adsabs/AstroCLIMB huggingface dataset:
Paper: Continued PSP/WISPR Observations of a Phaethon-related Dust Trail
Authors: Karl Battams, Angel J. Gutarra-Leon, Brendan M. Gallagher, Matthew M. Knight, Guillermo Stenborg, Sarah Tanner, Mark G. Linton, Jamey R. Szalay, Michael S. P. Kelley, Russell A. Howard
Figure caption: Illustration of a photometry-preserving averaging method for estimating the visual magnitude of the dust trail. The first panel shows an L3 image recorded on 2021 May 2 (E5) marked with an ROI centered along Phaethon’s orbit. The white box outlines the region of interest in which 396 cross-trail profiles were extracted. The second panel shows the resulting profile, averaged from these 396 profiles, and the third panel shows the result of a Gaussian fit to the profile, and the resulting fit parameters. The intensity is recorded in physical, calibrated units and thus can be directly interpreted from such plots.
Paper: Continued PSP/WISPR Observations of a Phaethon-related Dust Trail
Authors: Karl Battams, Angel J. Gutarra-Leon, Brendan M. Gallagher, Matthew M. Knight, Guillermo Stenborg, Sarah Tanner, Mark G. Linton, Jamey R. Szalay, Michael S. P. Kelley, Russell A. Howard
Figure caption: Panel (a) An LW-processed WISPR-O image recorded on 2021 January 20 09:05 UT, with a yellow dashed line indicating the orbit of Phaethon, with the dust trail very faintly following it. Panel (b) A simulation showing ∼14,000 Geminid orbits integrated into the same FOV as panel (a), with a black dashed line showing the orbit of Phaethon. The color scale of (b) represents the number of individual Geminid orbits that cross over any given pixel.
Paper: Continued PSP/WISPR Observations of a Phaethon-related Dust Trail
Authors: Karl Battams, Angel J. Gutarra-Leon, Brendan M. Gallagher, Matthew M. Knight, Guillermo Stenborg, Sarah Tanner, Mark G. Linton, Jamey R. Szalay, Michael S. P. Kelley, Russell A. Howard
Figure caption: Three WISPR-O LW-processed observations recorded on 2021 May 1 and 2 (E5), as indicated in the lower right of each panel. The data in each column are identical. The top row shows the nominal trajectory of Phaethon (red dashed lines). The bottom row shows the nominal trajectory of Phaethon with the argument of periapsis reduced by exactly 1°. The latter provides a far better visual correspondence to this portion of the dust trail.
Paper: Continued PSP/WISPR Observations of a Phaethon-related Dust Trail
Authors: Karl Battams, Angel J. Gutarra-Leon, Brendan M. Gallagher, Matthew M. Knight, Guillermo Stenborg, Sarah Tanner, Mark G. Linton, Jamey R. Szalay, Michael S. P. Kelley, Russell A. Howard
Figure caption: This illustration is the same as that shown in Figure 12, except the profile was extracted from an LW WISPR-O image. The sigma filter plus smoothing algorithm was applied again. The intensity is scaled to a minimum value of zero as a result of employing the LW algorithm, thus quantitative interpretation of intensity is not possible.
Paper: Continued PSP/WISPR Observations of a Phaethon-related Dust Trail
Authors: Karl Battams, Angel J. Gutarra-Leon, Brendan M. Gallagher, Matthew M. Knight, Guillermo Stenborg, Sarah Tanner, Mark G. Linton, Jamey R. Szalay, Michael S. P. Kelley, Russell A. Howard
Figure caption: A single cross-trail line profile (right panel) extracted along a ∼4° line (∼71 pixels long, red line in left panel), bisecting the dust trail and Phaethon’s orbit, as seen in WISPR-O (left panel) on 2021 May 2 07:34 UT. The profile is centered on the orbit of Phaethon, as indicated by the dark vertical line at 0°. The data intensity is in calibrated MSB units, and the width of the red line has been exaggerated to aid visibility. The contrast in the image has been manually changed to enhance the visibility of the trail in print copies of this manuscript.
Paper: Continued PSP/WISPR Observations of a Phaethon-related Dust Trail
Authors: Karl Battams, Angel J. Gutarra-Leon, Brendan M. Gallagher, Matthew M. Knight, Guillermo Stenborg, Sarah Tanner, Mark G. Linton, Jamey R. Szalay, Michael S. P. Kelley, Russell A. Howard
Figure caption: Illustration of a defined ROI (yellow dashed boundary) with the orbit of Phaethon (solid red line) passing through the center of the ROI, with the dust trail very faintly visible following this line. Green lines across the ROI illustrate the series of cross-trail profiles that we define and use to extract a signal from the ROI. Data from these lines are averaged (median) to produce a single cross-trail profile for that ROI. Note that this image is just illustrative of the process; actual ROI size and number of cross-trail lines will differ, as noted in the manuscript.
Paper: A Nonlocal Magneto-curvature Instability in a Differentially Rotating Disk
Authors: Fatima Ebrahimi, Matthew Pharr
Figure caption: Mode structures for the vertical magnetic field from the shooting method. (a) and (b) m = 1 mode at low field showing MRI and curvature mode localization between Alfvénic points at the inside/outside of the disk, respectively; (c) and (d), (e) at intermediate field in Figure 7 at (c) point 6, the point of convergence, (d) point 7, the m = 1 MRI mode, and (e) point 1, the m = 1 curvature mode (outer Alfvénic resonance not pictured at r out = 20.3r 1). (f) at high field for the most global curvature mode for m = 1 k = k 1 (γ = 0.021, ω  r  = 0.485 and Alfvénic resonances at r in = 1.04r 1, r out = 10.3r 1).
Paper: A Nonlocal Magneto-curvature Instability in a Differentially Rotating Disk
Authors: Fatima Ebrahimi, Matthew Pharr
Figure caption: Locations of the real and imaginary shooting tails and their overlap, where a solution fitting the boundary conditions exists. Purple indicates neither the real nor the imaginary tail is within a tolerance of zero, teal indicates one tail is near zero, and yellow indicates both tails go to zero and there is a mode in that neighborhood. (a) Shows the modes at k = 2k 1, V  A  = 0.2 r 1Ω0, and (b) shows the modes at k = k 1, V  A  = 0.57 r 1Ω0. The left-hand family of solutions is the low-frequency (outer) curvature mode, and the right-hand family of solutions is the high-frequency (inner) MRI mode. Both figures use a solely vertical background field and m = 1. Numbers show n  r .
Paper: A Nonlocal Magneto-curvature Instability in a Differentially Rotating Disk
Authors: Fatima Ebrahimi, Matthew Pharr
Figure caption: Progression through the m, k, and V  A  continuum between the curvature mode (point 1) and the MRI mode (point 7). Two distinct mode structures are recognized with the same m, k, and V  A  at points 1 and 7. Direct traversal from points 1 and 7 to m = 0 resulted in stability, partially seen in the blue curve ending at point 8, so an indirect path through varying k and V  A  was taken in points 2–6.
Paper: A Nonlocal Magneto-curvature Instability in a Differentially Rotating Disk
Authors: Fatima Ebrahimi, Matthew Pharr
Figure caption: (a) Growth rates and (b) mode frequencies from the global shooting method with a vertical seed field, for axisymmetric (m = 0) MRI, and nonaxisymmetric (m = 1) MRI and curvature modes with, k = k 1, 2k 1. Nonlinear NIMROD simulation (NVF-C in Table 1) is performed at the star point.
Paper: A Nonlocal Magneto-curvature Instability in a Differentially Rotating Disk
Authors: Fatima Ebrahimi, Matthew Pharr
Figure caption: Growth rates in high and low aspect ratio r 1/(r 2 − r 1) with the curvature and MRI modes, showing the curvature mode’s dominance in curved space and MRI’s dominance in quasi-Cartesian space. The normalization is against the outer parameters here because these values change as a function of the average curvature. Panel (c) shows how the aspect ratio affects the system geometry: The low- and high-aspect-ratio cases are shown in blue and green, respectively. Flow curvature and variation in shear are lower in the narrow-gap (green) case and is therefore closer to a Cartesian approximation.
Paper: A Nonlocal Magneto-curvature Instability in a Differentially Rotating Disk
Authors: Fatima Ebrahimi, Matthew Pharr
Figure caption: Contour plots of normalized WKB growth rates from (Equations (3)–(6)) in the k  z /k 1 and V  A /r 1Ω1 plane for k  r  = 0 (a) without δ  c  (in the Cartesian limit) (b) with δ  c  = 1 with a purely toroidal magnetic field. (c) and (d) are equivalent instead with a purely vertical magnetic field.
Paper: A Nonlocal Magneto-curvature Instability in a Differentially Rotating Disk
Authors: Fatima Ebrahimi, Matthew Pharr
Figure caption: (a) High-field and (b) low-field modes shown here in the super-Alfvénic region, i.e., high m (m = 10). We find that at a high toroidal mode number and high k (k = 80k 1), the range of magnetic fields to which the system is linearly unstable to a perturbation is narrowed to the low-field region. This can be seen in comparison with Figures 4, 8, and 9 varying V  A  for m = 1.
Paper: A Nonlocal Magneto-curvature Instability in a Differentially Rotating Disk
Authors: Fatima Ebrahimi, Matthew Pharr
Figure caption: (a) and (b) Growth rates. (c) Frequencies from both the global shooting method (Equation (16)) and numerical linear NIMROD points for both typical MRI modes (with various k  z  in color) and global curvature modes (green curve). All shooting done for m = 1.
Paper: A Nonlocal Magneto-curvature Instability in a Differentially Rotating Disk
Authors: Fatima Ebrahimi, Matthew Pharr
Figure caption: Equilibrium quantities for an unstratified, currentless Keplerian disk. As the magnetic field may vary, V  A  was arbitrarily chosen such that ﹩{{V}_{A}}_{z}=0.1{r}_{1}{{\rm{\Omega }}}_{0}﹩ and ﹩{{{V}_{A}}_{\phi }}_{0}=0.3{r}_{1}{{\rm{\Omega }}}_{0}﹩ for demonstration purposes.
Paper: The Physical Properties of Massive Green Valley Galaxies as a Function of Environments at 0.5 < z < 2.5 in 3D-HST/Candels Fields
Authors: Wenjun Chang, Guanwen Fang, Yizhou Gu, Zesen Lin, Shiying Lu, Xu Kong
Figure caption: Sérsic index n (top panels) and effective radius r  e  (bottom panels) as functions of M ⋆ in the highest (dark green) and lowest (light green) density quarters. The error bars are the 2σ uncertainties drawn from the bootstrap method with the 1000× resamples.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: The relationship between the PSD break frequency (f B) and black hole mass (M BH) and bolometric luminosity (L bol). The values of the horizontal axis are calculated using the expression given in McHardy et al. (2006) (which is shown as the diagonal black dotted line), while the observed break frequencies are got in our sample. The uncertainties of mass estimation are used to get the horizontal errors. The gray shadowed areas display ±0.7 dex regions around the model, as a nearer study by González-Martín (2018) shows standard deviations around this value. Related parameters are listed in Tables 3 and 5.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: Energy spectra and 0.3–1 keV PSDs of the AGN which have only one or no detection of high-frequency break. Black lines are the best-fit Model B (i.e., break power law) results for observations that report significant breaks, and are the best-fit Model A (i.e., single power law) results for observations that do not report significant breaks. The dashed lines and the dotted lines represent red noise components and Poisson terms, respectively. Particularly, the LRT1 p-values of Model A simulation for the 2016 observation of IRAS 13224-3809, the 2013 observation of NGC 1365, and the 2019 observation of NGC 4395are shown downside since they are lower than 0.01. Spectra and PSDs are shown in different colors denoting the observation date. The PSDs are arranged in order of flux.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: Energy spectra and 0.3–1 keV PSDs of the AGN that have no more than two detections of high-frequency breaks. Black lines are the best-fit Model B (i.e., break power law) results for observations that report significant breaks, and are the best-fit Model A (i.e., single power law) results for observations that do not report significant breaks. The dashed lines and the dotted lines represent red noise components and Poisson terms, respectively. Particularly, the LRT1 p-value of the Model A simulation for the 2001 observation of PG 1211+143 is shown downside since it is lower than 0.01. Spectra and PSDs are shown in different colors denoting the observation date. The PSDs are arranged in order of flux.
Paper: The Physical Properties of Massive Green Valley Galaxies as a Function of Environments at 0.5 < z < 2.5 in 3D-HST/Candels Fields
Authors: Wenjun Chang, Guanwen Fang, Yizhou Gu, Zesen Lin, Shiying Lu, Xu Kong
Figure caption: The extinction-corrected rest-frame U – V color of GV galaxies as a function of stellar mass in three redshift bins. In each panel, the background grayscale shades represent the distribution for all our parent massive galaxies. Green points are GV galaxies. The two criteria for each redshift bin from Wang et al. (2017) are separately shown as red and blue bands, where the edge of the ribbon corresponds to the range of redshift. The number of GV galaxies in each redshift bin is shown at the bottom of each panel.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: Time-averaged fluxed spectra unfolded through a power-law model with index 0 and normalization 1, which are largely free from effects of energy-dependent effective area and give representations of the underlying source spectra.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: Excess variance calculated using 20 ks segments of the light curve against the black hole mass. The sizes of the points indicate the relative 2–10 keV flux of corresponding observations. The best-fit relationship in Ponti et al. (2012) is marked by the black dotted line and the 1σ error region is shown as a gray shadowed area which comes from random sampling under distributions of slope and normalization from Ponti et al. (2012).
Paper: Independent Evidence for Earlier Formation Epochs of Fossil Groups of Galaxies through the Intracluster Light: The Case for RX J100742.53+380046.6
Authors: Renato A. Dupke, Yolanda Jimenez-Teja, Yuanyuan Su, Eleazar R. Carrasco, Anton M. Koekemoer, Rebeca M. Batalha, Lucas Johnson, Jimmy Irwin, Eric MIller, Paola Dimauro, Nícolas O. L. de Oliveira, Jose Vilchez
Figure caption: ICLf rest-frame color distribution for merging (red) and relaxed (blue) clusters studied in Jiménez-Teja et al. (2018). Black lines indicate the error weighted mean of each main-sequence spectral-type subsample and colored shadowed areas, the mean of the errors. We also plot the values for a candidate fossil cluster RX JJ105452.03+552112.5 in green (Yoo et al. 2021). Gray vertical lines at the top of the figure split the wavelength range expected for the peak emission for an average main-sequence star, labeled with gray letters. Although the distribution for relaxed clusters is mostly flat, that of merging clusters shows an excess in the region corresponding to the emission peaks of late A- and early F-type stars. RXJ1007 distribution is shown by the black squares and does not follow the typical behavior of a merging nor of a normal relaxed cluster. For the sake of visibility, we used a symbol size larger than the small error bars for the F606W filter.
Paper: Independent Evidence for Earlier Formation Epochs of Fossil Groups of Galaxies through the Intracluster Light: The Case for RX J100742.53+380046.6
Authors: Renato A. Dupke, Yolanda Jimenez-Teja, Yuanyuan Su, Eleazar R. Carrasco, Anton M. Koekemoer, Rebeca M. Batalha, Lucas Johnson, Jimmy Irwin, Eric MIller, Paola Dimauro, Nícolas O. L. de Oliveira, Jose Vilchez
Figure caption: Rest-frame ICLf/M 500 ratio comparison. In black we show the rest-frame ICLfM500 values derived in this work for RXJ1007 (black), for all relaxed (blue) and merging (red) ICLHST clusters analyzed in Jiménez-Teja et al. (2018) as well as for the Frontier Field clusters AS1063 and A370 (de Oliveira et al. 2022), the high-z merging cluster WHL J013719.8-08284 (Jiménez-Teja et al. 2021a) and a candidate fossil cluster RX J105452.03+552112.5 in green (Yoo et al. 2021). We show the transmission curves of the HST filters used to determine the ICL in RXJ1007 in the bottom. The error shaded bands are the same as in Figure 5.
Paper: Independent Evidence for Earlier Formation Epochs of Fossil Groups of Galaxies through the Intracluster Light: The Case for RX J100742.53+380046.6
Authors: Renato A. Dupke, Yolanda Jimenez-Teja, Yuanyuan Su, Eleazar R. Carrasco, Anton M. Koekemoer, Rebeca M. Batalha, Lucas Johnson, Jimmy Irwin, Eric MIller, Paola Dimauro, Nícolas O. L. de Oliveira, Jose Vilchez
Figure caption: Top panel: Redshift distribution of all galaxies with confirmed spectroscopic redshifts ≤ 0.3 within a field of view of 24′ × 24′. The red region shows the distribution of the 46 member galaxies of RXJ1007. The redshifts of individual galaxies are represented by tick marks at the top of the histogram. The inset shows the phase-space diagram normalized by the velocity dispersion as a function of the normalized radius. The dashed lines in the inset represent the escape velocity for a NFW halo projected in the line of sight (see the text). Bottom panel: Color–magnitude diagram of all galaxies brighter than r′= 23 mag inside 24′ × 24′ in the RXJ1007 field (gray points). The squares and triangles represent the members and foreground/background galaxies, respectively. The galaxies observed with GMOS are represented by red squares (member galaxies) and blue triangles (foreground/background galaxies). The solid red line fits the red sequence of the FG, while the dashed lines represent the ± 1.5σ from the best-fit of the red sequence.
Paper: The Intrinsic Multiplicity Distribution of Exoplanets Revealed from the Radial Velocity Method
Authors: Wei Zhu, 伟 祝
Figure caption: Likelihood contours between model parameters in the “all giant planet” case. We have used two different values for the maximum multiplicity, ﹩{k}_{\max }﹩, in the modeling: Blue filled contours correspond to ﹩{k}_{\max }=4﹩, which is the highest multiplicity with nonzero detections, whereas red dashed contours correspond to ﹩{k}_{\max }=5﹩. For each set of contours, the plus signs indicate the analytic solution (Equation (15)), and the contours with increasing levels of transparency correspond to the 1σ–3σ uncertainty regions. The constraints on the frequency of planetary systems, F p, and the average multiplicity, ﹩{\bar{m}}_{{\rm{p}}}﹩, are shown in the upper right corner. The inclusion of higher planet multiplicities with zero detections does not change the constraints on almost any of the low multiplicities. The only exception is seen in F 4, for which the lower limit is modified.
Paper: The Intrinsic Multiplicity Distribution of Exoplanets Revealed from the Radial Velocity Method
Authors: Wei Zhu, 伟 祝
Figure caption: Illustrations of the derived intrinsic planet multiplicity distributions of the five chosen planet classes. The maximum-likelihood solutions and 1σ–3σ confidence intervals are shown in blue colors with increasing transparency. For comparison, we also show in each panel the scaled Poisson distribution to the total frequency of the given planetary system as the gray points. The shape parameter of the Poisson distribution is set to be the average multiplicity of the given planet type. Values for the maximum-likelihood solution and 1σ confidence intervals (or in some cases, the 2σ upper limits) are tabulated in Table 2.
Paper: The Intrinsic Multiplicity Distribution of Exoplanets Revealed from the Radial Velocity Method
Authors: Wei Zhu, 伟 祝
Figure caption: The fraction of Sun-like stars with giant planets (top panel), the average number of giant planets per Sun-like star (middle panel), and the average multiplicity of giant planets (bottom panel), as functions of the average detection probability ﹩\bar{p}﹩. In each panel, the gray curve corresponds to the value from the analytic solution (Equation (15)), the black curve is the maximum-likelihood solution that takes into account the boundary conditions (i.e.,  F  > 0), and the horizontal line and shaded region are the derived frequency and the associated 1σ confidence interval, respectively. The vertical dashed line marks the value of p that is adopted in the maximum-likelihood analysis.
Paper: The Intrinsic Multiplicity Distribution of Exoplanets Revealed from the Radial Velocity Method
Authors: Wei Zhu, 伟 祝
Figure caption: The distribution of CLS planets with Sun-like hosts in the minimum mass vs. semimajor axis plane. Planets with different observed multiplicities are differentiated with different labels and colors. The contours are the survey completeness curves of 10% (darkest) to 90% (lightest), constructed based on the injection–recovery simulations of all Sun-like stars in the CLS sample (Rosenthal et al. 2021a). The vertical dashed line indicates the outer boundary (10 au) that is considered in this work, and the horizontal dashed line indicates the upper mass limit (13 M J). The positions of Jupiter and Saturn are also shown. The regions of three types of planets defined in Section 3 are given as the black boxes. The red solid and dashed lines denote the RV semi-amplitudes of 3 and 1 m s−1, respectively. Note that one additional planet, 55 Cnc e, with minimum mass ﹩m\sin i=9.4\,{M}_{\oplus }﹩ and semimajor axis a = 0.02  au, is slightly beyond the limit and thus does not appear on the plot.
Paper: The Intrinsic Multiplicity Distribution of Exoplanets Revealed from the Radial Velocity Method
Authors: Wei Zhu, 伟 祝
Figure caption: This figure shows in blue dots the planet detections from the CLS Sun-like sample whose properties are within our chosen parameter space. The values within each grid point gives the average number of such planets per 100 Sun-like stars. Error bars give the 68% confidence interval, whereas the values in red indicate the 95% upper limit. The integrated planet frequencies are ﹩{\bar{n}}_{{\rm{p}}}=0.076\pm 0.013﹩, 0.21 ± 0.05, 0.22 ± 0.03 for our definition of close-in giants, close-in intermediate-mass, and cold giant planets, respectively.
Paper: The Intrinsic Multiplicity Distribution of Exoplanets Revealed from the Radial Velocity Method
Authors: Wei Zhu, 伟 祝
Figure caption: Similar to Figure 4, except that now the y-axis is the RV semi-amplitude K. The dashed line indicates the upper mass limit of a planet (13 M J) around a 1 M ⊙ host. The frequency of planets with K > 3 m s−1 and a < 10  au is 0.42 ± 0.04. The frequency of planets with K > 1 m s−1 and a < 1  au is 0.58 ± 0.09.
Paper: The Intrinsic Multiplicity Distribution of Exoplanets Revealed from the Radial Velocity Method
Authors: Wei Zhu, 伟 祝
Figure caption: The cumulative distribution functions (CDFs) of planetary parameters for planets from systems with one planet detection (blue curves) and more than one planet detection (orange curves). In the left, middle, and right panels are shown the minimum mass, the semimajor axis, and the orbital eccentricity, respectively. The p value of the two-sample KS test is indicated in each of these comparisons.
Paper: The Intrinsic Multiplicity Distribution of Exoplanets Revealed from the Radial Velocity Method
Authors: Wei Zhu, 伟 祝
Figure caption: Cumulative distributions of the per-star detection probabilities p for the five chosen planet types. For any given planet type, the vertical dashed line of the same color indicate the average detection probability ﹩\bar{p}﹩.