adsabs/AstroCLIMB huggingface dataset:
Paper: Adaptive Weighted Multi-image Shape from Shading for Precise Topographic Reconstruction at the Lunar South Pole
Authors: Zhen Ye, Jia Qian, Yusheng Xu, Hong Zhang, Tao Tao, Rong Huang, Shijie Liu, Huan Xie, Xiaohua Tong
Figure caption: (a) Differences between the MI-AW-SFS DEM and the LOLA DEM for experimental data set 1. (b) Differences between the MI-AW-SFS DEM and the LOLA DEM for experimental data set 2.
Paper: Adaptive Weighted Multi-image Shape from Shading for Precise Topographic Reconstruction at the Lunar South Pole
Authors: Zhen Ye, Jia Qian, Yusheng Xu, Hong Zhang, Tao Tao, Rong Huang, Shijie Liu, Huan Xie, Xiaohua Tong
Figure caption: The LOLA DEM and the generated MI-AW-SFS DEM for experimental data set 1, with red dashed circles marking the corresponding locations across different DEMs and images.
Paper: Adaptive Weighted Multi-image Shape from Shading for Precise Topographic Reconstruction at the Lunar South Pole
Authors: Zhen Ye, Jia Qian, Yusheng Xu, Hong Zhang, Tao Tao, Rong Huang, Shijie Liu, Huan Xie, Xiaohua Tong
Figure caption: Elevation profile comparison of small craters for experimental data set 2.
Paper: Adaptive Weighted Multi-image Shape from Shading for Precise Topographic Reconstruction at the Lunar South Pole
Authors: Zhen Ye, Jia Qian, Yusheng Xu, Hong Zhang, Tao Tao, Rong Huang, Shijie Liu, Huan Xie, Xiaohua Tong
Figure caption: The LOLA DEM and the generated MI-AW-SFS DEM for experimental data set 2, with yellow dashed circles marking the corresponding locations across different DEMs and images.
Paper: Determining the Methanol Deuteration in the Disk Around V883 Orionis with Laboratory Measured Spectroscopy
Authors: Shaoshan Zeng, Jae-Hong Jeong, Takahiro Oyama, Jeong-Eun Lee, Yao-Lun Yang, Nami Sakai
Figure caption: The D/H ratio determined in water and methanol, inferred from CH2DOH, CH3OD, HDO, and CHD2OH, toward the Class 0 protostar IRAS 16293-2422 B (purple) (M. V. Persson et al. 2013; J. K. Jørgensen et al. 2018), the disk around the Class I/II outbursting star V883 Ori (blue; J. J. Tobin et al. 2023, , and this work), and the comet 67P/C-G (dark brown; M. N. Drozdovskaya et al. 2021). The D/H ratio is corrected by the relation of CH2DOH/CH3OH = 3(D/H) and HDO/H2O = 2(D/H). For the column density of CH2DOH in IRAS 16293-2422 B, the error bar takes into account a factor of two uncertainty assumed from the JPL spectroscopic data. For CH2DOH and CH3OD in 67P/C-G, beige, light brown, brown, and brick red denote deuteration in methyl (−CH3) and hydroxyl(−OH) considering a ﹩\tfrac{{\mathrm{CH}}_{2}\mathrm{DOH}}{{\mathrm{CH}}_{3}\mathrm{OH}}﹩ ratio of 20, 3, 1, and 0.3, respectively.
Paper: Variable Polarization of WR 31a: Binary Companion or Corotating Interaction Region?
Authors: Christiana Erba, Richard Ignace, Faith Simmons, Ben Davies
Figure caption: (a) Models with viewing inclination i = 75° and the longitude of periastron as ϕp = 0°. Panels show (a) Δq with orbital phase t/P, (b) Δu with orbital phase, (c) Δu with Δq, and (d) Δp with orbital phase. Note that Δp shows a triple peak near periastron passage at zero phase. The polarization quantities are in percent and also normalized to τ*. The five curves are for eccentricities e = 0.0, 0.1, 0.2, 0.3, 0.4, and 0.5, shown as orange, green, cyan, red, blue, and violet. (b) As in Figure 3(a), now with ϕp = 130°. Note that Δp shows a double peak near periastron passage at zero phase, with a lower peak preceding a higher one. (c) As in Figure 3(a), now with ϕp = 140°. Note that Δp shows a double peak near periastron passage at zero phase, with roughly equal peaks. (d) As in Figure 3(a), now with ϕp = 150°. Note that Δp shows a double peak near periastron passage at zero phase, with a higher peak preceding a lower one. Model calculations based on J. C. Brown et al. (1982) as described in the text. The different curves are for eccentricities e = 0.0, 0.1, 0.2, 0.3, and 0.4. The inclination is pole-on. Model parameters are described in the individual panel captions.
Paper: Variable Polarization of WR 31a: Binary Companion or Corotating Interaction Region?
Authors: Christiana Erba, Richard Ignace, Faith Simmons, Ben Davies
Figure caption: Independent sinusoidal fits to Δq (upper panel) and Δu (middle panel), assuming a circular orbit. The variations in Δu display a more prominent sinusoidal pattern, so we used its fit to set the period for the fit to Δq. The shading indicates the uncertainty in the period, fit to P = 16.7 ± 0.3 days. Time is represented in days advancing from the first day of observation (JD0). The lower panel shows the resulting model in comparison to the daily weighted means of the data.
Paper: Variable Polarization of WR 31a: Binary Companion or Corotating Interaction Region?
Authors: Christiana Erba, Richard Ignace, Faith Simmons, Ben Davies
Figure caption: q − u diagrams illustrating the time-variable polarization of WR 31a, with filters separated by color (see Table 1). The left panel shows the diagram before the means (Equation (3)) are subtracted; the right panel shows the diagram postmean subtraction (Equation (5)).
Paper: Measuring Interstellar Carbon Abundance via 158 μm [C II] Absorption with SOFIA—A Potential Detection and Proof-of-concept for Depletion Studies with Future Far-IR Facilities
Authors: Christopher J. R. Clark, Julia. C. Roman-Duval, Suzanne C. Madden, Marc Mertens, Claire E. Murray, Jürgen Stutzki, Elizabeth Tarantino, Kirill Tchernyshyov
Figure caption: Plot of predicted peak [C II] absorption opacity, ﹩{\tau }_{\mathrm{[C}\,\mathrm{II]}}^{(\mathrm{peak})}﹩, that would be observed at instrumental velocity resolution, against the integration time required to detect that absorption at S/N = 10. Points are plotted for FIRSST, PRIMA, the Single Aperture Large Telescope for Universe Studies (SALTUS), and Origins proposed FIR telescopes. For each telescope, we plot values corresponding to the 402 diffuse ISM candidate sightlines identified in Section 2.2. Additionally highlighted is the region of parameter space occupied by the three sightlines targeted by our SOFIA-upGREAT study; these values correspond to the predicted/notional values given in Table 1 (as both observed sightlines returned null results, due to instrumental or astrophysical artifacts). We mark the parameter space where observations should be most plausible (as discussed in Section 5). Integration times incorporate any additional time required or sky observations of off positions on either side of the target sightline.
Paper: Measuring Interstellar Carbon Abundance via 158 μm [C II] Absorption with SOFIA—A Potential Detection and Proof-of-concept for Depletion Studies with Future Far-IR Facilities
Authors: Christopher J. R. Clark, Julia. C. Roman-Duval, Suzanne C. Madden, Marc Mertens, Claire E. Murray, Jürgen Stutzki, Elizabeth Tarantino, Kirill Tchernyshyov
Figure caption: SOFIA-upGREAT 157.7 μm spectrum for the Circinus sightline (in blue), binned to 5 km s−1. The SOFIA-upGREAT spectra extend to lower velocities; however, strong atmospheric features dominate the data <−150 km s−1, so we do not plot those velocity ranges here here. For comparison, we also plot the expected level of dust continuum emission from Circinus, based on measured Herschel-PACS 160 μm surface brightness. Also plotted (in red) is a version of the [C II] spectrum that has had a 75 km s−1 median filter applied and subtracted, after which the spectrum was rescaled to the 0.278 K continuum expected from Herschel-PACS 160 μm data. Shown for reference (in black) is the HI4PI H I spectrum, with the Milky Way H I velocity range highlighted; the H I spectrum is plotted with Tb × 0.05, for ease of comparison with the [C II] data. Two high-velocity clouds are also present in the H I spectrum toward Circinus (at ≈+40 and ≈+70 km s−1).
Paper: Measuring Interstellar Carbon Abundance via 158 μm [C II] Absorption with SOFIA—A Potential Detection and Proof-of-concept for Depletion Studies with Future Far-IR Facilities
Authors: Christopher J. R. Clark, Julia. C. Roman-Duval, Suzanne C. Madden, Marc Mertens, Claire E. Murray, Jürgen Stutzki, Elizabeth Tarantino, Kirill Tchernyshyov
Figure caption: Plot of the relationship between size of sky aperture, and median error on predicted value of sky brightness. Solid points show median error when using a range of aperture sizes for our IRAS simulations. The best-fit power law to these points is plotted with the solid line; the dotted line extrapolates this to smaller aperture sizes. The predicted error on sky brightness predictions for 20″ apertures is shown with the hollow diamond point.
Paper: Measuring Interstellar Carbon Abundance via 158 μm [C II] Absorption with SOFIA—A Potential Detection and Proof-of-concept for Depletion Studies with Future Far-IR Facilities
Authors: Christopher J. R. Clark, Julia. C. Roman-Duval, Suzanne C. Madden, Marc Mertens, Claire E. Murray, Jürgen Stutzki, Elizabeth Tarantino, Kirill Tchernyshyov
Figure caption: Illustration of aperture arrangement used in our IRAS simulations of sky estimation and subtraction, for simulated sightline offset 1° away from the true sightline for NGC 1266. The dotted circle indicates the aperture at simulated target position (diameter 1 FWHM) for which we wish to estimate and subtract the emission level. Solid circles indicate the sky apertures, with a set of sky apertures located either side of the target. Each set of sky apertures covers 3 FWHM of sky along the sampling axis. The apertures within each set are spaced with separation of 1/3 FWHM. The 4﹩\mathop{.}\limits^{{\rm{^{\prime} }}}﹩3 FWHM of the IRAS-IRIS 100 μm beam is illustrated by the filled translucent circle in the lower-right corner.
Paper: Measuring Interstellar Carbon Abundance via 158 μm [C II] Absorption with SOFIA—A Potential Detection and Proof-of-concept for Depletion Studies with Future Far-IR Facilities
Authors: Christopher J. R. Clark, Julia. C. Roman-Duval, Suzanne C. Madden, Marc Mertens, Claire E. Murray, Jürgen Stutzki, Elizabeth Tarantino, Kirill Tchernyshyov
Figure caption: Illustration of how we use Gaussian process regression (GPR) to estimate and subtract sky emission levels for target sightlines in our simulations. Measured surface brightnesses are for the example sightline shown in Figure C2. The vertical height of the shaded region shows the 1.4% average error on sky estimation that we find across all sightlines. The width of the shaded region corresponds to the 4﹩\mathop{.}\limits^{{\rm{^{\prime} }}}﹩3 FWHM diameter of the apertures.
Paper: A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection
Authors: Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
Figure caption: For the injection tests, the distribution of quasi-FA detections (188/1000, blue) and injected transits (gray dashed) as a function of their detected or injected periods respectively are plotted as a normalized density. Half of the FA detections have a period between 10 and 15 days, likely due to the 13.7 days downlink cycle. The density of FAs further increases with period, likely due to outlier scatter. We note that the bin size on the x-axis is not uniform.
Paper: A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection
Authors: Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
Figure caption: The 1σ stochastic and systematic noise levels over time are shown for a random selection of light curves from year 2, sector 14. The mean noise term μz (dark purple), the 1σ stochastic noise level ﹩\sqrt{{\mathrm{Cov}}_{{\boldsymbol{s}}}[n,n]}﹩ (light purple), and the 1σ joint stochastic and systemic noise level ﹩\sqrt{{\mathrm{Cov}}_{{\boldsymbol{z}}}[n,n]}﹩ (gray) are overplotted for each light curve. These noise covariance terms are described in Section 2.1. Although the relative contribution of the stochastic and systematic noise varies, they are generally of a similar magnitude. The masking is highly nonuniform between light curves in the same sector. We note that off-diagonal covariance terms are not depicted here; the full covariance of the light curve in the first panel (TID: 237097189) is shown in Figure 8.
Paper: A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection
Authors: Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
Figure caption: The distribution of detections in the TESS data search (Section 3.2) each year over period. As in the injection tests (Figure 13) there is an increase in suspected FA detections for periods P < 20 days, likely due to residual systematic scatter.
Paper: A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection
Authors: Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
Figure caption: Sorted skyline histogram of the relative contribution of individual cadences to the detection statistics (as a normalized density) for all light curves. The x-axis markers indicate the number of individual cadences to the left of each marker, sorted in order of transit detection contribution (density). Separate histograms are plotted for the year 1, 2, and 3 data. The sort order of individual cadences by density differs by year. The red part of the curve indicates the knee cutoff used to mask cadences with anomalous density, and therefore likely unmodeled residual systematic errors. More cadences are filtered in the year 1 and 2 data compared to year 3.
Paper: A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection
Authors: Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
Figure caption: A skyline plot of the mean light curve (blue) here formed as the average over all detrended and masked detection light curves with a period in the range [1, 20] days in the sector 1 data. The vertical dashed gray lines indicate momentum dump events. The purple light curve is proportional to the frequency with which each individual cadence appears in any detected transit. Those cadences marked in red were filtered based on a skyline histogram analysis (Figure 9). Significant uncorrected systematics are visible in the cadence range 16,000–17,500, as evident in both the mean light curve (blue) and filtered cadences (red). However, overall for this period range the density of detections is not attributable to a single systematic source.
Paper: A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection
Authors: Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
Figure caption: Detection counts for the TESS data search tabulated over detected period (P ≤ 19 days and detection test statistic ﹩10\,\leqslant \,T(\hat{{\boldsymbol{y}}})\leqslant 20)﹩) for all 3 yr combined. The overdensity of detections between 1 and 3 days and 11–15 days are very likely FAs due to residual systematic scatter. Both period ranges map directly to mission instrumental cycles, as described in Section 3.1.
Paper: A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection
Authors: Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
Figure caption: The detection rate of the joint detector at a threshold of τ = 10 for transit injection tests with 1000 light curves from year 1, tabulated over orbital period and planet-to-star ratio ﹩{R}_{p}/{R}_{* }﹩. The distribution of simulated transit signal parameters can be found in Table 2. The mean detection rate and quasi-FA rate are RD = 80.0% and RQFA = 19.1%, respectively.
Paper: A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection
Authors: Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
Figure caption: A sample joint-covariance matrix is shown for a light curve. The noise exhibits a diagonal component of positive correlation due to short-term correlated noise described by s, as well as systematic variability described by l. Longer-term correlations are also seen with a 13.7 days blocked structure due to the dominant systematic, the 13.7 days downlink cycle. The dominant systematic is driven by the 13.7 days period orbit of TESS about the Earth. During the orbit the spacecraft experiences thermal changes and varying degrees of scattered light from the Earth and the Moon.
Paper: A Search for Exoplanet Candidates in TESS 2 minute Light Curves Using Joint Bayesian Detection
Authors: Jamila S. Taaki, Athol J. Kemball, Farzad Kamalabadi
Figure caption: Injection test detection rate vs. quasi-FA rate over detection threshold τ (right color wedge) for the joint and standard reference detection algorithms. The two methods are comparable in performance, showing only a marginal improvement in detection power for the joint method.
Paper: Additive Attention for Vetting Transiting Exoplanet Candidates
Authors: Àlvar Hernàndez-Carnerero, Miquel Sànchez-Marrè, Juan Carlos Morales
Figure caption: Visualization of attention weights learned by the Optimized with Attention model for each data point in the secondary view from the TESS data set. Attention weights are depicted using a blue line. The average of light-curve views from the test set is shown with a green line, with standard deviation represented by shaded areas around the mean. This visualization is separately displayed for (a) true positive, (b) false negative, (c) true negative, and (d) false positive groups of test instances.
Paper: Additive Attention for Vetting Transiting Exoplanet Candidates
Authors: Àlvar Hernàndez-Carnerero, Miquel Sànchez-Marrè, Juan Carlos Morales
Figure caption: Scatter plot of the instances across orbital period and transit depth for the Kepler data set, presented in a log−log scale. Data points are categorized into true positives, false negatives, true negatives, and false positives. The top and right marginal panels show normalized histograms (area = 1 for each category) along each axis. Each marginal panel contains two histograms: one for the true negative and false positive categories and another for the true positive and false negative categories.
Paper: Additive Attention for Vetting Transiting Exoplanet Candidates
Authors: Àlvar Hernàndez-Carnerero, Miquel Sànchez-Marrè, Juan Carlos Morales
Figure caption: Scatter plot of the instances across orbital period and transit depth for the TESS data set, presented in a log−log scale. Data points are categorized into true positives, false negatives, true negatives, and false positives. The top and right marginal panels show normalized histograms (area = 1 for each category) along each axis. Each marginal panel contains two histograms: one for the true negative and false negative categories and another for the true positive and false positive categories.
Paper: Additive Attention for Vetting Transiting Exoplanet Candidates
Authors: Àlvar Hernàndez-Carnerero, Miquel Sànchez-Marrè, Juan Carlos Morales
Figure caption: Visualization of attention weights learned by the Optimized with Attention model for each data point in the local view from the TESS data set. Attention weights are depicted using a blue line. The average of light-curve views from the test set is shown with a green line, with standard deviation represented by shaded areas around the mean. This visualization is separately displayed for (a) true positive, (b) false negative, (c) true negative, and (d) false positive groups of test instances.
Paper: Additive Attention for Vetting Transiting Exoplanet Candidates
Authors: Àlvar Hernàndez-Carnerero, Miquel Sànchez-Marrè, Juan Carlos Morales
Figure caption: Visualization of attention weights learned by the Optimized with Attention model for each data point in the global view from the TESS data set. Attention weights are depicted using a blue line. The average of light-curve views from the test set is shown with a green line, with standard deviation represented by shaded areas around the mean. This visualization is separately displayed for (a) true positive, (b) false negative, (c) true negative, and (d) false positive groups of test instances.
Paper: Determining the Methanol Deuteration in the Disk Around V883 Orionis with Laboratory Measured Spectroscopy
Authors: Shaoshan Zeng, Jae-Hong Jeong, Takahiro Oyama, Jeong-Eun Lee, Yao-Lun Yang, Nami Sakai
Figure caption: Derived CH2DOH column density by using different detected transitions at various frequency ranges between 216 and 264 GHz in V883 Ori. The frequency ranges are set by roughly mimicking the spectral windows which are typically used in observation setup (e.g., F. Fontani et al. 2015; E. Bianchi et al. 2017; J. Ospina-Zamudio et al. 2019). The number in each bracket indicate the number of transitions included in the corresponding frequency range. Results employed SUMIRE and JPL spectroscopic data are indicated in purple and brown respectively. The dash line denotes the CH2DOH column density derived by including all available transitions and the shaded area denotes the associated uncertainty.
Paper: Determining the Methanol Deuteration in the Disk Around V883 Orionis with Laboratory Measured Spectroscopy
Authors: Shaoshan Zeng, Jae-Hong Jeong, Takahiro Oyama, Jeong-Eun Lee, Yao-Lun Yang, Nami Sakai
Figure caption: Unblended and optically thin (τ ≤ 0.3) transitions of CH2DOH detected in V883 Ori. The observed spectra are plotted as gray histograms in the order of increasing frequency. Assuming the same excitation temperature (Tex = 120 K), radial velocity (νLSR), linewidth (FWHM = 3.0 km s−1), and beam-filling factor (0﹩\mathop{.}\limits^{\unicode{x02033}}﹩384), the result of the best LTE fit using spectroscopic data from JPL and SUMIRE is shown in gray dashed line and red line respectively. The overall fitting i.e., by including the contribution from all other molecular species detected in V883 Ori in J.-H. Jeong et al. (2025), is in the purple dashed line (JPL) and purple line (SUMIRE). The quantum numbers and value of Eup of each transition are listed on the upper part of each panel.
Paper: Adaptive Weighted Multi-image Shape from Shading for Precise Topographic Reconstruction at the Lunar South Pole
Authors: Zhen Ye, Jia Qian, Yusheng Xu, Hong Zhang, Tao Tao, Rong Huang, Shijie Liu, Huan Xie, Xiaohua Tong
Figure caption: Comparison of hillshade images generated from different DEMs. Panels (a) and (b) show the hillshade image from the SI-SFS and SI-SFS+ASW DEMs using the Sun illumination direction, respectively. Panels (c) and (d) show the hillshade image from the SI-SFS and SI-SFS+ASW DEMs using the cross-Sun direction, respectively. Panels (e) and (f) show the hillshade image from the MI-SFS and MI-SFS+ASW DEMs using the Sun illumination direction, respectively. Panels (g) and (h) show the hillshade image from the MI-SFS and MI-SFS+ASW DEMs using the cross-Sun direction, respectively.
Paper: Adaptive Weighted Multi-image Shape from Shading for Precise Topographic Reconstruction at the Lunar South Pole
Authors: Zhen Ye, Jia Qian, Yusheng Xu, Hong Zhang, Tao Tao, Rong Huang, Shijie Liu, Huan Xie, Xiaohua Tong
Figure caption: The photogrammetric DEM and the generated MI-AW-SFS DEM, with red dashed circles marking the corresponding locations across different DEMs and images.
Paper: Determining the Methanol Deuteration in the Disk Around V883 Orionis with Laboratory Measured Spectroscopy
Authors: Shaoshan Zeng, Jae-Hong Jeong, Takahiro Oyama, Jeong-Eun Lee, Yao-Lun Yang, Nami Sakai
Figure caption: Unblended and optically thin transitions of CH3OD detected in V883 Ori. The observed spectra are plotted as gray histograms in the order of increasing frequency. The best LTE fit by fixing Tex = 120 K is shown in red line and the overall fitting, i.e., by including the contribution from all other molecular species detected in V883 Ori in J.-H. Jeong et al. (2025), is in purple line. The quantum numbers and value of Eu of each transitions are listed on the upper part of each panel.
Paper: Adaptive Weighted Multi-image Shape from Shading for Precise Topographic Reconstruction at the Lunar South Pole
Authors: Zhen Ye, Jia Qian, Yusheng Xu, Hong Zhang, Tao Tao, Rong Huang, Shijie Liu, Huan Xie, Xiaohua Tong
Figure caption: Surface roughness maps for the MI-AW-SFS DEM (panels (a) and (c)) and LOLA DEM (panels (b) and (d)) for experimental data sets 1 and 2.