adsabs/AstroCLIMB huggingface dataset:
Paper: TiDES: The 4MOST Time Domain Extragalactic Survey
Authors: C. Frohmaier, M. Vincenzi, M. Sullivan, S.F. Hönig, M. Smith, H. Addison, T. Collett, G. Dimitriadis, R. S. Ellis, P. Gandhi, O. Graur, I. Hook, L. Kelsey, Y.-L. Kim, C. Lidman, K. Maguire, L. Makrygianni, B. Martin, A. Möller, R. C. Nichol, M. Nicholl, P. Schady, B. D. Simmons, S. J. Smartt, E. Tempel, P. Wiseman
Figure caption: The distribution of light curve trigger phases and the phase of spectroscopic follow-up by 4MOST is shown, broken down into transient subtypes. All phases are measured relative to the light curve peak. The methodology used to generate this figure is identical to that presented in Figure 7.
Paper: Breaking Gyrochronology through the Collapse of Coronal Winds
Authors: Michaël Lévesque, Paul Charbonneau
Figure caption: Angular momentum loss rate (top panel) and mass-loss rate (bottom panel) as a function of coronal base temperature in WD wind solutions with various values of the polytropic index α, as color-coded. The vertical dashed lines indicate the corresponding hydrostatic corona limiting temperature. In all cases, the rotation rate and magnetic field strength are held at their solar values, and the coronal base density is fixed at ρ0 = 1014mp m−3 in calculating the mass-loss rate.
Paper: Breaking Gyrochronology through the Collapse of Coronal Winds
Authors: Michaël Lévesque, Paul Charbonneau
Figure caption: Top panel: radial profiles of wind variables for an α = 1.125 WD solution with solar rotation and magnetic field strength and a “low” coronal base temperature T0 = 1.23 × 106 K. The black dashed line shows the ur(r) profile for a nonrotating, unmagnetized coronal wind of the same base temperature and polytropic index. The two filled dots indicate the corresponding Alfvén points. The bottom panel shows the corresponding acceleration terms in the momentum equation: gravity, pressure, centrifugal, and magnetic force, as labeled. The solid blue line gives the resulting Lagrangian acceleration. Note how centrifugal and magnetic forces dominate beyond the sonic point (blue inverted triangle).
Paper: Breaking Gyrochronology through the Collapse of Coronal Winds
Authors: Michaël Lévesque, Paul Charbonneau
Figure caption: Variations of the Alfvén radius rA (red), base flow speed ur0 (blue), and angular momentum loss rate ﹩\dot{J}﹩ (green) vs. coronal base temperature, as obtained from a sequence of α = 1.1 WD wind solutions at fixed solar rotation rate and surface magnetic field strength.
Paper: Breaking Gyrochronology through the Collapse of Coronal Winds
Authors: Michaël Lévesque, Paul Charbonneau
Figure caption: Radial profiles of wind (solid lines) and Alfvén (dashed lines) speed from WD solutions with rotation rates Ω/Ω⊙ = 0.6 (blue), 1 (green), and 2 (orange). In all cases, r0/R⊙ = 1.15, T0 = 1.5 × 106 K, α = 1.1, and Br0 ∝ Ω.
Paper: Breaking Gyrochronology through the Collapse of Coronal Winds
Authors: Michaël Lévesque, Paul Charbonneau
Figure caption: Two representative simulation runs of the K. B. MacGregor & M. Brenner (1991) spin-down model for fixed coupling timescale τc = 107 yr and initial conditions on the ZAMS Ω/Ω⊙ = 5 and 25. Solid (dashed–dotted) lines give the angular velocities of the convective envelope (radiative core) in each case. The dashed line is the Skumanich t−1/2 law pinned to the present-day Sun.
Paper: On the Formation of Star-forming Galaxies Having Anomalously Low-metallicity Regions: The Role of Galaxy Interaction and Circumgalactic Medium/Intergalactic Medium Accretion
Authors: Yibo Cao, Zhizheng Pan
Figure caption: Bar plot showing the LSS environment distribution for nontidal normal SF galaxies and nontidal ALM galaxies. The LSS environment is categorized into four groups: cluster, filament, sheet, and void. For each sample, the number marked within the bar shows the fraction of galaxies residing in that LSS environment. The error bar in purple indicates the standard deviation of the fractions calculated from 10 control samples, while the error bar in red indicates the 1σ confidence interval of the fraction for nontidal ALM galaxies when treated as beta distribution.
Paper: On the Formation of Star-forming Galaxies Having Anomalously Low-metallicity Regions: The Role of Galaxy Interaction and Circumgalactic Medium/Intergalactic Medium Accretion
Authors: Yibo Cao, Zhizheng Pan
Figure caption: The gas-phase metallicity gradient as a function of stellar mass. Nontidal ALM, tidal ALM, and nontidal normal SFGs are shown in blue, orange, and purple symbols, respectively. The shaded region indicates the 16–84 percentile for each sample. The running medians of the samples are shown in solid lines.
Paper: On the Formation of Star-forming Galaxies Having Anomalously Low-metallicity Regions: The Role of Galaxy Interaction and Circumgalactic Medium/Intergalactic Medium Accretion
Authors: Yibo Cao, Zhizheng Pan
Figure caption: Bar plots showing the morphological type distributions of nontidal normal SFGs and nontidal ALM galaxies. The height of the blue thick bar indicates the mean value of the type fraction for control sample selected from nontidal normal SF galaxies, and the height of the orange thick bar is the type fraction for nontidal ALM galaxies. The error bar in purple represents the standard deviation of the fraction for the control sample, while the error bar in red indicates the 1σ confidence interval calculated for a binomial population (E. Cameron 2011).
Paper: On the Formation of Star-forming Galaxies Having Anomalously Low-metallicity Regions: The Role of Galaxy Interaction and Circumgalactic Medium/Intergalactic Medium Accretion
Authors: Yibo Cao, Zhizheng Pan
Figure caption: Local matter density distributions of nontidal normal SF galaxies (translucent blue) and the distribution of nontidal ALM galaxies (translucent orange). Each distribution is normalized so that the sum of the heights of each category equals to 1. The error bar in purple represents the standard deviation of the fraction for control sample in each bin, while the error bar in red indicates the 1σ confidence interval of the fraction for nontidal ALM galaxies in each bin when treated as beta distribution. The dashed lines indicate the median values of the two histograms.
Paper: On the Formation of Star-forming Galaxies Having Anomalously Low-metallicity Regions: The Role of Galaxy Interaction and Circumgalactic Medium/Intergalactic Medium Accretion
Authors: Yibo Cao, Zhizheng Pan
Figure caption: Left: tidal fraction as a function of stellar mass. ALM and normal SFGs are shown in orange and blue, respectively. Right: the average tidal fractions for ALM and normal SFGs. The error bar is the 1σ confidence interval calculated for a binomial population (E. Cameron 2011).
Paper: On the Formation of Star-forming Galaxies Having Anomalously Low-metallicity Regions: The Role of Galaxy Interaction and Circumgalactic Medium/Intergalactic Medium Accretion
Authors: Yibo Cao, Zhizheng Pan
Figure caption: Relation between SFR and M*. ALM galaxies and normal SFGs are shown in orange and blue symbols, respectively. For each sample, the running median value is shown in solid line, and the shaded region indicates the 16–84 percentile.
Paper: On the Formation of Star-forming Galaxies Having Anomalously Low-metallicity Regions: The Role of Galaxy Interaction and Circumgalactic Medium/Intergalactic Medium Accretion
Authors: Yibo Cao, Zhizheng Pan
Figure caption: Similar to Figure 4, but with the O3N2 calibrator.
Paper: On the Formation of Star-forming Galaxies Having Anomalously Low-metallicity Regions: The Role of Galaxy Interaction and Circumgalactic Medium/Intergalactic Medium Accretion
Authors: Yibo Cao, Zhizheng Pan
Figure caption: Similar to Figure 6, but with the O3N2 calibrator.
Paper: On the Formation of Star-forming Galaxies Having Anomalously Low-metallicity Regions: The Role of Galaxy Interaction and Circumgalactic Medium/Intergalactic Medium Accretion
Authors: Yibo Cao, Zhizheng Pan
Figure caption: Similar to Figure 5, but with the O3N2 calibrator.
Paper: Long-term Simultaneous 2.25/8.60 GHz Monitoring of the Newly Discovered Repeating FRB 20240114A
Authors: Xiao-Wei Wang,  啸 威 王, Zhen Yan,  振 闫, Zhi-Qiang Shen,  志 强 沈, Ke-Jia Lee,  柯 伽 李, Ya-Jun Wu,  亚 军 吴, Rong-Bing Zhao,  融 冰 赵, Jie Liu,  杰 刘, Rui Wang,  睿 王, Kuo Liu,  阔 刘, Yuan-Chuan Zou,  远 川 邹, Zhi-Peng Huang, 志 鹏 黄, Chu-Yuan Zhang,  楚 原 张, Fan Yang,  帆 杨, Zhen-Long Liao,  振 龙 廖, Yang-Yang Lin,  扬 洋 林
Figure caption: The two-dimensional posterior distribution of the Weibull shape parameter k and burst rate r for the observation on 2024 July 23 (O20). The blue contours in the bottom left subpanel represent the 68%, 95%, and 99% confidence regions, with the maximum-likelihood point marked by the orange cross. The marginal distributions of r and k are shown in the bottom right and top left subpanels, respectively. The shaded orange regions represent the 68%, 95%, and 99% confidence levels.
Paper: Long-term Simultaneous 2.25/8.60 GHz Monitoring of the Newly Discovered Repeating FRB 20240114A
Authors: Xiao-Wei Wang,  啸 威 王, Zhen Yan,  振 闫, Zhi-Qiang Shen,  志 强 沈, Ke-Jia Lee,  柯 伽 李, Ya-Jun Wu,  亚 军 吴, Rong-Bing Zhao,  融 冰 赵, Jie Liu,  杰 刘, Rui Wang,  睿 王, Kuo Liu,  阔 刘, Yuan-Chuan Zou,  远 川 邹, Zhi-Peng Huang, 志 鹏 黄, Chu-Yuan Zhang,  楚 原 张, Fan Yang,  帆 杨, Zhen-Long Liao,  振 龙 廖, Yang-Yang Lin,  扬 洋 林
Figure caption: Scaled burst rates as a function of frequency, shown for two time periods: 2024 January–February (blue) and 2024 May–July (red). The horizontal bars indicate the frequency coverage of the corresponding observations. The fitted power-law models are plotted as dashed lines. The upper limit derived from the TMRT 8.60 GHz observations during 2024 January–February is split into two parts to account for the suboptimal sensitivity in a subset of observations (O1–5; see Section 2) due to the pointing offsets.
Paper: Long-term Simultaneous 2.25/8.60 GHz Monitoring of the Newly Discovered Repeating FRB 20240114A
Authors: Xiao-Wei Wang,  啸 威 王, Zhen Yan,  振 闫, Zhi-Qiang Shen,  志 强 沈, Ke-Jia Lee,  柯 伽 李, Ya-Jun Wu,  亚 军 吴, Rong-Bing Zhao,  融 冰 赵, Jie Liu,  杰 刘, Rui Wang,  睿 王, Kuo Liu,  阔 刘, Yuan-Chuan Zou,  远 川 邹, Zhi-Peng Huang, 志 鹏 黄, Chu-Yuan Zhang,  楚 原 张, Fan Yang,  帆 杨, Zhen-Long Liao,  振 龙 廖, Yang-Yang Lin,  扬 洋 林
Figure caption: The distribution of waiting times of TMRT-detected bursts from FRB 20240114A. Note that all waiting times are calculated using one TOA per burst, regardless of subburst structure (see Section 3 for the definition of TOA). The green line represents the best-fitting LN function for waiting times above 0.1 s, which peaks at 1019 ± 66 s. The red vertical dashed line indicates the median duration of TMRT observations (∼7200 s).
Paper: Long-term Simultaneous 2.25/8.60 GHz Monitoring of the Newly Discovered Repeating FRB 20240114A
Authors: Xiao-Wei Wang,  啸 威 王, Zhen Yan,  振 闫, Zhi-Qiang Shen,  志 强 沈, Ke-Jia Lee,  柯 伽 李, Ya-Jun Wu,  亚 军 吴, Rong-Bing Zhao,  融 冰 赵, Jie Liu,  杰 刘, Rui Wang,  睿 王, Kuo Liu,  阔 刘, Yuan-Chuan Zou,  远 川 邹, Zhi-Peng Huang, 志 鹏 黄, Chu-Yuan Zhang,  楚 原 张, Fan Yang,  帆 杨, Zhen-Long Liao,  振 龙 廖, Yang-Yang Lin,  扬 洋 林
Figure caption: Left panel: the cumulative burst energy distribution. The solid black line denotes the best-fitting power-law function to bursts above the completeness threshold. Right panel: the power-law index γ as a function of energy, determined via the maximum-likelihood estimation. The best-fitting power-law index γ and its uncertainty are indicated by the horizontal black solid line and the gray shaded regions, respectively. The vertical gray dashed line in each panel represents the completeness threshold.
Paper: Long-term Simultaneous 2.25/8.60 GHz Monitoring of the Newly Discovered Repeating FRB 20240114A
Authors: Xiao-Wei Wang,  啸 威 王, Zhen Yan,  振 闫, Zhi-Qiang Shen,  志 强 沈, Ke-Jia Lee,  柯 伽 李, Ya-Jun Wu,  亚 军 吴, Rong-Bing Zhao,  融 冰 赵, Jie Liu,  杰 刘, Rui Wang,  睿 王, Kuo Liu,  阔 刘, Yuan-Chuan Zou,  远 川 邹, Zhi-Peng Huang, 志 鹏 黄, Chu-Yuan Zhang,  楚 原 张, Fan Yang,  帆 杨, Zhen-Long Liao,  振 龙 廖, Yang-Yang Lin,  扬 洋 林
Figure caption: The width–fluence distribution for our sample of 155 bursts detected at 2.25 GHz (blue circles). The blue dashed line represents the 7σ detection threshold of the S/N of the TMRT for bursts with different temporal widths. We also show bursts detected by MeerKAT (J. Tian et al. 2024b) at the L band (856−1712 MHz) and the UHF band (544−1088 MHz), represented by green and orange triangles, respectively. The top and right panels show the histograms of the fluence and width distributions, respectively.
Paper: Long-term Simultaneous 2.25/8.60 GHz Monitoring of the Newly Discovered Repeating FRB 20240114A
Authors: Xiao-Wei Wang,  啸 威 王, Zhen Yan,  振 闫, Zhi-Qiang Shen,  志 强 沈, Ke-Jia Lee,  柯 伽 李, Ya-Jun Wu,  亚 军 吴, Rong-Bing Zhao,  融 冰 赵, Jie Liu,  杰 刘, Rui Wang,  睿 王, Kuo Liu,  阔 刘, Yuan-Chuan Zou,  远 川 邹, Zhi-Peng Huang, 志 鹏 黄, Chu-Yuan Zhang,  楚 原 张, Fan Yang,  帆 杨, Zhen-Long Liao,  振 龙 廖, Yang-Yang Lin,  扬 洋 林
Figure caption: Top panel: the burst profile of burst B31 at 2.25 GHz (black line) and 8.60 GHz (gray line). Bottom panel: the dynamic spectrum of burst B31 at 2.25 and 8.60 GHz after correcting for the dispersion delay between the two observing frequencies. The horizontal white lines, with red markers on the left side, represent masked channels. For visual purposes, the intensity value of the dynamic spectrum is saturated at the 2nd and 98th percentiles.
Paper: The Cosmic Shoreline Revisited: A Metric for Atmospheric Retention Informed by Hydrodynamic Escape
Authors: Xuan Ji, 纪璇, Richard D. Chatterjee, Brandon Park Coy, Edwin Kite
Figure caption: Cosmic shoreline revisited: critical instellations for atmospheric retention vs. planetary escape velocity across different escape models/compositions binned by host-star mass and probing a range of volatile abundances. The right y-axis also shows the corresponding equilibrium temperature (Teq), assuming zero albedo and full heat redistribution. The top row shows results for CO2-dominated atmospheres, the middle row shows CH4-dominated atmospheres, and the bottom row shows N2-dominated atmospheres. Each column corresponds to a specific range of host stellar masses. Blue, yellow, and red lines indicate a 90% probability of atmosphere retention with initial volatile fractions of 10−4, 10−3, and 10−2 of the planetary mass, respectively. The shaded regions in blue, yellow, and red represent a 50-99% probability of atmosphere retention. The hatched region above the 50% red line represents conditions where planets are unlikely to retain an atmosphere even if volatile-rich. For comparison, the thick gray line reproduces the XUV-driven cosmic shoreline from Figure 2 of K. J. Zahnle & D. C. Catling (2017), with cumulative XUV flux converted to bolometric flux to match our y-axis, using the relation ﹩S={F}_{\,\rm{XUV}\,}{({L}_{* }/{L}_{\odot })}^{0.6}﹩ (their Equation (27)). The horizontal dashed gray lines mark the runaway greenhouse limit from R. Kopparapu et al. (2013). Venus (♀) and Earth (⊕) are plotted for reference. The symbols mark exoplanet targets from four different samples (Section 4.3.1). For planets with both radius and mass measurements, the density-scaled to that of a planet with Earth-like composition (ρ⊕,s(Rp))-is color-coded. Lower densities may suggest thicker atmospheres or higher volatile content. Planets with confirmed (55 Cnc e) and tentative (TOI-431 b, LHS 1478 b) atmosphere detections are labeled. Crosses denote planets with thick atmosphere ruled out: TRAPPIST-1c, b, GJ 1132 b, GJ 1252 b, LTT 1445 A b, GJ 486 b, TOI-1468 b, GJ 367 b, and TOI-1685 b (left to right). See Table 3 and Section 4.3.2 for planet-by-planet details.
Paper: The Cosmic Shoreline Revisited: A Metric for Atmospheric Retention Informed by Hydrodynamic Escape
Authors: Xuan Ji, 纪璇, Richard D. Chatterjee, Brandon Park Coy, Edwin Kite
Figure caption: How the cosmic shoreline shapes the trend of ratioed density (ρ/ρ⊕,s) for different assumptions of solid-body density distribution (Scenario (a) and (b) as seen in Table 4). Panels (a) and (b) present scatter plots of a subset of 103 planets, plotted as planetary mass (Mp) against equilibrium temperature(Teq)—an alternative representation of the traditional cosmic shoreline format, since vesc scales with Mp, and Teq is derived from instellation (S/S0). The dots are color-coded by the ratioed density with the upper-limit estimate, where atmosphere has two layers and Ptransit = 10−6 bar. In (a), the cosmic shoreline shapes the boundary between yellow dots (bare rocks without atmosphere) and black dots (planets where the radius-boosting effect of an atmosphere is most distinguishable). In (b), where solid-body density varies, the transition is less distinct, but a visual trend remains, with more yellow points clustered in the upper-left region (high-temperature, low-mass planets), indicating that atmospheric loss is more severe in this regime. For better visualization, the color scale is limited between 0.9 and 1.0, although actual density values can extend beyond this range. Panels (a.1) and (b.1): a bivariate histogram is computed and visualized as a heatmap, where darker colors indicate higher number density. Linear regression of ρ/ρ⊕,s as a function of equilibrium temperature (Teq) for the full 10,000-planet sample. A decreasing trend is observed, as planets at high Teq are more likely to be bare rocks with higher densities. Panels (a.2) and (b.2): linear regression of ρ/ρ⊕,s as a function of planetary mass (Mp), also showing a decreasing trend. This is because lower-mass planets are more likely to be stripped of their atmospheres, leading to a larger fraction of high-density bare rocky planets at lower masses.
Paper: The Cosmic Shoreline Revisited: A Metric for Atmospheric Retention Informed by Hydrodynamic Escape
Authors: Xuan Ji, 纪璇, Richard D. Chatterjee, Brandon Park Coy, Edwin Kite
Figure caption: Critical instellations for atmospheric retention vs. stellar mass for Earth-mass planets across different escape models/compositions and probing a range of volatile abundances. The critical bolometric instellation (﹩{S}_{\mathrm{bol}}^{* }﹩) is normalized to Earth’s insolation and stellar mass is given in units of the Sun. The right y-axis also shows the corresponding equilibrium temperature (Teq), assuming no albedo and perfect redistribution. Blue, yellow, and red lines correspond to initial volatile fractions of 10−4, 10−3, and 10−2 in planetary mass, respectively. The shaded regions represent a 50%–99% probability range of atmospheric retention output by our model, and the solid curves represent the 90% probability of atmospheric retention. For H2O atmospheres, the blue line lies below 1 S⊕. For an N2-dominated atmosphere, predictions from A. Nakayama et al. (2022, N2022) suggest that all three cosmic shorelines exceed 104 S⊕, indicating extreme resilience to atmospheric escape. In contrast, R. D. Chatterjee & R. T. Pierrehumbert (2024, CP2024) predicts less permissive cosmic shorelines. The horizontal dashed line marks the runaway greenhouse limit from R. Kopparapu et al. (2013).
Paper: The Cosmic Shoreline Revisited: A Metric for Atmospheric Retention Informed by Hydrodynamic Escape
Authors: Xuan Ji, 纪璇, Richard D. Chatterjee, Brandon Park Coy, Edwin Kite
Figure caption: Planetary thermal structure and two end-member estimates for transit radius. The thin black line denotes an isothermal atmosphere in the radiative layer, while the thick black line represents an adiabatic profile in the convective layer. The white line corresponds to the rheological transition (∼40% melt fraction) P–T relation for rock. If Tsurf > Trheo(P = Psurf), the surface is a low-viscosity magma ocean. The intersection of the thick black line with the white line marks the depth at which magma crystallizes. Volatiles are assumed to be partitioned between the magma and atmosphere, with surface pressure governed by the solubility law. The pressure level probed during a transit (Ptransit) is set to a constant value. (1) Upper-limit estimate of atmospheric height: Assumes the entire atmosphere below the RCB is fully convective, following a dry adiabatic profile. Ptransit = 10−6 bar. (2) Lower-limit estimate of atmospheric height: Assumes a radiative layer extends from the surface up to P = 100 bar. Ptransit = 0.02 bar.
Paper: The Cosmic Shoreline Revisited: A Metric for Atmospheric Retention Informed by Hydrodynamic Escape
Authors: Xuan Ji, 纪璇, Richard D. Chatterjee, Brandon Park Coy, Edwin Kite
Figure caption: Atmospheric radius boosting effect. Top: the ratio of the transit radius to the radius of the solid surface (including the magma layer if present) as a function of the initial volatile fraction (finitial). The right y-axis shows the corresponding ratioed density. Solid lines correspond to the two-layer model (Scenario (1) in Figure 5) with Ptransit = 10−6 bar, where the atmosphere consists of a convective lower layer and an isothermal upper layer beyond the radiative-convective boundary (RCB). Dashed lines represent the three-layer model (Scenario (2) in Figure 5 but with adjusted Ptransit), which includes an additional radiative layer near the surface. The lighter-colored lines indicate the same atmospheric conditions, but the transit radius is measured at Ptransit = 0.02 bar. Middle: Surface temperature for the different atmospheric scenarios described above. At T ⪆ 104 K, the silicate and Fe will expand (S. J. Lock & S. T. Stewart 2017), which is not considered in our model. Bottom: Magma ocean mass fraction for different atmospheric structures. The layered structure of the atmosphere influences the transit radius only when finitial is sufficiently high for the surface pressure to exceed 100 bar. The choice of Ptransit has a much greater impact on the derived transit radius than the atmospheric structure alone.
Paper: The Cosmic Shoreline Revisited: A Metric for Atmospheric Retention Informed by Hydrodynamic Escape
Authors: Xuan Ji, 纪璇, Richard D. Chatterjee, Brandon Park Coy, Edwin Kite
Figure caption: Atmospheric loss rates for planet of different masses orbiting a Sun-like star at t = 100 Myr for a range of escape models/compositions. For CO2-dominated and CH4-dominated atmospheres, the escape rates for varying Mp are color-coded, as indicated in the legend. For N2-dominated atmospheres, we use results from two different studies. CP24 refers to the analytical framework developed by R. D. Chatterjee & R. T. Pierrehumbert (2024), which provides rates for varying Mp, while N22 is a 1D numerical model from A. Nakayama et al. (2022), which only applies to Earth-mass planets. The shaded regions represent the range of atmospheric loss rates, including uncertainties in XUV flux. Additional uncertainties are included for specific atmospheres, such as CO2 interpolation methods, the FX/FEUV ratio (H2O atmosphere), and efficiency (ϵ) (CH4 atmosphere) (Table 2). For CH4 atmospheres, the loss rate weakly depends on Mp, whereas CO2 loss is strongly mass-dependent. For N2-dominated atmospheres, the only two studies that consider atomic line cooling show the escape rates stay constant at higher XUV flux, but the values differ significantly: A. Nakayama et al. (2022) suggests that N2-dominated atmospheres escape very slowly, whereas R. D. Chatterjee & R. T. Pierrehumbert (2024) predicts high escape rates at high XUV flux.