adsabs/AstroCLIMB huggingface dataset:
Paper: Constraining the Binarity of Black Hole Candidates: A Proof-of-concept Study of Gaia BH1 and Gaia BH2
Authors: Toshinori Hayashi, 利憲 林, Yasushi Suto, 靖 須藤, Alessandro A. Trani, 虎似 三努郎
Figure caption: Relations between i out and I los (top) and i mut and I los (bottom). The left and right panels correspond to Gaia BH1 and Gaia BH2, respectively. Shaded regions in the top panels are excluded due to the observed value of the inclination I obs (see Table 1). The bottom panels plot I los against i mut for given values of ξ. The region between two lines is permitted for each ξ, and the shaded regions correspond to ξ > 1.2 for Gaia BH1 and ξ > 0.9 for Gaia BH2, which are excluded from dynamical stability viewpoint.
Paper: Constraining the Binarity of Black Hole Candidates: A Proof-of-concept Study of Gaia BH1 and Gaia BH2
Authors: Toshinori Hayashi, 利憲 林, Yasushi Suto, 靖 須藤, Alessandro A. Trani, 虎似 三努郎
Figure caption: Relation of i out and i mut, Equation (25) for different ξ = 0.3, 0.6, 0.9, 1.2, and 10. For reference, we plot the dashed line that corresponds to the asymptotic limit of ξ → ∞ . Figures 2 and 5 imply that ξ = 1.2 and 0.9 roughly correspond to the maximum possible values for Gaia BH1 and Gaia BH2, respectively.
Paper: Constraining the Binarity of Black Hole Candidates: A Proof-of-concept Study of Gaia BH1 and Gaia BH2
Authors: Toshinori Hayashi, 利憲 林, Yasushi Suto, 靖 須藤, Alessandro A. Trani, 虎似 三努郎
Figure caption: The ratio of the inner and outer angular momenta, ξ, plotted against P in for different q 21 ≡ m 2/m 1 and e in. The solid and dashed lines correspond to Gaia BH1 and Gaia BH2, respectively.
Paper: Constraining the Binarity of Black Hole Candidates: A Proof-of-concept Study of Gaia BH1 and Gaia BH2
Authors: Toshinori Hayashi, 利憲 林, Yasushi Suto, 靖 須藤, Alessandro A. Trani, 虎似 三努郎
Figure caption: The normalized timescale of the nodal precession, P Ω/P out, plotted against ﹩\cos {i}_{\mathrm{mut}}﹩ for different ξ. The solid and dashed lines correspond to Gaia BH1 and Gaia BH2, respectively. We fix q 21 = 1 and e in = 0 for simplicity.
Paper: Constraining the Binarity of Black Hole Candidates: A Proof-of-concept Study of Gaia BH1 and Gaia BH2
Authors: Toshinori Hayashi, 利憲 林, Yasushi Suto, 靖 須藤, Alessandro A. Trani, 虎似 三努郎
Figure caption: The normalized timescale of the nodal precession, P Ω/P out, plotted against ξ for i mut = 10° (red) and 50° (blue). The solid and dashed curves correspond to Gaia BH1 and Gaia BH2, respectively. The q 21 and e in are fixed as 1.0 and 0.0, respectively.
Paper: Constraining the Binarity of Black Hole Candidates: A Proof-of-concept Study of Gaia BH1 and Gaia BH2
Authors: Toshinori Hayashi, 利憲 林, Yasushi Suto, 靖 須藤, Alessandro A. Trani, 虎似 三努郎
Figure caption: Example of evolution of simulated RV semi-amplitudes and the mutual inclination angles for the initial values of i mut = 20° (top), 60° (middle), and 90° (bottom). The left and right panels correspond to Gaia BH1 (P in = 10 days and I los = 120°) and Gaia BH2 (P in = 50 days and I los = 30°), respectively. For simplicity, we assume the equal-mass inner binary (q 12 = 1) in an initially circular orbit (e in = 0). For reference, the range of the analytic estimate of Δ K , Equation (31), is plotted in magenta regions, and the expected semi-amplitude change, from Equation (27), is plotted as dotted green curves. Equation (10) diverges for i mut = 90°, and we do not show the analytic predictions in those cases.
Paper: Exploring the Origin of Solar Energetic Electrons. I. Constraining the Properties of the Acceleration Region Plasma Environment
Authors: Ross Pallister, Natasha L. S. Jeffrey
Figure caption: Fluence (upper) and peak-electron flux (lower) spectra of the ejected population for intermediate collisional region plasma properties and varying analytical parameters: the distance of the virtual measurement from the Sun R  i  (left), the total integration time of the simulation τ  i  (middle), and the energy bin resolution S (right). Other analytical parameters are fixed at R  i  = 1.0 au, τ  i  = 50,000 s, and S = 3 keV. The fluence is effectively unchanged across the heliosphere at the maximum integration time with greater peak flux values at all energies closer to the Sun. Shorter integration times show a significant reduction of fluence at 1.0 au. Bin sizes larger than ∼3 keV mask the maximum values of peak flux and fluence and make it difficult to identify features at the low-energy ranges (<10 keV) of both distributions.
Paper: Exploring the Origin of Solar Energetic Electrons. I. Constraining the Properties of the Acceleration Region Plasma Environment
Authors: Ross Pallister, Natasha L. S. Jeffrey
Figure caption: Simplified cartoon indicating one possible magnetic topology (such as emerging flux) that could lead to the production of both flare hard X-ray-producing, and in situ detected electrons in close proximity, in hot and over-dense regions close to the flare energy release site. Here we concentrate on studying the properties of those electrons accelerated during the flare but observed in situ, by modeling the transport of an injected electron population through a hot and over-dense coronal region related to the flare (black-lined rectangle) of various temperature T, number density n  e , and size L, and then out into the heliosphere until 1.0 au.
Paper: Exploring the Origin of Solar Energetic Electrons. I. Constraining the Properties of the Acceleration Region Plasma Environment
Authors: Ross Pallister, Natasha L. S. Jeffrey
Figure caption: Example ejected electron fluence (blue) vs. energy (left) and pitch angle (right). The injected distribution (power law, beamed) is denoted by the black curve in the left plot and by the dashed black line in the right. The injected distribution travels through a “flare” region with the following plasma properties: length L = 30 Mm, temperature T = 20 MK, and number density n  e  = 5 × 109 cm−3. A thermal distribution corresponding to a plasma temperature of T = 20 MK is also shown (gray dotted, left)
Paper: Exploring the Origin of Solar Energetic Electrons. I. Constraining the Properties of the Acceleration Region Plasma Environment
Authors: Ross Pallister, Natasha L. S. Jeffrey
Figure caption: Full collisional-region parameter analysis at 0.4 au (upper) and 1.0 au (lower). The energies where the maximum fluence (left) and peak flux (right) occur are shown for 3 keV (thin line) and 1 keV (thick line) resolutions. Ratios of the [7–10) to [4–7) keV bin heights for both fluence (circles) and flux (crosses) are calculated and displayed in the right column. While the size of some 1 and 3 keV bins mask the change in peaks (fluence and peak flux) between parameter sets for regions with temperatures above 10 MK, the bin height ratios demonstrate the same relation for a sufficiently long integration time.
Paper: Exploring the Origin of Solar Energetic Electrons. I. Constraining the Properties of the Acceleration Region Plasma Environment
Authors: Ross Pallister, Natasha L. S. Jeffrey
Figure caption: Collisional-boundary electron energy (upper) and pitch-angle (lower) fluence distributions independently varying each parameter between their minimum (blue) and maximum (pink) values, while fixing the other parameters at intermediate values. Dotted lines represent the thermal distributions associated with the given temperature values. The fluence peaks at higher energies for smaller, hotter, and sparser regions, which also correspond to less isotropic ejecta distributions. As expected, the electron spectra above 20 keV remain relatively unchanged regardless of region parameters.
Paper: Exploring the Origin of Solar Energetic Electrons. I. Constraining the Properties of the Acceleration Region Plasma Environment
Authors: Ross Pallister, Natasha L. S. Jeffrey
Figure caption: Peak (in energy) of ejected electron fluence for every simulated parameter set, with each window corresponding to a different region size. The parameter set labels (x-axis) are formatted in order of region temperature and electron density. Increasing the electron density of the region significantly reduces the energy at which the fluence peaks for most region sizes, with a greater degree of deceleration for colder plasmas.
Paper: Exploring the Origin of Solar Energetic Electrons. I. Constraining the Properties of the Acceleration Region Plasma Environment
Authors: Ross Pallister, Natasha L. S. Jeffrey
Figure caption: Fluence (upper) and peak flux (lower) distributions of the ejected population at 1.0 au with a simulated energy binning of 3 keV for the minimum and maximum collisional region parameters (shown in each legend). The fluence and flux distributions peak at higher energies for hotter and sparser collisional regions, similar to the region boundary results, with the largest divergence found between minimum and maximum temperature parameter sets.
Paper: Exploring the Origin of Solar Energetic Electrons. I. Constraining the Properties of the Acceleration Region Plasma Environment
Authors: Ross Pallister, Natasha L. S. Jeffrey
Figure caption: Temperature dependence of the ejected electron fluence distributions compared for minimum (left) and maximum (right) simulated densities, and L = 30 Mm. Distribution shape is very similar in all low-density regions, but the spectral differences due to temperature can be clearly seen in higher-density cases.
Paper: Resolved Star Formation in TNG100 Central and Satellite Galaxies
Authors: Bryanne McDonough, Olivia Curtis, Tereasa G. Brainerd
Figure caption: Population-averaged radial profiles of ΔΣSFR (left) and Age L  (right). Profiles are shown separately for starburst (pink), main-sequence (blue), green valley (green), and quenched (red) populations. Shaded regions indicate the error computed via 2000 bootstrap resamplings; where not visible, the errors are smaller than the width of the lines. The black dashed line on the left figure indicates the quenching threshold for spaxels (ΔΣSFR = −2.4), below which a spaxel is considered to be quenched. The legends include a profile gradient, the slope of a line fit to the profiles for R ≤ 1R  e . A positive gradient in ΔΣSFR is indicative of inside-out quenching, or in the case of the starbursts, indicative of star bursting occurring in the outskirts. A negative gradient in Age L  is indicative of inside-out quenching, or star bursting in the outskirts.
Paper: Resolved Star Formation in TNG100 Central and Satellite Galaxies
Authors: Bryanne McDonough, Olivia Curtis, Tereasa G. Brainerd
Figure caption: Dependence of Age L  radial profile on stellar mass. Formatting is identical to Figure 3. Panel (a) includes all galaxies and is a reproduction of Figure 3 (right). With the exception of the starburst profiles in panels (d) and (e), at least 20 galaxies contribute to each individual profile. In all cases, however, the value of Age L  for each radial bin is computed using at least 1000 particles. It should be noted that there are no starburst galaxies in the highest mass bin. Errors are computed from 2000 bootstrap resamplings. Error bounds that are wider than the linewidth are indicated by shaded regions, and are omitted from the figure when they are comparable to or smaller than the linewidth.
Paper: Resolved Star Formation in TNG100 Central and Satellite Galaxies
Authors: Bryanne McDonough, Olivia Curtis, Tereasa G. Brainerd
Figure caption: Dependence of ΔΣSFR radial profile on stellar mass. Formatting is identical to Figure 3. Panel (a) includes all galaxies and is a reproduction of Figure 3 (left). With the exception of the starburst galaxies in panels (d) and (e), which each contain only three objects, at least 20 galaxies contribute to each individual profile. It should be noted that there are no starburst galaxies in the mass range of panel (f). Errors are computed from 2000 bootstrap resamplings. Error bounds that are wider than the linewidth are indicated by shaded regions, and are omitted from the figure when they are comparable to or smaller than the linewidth.
Paper: Resolved Star Formation in TNG100 Central and Satellite Galaxies
Authors: Bryanne McDonough, Olivia Curtis, Tereasa G. Brainerd
Figure caption: Radial profiles of Age L , with galaxies separated into centrals (left) and satellites (right). Formatting is identical to Figure 3 (right). Population-averaged profiles are shown in the top row for all centrals (panel (a)) and all satellites (panel (b)), and subsequent rows show profiles for the low-mass (﹩{\mathrm{log}}_{10}{M}_{* }/{M}_{\odot }\lt 10﹩, middle) and high-mass (﹩{\mathrm{log}}_{10}{M}_{* }/{M}_{\odot }\gt 10﹩, bottom) subsets of the central and satellite populations. All populations except for the high- and low-mass starbursts have at least 20 contributing galaxies. There are only 2 (36) low- (high-) mass starburst centrals and only 16 (4) low- (high-)mass starburst satellites. All bins are computed with at least 1000 stellar particles regardless of how many galaxies contribute. Errors, represented by the shaded regions, are computed via 2000 bootstrap resamplings and are smaller than the width of the lines when not visible.
Paper: Resolved Star Formation in TNG100 Central and Satellite Galaxies
Authors: Bryanne McDonough, Olivia Curtis, Tereasa G. Brainerd
Figure caption: Left: resolved star-forming main sequence for “spaxels” from maps of TNG100 galaxies. Star formation rate surface density is plotted against stellar mass surface density for each spaxel, which has been hexagonally binned. Point color is determined by ΔΣSFR. Yellow line: the resolved main sequence. Right: distribution of ΔΣSFR values, weighted by ﹩{{\rm{e}}}^{{\rm{\Delta }}{{\rm{\Sigma }}}_{\mathrm{SFR}}}﹩. Main figure: distribution of spaxels for each galaxy type (starbursts—pink, main sequence—blue, green valley—green, and quenched—red). Inset: distribution of all spaxels from the entire sample. Orange dashed line: minimum of the distribution, below which a spaxel is considered to be quenched.
Paper: Resolved Star Formation in TNG100 Central and Satellite Galaxies
Authors: Bryanne McDonough, Olivia Curtis, Tereasa G. Brainerd
Figure caption: Profile gradients from the legend of Figure 3 in this work (closed squares) and from Figure 3 in Bluck et al. (2020b; open squares). The left panel shows the negative of the ΔΣSFR gradient, while the right panel shows the Age L  gradient. The dashed black lines are located at ﹩{{\rm{\nabla }}}_{1{R}_{e}}﹩(ΔΣSFR) = 0 and ﹩{{\rm{\nabla }}}_{1{R}_{e}}﹩(Age L ) = 0, where a profile would be flat.
Paper: Resolved Star Formation in TNG100 Central and Satellite Galaxies
Authors: Bryanne McDonough, Olivia Curtis, Tereasa G. Brainerd
Figure caption: Profile gradients from the legend of Figure 6 in this work (closed squares) and from Figure 3 in Bluck et al. (2020b; open squares). Gradients are plotted for centrals (left) and satellites (right); both panels share a y-axis. The dashed black lines are located at ﹩{{\rm{\nabla }}}_{1{R}_{e}}﹩Age L  = 0, where a profile would be flat.
Paper: Calibrating VLBI Polarization Data Using GPCAL. I. Frequency-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Linear polarization images of 3C 273 from the synthetic data set generated based on the real VLBA 15 GHz data. Colored ticks indicate EVPAs, with colors corresponding to linearly polarized intensities. We have made Ricean debiasing corrections (i.e., ﹩{P}_{\mathrm{corr}}={P}_{\mathrm{obs}}\sqrt{1-({\sigma }_{P}/{P}_{\mathrm{obs}})}﹩) to the images (Wardle & Kronberg 1974), where P corr and P obs denote the corrected and original linearly polarized intensity, respectively. The white crosses in the bottom right corner represent the shape of the synthesized beam. The top left image is the ground-truth image used for synthetic data generation. The top right image is obtained from the data without being corrupted by polarimetric leakage (“No D-Terms”). Hence, this image comprises solely of two potential sources of error, namely thermal noise within the data and inaccuracies caused by the utilization of the CLEAN algorithm. Consequently, this image could serve as a benchmark reference for the purpose of scrutinizing the influence of polarimetric leakages within the data. In the bottom left image, we have applied our method of frequency-dependent instrumental polarization calibration to data where frequency-dependent leakage corruption has been introduced (“channel-by-channel D-term correction”). Using the same data, the bottom right image was produced by averaging the data over frequency for each IF and then performing instrumental polarization calibration based on the averaged data (“D-term correction using frequency-averaged data”). A comparison of the bottom left and right images can be used to evaluate the effect of frequency-dependent leakage calibration. With the exception of the ground-truth image, which is noise-free, each panel exhibits the DR of the linear polarization images.
Paper: Calibrating VLBI Polarization Data Using GPCAL. I. Frequency-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: D-terms for RCP (blue) and LCP (green) for BL273AK (left, 15 GHz) and BM462M (right, 43 GHz) data. The D-terms of specific stations, such as BR for BL273AK and PT for BM462M, are presented as examples. The open circles indicate the D-term spectra derived from GPCAL’s frequency-dependent leakage calibration (D(ν)), while the solid lines indicate D-terms obtained from the frequency-averaged data set (﹩D(\bar{\nu })﹩). We note that in the right figure, the green and blue solid lines representing the amplitudes of the fourth IF overlap, making them difficult to distinguish from each other. The D-term spectra exhibit smooth and continuous variations over frequency within and across IFs. The ﹩D(\bar{\nu })﹩ is a good approximation of the D(ν) for both data sets. It is worth noting a noticeable discrepancy between ﹩D(\bar{\nu })﹩ and D(ν) in the right figure. However, the numerical difference is relatively small, and it is important to emphasize that ﹩D(\bar{\nu })﹩ is not necessarily an average of D(ν), as discussed in Appendix A.
Paper: Calibrating VLBI Polarization Data Using GPCAL. I. Frequency-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Cross power spectra (amplitude: ∣V∣ and phase: ϕ) of the cross-hand visibilities (RL: upper; LR: lower) of 3C 279 obtained from the BL273AK data. The baselines associated with the BR station averaged over one scan are shown. The upper and lower spectra are presented before and after correcting for frequency-dependent polarimetric leakage, respectively.
Paper: Calibrating VLBI Polarization Data Using GPCAL. I. Frequency-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Dirty images of the residual visibilities of synthetic data for 3C 273, which represent the visibilities obtained after subtracting the CLEAN model visibilities for Stokes Q (upper) and U (lower). White contours represent the contour of the Stokes I image, with the contour level set at three times the off-source image rms noise, delineating the source region. Images on the left, obtained with frequency-dependent D-term correction, exhibit significantly reduced noise levels compared to those on the right, which use frequency-averaged data for D-term correction.
Paper: Calibrating VLBI Polarization Data Using GPCAL. I. Frequency-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Linear polarization images of 3C 273 from the BL273AK data (upper, 15 GHz) and BM462M data (lower, 43 GHz). Colored ticks indicate EVPAs, with colors corresponding to linearly polarized intensities. The white crosses in the bottom right corner of the right panel represent the shape of the synthesized beam. The images obtained by using the GPCAL pipeline using the data averaged over frequency within each IF are presented in the left panels. The images obtained by correcting frequency-dependent polarimetric leakages using the method presented in this paper are shown in the right panels. The polarization image DR is noted in each panel.
Paper: Calibrating VLBI Polarization Data Using GPCAL. I. Frequency-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Same as Figure 5 but for the PT baselines of the BM462M data observed at 43 GHz.
Paper: Calibrating VLBI Polarization Data Using GPCAL. I. Frequency-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Same as Figure 3 but for the synthetic data including both frequency-dependent polarimetric leakage and antenna gain corruptions.
Paper: Calibrating VLBI Polarization Data Using GPCAL. I. Frequency-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Same as Figure 1 but for the synthetic data including both frequency-dependent polarimetric leakage and antenna gain corruptions.
Paper: Calibrating VLBI Polarization Data Using GPCAL. I. Frequency-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Same as Figure 2 but for the synthetic data including both frequency-dependent polarimetric leakage and antenna gain corruptions.
Paper:  r-process Abundance Patterns in the Globular Cluster M92
Authors: Evan N. Kirby, Alexander P. Ji, Mikhail Kovalev
Figure caption: The Gaia CMD for M92. Colors and magnitudes are corrected for reddening and extinction. The right axis gives the absolute G 0 magnitude. The color scale gives the effective temperature (Section 3). The subgiants are all hotter than 5420 K, and they are shown with the darkest shade of purple to give the RGB more color range. The symbol shape depicts the evolutionary state of the star, which is determined based on the location in the CMD.
Paper: Local Star-forming Galaxies Build Up Central Mass Concentration Most Actively near M ∗ = 1010 M ⊙ 
Authors: Zhizheng Pan, Xianzhong Zheng, Xu Kong
Figure caption: Left: the R e−M * relation for the NSA SFG sample selected at 0.02 < z < 0.05. Large symbols show the median R e values of each stellar mass bin, with a bin size of ΔM * = 0.2 dex. The two blue dashed lines indicate the 16–84 percentile region. The red region indicates the 16–84 region of MaNGA SFGs as shown in Figure 3. Right: the fraction of SFGs with n > 2 in the MaNGA and NSA-Sloan sample. The shaded region indicates the 1σ  region.
Paper: Local Star-forming Galaxies Build Up Central Mass Concentration Most Actively near M ∗ = 1010 M ⊙ 
Authors: Zhizheng Pan, Xianzhong Zheng, Xu Kong
Figure caption: Top left: the mass-weighted age gradient as a function of M *. The stellar mass bin size is ΔM * = 0.2 dex. Large symbols show the median values of each stellar mass bin. Top right: D4000 gradient as a function of M *. Bottom left: the Hα flux gradient as a function of M *. Bottom right: the Hα flux gradient as a function of luminosity-weighted age gradient. Large symbols show the median values of each ∇age bin. In each panel, the shaded region indicates the 16–84 percentile region.