascha P. Quanz
Figure caption: Testing different levels of “imperfect” individual observations, modeled as a sample (top) and interpretation uncertainty (bottom). Showing the difference between assuming “perfect” individual observations (solid line) and more realistic results with various levels of sample and interpretation uncertainty. For clarity we show only the calculations using the Jeffrey’s prior, as it seems to represent a good compromise between all the priors in the first general analysis (see, e.g., Figure 2).
Paper: What if we Find Nothing? Bayesian Analysis of the Statistical Information of Null Results in Future Exoplanet Habitability and Biosignature Surveys
Authors: Daniel Angerhausen, Amedeo Balbi, Andjelka B. Kovačević, Emily O. Garvin, Sascha P. Quanz
Figure caption: Comparison of the various priors used in this study. While the Bayes–Laplace (“flat”) prior might seem “uninformative” when plotted in linear space, the logarithmic scale shows how it “optimistically” puts a lot of weight in values of ηobs ∼ 1. This might not be the best choice for astrobiological questions, if one assumes that processes are either extremely rare or very frequent. Therefore we also chose more “neutral” priors such as the Jeffreys or Kerman ones, and also one extremely “pessimistic” one, giving more weight to ηobs ≈ 0.
Paper: SDSS J100711.74+193056.2: A Candidate Common Motion Substellar Companion to the Nearest B-type Star Regulus
Authors: Eric E. Mamajek, Adam J. Burgasser
Figure caption: Top: Keck/NIRES spectrum of SDSS J100711.74+193056.2 (gray line shows full-resolution, black lines shows smoothed spectrum with λ/Δλ = 100) compared to the low-resolution spectrum of the L9 near-infrared standard DENIS J025503.3-470049 (magenta line; data from A. J. Burgasser et al. 2006). Regions of strong telluric absorption masked out in the data are indicated by vertical gray bands. The inset box shows a close-up of the 1.2432 and 1.2522 μm K I doublet with equivalent NIRES data for DENIS J025503.3-470049 from C. A. Theissen et al. (2022). Below this is the difference spectrum between SDSS J100711.74+193056.2 and DENIS J025503.3-470049 compared to the measured spectral uncertainty (horizontal gray band). Bottom left: smoothed and absolute flux-calibrated NIRES spectrum of SDSS J1007+1930 (black line) compared to the best-fit SAND model (magenta line, parameters in legend and main text), with residuals shown in the bottom panel. Bottom righ): best-fit forward model (magenta line) of the 2.27–2.39 μm NIRES spectrum (black line), showing contributions from telluric (green line) and stellar models (blue line), with residuals (black line) shown at the bottom.
Paper: A First Taste of MEAD (Measuring Extinction and Abundances of Dust). I. Diffuse Milky Way Interstellar Dust Extinction Features in JWST Infrared Spectra
Authors: Marjorie Decleir, Karl D. Gordon, Karl A. Misselt, Burcu Günay, Julia Roman-Duval, Sascha T. Zeegers
Figure caption: Silicate feature peak optical depth compared to the column densities of Mg, Fe, and O in dust, taken from A. M. Ritchey et al. (2023; or E. B. Jenkins 2009). The black line is a fit to the black data points, with its equation given in the top right corner of each panel. The colored lines correspond to different dust grain models for A(V)s between 1.2 and 2.5.
Paper: Eighteen Exoplanet Host Stars from the NPOI Data Archive
Authors: Ellyn K. Baines, Jeremy Jones, James H. Clark, Henrique R. Schmitt, Jordan M. Stone
Figure caption: Comparing the stellar radius (left panel) and effective temperature (right panel) from EPE with those determined from NPOI measurements. The dotted lines show the 1:1 ratio, and the solid red lines are the linear fits of f(x) = 1.020x − 0.003 and f(x) = 0.845x − 834.34 for the radius and effective temperature, respectively. The bottom parts of each plot show the residuals to the 1:1 ratio line.
Paper: Eighteen Exoplanet Host Stars from the NPOI Data Archive
Authors: Ellyn K. Baines, Jeremy Jones, James H. Clark, Henrique R. Schmitt, Jordan M. Stone
Figure caption: A color–magnitude diagram of the exoplanet host stars presented here (red squares), past NPOI targets (large black circles), and targets from JSDC (L. Bourgés et al. 2014; small black points) that fall within the limits of the NPOI observable range of decl. north of −10 deg and brighter than V = 6.0.
Paper: Kinematics of Cataclysmic Variables in the Solar Neighborhood in the Gaia Era
Authors: Remziye Canbay, Tansel AK, Selçuk Bilir, Faruk Soydugan, Zeki Eker
Figure caption: U–V and W–V diagrams of CV groups according to their total space velocity errors Serr (a and b), and U–V and W–V diagrams of magnetic (polars: P, and intermediate polars: IP) and nonmagnetic systems in the sample of 432 CVs (c and d).
Paper: Kinematics of Cataclysmic Variables in the Solar Neighborhood in the Gaia Era
Authors: Remziye Canbay, Tansel AK, Selçuk Bilir, Faruk Soydugan, Zeki Eker
Figure caption: (a) Comparison of systemic velocities measured from emission (γems) and absorption (γabs) lines for 44 CVs in the sample. Solid black lines and blue dotted lines represent the linear fit and 1σ limits, respectively. The solid red line in the upper panel is the one-to-one line. (b) Distribution of velocity differences. Red and black lines show zero level and mean value of velocity differences, respectively.