adsabs/AstroCLIMB huggingface dataset:
Paper: Projections of Earth’s Technosphere: Strategies for Observing Technosignatures on Terrestrial Exoplanets
Authors: Jacob Haqq-Misra, Ravi K. Kopparapu, George Profitiliotis
Figure caption: Albedo spectra of preagricultural Earth (red line; scenario R0 from Table 1) and present-day Earth (dark line; scenario R1 from Table 1) observed 10 pc away at nominal HWO wavelengths. The noticeable difference between the spectra in the 0.3–0.6 μm region arises from the significant production of NO2 pollution from industrial activity, as well as large-scale agriculture, on present-day Earth. Note that we assume an isoprofile abundance for the NO2 gas concentration, which overestimates the absorption feature for the present-day Earth. The small difference between the spectra near 1.6 μm is due to the excess production of CH4 from human activity (including agriculture, combustion, and decomposition of landfill waste). Scenarios S5, S9, and S10 are spectrally identical to preagricultural Earth (R0).
Paper: Galaxy Spin Alignment with Tidal Fields in the SDSS-IV MaNGA Survey
Authors: Jun-Sung Moon, Teppei Okumura
Figure caption: Top: mean absolute values of the cosines of the angles between stellar spin vectors and the three principal axes of the local tidal tensor as a function of stellar mass. From left to right, the panels correspond to the major (green), intermediate (red), and minor (blue) principal axes. In each panel, the sample is divided into bins of equal size. The shaded regions indicate the 1σ intervals from 1000 randomly shuffled samples, and the dashed lines mark the expected value for a random orientation. The detection significance for each bin is indicated below each point. Bottom: same as the top row, but for galaxies in regions of strong tidal anisotropy (q > 1.235).
Paper: Galaxy Spin Alignment with Tidal Fields in the SDSS-IV MaNGA Survey
Authors: Jun-Sung Moon, Teppei Okumura
Figure caption: Normalized conditional mutual information ﹩I(| \hat{{\boldsymbol{j}}}\cdot {\hat{{\boldsymbol{e}}}}_{k}| ;Y| Z)﹩ (k = 1, 2, 3) for various combinations of Y and Z. Each value is normalized by the mean and standard deviation estimated from 1000 randomly shuffled samples. Darker colors indicate stronger importance of Y in determining spin alignments after controlling for Z.
Paper: Galaxy Spin Alignment with Tidal Fields in the SDSS-IV MaNGA Survey
Authors: Jun-Sung Moon, Teppei Okumura
Figure caption: Same as Figure 1, but for galaxies residing in high-δ (top), intermediate-δ (middle), and low-δ (bottom) regions.
Paper: Galaxy Spin Alignment with Tidal Fields in the SDSS-IV MaNGA Survey
Authors: Jun-Sung Moon, Teppei Okumura
Figure caption: Same as Figure 1, but showing the spin–tidal alignments for the gas spin vectors.
Paper: Galaxy Spin Alignment with Tidal Fields in the SDSS-IV MaNGA Survey
Authors: Jun-Sung Moon, Teppei Okumura
Figure caption: Same as Figure 1, but for lenticulars (−2 ≤ TType ≤ 0; top), early-type spirals (1 ≤ TType ≤ 3; middle), and late-type spirals (4 ≤ TType ≤ 8; bottom) in high-q regions.
Paper: Galaxy Spin Alignment with Tidal Fields in the SDSS-IV MaNGA Survey
Authors: Jun-Sung Moon, Teppei Okumura
Figure caption: Same as Figure 1, but for galaxies residing in the sheet (top), filament (middle), and cluster (bottom) environments. Galaxies in void environments are not shown because of their small sample size.
Paper: Galaxy Spin Alignment with Tidal Fields in the SDSS-IV MaNGA Survey
Authors: Jun-Sung Moon, Teppei Okumura
Figure caption: Same as the bottom panels of Figure 1, but recomputed with the sign of ﹩{\hat{j}}_{r}﹩ fixed to either + (top) or − (bottom).
Paper: The Dynamical Interaction between Low-mass Planets and Dust Coagulation
Authors: Qiang Hou, Cong Yu, Shu-ichiro Inutsuka
Figure caption: The waveforms of CM, which illustrate the mechanism of CI. The three waveforms represent the real parts of the perturbations in dust surface density δΣd, radial velocity δudx, and stopping time δτ. Their amplitudes have been rescaled to the same order. The propagation direction of the waves is inward, as indicated by the black arrow. A positive δΣd leads to an increase in δτ with a phase shift of π/2 due to dust coagulation. As δτ increases, the aerodynamic drag exerted by the gas on the dust decreases, which in turn increases the dust radial velocity. In the figure, δudx is approximately out of phase with δτ. Consequently, the phase difference between δudx and δΣd is close to π/2, implying that dust grains tend to accumulate near the crests of δΣd and disperse from the troughs, as indicated by the red arrows. This leads to the amplification of the initial δΣd. The positive feedback among δΣd, δτ, and δudx ultimately drives the CI.
Paper: Discovery of SN 2025wny: A Strongly Gravitationally Lensed Superluminous Supernova at z = 2.01
Authors: Joel Johansson, Daniel A. Perley, Ariel Goobar, Jacob L. Wise, Yu-Jing Qin, Zoë McGrath, Steve Schulze, Cameron Lemon, Anjasha Gangopadhyay, Konstantinos Tsalapatas, Igor Andreoni, Eric C. Bellm, Joshua S. Bloom, Richard Dekany, Suhail Dhawan, Claes Fransson, Christoffer Fremling, Matthew J. Graham, Steven L. Groom, Daniel Gruen, Xander J. Hall, George Helou, Mansi Kasliwal, Russ R. Laher, Ragnhild Lunnan, Ashish A. Mahabal, Adam A. Miller, Edvard Mörtsell, Jakob Nordin, Jacob Osman Hjortlund, R. Michael Rich, Reed L. Riddle, Avinash Singh, Jesper Sollerman, Alice Townsend, Lin Yan
Figure caption: Left panel: public ZTF g- and r-band light curves of SN 2025wny, shown as green and red symbols. Black vertical lines indicate the time of the discovery, spectroscopic observations, and our reported AstroNotes (J. Johansson et al. 2025; J. Wise et al. 2025). Right panel: spectra of SN 2025wny (black lines) and the two galaxies forming the lens system (blue lines). The spectra have been offset for clarity. Prominent absorption lines from the SN host galaxy at z = 2.010, and the two lens galaxies at zlens = 0.375, are marked with vertical red and blue lines, respectively. The dashed green curves show blackbody fits to the SN spectra, with TBB ∼ 29,000, 23,000, and 19,000 K, for the three spectra.
Paper: Discovery of SN 2025wny: A Strongly Gravitationally Lensed Superluminous Supernova at z = 2.01
Authors: Joel Johansson, Daniel A. Perley, Ariel Goobar, Jacob L. Wise, Yu-Jing Qin, Zoë McGrath, Steve Schulze, Cameron Lemon, Anjasha Gangopadhyay, Konstantinos Tsalapatas, Igor Andreoni, Eric C. Bellm, Joshua S. Bloom, Richard Dekany, Suhail Dhawan, Claes Fransson, Christoffer Fremling, Matthew J. Graham, Steven L. Groom, Daniel Gruen, Xander J. Hall, George Helou, Mansi Kasliwal, Russ R. Laher, Ragnhild Lunnan, Ashish A. Mahabal, Adam A. Miller, Edvard Mörtsell, Jakob Nordin, Jacob Osman Hjortlund, R. Michael Rich, Reed L. Riddle, Avinash Singh, Jesper Sollerman, Alice Townsend, Lin Yan
Figure caption: RGB composite images of the lens system from Legacy Survey (g- and z-bands) and CFHT R-band imaging (left panel) prior to the SN explosion. The following panels show the Pan-STARRS images used for image subtraction (center left), LT gri images from 2025 October 4 (center right), and the four lensed images of SN 2025wny after subtraction of the reference image (right panel).
Paper: The Dynamical Interaction between Low-mass Planets and Dust Coagulation
Authors: Qiang Hou, Cong Yu, Shu-ichiro Inutsuka
Figure caption: Panels (a) and (b): the real and imaginary parts of kx for the quasi-drift mode and CMs. The solid dots represent our numerical results. Panels (c)–(f): the wave functions normalized by their respective equilibrium values. The parameters are set as τ = 0.1, ky = 0.3, and α = 1 × 10−3. In those four panels, the blue, orange, and gray lines represent the real part, imaginary part, and amplitude, respectively.
Paper: Discovery of SN 2025wny: A Strongly Gravitationally Lensed Superluminous Supernova at z = 2.01
Authors: Joel Johansson, Daniel A. Perley, Ariel Goobar, Jacob L. Wise, Yu-Jing Qin, Zoë McGrath, Steve Schulze, Cameron Lemon, Anjasha Gangopadhyay, Konstantinos Tsalapatas, Igor Andreoni, Eric C. Bellm, Joshua S. Bloom, Richard Dekany, Suhail Dhawan, Claes Fransson, Christoffer Fremling, Matthew J. Graham, Steven L. Groom, Daniel Gruen, Xander J. Hall, George Helou, Mansi Kasliwal, Russ R. Laher, Ragnhild Lunnan, Ashish A. Mahabal, Adam A. Miller, Edvard Mörtsell, Jakob Nordin, Jacob Osman Hjortlund, R. Michael Rich, Reed L. Riddle, Avinash Singh, Jesper Sollerman, Alice Townsend, Lin Yan
Figure caption: Keck/LRIS spectrum of SN 2025wny (black line) compared to HST spectra of the low-z SLSNe-I 2016eay (a.k.a Gaia16apd; blue line) and SN 2017egm (green line) and a Magellan/LDSS3 spectrum of high-z DES16C2nm (red line). All spectra are scaled by their luminosity distance relative to SN 2025wny, and for clarity SNe 2016eay and 2017egm have been offset by multiplicative factors of 20 and 15, respectively.
Paper: Discovery of SN 2025wny: A Strongly Gravitationally Lensed Superluminous Supernova at z = 2.01
Authors: Joel Johansson, Daniel A. Perley, Ariel Goobar, Jacob L. Wise, Yu-Jing Qin, Zoë McGrath, Steve Schulze, Cameron Lemon, Anjasha Gangopadhyay, Konstantinos Tsalapatas, Igor Andreoni, Eric C. Bellm, Joshua S. Bloom, Richard Dekany, Suhail Dhawan, Claes Fransson, Christoffer Fremling, Matthew J. Graham, Steven L. Groom, Daniel Gruen, Xander J. Hall, George Helou, Mansi Kasliwal, Russ R. Laher, Ragnhild Lunnan, Ashish A. Mahabal, Adam A. Miller, Edvard Mörtsell, Jakob Nordin, Jacob Osman Hjortlund, R. Michael Rich, Reed L. Riddle, Avinash Singh, Jesper Sollerman, Alice Townsend, Lin Yan
Figure caption: Rest-frame UV light curve of image A of SN 2025wny (from the ZTF r-band) compared to a set of comparison SLSN curves in similar rest-frame bands: SN 2017egm, SN 2016eay, PS1-13or, DES15E2mlf, and DES16C2nm. The observation times of the spectra used for the comparison in Figure 3 are marked with an “S”.
Paper: Discovery of SN 2025wny: A Strongly Gravitationally Lensed Superluminous Supernova at z = 2.01
Authors: Joel Johansson, Daniel A. Perley, Ariel Goobar, Jacob L. Wise, Yu-Jing Qin, Zoë McGrath, Steve Schulze, Cameron Lemon, Anjasha Gangopadhyay, Konstantinos Tsalapatas, Igor Andreoni, Eric C. Bellm, Joshua S. Bloom, Richard Dekany, Suhail Dhawan, Claes Fransson, Christoffer Fremling, Matthew J. Graham, Steven L. Groom, Daniel Gruen, Xander J. Hall, George Helou, Mansi Kasliwal, Russ R. Laher, Ragnhild Lunnan, Ashish A. Mahabal, Adam A. Miller, Edvard Mörtsell, Jakob Nordin, Jacob Osman Hjortlund, R. Michael Rich, Reed L. Riddle, Avinash Singh, Jesper Sollerman, Alice Townsend, Lin Yan
Figure caption: Selection of absorption lines identified in the Keck/LRIS spectrum of SN 2025wny, used to determine the SN host redshift (z = 2.0104 ± 0.0005).
Paper: Ocean Circulation on Tide-locked Lava Worlds: 3D Modeling with a Simple Boundary Iteration Method
Authors: Jun Yang, Chengyao Tang, Zimu Wang, Yanhong Lai, Wanying Kang
Figure caption: Results of the vertical diffusion sensitivity tests. (a) Area-mean ocean depth as a function of the diffusion coefficient, (b) the strength of zonal-mean zonal ocean current, and (c) the divergence of zonal ocean heat transport for the three different diffusion coefficients, 4 × 10−6, 4 × 10−5, and 4 × 10−4 m s−2. Note the stellar flux on the planetary surface is in the order of 106 W m−2, being about 2 orders larger than the area-mean ocean heat transport. The theoretical lines are from Table 2 in Y. Lai et al. (2024a). Panels (d)–(f): sea surface temperature (SST, color-shaded in units of K) and sea surface height (SSH, contour lines in unit of m) (d), lava temperature along the equator (e), and horizontal ocean currents (vectors) and the strength of the currents (color shading) in the experiment with an diffusivity of 4 × 10−4 m s−2 (f). Panels (g)–(i): same as panels (d)–(f) but for the experiment of 4 × 10−6 m s−2. The contour interval is 2 m in (d) but 0.2 m in (g), and the reference vector is 1.0 m s−1 in (f) but 0.1 m s−1 in (i). When the vertical diffusivity is very small, the ocean currents and heat transports are weak, and the largest SSH is very close to the substellar point. When the vertical diffusivity increases, the ocean becomes deeper, the ocean currents and associated horizontal and vertical heat transports become stronger, the value of SSH increases, and the largest SSH moves from the equator to the extratropics.
Paper: Ocean Circulation on Tide-locked Lava Worlds: 3D Modeling with a Simple Boundary Iteration Method
Authors: Jun Yang, Chengyao Tang, Zimu Wang, Yanhong Lai, Wanying Kang
Figure caption: Ocean currents in the control experiment. (a) Horizontal currents (u, v) at the sea surface; (b) horizontal currents at 99 m depth; (c) zonal-vertical section (u, w) along the equator; (d) zonal-vertical section at 40°S; (e) meridional-vertical section (v, w) along 0° longitude; (f) meridional-vertical section along 40° longitude, in the west of the substellar point. Note that the color bar range (representing velocity magnitude, ﹩\sqrt{{u}^{2}+{v}^{2}+{w}^{2}}﹩) and the reference vector length vary between different panels.
Paper: Ocean Circulation on Tide-locked Lava Worlds: 3D Modeling with a Simple Boundary Iteration Method
Authors: Jun Yang, Chengyao Tang, Zimu Wang, Yanhong Lai, Wanying Kang
Figure caption: Lava temperature and ocean depth in the control experiment with a vertical diffusivity of 4 × 10−5 m2 s−1. (a) SST (in units of K, color-shaded) and surface surface height (in units of m, contour lines); (b), (c) temperature slices at 99 and 297 m depth; (d) equatorial cross-section temperature; (e) meridional cross-section temperature at the substellar longitude (0°); (f) 3D perspective view of ocean depth (in units of m). On the nightside and near the terminators, the ocean depth is zero everywhere. White areas indicate solid regions (temperature below 2000 K), which are not included in the simulation domain (the same applies to all following figures).
Paper: Ocean Circulation on Tide-locked Lava Worlds: 3D Modeling with a Simple Boundary Iteration Method
Authors: Jun Yang, Chengyao Tang, Zimu Wang, Yanhong Lai, Wanying Kang
Figure caption: Sensitivity tests of the boundary iteration method under four different initial conditions. The top row shows the control case, and the other rows show variations in initial ocean temperature, depth, and current strength. The first column displays the initial condition for each test, while the remaining columns show intermediate and final states during the iteration process. The colored regions represent the active simulation domain; white areas are not simulated. Although the initial conditions vary significantly, all experiments roughly converge to similar equilibrium states with an ocean depth of approximately 200–400 m along the equator. Note: the y-axis range differs in the rightmost column.
Paper: Ocean Circulation on Tide-locked Lava Worlds: 3D Modeling with a Simple Boundary Iteration Method
Authors: Jun Yang, Chengyao Tang, Zimu Wang, Yanhong Lai, Wanying Kang
Figure caption: Schematic diagram of the boundary iteration method. The red star marks the substellar point. In each panel, the colored region represents the active simulation domain, while the white area is not simulated. Solid, dashed, dotted, and dotted-dashed black lines denote the simulation boundaries, and the red curve indicates the 2000 K isotherm (freezing point). At each iteration, the new simulation boundary is defined as the midpoint between the 2000 K isotherm and the previous iteration’s boundary. Iterations continue until the simulation boundaries converge. Initial lateral and bottom ocean boundaries are arbitrarily defined (see Figure 2).
Paper: The Dynamical Interaction between Low-mass Planets and Dust Coagulation
Authors: Qiang Hou, Cong Yu, Shu-ichiro Inutsuka
Figure caption: 2D morphologies illustrating the effects of a planet on dust coagulation, with τ = 0.1, α = 1 × 10−4, and εeff = 1.0 except for panels (d), (e), and (f). The x- and y-axes correspond to the radial and azimuthal directions, respectively. Subtitles within each panel indicate the specific parameters used. Panel (a) shows the perturbations in stopping time. Panel (b) shows the perturbations in dust size. Panels (c) and (d) provide the zoomed-in views of the dust size perturbations for τ = 0.1 and τ = 0.05, respectively. Panel (e) shows the dust size perturbations for α = 1 × 10−3. Panel (f) shows the dust size perturbations with εeff = 0.5. Panel (g) shows the dust density perturbations with εeff = 0.5. Gray solid lines with arrows: those panels indicate the equilibrium streamlines. The colorbar denotes the normalized values. For comparison, the values in panels (b)–(f) are normalized by their common maximum value.
Paper: The Dynamical Interaction between Low-mass Planets and Dust Coagulation
Authors: Qiang Hou, Cong Yu, Shu-ichiro Inutsuka
Figure caption: Dusty torque on the planet with different values of εeff and α. Lines with different colors correspond to different α as the legend labels. Dashed lines represent the results with εeff = 0, i.e., without dust coagulation. Dotted–dashed lines represent the results with εeff = 0.5. Solid lines represent the results with εeff = 1.0, i.e., perfect sticking.
Paper: The Dynamical Interaction between Low-mass Planets and Dust Coagulation
Authors: Qiang Hou, Cong Yu, Shu-ichiro Inutsuka
Figure caption: Disk torque map with perfect sticking. The y-axis represents gaseous turbulent strength. The black solid line marks the zero-torque contour, while three gray solid lines show the zero-torque contours with different sticking efficiency.
Paper: Ocean Circulation on Tide-locked Lava Worlds: 3D Modeling with a Simple Boundary Iteration Method
Authors: Jun Yang, Chengyao Tang, Zimu Wang, Yanhong Lai, Wanying Kang
Figure caption: Results of the simulated ocean circulation. Same as Figure 4 in the main text, but for the first sensitivity experiment, within which the initial ocean depth, ocean temperature, and ocean current speed are 10 km, 3000 K, and 0, respectively.
Paper: Ocean Circulation on Tide-locked Lava Worlds: 3D Modeling with a Simple Boundary Iteration Method
Authors: Jun Yang, Chengyao Tang, Zimu Wang, Yanhong Lai, Wanying Kang
Figure caption: Results of the simulated ocean circulation. Same as Figure 4 in the main text, but for the second sensitivity experiment, within which the initial ocean depth, ocean temperature and ocean current speed are 2 km, 273 K, and 0, respectively.
Paper: Unveiling Chemical Enrichment in the A2029 Core with XRISM, XMM-Newton, and Chandra
Authors: Arnab Sarkar, Eric D. Miller, Brian McNamara, Ming Sun, Richard Mushotzky, Stefano Ettori, Lorenzo Lovisari, Irina Zhuravleva, Naomi Ota
Figure caption: Top left: XRISM/Resolve full-array spectrum of A2029 (except pixels 12 and 27) from the central region, shown along with the best-fit model (red: total; blue: NXB). Top right: XRISM/Xtend spectrum from the central ﹩{3}^{{\prime} }\times {3}^{{\prime} }﹩ region (matching the Resolve FOV) of A2029 with best-fit model (red). Middle left: EPIC/MOS1 (black), EPIC/MOS2 (red), and EPIC/pn (blue) spectra from the similar region used for Xtend, with best-fit models. Middle right: RGS1 (black) and RGS2 (red) first-order spectra extracted from a cross-dispersion region of ﹩0\mathop{.}\limits^{\unicode{x000b0}}8﹩, with best-fit models. Bottom: Chandra/ACIS spectrum of A2029 from the central ﹩{3}^{{\prime} }\times {3}^{{\prime} }﹩ region, with the best-fit model. For each instrument, the spectra from multiple observations have been combined to plot a single spectrum. In all panels, the lower subpanels show the ratio between the observed data and the best-fit total models.
Paper: Unveiling Chemical Enrichment in the A2029 Core with XRISM, XMM-Newton, and Chandra
Authors: Arnab Sarkar, Eric D. Miller, Brian McNamara, Ming Sun, Richard Mushotzky, Stefano Ettori, Lorenzo Lovisari, Irina Zhuravleva, Naomi Ota
Figure caption: Top left: XRISM/Xtend count image of A2029 in the 0.6–10 keV energy band. Top right: exposure-corrected, background-subtracted Chandra ACIS-I image of A2029 in the 0.5–7 keV energy band. Black surface brightness contours highlight the cold-gas sloshing spiral in the cluster center. Bottom: exposure-corrected, QPB-subtracted, merged XMM-Newton EPIC image of A2029. White boxes in all three panels represent the XRISM/Resolve FOVs used to extract spectra from all three instruments.
Paper: Unveiling Chemical Enrichment in the A2029 Core with XRISM, XMM-Newton, and Chandra
Authors: Arnab Sarkar, Eric D. Miller, Brian McNamara, Ming Sun, Richard Mushotzky, Stefano Ettori, Lorenzo Lovisari, Irina Zhuravleva, Naomi Ota
Figure caption: Top: absolute elemental abundance of different light and heavy elements in the central region of A2029 measured using XRISM (Resolve+Xtend), XMM-Newton (MOS+pn, RGS), and Chandra (ACIS). Bottom: abundance ratios of different elements with respect to Fe (X/Fe). Gray squares and gray bow ties represent the X/Fe for CHEERS samples of clusters/groups (F. Mernier et al. 2018b) and the Perseus Cluster (A. Simionescu et al. 2019), respectively.
Paper: Unveiling Chemical Enrichment in the A2029 Core with XRISM, XMM-Newton, and Chandra
Authors: Arnab Sarkar, Eric D. Miller, Brian McNamara, Ming Sun, Richard Mushotzky, Stefano Ettori, Lorenzo Lovisari, Irina Zhuravleva, Naomi Ota
Figure caption: Average elemental abundance ratios of different elements at the A2029 center (black data) fitted with CCSN (magenta; K. Nomoto et al. 2013) and SN Ia (blue) yield models. Top left: SN Ia yield assuming a pure deflagration explosion mechanism (M. Fink et al. 2014); top right: SN Ia yield assuming a delayed-detonation explosion mechanism (I. R. Seitenzahl et al. 2013); bottom left: SN Ia yield assuming a single-degenerate explosion mechanism (S. A. Sim et al. 2010); bottom right: SN Ia yield assuming a double-degenerate explosion mechanism (R. Pakmor et al. 2012).
Paper: Unveiling Chemical Enrichment in the A2029 Core with XRISM, XMM-Newton, and Chandra
Authors: Arnab Sarkar, Eric D. Miller, Brian McNamara, Ming Sun, Richard Mushotzky, Stefano Ettori, Lorenzo Lovisari, Irina Zhuravleva, Naomi Ota
Figure caption: Average elemental abundance ratios of different elements at the A2029 center (black data) fitted with CCSN (magenta; K. Nomoto et al. 2013) and SN Ia yields assuming a double-degenerate explosion mechanism (R. Pakmor et al. 2012) and Ca-gap transients (R. Waldman et al. 2011).
Paper: Revealing an Oscillating and Contracting Compact Corona near the Event Horizon of the Supermassive Black Hole in 1ES 1927+654
Authors: Qing-Cang Shui, Shu Zhang, Shuang-Nan Zhang, Hua Feng, Yu-Peng Chen, Long Ji, Ling-Da Kong, Liang Zhang, Jing-Qiang Peng, Peng-Ju Wang
Figure caption: rms–energy and lag–energy spectra of the X-ray QPO in 1ES 1927+654 and corresponding fitting models. The error bars represent 1σ confidence intervals. The black dashed lines show the best-fit results from the joint fitting of time-averaged spectra and the the QPO rms–energy and lag–energy spectra with the time-dependent Comptonization model. (A) QPO rms–energy spectra. The black stars represent values from conventional PSD modeling using a Lorentzian function; the colored circles show results from the phase-resolved analysis. (B) QPO lag–energy spectra with the 0.3–0.5 keV energy band as the reference (gray shaded region), defined as zero lag. The uncertainty in the reference band is based on the arithmetic mean of the 1σ errors in other energy bands. The blue solid lines represent a model with a soft Plank function and a hard logarithmic function, and the blue dotted lines show the corresponding hard logarithmic function.