adsabs/AstroCLIMB huggingface dataset:
Paper: A Detailed Chemical Analysis of the Red Giant Orbiting Gaia BH3: From Lithium to Thorium 
Authors: Zoe Hackshaw, Keith Hawkins, Catherine Manea
Figure caption: Similar to the middle panel of Figure 8, we show the observed spectrum of BH3⋆ in black points with a synthetic spectrum fit to [Th/Fe] = 0.25 (pink) and a ±0.1 dex region around our fit (purple). A Th abundance of [Th/Fe]= −∞ is shown with the blue dashed line. We then fix an age of 13.4 Gyr and the H. Schatz et al. (2002) production ratio to solve for the [Th/Fe] needed, resulting in [Th/Fe] = 1.14 (green). We show that the Th abundance found using the probable age and production ratio cannot conceivably fit our observed data.
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: Comparisons between our “injected” star formation histories and “recovered” star formation histories in the two mock galaxies described in Section 5.1. (Left) Density maps for the observed, best-fit, and residual CMDs, expressed in units of Poisson standard deviations. (Middle) Cumulative stellar mass formed as a function of time. (Right) Total star formation rate as a function of time. These tests illustrate our ability to self-consistently recover SFHs from AGB stars.
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: Spatial map of AGB stars from our UKIRT data over the entire region of M31 covered by our data. The PHAT footprint is overlaid in black and includes data out to a deprojected distance of d ≲ 20 kpc in the northeastern quadrant of M31. We excluded data inside a deprojected distance of d = 11 kpc, denoted by the shaded gray hatched ellipse, to avoid the crowded and reddened inner regions of M31’s disk that significantly affect the optical CMD.
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: COLIBRI isochrones of the asymptotic giant branch with a constant age of 1 Gyr and a range of metallicities. Metallicity has a modest effect on AGB star positions in an NIR CMD compared to age.
Paper: Probing Proton versus Electron Heating and Energization during Magnetic Reconnection
Authors: Zhiyu Yin, 志宇 尹, J. F. Drake, M. Swisdak
Figure caption: Early phase evolution of particle temperatures during magnetic reconnection for the simulation in Figure 1. In (a) and (b), the spacetime evolution of the parallel electron and proton temperatures, respectively, along the center of the current sheet. Panel (c) shows cuts of the parallel temperature of protons (blue) and electrons (orange) along the center of the current sheet at t = 2.5 τA. The red dashed line marks the initial temperature.
Paper: Probing Proton versus Electron Heating and Energization during Magnetic Reconnection
Authors: Zhiyu Yin, 志宇 尹, J. F. Drake, M. Swisdak
Figure caption: Energy spectra of electrons and protons from four simulations with different initial electron-to-proton temperature ratios. The initial proton temperature is held constant, while the initial electron temperature is varied as Te(initial) = 0.5Ti(initial), Te(initial) = Ti(initial), Te(initial) = 2Ti(initial), and Te(initial) = 5Ti(initial), as indicated in each panel. The energy spectra are computed at a late time, after the formation of a dominant magnetic island in the current sheet, by summing particles across the entire simulation domain. Dashed lines represent initial spectra, while solid lines indicate late-time spectra for protons (blue) and electrons (orange). At a late time, the spectral indices with the various initial electron temperatures differ only slightly from the equal temperature simulation. The power-law slopes of the proton spectra in these settings range from −4.0 to −3.6, whereas those of the electron spectra range from −3.2 to −3.0
Paper: Probing Proton versus Electron Heating and Energization during Magnetic Reconnection
Authors: Zhiyu Yin, 志宇 尹, J. F. Drake, M. Swisdak
Figure caption: Spacetime diagrams of particle temperature along the center of the current sheet for different initial electron-to-proton temperature ratios. Panels (a)–(d) show the evolution of electron temperature, while panels (e)–(h) display the corresponding proton temperature. The horizontal axis is the position X/L0 along the current sheet, and the vertical axis shows time t/τA of the cut. The color scale indicates normalized temperature, with redder regions corresponding to higher temperatures. From top to bottom, each row corresponds to a different initial temperature ratio: Te(initial)/Ti(initial) = 1, 0.5, 2, and 5, respectively. The results show how both electron and proton heating profiles vary with the initial electron temperature. Higher initial electron temperatures yield stronger electron heating and reduced proton heating.
Paper: Probing Proton versus Electron Heating and Energization during Magnetic Reconnection
Authors: Zhiyu Yin, 志宇 尹, J. F. Drake, M. Swisdak
Figure caption: Temperature evolution and late-time profile for a simulation with Te(initial) = Ti(initial) and mi/me = 25. Panels (a) and (b) show the spacetime diagrams of the parallel electron and proton temperatures, respectively, along the center of the current sheet. The horizontal axis represents position X/L0, and the vertical axis shows time normalized to the Alfvén time τA. The color scale indicates normalized temperature, with redder regions corresponding to higher temperatures. Panel (c) presents a late-time 1D cut through the center of the current sheet, showing parallel electron temperature Te (orange) and proton temperature Ti (blue). The red dashed line marks the initial temperature for both species, ﹩{T}_{0}=0.0625{m}_{i}{C}_{A0}^{2}﹩.
Paper: Probing Proton versus Electron Heating and Energization during Magnetic Reconnection
Authors: Zhiyu Yin, 志宇 尹, J. F. Drake, M. Swisdak
Figure caption: Parallel electron temperature profiles at the current sheet at t = 2.2 τA for three different mass ratios: mi/me = 25 (orange), mi/me = 100 (green), and mi/me = 400 (blue), with the ion mass mi held constant in all simulations. The red dashed line denotes the initial electron temperature, ﹩{T}_{e0}=0.0625\,{m}_{i}{C}_{A0}^{2}﹩. The horizontal axis is the spatial coordinate x, normalized to the characteristic length scale L0. Results show that heavier electrons (i.e., lower mass ratios) gain more energy than lower mass electrons during their initial injection into reconnection exhausts, consistent with Fermi reflection scaling, where energy gain is proportional to the square root of the electron mass (see Equation (2)).
Paper: Molecular Gas and Star Formation in Dwarf Galaxies Observed by the Atacama Large Millimeter/submillimeter Array
Authors: Kijeong Yim, Soo-Chang Rey
Figure caption: NIR images used to trace stellar mass distributions. For NGC 5692, the WISE 3.4 μm image is shown, while Spitzer IRAC 3.6 μm images are displayed for all other galaxies. The contours represent regions of significant stellar emission, beginning at approximately 15σ. The point-spread function of the images is marked by the ellipse in the lower-right corner of each panel, illustrating the differences in spatial resolution between the WISE (7﹩\mathop{.}\limits^{^{\prime\prime} }﹩5) and Spitzer (1﹩\mathop{.}\limits^{\unicode{x02033}}﹩6) images.
Paper: Molecular Gas and Star Formation in Dwarf Galaxies Observed by the Atacama Large Millimeter/submillimeter Array
Authors: Kijeong Yim, Soo-Chang Rey
Figure caption: CO integrated intensity maps for the dwarf galaxies in our sample. Contour levels begin at approximately 5σ to clearly delineate reliable molecular gas detections. The synthesized beam size is indicated by the ellipse in the lower-right corner of each panel.
Paper: Probing Proton versus Electron Heating and Energization during Magnetic Reconnection
Authors: Zhiyu Yin, 志宇 尹, J. F. Drake, M. Swisdak
Figure caption: Time evolution of the energy spectra of electrons (dashed lines) and protons (solid lines) during the simulation with equal initial temperatures. The initial spectrum (proton/electron) is shown as a black solid line. Subsequent spectra are plotted at t/τA = 2, 3, 6, and 18. A black dashed line with a slope of −3.6 matches the slope of the late-time proton spectrum. The late-time power-law index of the electrons is around −3.2.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: Denoising results using filters of different sizes. From left to right, the images show: the original noisy images; images denoised using Gaussian filtering (σ = 1 and 2); images denoised with CAE filters of sizes 3 × 3, 5 × 5, and 7 × 7; and images denoised using only a single convolutional layer. The denoising performance of the 5 × 5 and 7 × 7 filter sizes is quite similar; however, some small and faint structures in galaxies may be overlooked when using the 7 × 7 filter, as indicated by the arrows. The white bar in the first panel indicates an angular scale of 1″ (≈33 pixels).
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: Denoising results obtained with different configurations. The first column shows raw images of five randomly selected galaxies; the second column shows the denoising results with the configuration used in this manuscript (hidden dim = 40); the third column shows the denoising results when the hidden dimension is reduced to 16; the fourth column shows the denoising results when 15 more training epochs are added; the fifth column shows the denoising results when using the binary cross-entropy loss function.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: Left: distribution of mean pixel value differences for galaxy images before and after 90° rotation, comparing cases with (blue) and without (gray) APCT. Each value represents the per-galaxy average of absolute differences ∣ΔI(x, y)∣ across all pixel positions. APCT results in near-zero differences, demonstrating strong rotational invariance. In contrast, non-APCT images exhibit significant deviations due to imperfect centrosymmetry. Right: example galaxy processed with APCT under rotations of 0°, 90°, 180°, and 270°, showing that the APCT-processed images remain nearly unchanged, regardless of the rotation of the original input.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: CAE architecture with a symmetric encoder-decoder structure. Encoder: 100 × 100 input undergoes two 5 × 5 convolutional layers (16 channels throughout), interleaved with max pooling, producing 25 × 25 × 16 features. The resulting feature maps are flattened to a 40D vector that encodes galaxy features.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: The distribution in the Imag–redshift (z) parameter space of galaxies in the COSMOS field. Marginalized number distributions along the Imag and z dimensions are projected at the top margin and right margin, respectively. The subsample satisfying the selection criteria 0.2 < z < 1.2 and Imag < 25 is highlighted in red.
Paper: Rotational Evolution of Deformed Magnetized Neutron Stars: Implications for Obliquity Distribution and Braking Indices Statistics
Authors: Anton Biryukov, Pavel Abolmasov, Amir Levinson
Figure caption: Reduced braking index nobsP versus the characteristic age for isolated radio pulsars. The gray dots designate 249 pulsars for which ﹩\ddot{{\rm{\Omega }}}﹩ is estimated with an accuracy better than 20% and are stored in the ATNF database. The colored circles depict those 108 pulsars from G. Hobbs et al. (2010), whose ﹩\ddot{{\rm{\Omega }}}﹩ is likely affected by long-term evolution rather than by timing noise. Their color indicates magnetic deformation ﹩{\hat{\varepsilon }}_{\mu }﹩ defined in Equation (23). The lines (solid, dashed, and dotted) show the expected behavior of the braking index for hydrostatically deformed NSs (Equation (53)) with deformation parameters εdΔχ = 10−10, 10−12, and 10−14.
Paper: Rotational Evolution of Deformed Magnetized Neutron Stars: Implications for Obliquity Distribution and Braking Indices Statistics
Authors: Anton Biryukov, Pavel Abolmasov, Amir Levinson
Figure caption: Top row: synthetic distributions of magnetic angles of pulsars with ages uniformly distributed up to 108 yrs. All distributions in this row are normalized to unity. Initial spin periods and respective magnetic fields were taken from A. P. Igoshev et al. (2022). The distribution of the initial spin and magnetic axes were taken to be isotropic in the principal frame. The values of ﹩\mathrm{log}{\varepsilon }_{3}﹩ were drawn from a uniform distribution in the interval −16..−10. In the simulations of triaxial stars (cases b and d), ε1 = −ε3 was adopted. The plot shows that the magnetic angle distribution of highly magnetized stars (whose precession is weakly affected by deformation) is highly nonuniform, with an excess of aligned rotators. Weakly magnetized stars show a uniform or isotropic distribution in χ. Bottom row: histograms of the magnetic fields of the same pulsars. They are not normalized; hence the areas under the histograms reflect fractions of pulsars within a particular range of ∣εμ∣/εd. If the field decays with time, a larger fraction of pulsars has a low ∣εμ∣/εd ratio—see plots (c) and (d). Such pulsars then will dominate the distribution of χ, which becomes more isotropic.
Paper: Rotational Evolution of Deformed Magnetized Neutron Stars: Implications for Obliquity Distribution and Braking Indices Statistics
Authors: Anton Biryukov, Pavel Abolmasov, Amir Levinson
Figure caption: Illustration of the two possible variants of the pulsar timing variations spectrum. The dashed line represents a broadband power-law timing noise whose high-frequency part (days-to-months) is directly observed within standard observational time spans. We speculate that such a spectrum tends to drop off at timescale ﹩{T}_{{\rm{\max }}}\sim 1{0}^{4}﹩ yr < τpsr, and its low-frequency part can, in principle, dominate the observed braking indices. The solid line represents another option: a spectrum that might consist of two components of a different nature. If this is the case, then only its high-frequency component is related to the common timing noise, while a separate low-frequency component can be connected to the mechanical precession.
Paper: Rotational Evolution of Deformed Magnetized Neutron Stars: Implications for Obliquity Distribution and Braking Indices Statistics
Authors: Anton Biryukov, Pavel Abolmasov, Amir Levinson
Figure caption: A plot of 366 pulsars whose timing noise properties have been studied in G. Hobbs et al. (2010). The vertical axis shows the relative precision of the measurement of ﹩\ddot{{\rm{\Omega }}}﹩, and the horizontal axis shows the ratio σ2/σ1, where σ1 is the timing residuals rms after subtraction of the quadratic timing model and σ2 is the same after subtraction of the cubic model. The color indicates the time span used for the timing measurement. Pulsars within the shaded (orange) area have ﹩| \delta \ddot{{\rm{\Omega }}}/\ddot{{\rm{\Omega }}}| \leqslant 0.1﹩ and σ2/σ1 < 0.5. For these, ﹩\ddot{{\rm{\Omega }}}﹩ is expected to be dominated by the long-term spin-down evolution rather than timing noise within the measurement duration. The effect of long-term evolution on ﹩\ddot{{\rm{\Omega }}}﹩ for the other pulsars in this sample is uncertain.
Paper: Rotational Evolution of Deformed Magnetized Neutron Stars: Implications for Obliquity Distribution and Braking Indices Statistics
Authors: Anton Biryukov, Pavel Abolmasov, Amir Levinson
Figure caption: Spin axis trajectory for a triaxial star with magnetic field decay. For this simulation εμ,0 = −3εd has been adopted. The magnetic field history is shown by the red line in the bottom plot (and the corresponding right vertical axis). During rapid magnetic field decay, the spin axis follows the changing precession axis and ultimately aligns with one of the principal axes. This leads to a gradual increase in the magnetic angle. The radius of the precessional orbit remains practically unaffected during the magnetic field decay, as it occurs much faster than the spin-down time. In the upper panel, the gray contours and the precession poles correspond to the initial, strongly magnetized, configuration.
Paper: Rotational Evolution of Deformed Magnetized Neutron Stars: Implications for Obliquity Distribution and Braking Indices Statistics
Authors: Anton Biryukov, Pavel Abolmasov, Amir Levinson
Figure caption: Example of the evolution of nobs · P (upper-left panel) of a biaxial oblate star with θm = 45°, εμ = −ε3 = −10−11, and fixed magnetic dipole. The color indicates the actual age of the pulsar, given in the χ(t) plot (bottom-left panel). The black dots on the nobsP − τch plot (upper-left panel) depict the 249 pulsars from the ATNF sample, with known braking indices shown in Figure 13.
Paper: Rotational Evolution of Deformed Magnetized Neutron Stars: Implications for Obliquity Distribution and Braking Indices Statistics
Authors: Anton Biryukov, Pavel Abolmasov, Amir Levinson
Figure caption: Same as Figure 7, but for a triaxial star (ε3 = −ε1 = 10−12) with the magnetic axis along the direction (φm, θm) = (72°, 72°). The difference between plots (a) and (b) is the initial orientation of the spin axis (Ω0). In (a), the initial magnetic angle is close to 50°, while in (b) it is 75°. As a result of evolution for identical global parameters, the spin axes in the two cases align with different magnetic poles.
Paper: The First LWA Swarm Calibrator Survey
Authors: C. A. Taylor, G. B. Taylor, J. Dowell, S. Pezzaioli
Figure caption: Standard bandpass profile for LWA Swarm interferometry observations. This figure shows the 55 MHz tuning at LWA1 for the left-hand circular polarized visibility data.
Paper: Probing the Nature of High-redshift Long GRB 250114A and Its Magnetar Central Engine
Authors: Wen-Yuan Yu, Hou-Jun Lü, Xiao Tian, Liang-Jun Chen, En-Wei Liang
Figure caption: Left panel: XRT (black) light curve of GRB 250114A. The red solid line represents the total component fitting line. The blue, green, and orange dashed lines are the best fits for the PL, flare, and plateau, respectively. The red, yellow, green, and dark-red data points are multiband optical data collected from GCN reports. Right panel: corner plots and parameter constraints for the fitting parameters of the XRT light curve of GRB 250114A.
Paper: Probing the Nature of High-redshift Long GRB 250114A and Its Magnetar Central Engine
Authors: Wen-Yuan Yu, Hou-Jun Lü, Xiao Tian, Liang-Jun Chen, En-Wei Liang
Figure caption: Light curves of prompt emission (black line in top panel) observed by BAT and X-ray emission (blue line in top panel), as well as Ep evolution (bottom panel) of GRB 250114A. The red step line is Bayesian block analysis for the BAT light curve.
Paper: Probing the Nature of High-redshift Long GRB 250114A and Its Magnetar Central Engine
Authors: Wen-Yuan Yu, Hou-Jun Lü, Xiao Tian, Liang-Jun Chen, En-Wei Liang
Figure caption: Left panel: X-ray light curve of GRB 250114A (black points) with magnetar model fits. The solid black line represents the maximum likelihood model, while the red lines represent 100 posterior samples, illustrating the uncertainty in the model fit. Right panel: 2D histograms and parameter constraints of the model fits for GRB 250114A. The 1D histograms show the distributions for each parameter. The dashed lines indicate the median and ±2σ uncertainty of the values.
Paper: Probing the Nature of High-redshift Long GRB 250114A and Its Magnetar Central Engine
Authors: Wen-Yuan Yu, Hou-Jun Lü, Xiao Tian, Liang-Jun Chen, En-Wei Liang
Figure caption: Left panel: Ep and Eγ,iso correlation diagram. Black points and gray diamonds correspond to Type I and Type II GRBs, respectively. The red star is GRB 250114A, and other data are taken from B. Zhang et al. (2009). Right panel: 1D and 2D distributions of GRB samples in T90 − ϵ space. The dashed line indicates ϵ = 0.03, and the data come from H.-J. Lü et al. (2010).
Paper: Probing the Nature of High-redshift Long GRB 250114A and Its Magnetar Central Engine
Authors: Wen-Yuan Yu, Hou-Jun Lü, Xiao Tian, Liang-Jun Chen, En-Wei Liang
Figure caption: Inferred magnetar parameters of GRB 250114A and initial spin period P0 versus surface polar cap magnetic field strength Bp. Other candidates for the magnetar central engine are taken from H.-J. Lü & B. Zhang (2014). The vertical solid line is the breakup spin period for a neutron star (J. M. Lattimer & M. Prakash 2004).
Paper: Probing the Nature of High-redshift Long GRB 250114A and Its Magnetar Central Engine
Authors: Wen-Yuan Yu, Hou-Jun Lü, Xiao Tian, Liang-Jun Chen, En-Wei Liang
Figure caption: Comparison of GRB 250114A and Swift sample GRBs with z > 4.5 in the X-ray afterglow.
Paper: Probing the Nature of High-redshift Long GRB 250114A and Its Magnetar Central Engine
Authors: Wen-Yuan Yu, Hou-Jun Lü, Xiao Tian, Liang-Jun Chen, En-Wei Liang
Figure caption: Comparison of GRB 250114A and Swift sample GRBs with z > 4.5 in prompt emission.
Paper: Investigation of Turbulent Fluctuations in the Fast and Alfvénic Slow Solar Wind at 1 au
Authors: Monika Karki, Gary P. Zank, Laxman Adhikari, Ashok Silwal, Sujan Prasad Gautam, Prashrit Baruwal, Prashant Baruwal, Ismita Tasnim, Lingling Zhao, Alexander Pitňa
Figure caption: Superposed epoch analysis of PSDs for the density fluctuations, consisting of entropy (black curve), fast (green curve), and slow (orange curve) MS modes (left column), velocity field fluctuations, consisting of Alfvén (blue curve), fast (green curve) and slow (orange curve) MS modes (middle column), and magnetic field fluctuation, consisting of magnetic islands (purple curve), Alfvén (blue curve), fast (green curve) and slow (orange curve) MS modes (right column) over ten 30 minute subintervals in Alfvénic slow solar wind.