adsabs/AstroCLIMB huggingface dataset:
Paper: Estimate of Current Mass of the Large Magellanic Cloud from the Orphan–Chenab Tidal Stream
Authors: Hiroka T. Warren, Heidi Jo Newberg, Autumn G. Guffey, JiaZhao Lin, Eric J. Mendelsohn, Kevin Roux
Figure caption: Simulated OCS derived by modeling the DG with a two-component Plummer sphere that represents baryon particles and dark matter particles separately. We switched the DG model from a single Plummer to a double Plummer here, but we used the same best-fit OCS parameters using the Erkal2019 potential with a Plummer model LMC listed in Table 3. The baryon particles are colored blue, and the dark matter particles are colored orange. This illustrates that the long tidal tails that exceed the data in Figure 8 are mostly dark matter particles. The fact that the baryon (blue) particles are still a good match to the real data suggests that use of a one- or two-component DG does not significantly affect the LMC mass measurement.
Paper: Estimate of Current Mass of the Large Magellanic Cloud from the Orphan–Chenab Tidal Stream
Authors: Hiroka T. Warren, Heidi Jo Newberg, Autumn G. Guffey, JiaZhao Lin, Eric J. Mendelsohn, Kevin Roux
Figure caption: Proper motions in R.A. and decl. of our best-fit OC streams with Plummer LMC using Erkal2019, Salas2019, Mendelsohn2022, and MMWPotential2014 MW potential models (from top to bottom). The black points are data from S. E. Koposov et al. (2019). The range and mean of deviations of the data points from the center of the simulation are given in the bottom right corner of the μα vs. ϕ1 panels and the top left corner for the μδ vs. ϕ1 panels. They all fit well, except that the proper motions for Mendelsohn2022 show a larger-than-expected error of 3σ–4σ.
Paper: Estimate of Current Mass of the Large Magellanic Cloud from the Orphan–Chenab Tidal Stream
Authors: Hiroka T. Warren, Heidi Jo Newberg, Autumn G. Guffey, JiaZhao Lin, Eric J. Mendelsohn, Kevin Roux
Figure caption: Proper motions in R.A. and decl. of our best-fit OC streams with the Hernquist LMC under Erkal2019, Salas2019, Mendelsohn2022, and MMWPotential2014 MW potential models (from top to bottom). The black points are data from S. E. Koposov et al. (2019). The range and mean of deviations of the data points from the center of the simulation are given in the bottom right corner for the μα vs. ϕ1 panels and top left corner for the μδ vs. ϕ1 panels. Again, they all fit well, except that the proper motion in decl. for Mendelsohn2022 deviates from the data by as much as 4σ, which is significantly larger than any other model.
Paper: Estimate of Current Mass of the Large Magellanic Cloud from the Orphan–Chenab Tidal Stream
Authors: Hiroka T. Warren, Heidi Jo Newberg, Autumn G. Guffey, JiaZhao Lin, Eric J. Mendelsohn, Kevin Roux
Figure caption: Acceleration of the best-fit LMC using the upper bound (dark color) and lower bound (light color) with the Plummer (blue) and Hernquist profiles (red). The vertical dashed lines are the closest approach of the LMC, and the large dots show the acceleration at closest approach for each case. As for all other best-fit LMC masses, the acceleration is about (1.0–1.3) × 108 (km s−1)2 kpc−1.
Paper: So Long Kolmogorov: The Forward and Backward Turbulence Cascades in a Supernovae-driven, Multiphase Interstellar Medium
Authors: James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz, Christoph Federrath
Figure caption: Time-averaged shell-to-shell transfer of kinetic energy between logarithmic shells, with transfers parallel to the gravitational potential (k∥; top row) and perpendicular to it (k⊥; bottom row). All transfers are between like modes (uc ↔ uc or us ↔ us) of velocity (Equations (29)–(32)), colored by the velocity flux ε, normalized to the maximum, absolute value, ε0, in each transfer. The black horizontal and vertical lines in the ﹩{{ \mathcal T }}_{ss}^{s}({Q}_{\parallel },{K}_{\parallel })﹩ panel indicate the k of the gaseous disk scale height, ﹩{k}_{0}\sim {\ell }_{0}^{-1}﹩ (Section 2.1.2), and the lines in the ﹩{{ \mathcal T }}_{ss}^{c}(Q,K)﹩ panels indicate the approximate cooling radius, ﹩{R}_{{\rm{cool}}}^{-1}﹩, of the SNe (Equation (25)). Most compressible uc and incompressible us modes exhibit direct turbulent cascades (positive velocity flux from large to small scales). However, us → us mediated by uc interactions exhibits an inverse (negative velocity flux) cascade from small to large scales. This takes energy from below the disk scales, k > k0, out to larger scales, k < k0, potentially then fueling the direct cascades in the other transfer functions (and, e.g., the winds out of the disk). Shell-to-shell transfers between mixed modes are included in Appendix B.
Paper: So Long Kolmogorov: The Forward and Backward Turbulence Cascades in a Supernovae-driven, Multiphase Interstellar Medium
Authors: James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz, Christoph Federrath
Figure caption: Similar to Figure 4, but each row corresponds to slices of the terms responsible for generating vorticity modes, ∂tω (Equation (38)), probing the generation of modes that participate in the incompressible turbulence cascade. Top row: vortex compression, ∼ω(∇ · u). Middle row: vortex stretching, ﹩\sim {\boldsymbol{\omega }}\cdot {\mathbb{S}}﹩, where ﹩{\mathbb{S}}﹩ is the strain-rate tensor (see J. R. Beattie et al. 2023a for why we use ﹩{\mathbb{S}}﹩ instead of the full ∇ ⨂ u). Bottom row: baroclinicity, ∼∇ρ × ∇P, is the only battery term, in that it generates ω without any initial seed ω. Each panel is normalized by the instantaneous rms value of the respective field. Therefore, these panels do not give information about the absolute values of each term (see Figure 12 for the rms amplitudes of each term), but emphasize the spatial structure of each individual component. All of the ω generation terms are strongly correlated, and they are mostly sensitive to the post-shock regions inside of the SNRs, as well as to the SNe shock fronts themselves. However, in the ∇ρ × ∇P term, the most notable sources of ω generation are the fractal cooling layers (e.g., D. B. Fielding et al. 2020) between the cold (exterior; T ∼ 104 K) and hot (interior; T ≳ 104 K) gas in the SNRs.
Paper: So Long Kolmogorov: The Forward and Backward Turbulence Cascades in a Supernovae-driven, Multiphase Interstellar Medium
Authors: James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz, Christoph Federrath
Figure caption: The same terms from Figure 11 but for the evolution of their rms normalized by ﹩{t}_{0}^{-1}﹩. Throughout the entire evolution of the simulation, the baroclinic term (green) dominates over the other two. During the steady state (shaded gray region), it is greater by approximately ∼3 orders of magnitude, making it the leading-order term in generating vorticity. Unlike the other two terms, baroclinicity generates vorticity without the need for any seed vorticity, and hence it can be completely fueled by compressible modes that source strong ∇ρ and ∇P misalignments through corrugated pressure and density interfaces (like fractal cooling layers, corrugated shocks, etc.) or interacting shock fronts.
Paper: So Long Kolmogorov: The Forward and Backward Turbulence Cascades in a Supernovae-driven, Multiphase Interstellar Medium
Authors: James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz, Christoph Federrath
Figure caption: A two-dimensional logarithmic temperature (normalized by T = 104 K) slice of a zoom-in of the lower left panel in Figure 11, revealing that the baroclinc term, ∝∇ρ × ∇P, is the strongest at the fractal cooling layer at Rcool between the hot T > 104 K plasma inside of the SNRs (shown in red) and the colder T < 104 K plasma outside of the SNRs (shown in blue). Because the baroclinic term dominates the total ω generation (Figure 12), this suggests that phase mixing through the fractal cooling layer is the strongest source of incompressible turbulence in the SNe-driven medium, and because the incompressible turbulence dominates the total energy in the turbulence (Figure 5; peaking at Rcool), phase mixing is potentially the largest source of turbulence, in general.
Paper: So Long Kolmogorov: The Forward and Backward Turbulence Cascades in a Supernovae-driven, Multiphase Interstellar Medium
Authors: James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz, Christoph Federrath
Figure caption: Two-dimensional slices of ﹩{{ \mathcal T }}_{ss}^{c}(x,y,z)﹩ (the velocity flux between us modes mediated by uc modes; Equation (37)), Fourier filtered over 11 ≤ k⊥ ≤ 45 with Q⊥ < K⊥, covering the range of modes where the inverse cascade is observed in the ﹩{{ \mathcal T }}_{ss}^{c}﹩ transfer function (see bottom right-hand panel of Figure 8). For ﹩{{ \mathcal T }}_{ss}^{c}\gt 0﹩ (red), the region of space is undergoing an inverse cascade, and for ﹩{{ \mathcal T }}_{ss}^{c}\lt 0﹩ (blue), a direct cascade. In the top panel, the slice is parallel to ∇ϕ through the center of the domain, with the measured gaseous scale height ℓ0 annotated in a similar way as in Figure 4. In the bottom panel, we slice perpendicular to ∇ϕ, through the center of the galactic disk.
Paper: So Long Kolmogorov: The Forward and Backward Turbulence Cascades in a Supernovae-driven, Multiphase Interstellar Medium
Authors: James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz, Christoph Federrath
Figure caption: A schematic summarizing the incompressible us mode (blue) generation through the corrugated cooling layer (black) between the hot (orange) and warm (teal) gas, which are stretched to larger scales by the compressible uc modes (red) associated with the expanding SNRs. The cooling layer generates a large spectrum of us modes, due to the fractal nature of the layer (see D. B. Fielding et al. 2020, for the fractal characterization of such a layer). The rate at which the baroclinc term generates us modes admits to the Green’s function solution where f = ∇ × (∇ρ × ∇P/ρ2) (Equation (42)), where examples of the ∇P for the layer are shown in pink and examples of the ∇ρ are shown in green.
Paper: So Long Kolmogorov: The Forward and Backward Turbulence Cascades in a Supernovae-driven, Multiphase Interstellar Medium
Authors: James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz, Christoph Federrath
Figure caption: The ratio between the power spectrum of incompressible velocity modes, ﹩{{ \mathcal P }}_{{u}_{s}}(k)﹩, and the total velocity modes, ﹩{{ \mathcal P }}_{u}(k)﹩ and ﹩{{ \mathcal P }}_{{u}_{s}}(k)/{{ \mathcal P }}_{u}(k)﹩, colored by k⊥ (blue) and k∥ (black). The gaseous scale height ℓ0 is indicated in the plot by the vertical black dashed line. The ratio shows that all scales in the ISM are dominated by us modes, with a further significant enhancement on scales ℓ ≈ Rcool, where Rcool ≈ (10–30) pc, (Equation (25)) is the cooling radius of the SNe (J. M. Blondin et al. 1998; D. F. Cioffi et al. 1988).
Paper: So Long Kolmogorov: The Forward and Backward Turbulence Cascades in a Supernovae-driven, Multiphase Interstellar Medium
Authors: James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz, Christoph Federrath
Figure caption: Top: The shell-to-shell energy transfer us → us modes, mediated by us modes, ﹩{{ \mathcal T }}_{ss}^{s}﹩ (Equation (32); i.e., the transfer function that would capture the classical, incompressible, Kolmogorov-type cascade (A. N. Kolmogorov (1941)), for the five time realizations averaged over in the transfer function analysis. The extent (how many k modes in the cascade), the direction of the cascade (whether it is inverse or direct), and the total velocity flux Π/Π0, change significantly between different realizations in the stationary state, indicating that the entire ISM cascade fluctuates significantly in time. Bottom: The time evolution of ﹩{\langle {u}^{2}\rangle }_{{ \mathcal V }}﹩, normalized by the time-averaged ﹩{\langle {u}^{2}\rangle }_{{ \mathcal V }}﹩, within the stationary state of the simulation.
Paper: So Long Kolmogorov: The Forward and Backward Turbulence Cascades in a Supernovae-driven, Multiphase Interstellar Medium
Authors: James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz, Christoph Federrath
Figure caption: A visual summary of the flux transfers described in Section 5. ﹩{{\boldsymbol{u}}}_{s}\mathop{\to }\limits^{{{\boldsymbol{u}}}_{c},\,{{\boldsymbol{u}}}_{s}}{{\boldsymbol{u}}}_{c}﹩ and ﹩{{\boldsymbol{u}}}_{c}\mathop{\to }\limits^{{{\boldsymbol{u}}}_{c},\,{{\boldsymbol{u}}}_{s}}{{\boldsymbol{u}}}_{s}﹩ transfers (top and bottom expressions) define velocity fluxes between modes within each of the cascades, and ﹩{{\boldsymbol{u}}}_{c}\mathop{\to }\limits^{{{\boldsymbol{u}}}_{c},\,{{\boldsymbol{u}}}_{s}}{{\boldsymbol{u}}}_{s}﹩ and ﹩{{\boldsymbol{u}}}_{s}\mathop{\to }\limits^{{{\boldsymbol{u}}}_{c},\,{{\boldsymbol{u}}}_{s}}{{\boldsymbol{u}}}_{c}﹩ transfers (middle expression) define fluxes between cascades (shown in Appendix B).
Paper: Probing Accretion Disk Winds of Stratified Nature with Fe XXVI Doublet in Black Hole X-Ray Binaries
Authors: Keigo Fukumura, Shoji Ogawa, Atsushi Tanimoto, Francesco Tombesi, Alfredo Luminari, Maxime Parra, Megumi Shidatsu, Liyi Gu, Ehud Behar
Figure caption: (a) Distribution of the Fe XXVI (hydrogen-equivalent) local column NH per radial bin (dark), the cumulative column (blue), and the wind temperature T (red) as a function of ionization parameter ξ (and LoS distance ﹩{\mathrm{log}}\,r[\mathrm{cm}]﹩) for θ = 70° (LoS). The vertical dashed line denotes the peak (at r = rpeak) point where the Fe XXVI column is maximum. (b) Calculated doublet structure of the Fe XXVI absorption line corresponding to Figure 2(a) for various broadening dispersion factors fturb. Rest-frame Lyα1 and Lyα2 energies are denoted by vertical lines. We assume fden = 2 (i.e., nofden = 2.7 × 1017 cm−3), p = 1.2, and fv = 0.1 under the optically thin regime.
Paper: Probing Accretion Disk Winds of Stratified Nature with Fe XXVI Doublet in Black Hole X-Ray Binaries
Authors: Keigo Fukumura, Shoji Ogawa, Atsushi Tanimoto, Francesco Tombesi, Alfredo Luminari, Maxime Parra, Megumi Shidatsu, Liyi Gu, Ehud Behar
Figure caption: (a) Three-dimensional rendering of three individual streamlines launched magnetically from different locations. On the X–Z plane, we show the poloidal distribution of the normalized wind density (color coded) ﹩{\mathrm{log}}\,\tilde{n}(r,\theta ),﹩ density contours (dashed), and the poloidal projection of magnetic field lines (thick solid). The Y–Z plane shows the distribution of the normalized poloidal turbulent velocity ﹩{\mathrm{log}}\,{\tilde{v}}_{{\rm{turb}}}(r,\theta )﹩ (color coded) with its contours (dashed). The toroidal projection of the streamlines is shown on the X–Y plane. (b) The intrinsic X-ray ionizing spectrum (relevant to the bright soft state of BH XRBs dominated by thermal radiation from the disk) is adopted for postprocess radiative transfer calculations with xstar in this work (see M. Shidatsu & C. Done 2019 and A. Tanimoto et al. 2025 for details).
Paper: Probing Accretion Disk Winds of Stratified Nature with Fe XXVI Doublet in Black Hole X-Ray Binaries
Authors: Keigo Fukumura, Shoji Ogawa, Atsushi Tanimoto, Francesco Tombesi, Alfredo Luminari, Maxime Parra, Megumi Shidatsu, Liyi Gu, Ehud Behar
Figure caption: (a) Calculated line ratio (Lyα1/Lyα2) corresponding to Figure 2(b) as a function of broadening dispersion fturb with fv = 0.1 and fden = 2 where the red line denotes the expected 1:2 ratio under the optically thin regime. Denoted is the corresponding vturb,in value. (b) Simulated 50 ks XRISM/Resolve spectrum with fden = 2 and fv = 0.1 assuming 2–10 keV flux of 10−10 [cgs] for various dispersions: fturb = 0.1 (dark), 1 (red), 1.3 (blue), and 4 (green).
Paper: Probing Accretion Disk Winds of Stratified Nature with Fe XXVI Doublet in Black Hole X-Ray Binaries
Authors: Keigo Fukumura, Shoji Ogawa, Atsushi Tanimoto, Francesco Tombesi, Alfredo Luminari, Maxime Parra, Megumi Shidatsu, Liyi Gu, Ehud Behar
Figure caption: Similar to Figure 2(b) but for various fden ranging from the optically thin regime (e.g., fden ≲ 2 or ﹩{N}_{{\rm{H}}}^{{\rm{peak}}}\lesssim 1{0}^{21}﹩ cm−2 yielding a roughly 1:2 ratio) to the optically thick regime (e.g., fden = 10 or ﹩{N}_{{\rm{H}}}^{{\rm{peak}}}\gtrsim 1{0}^{22}﹩ cm−2 leading approximately to 1:1) in the same wind model with fv = 0.1 and fturb = 1. Note that the cumulative column exceeds ∼1023 cm−2 for fden ≳ 5.
Paper: Validating Open Cluster Candidates with Photometric Bayesian Evidence
Authors: Lu Li, 璐 李, Zhaozhou Li, 昭洲 李, Zhengyi Shao, 正义 邵
Figure caption: Distributions of Bayes factor (BF) for random field samples (orange) and confirmed OCs (blue). To accommodate the wide dynamical range of ﹩{\mathrm{log}}_{10}{\rm{BF}}﹩, the x-axis adopts an arcsinh scale, which is linear near zero and logarithmic at large values. The probability density on the y-axis is computed for ﹩{\rm{arcsinh}}\,({\mathrm{log}}_{10}{\rm{BF}})﹩ accordingly. A threshold of ﹩{\mathrm{log}}_{10}{\rm{BF}}\simeq 2﹩ effectively separates real clusters from field samples.
Paper: Validating Open Cluster Candidates with Photometric Bayesian Evidence
Authors: Lu Li, 璐 李, Zhaozhou Li, 昭洲 李, Zhengyi Shao, 正义 邵
Figure caption: Example CMDs for different types of targets. Left: random field regions (﹩{\mathrm{log}}_{10}{\rm{BF}}\lt 0﹩). Middle: ambiguous candidates (﹩{\mathrm{log}}_{10}{\rm{BF}}\sim 1﹩). Right: confirmed OCs with strong evidence (log10BF > 3). BF denotes the Bayes factor comparing a mixture model of SSP+field to a pure field-star model.
Paper: Validating Open Cluster Candidates with Photometric Bayesian Evidence
Authors: Lu Li, 璐 李, Zhaozhou Li, 昭洲 李, Zhengyi Shao, 正义 邵
Figure caption: CMD examples illustrating the impact of field-star model mismatch. In both panels, black points represent 200 field stars within 100 pc. Left: using a representative field model built from stars in the same distance range (gray points). Right: using a mismatched field model built from a broader distance range (d < 2 kpc).
Paper: Validating Open Cluster Candidates with Photometric Bayesian Evidence
Authors: Lu Li, 璐 李, Zhaozhou Li, 昭洲 李, Zhengyi Shao, 正义 邵
Figure caption: Relation between the Bayes factor (BF) and the field star fraction (ffs) for the 1232 confirmed OCs from the MiMO catalog. Points are color-coded by the number of inferred member stars (Nmemb).
Paper: Discovery of Changing-look Behavior in AGN NGC 3822: A Long-term Multiwavelength Study
Authors: Narendranath Layek, Prantik Nandi, Sachindra Naik, Birendra Chhotaray, Arghajit Jana, Priyadarshee P. Dash, Neeraj Kumari, C. S. Stalin, Srikanth Bandari, S. Muneer
Figure caption: Left: temporal variation of X-ray (0.3–10 keV range), UV, and optical continuum flux obtained from the Swift (XRT and UVOT) and XMM-Newton (EPIC and OM) observations for the years 2008–2024. The shaded areas in cyan and gray indicate the observations for the years 2013 and 2022, respectively, during which the source exhibited significantly enhanced flux levels across all bands compared to other epochs. The dotted blue vertical line indicates the epoch when BELs are detected, while the red line marks the epoch when BELs are not detected. Right: zoomed-in view of the 2022 monitoring campaign, covering the period from 2022 March to 2022 December. The X-ray flux is given in units of 10−12 erg cm−2 s−1 and the optical/UV monochromatic flux is in units of 10−15 erg s−1 cm−2 Å−1.
Paper: Discovery of Changing-look Behavior in AGN NGC 3822: A Long-term Multiwavelength Study
Authors: Narendranath Layek, Prantik Nandi, Sachindra Naik, Birendra Chhotaray, Arghajit Jana, Priyadarshee P. Dash, Neeraj Kumari, C. S. Stalin, Srikanth Bandari, S. Muneer
Figure caption: Left panel (1): the spectra from the 2010 June XMM-Newton (XMM) observation, fitted with an absorbed power-law model. Panels (A)–(B) represent the corresponding residual plots. Middle and right panels ((2) and (3)): The broadband spectra from the 2016 January (XRT4+NU1) and 2022 June (XRT5b+NU2) observations are fitted with the Cutoffpl/CompTT model. Panels (A)–(D) display respective residual plots. Detailed explanations of the figure are provided in Section 3.2.1.
Paper: Discovery of Changing-look Behavior in AGN NGC 3822: A Long-term Multiwavelength Study
Authors: Narendranath Layek, Prantik Nandi, Sachindra Naik, Birendra Chhotaray, Arghajit Jana, Priyadarshee P. Dash, Neeraj Kumari, C. S. Stalin, Srikanth Bandari, S. Muneer
Figure caption: Corner plots of spectral parameters from MCMC analysis for the XRT4+NU1 (left) and XRT5b+NU2 (right) using the CompTT model. One-dimensional histograms represent the probability distribution. Three vertical lines in the 1D distribution show 16%, 50%, and 90% quantiles. We used CORNER.PY (D. Foreman-Mackey 2017) to plot the distributions. The units of NH, kTe, and Norm are in 1022 cm−2, keV, and photons keV−1 cm−2 s−1, respectively.
Paper: Discovery of Changing-look Behavior in AGN NGC 3822: A Long-term Multiwavelength Study
Authors: Narendranath Layek, Prantik Nandi, Sachindra Naik, Birendra Chhotaray, Arghajit Jana, Priyadarshee P. Dash, Neeraj Kumari, C. S. Stalin, Srikanth Bandari, S. Muneer
Figure caption: Fractional variation of the X-ray, UV, and optical continuum bands as a function of wavelength.
Paper: Discovery of Changing-look Behavior in AGN NGC 3822: A Long-term Multiwavelength Study
Authors: Narendranath Layek, Prantik Nandi, Sachindra Naik, Birendra Chhotaray, Arghajit Jana, Priyadarshee P. Dash, Neeraj Kumari, C. S. Stalin, Srikanth Bandari, S. Muneer
Figure caption: Optical spectrum of NGC 3822 as observed with HFOSC (Gr7 and Gr8) and X-Shooter (UBV and VIS arm). The green line represents the observed spectrum. The red line is the pPXF fit for the stellar component, and the host galaxy subtracted AGN spectrum is shown by the blue line.
Paper: Reconstructing the Anisotropic Ultralong Wavelength Spectra Using a Single Antenna on Lunar Orbit
Authors: Qige Ao, 琦格 奥, Furen Deng, 辅仁 邓, Yidong Xu, 怡冬 徐, Bin Yue, 斌 岳, Huanyuan Shan, 欢源 陕, Xuelei Chen, 学雷 陈
Figure caption: The fitted spectra for the nine regions as illustrated in Figure 9. The line labels are the same as in Figure 8.
Paper: Reconstructing the Anisotropic Ultralong Wavelength Spectra Using a Single Antenna on Lunar Orbit
Authors: Qige Ao, 琦格 奥, Furen Deng, 辅仁 邓, Yidong Xu, 怡冬 徐, Bin Yue, 斌 岳, Huanyuan Shan, 欢源 陕, Xuelei Chen, 学雷 陈
Figure caption: The turnover frequency νt,j for the nine regions with labeled sequence on each pixel.
Paper: Discovery of Changing-look Behavior in AGN NGC 3822: A Long-term Multiwavelength Study
Authors: Narendranath Layek, Prantik Nandi, Sachindra Naik, Birendra Chhotaray, Arghajit Jana, Priyadarshee P. Dash, Neeraj Kumari, C. S. Stalin, Srikanth Bandari, S. Muneer
Figure caption: The confidence interval plot of the high-energy cutoff parameter Ecut for the observation XRT4+NU1 and XRT5b+NU2. The plots illustrate that Ecut could not be constrained owing to low-quality data.
Paper: The Ultraviolet/Optical Continuum Reverberation Mapping of Eight Active Galactic Nuclei with Swift: Further Evidence for the Outer Component
Authors: Chi-Zhuo Wang, Xue-Bing Wu, Yuanzhe Jiang, Qinchun Ma, Huapeng Gu, Yuhan Wen
Figure caption: The ICCF-Cut and JAVELIN Pmap model results for Fairall 9. The top left panel shows the ICCF-Cut light curves, including the observed UVW2 (blue), the observed U (red), and the cut (green; i.e., the observed U-band light curve minus the predicted disk emission light curve in that band) light curves. All these light curves have subtracted the host-galaxy flux. The middle left panel displays these light curves scaled to the predicted disk flux in the U band and shifted by their respective lags. The bottom left panel shows the observed light curves and the JAVELIN fittings in the UVW2 and U bands. The top right panel presents the CCF and CCCD between the UVW2 and cut light curves. The bottom right panel shows the posterior distribution of the lags given by the JAVELIN Pmap model. The masked data in the JAVELIN results are denoted by the light gray. The maximum of the CCF and the lag estimation of the ICCF-Cut method and the JAVELIN Pmap model, r﹩{}_{\max }﹩, τcut, and τjav respectively, can be found in the corresponding panels. All lags presented here are in the rest frame.