adsabs/AstroCLIMB huggingface dataset:
Paper: exoALMA. XVI. Predicting Signatures of Large-scale Turbulence in Protoplanetary Disks
Authors: Marcelo Barraza-Alfaro, Mario Flock, William Béthune, Richard Teague, Jaehan Bae, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Jane Huang, John D. Ilee, Andrés F. Izquierdo, Kazuhiro Kanagawa, Eric W. Koch, Geoffroy Lesur, Cristiano Longarini, Ryan A. Loomis, Ryuta Orihara, Christophe Pinte, Daniel J. Price, Giovanni Rosotti, Jochen Stadler, Gaylor Wafflard-Fernandez, Andrew J. Winter, Lisa Wölfer, Hsi-Wei Yen, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: Cartesian view of perturbations at the disk midplane for the HD (top), MHD (middle), and SGHD (bottom) simulations, with active VSI, MRI, and GI, respectively. From left to right, we show gas density perturbations, radial velocity, meridional velocity, and azimuthal velocity perturbations. The color bar limits are adjusted for each instability.
Paper: exoALMA. XVI. Predicting Signatures of Large-scale Turbulence in Protoplanetary Disks
Authors: Marcelo Barraza-Alfaro, Mario Flock, William Béthune, Richard Teague, Jaehan Bae, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Jane Huang, John D. Ilee, Andrés F. Izquierdo, Kazuhiro Kanagawa, Eric W. Koch, Geoffroy Lesur, Cristiano Longarini, Ryan A. Loomis, Ryuta Orihara, Christophe Pinte, Daniel J. Price, Giovanni Rosotti, Jochen Stadler, Gaylor Wafflard-Fernandez, Andrew J. Winter, Lisa Wölfer, Hsi-Wei Yen, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: Cartesian view of perturbations at Z ∼ 2.5H for the SGHD simulation with active GI, showing the simulation full domain. From left to right, we show gas density perturbations, radial velocity, meridional velocity, and azimuthal velocity perturbations. The dotted lines enclose the radial region of the simulation considered in our study.
Paper: Direct Evidence for r-process Nucleosynthesis in Delayed MeV Emission from the SGR 1806–20 Magnetar Giant Flare
Authors: Anirudh Patel, Brian D. Metzger, Jakub Cehula, Eric Burns, Jared A. Goldberg, Todd A. Thompson
Figure caption: Example ∼ MeV gamma-ray light curve Lγ(t) of r-process ejecta, calculated based on a multizone ejecta model from A. Patel et al. (2025), with Mej ≈ 1.2 × 10−6 M⊙, Mr ≈ 7 × 10−7 M⊙, ﹩\bar{v}=0.15c﹩, and β = 6, fΩ = 3/4. Attenuation is treated approximately following K. Hotokezaka et al. (2016) for an assumed constant opacity κγ = 0.1 cm2 g−1. Shown with a purple line is the late-time MeV light curve of the SGR 1806–20 giant flare detected by INTEGRAL ACS (S. Mereghetti et al. 2005) over the time window 675–12,000 s, with the best-fit decay rate ∝ t−1.2±0.1 in dark purple above the light curve to guide the eye (Figure 4; Appendix A). The top panel shows the cumulative fluence for an assumed source distance d = 8.7 kpc (J. L. Bibby et al. 2008) in comparison to the estimated total fluence based on measurements from ACS and RHESSI (S. E. Boggs et al. 2007; Appendix A).
Paper: Direct Evidence for r-process Nucleosynthesis in Delayed MeV Emission from the SGR 1806–20 Magnetar Giant Flare
Authors: Anirudh Patel, Brian D. Metzger, Jakub Cehula, Eric Burns, Jared A. Goldberg, Todd A. Thompson
Figure caption: Schematic figure showing the three phases of high-energy emission following magnetar giant flares, as observed in the 2004 event from SGR 1806–20. After the prompt ≲1 s gamma-ray spike, and the minutes-long pulsating X-ray tail modulated on the neutron star rotation period, a third emission phase was observed in the form a smoothly evolving MeV component (S. Mereghetti et al. 2005; S. E. Boggs et al. 2007; D. D. Frederiks et al. 2007). This delayed MeV emission rose to a peak luminosity over t ≈ 600–800 s, thereafter decaying smoothly until fading below the instrumental background a few hours later (see Appendix A and the bottom panel of Figure 2). The mechanism of baryon ejection shown in panel (a) is uncertain, but shock heating of the neutron star crust by energy released during magnetic reconnection is one possibility (C24) which would naturally lead to both a spin modulated X-ray tail and, as we argue here, delayed gamma rays from the freshly synthesized radioactive r-process material. We have illustrated the ejection as equatorial, but the direction of the mass ejection relative to the magnetic and spin axes is uncertain.
Paper: Time–Frequency Correlation of Repeating Fast Radio Bursts: Correlated Aftershocks Tend to Exhibit Downward Frequency Drifts
Authors: Shotaro Yamasaki, Tomonori Totani
Figure caption: Left: the peak frequency correlation function, ξ(Δνpeak), for bursts with short time separation Δt < 300 ms from five FRB data sets. The magenta open circles represent the results for the original νpeak data, with shaded regions indicating uncertainties due to Poisson statistics in the DD and RR pair counts. The teal open triangles represent the uncorrelated ξ, derived from the averaged results of randomly shuffled νpeak data, with the shaded regions indicating the statistical scatter among the shuffled data sets. Right: comparison of the ξ(νpeak) disparity moments, ﹩{ \mathcal M }﹩, for the original data sets with the moment distribution of the shuffled data sets. The vertical dashed lines represent the mean ﹩{{ \mathcal M }}_{{\rm{shuffle}}}﹩, and the standard z-score of ﹩{{ \mathcal M }}_{{\rm{original}}}﹩ is shown in each panel (see also Table 1 for details).
Paper: Time–Frequency Correlation of Repeating Fast Radio Bursts: Correlated Aftershocks Tend to Exhibit Downward Frequency Drifts
Authors: Shotaro Yamasaki, Tomonori Totani
Figure caption: Schematic illustration of two possible interpretations. (a) The independent aftershock scenario, where all bursts are independent yet physically correlated aftershocks. (b) The extended subburst scenario, which includes a mix of independent, physically correlated pairs as in scenario (a) and widely separated pairs that are actually part of the same event, with their broad component undetectable due to sensitivity limits. In both panels, the observed light curve is depicted by a solid blue line (with added noise), while independent events are represented by dashed lines. In panel (b), a single event with interdependent yet physically uncorrelated apparent substructures is represented by a dashed–dotted line. The shaded gray regions indicate areas below the detection threshold.
Paper: Time–Frequency Correlation of Repeating Fast Radio Bursts: Correlated Aftershocks Tend to Exhibit Downward Frequency Drifts
Authors: Shotaro Yamasaki, Tomonori Totani
Figure caption: Distribution of DD pairs (left) and two-point correlation function ξ (right) in Δt–Δνpeak phase space for different repeating FRB data sets. The vertical dashed black lines represent the Δt = 0.3 s threshold for analyzing short-time-separated pairs (see Section 3.2).
Paper: Time–Frequency Correlation of Repeating Fast Radio Bursts: Correlated Aftershocks Tend to Exhibit Downward Frequency Drifts
Authors: Shotaro Yamasaki, Tomonori Totani
Figure caption: Distribution of peak frequency data used in this study. The magenta (FAST) and light blue (Arecibo) curves represent the full-band data sets, while vertical dotted lines show the trimming condition with 30 MHz edges to minimize observational biases (see Section 2 for the details).
Paper: Time–Frequency Correlation of Repeating Fast Radio Bursts: Correlated Aftershocks Tend to Exhibit Downward Frequency Drifts
Authors: Shotaro Yamasaki, Tomonori Totani
Figure caption: Same as Figure 3, but for burst pairs with time separation 30 ms < Δt < 300 ms.
Paper: Shear–Gravity Transition Determines the Steep Velocity Dispersion–Size Relation in Molecular Clouds: Confronting Analytical Formula with Observations
Authors: Yi-Heng Xie, Guang-Xing Li
Figure caption: Left: fitted velocity dispersion–size relation in the solar vicinity. The red dashed line shows the one-dimensional σv−R relation derived from J.-X. Zhou et al. (2022). The scatters show the corresponding velocity dispersion of clouds from Y.-H. Xie et al. (2024) calculated via Equation (6) with 20% Gaussian noise. The green dashed line shows the estimated result with the parameters A = 1.94 and f = 0.96 of Equation (1). The color of scatters represents the σv contribution ratio between self-gravity and shear calculated via Equation (8). The red and blue ellipses show the gravity-dominated and shear-dominated regions, respectively. Right: contribution ratio between self-gravity and shear as a function of cloud size. The green line shows where self-gravity and shear contribute equally to velocity dispersion. The yellow region represents the transition scale of  ∼100 pc. The background gray colormap shows the kernel density estimation result.
Paper: Shear–Gravity Transition Determines the Steep Velocity Dispersion–Size Relation in Molecular Clouds: Confronting Analytical Formula with Observations
Authors: Yi-Heng Xie, Guang-Xing Li
Figure caption: Locations of shear-dominated and gravity-dominated clouds in the Milky Way disk. The map shows the cloud spatial distribution projected on the Galactic mid-plane (X–Y plane). The color of clouds refers to the velocity dispersion contribution ratio between gravity and shear calculated via Equation (8).
Paper: Shear–Gravity Transition Determines the Steep Velocity Dispersion–Size Relation in Molecular Clouds: Confronting Analytical Formula with Observations
Authors: Yi-Heng Xie, Guang-Xing Li
Figure caption: Virial parameter as a function of cloud size. The blue dashed line shows the fitting result. The green solid line represents where clouds are in virial equilibrium (αvir = 2).
Paper: Angular Momentum Transport by Internal Gravity Waves across Age
Authors: T. M. Rogers, R. P. Ratnasingam
Figure caption: (a) Time-averaged Reynolds stress (second term in (4)) as a function of radius for all ages. Averaged over the last 5 × 106 s for each model, i.e., from 1 × 107 to 1.5 × 107 s. (b) Absolute value of the angular momentum luminosity, as defined in S. Talon & C. Charbonnel (2003). (c) Time-averaged Reynolds stress for Xc = 0.69 for the same time interval shown in (a) (solid line) and for 3–4 × 107 s (dotted), 4–5 × 107 s (dashed), and 5–6 × 107 s. All quantities are in cgs units. The data for (a) and (b) is available on Zenodo doi:10.5281/zenodo.15044247.
Paper: Angular Momentum Transport by Internal Gravity Waves across Age
Authors: T. M. Rogers, R. P. Ratnasingam
Figure caption: (a) Time- and longitude-averaged angular velocity. Time-averaging is done from 1 to 1.5 × 107 s for all models, with different colors representing different ages, as seen in the legend. The dotted part of the Xc = 0.69 line represents a negative angular velocity. (b) Rotational frequency as a function of age, averaged over the same time period and calculated using a Brunt–Väisälä-weighted average, as in R. M. Ouazzani et al. (2019).
Paper: Shear–Gravity Transition Determines the Steep Velocity Dispersion–Size Relation in Molecular Clouds: Confronting Analytical Formula with Observations
Authors: Yi-Heng Xie, Guang-Xing Li
Figure caption: Prediction of the variation of velocity dispersion at different Galactocentric distances. The red (Rgal = 5−6 kpc) and blue (Rgal = 10−11 kpc) contours show the kernel density estimation of the observation result from M.-A. Miville-Deschênes et al. (2017). The red (Rgal = 5−6 kpc) and blue (Rgal = 10−11 kpc) dashed lines represent our prediction result using Equation (1).
Paper: Shear–Gravity Transition Determines the Steep Velocity Dispersion–Size Relation in Molecular Clouds: Confronting Analytical Formula with Observations
Authors: Yi-Heng Xie, Guang-Xing Li
Figure caption: Prediction of the slope of velocity dispersion–size relation at different Galactocentric distances. The left, middle, and right panels show the observation and prediction results at Rgal  <  10.5 kpc, 10.5 ≤ Rgal  <  12.5 kpc, and Rgal ≥ 12.5 kpc, respectively. The blue scatters and the contours show the observation result from Y. Sun et al. (2024), and the blue solid lines represent their fitting results. The green dashed lines represent our prediction results.
Paper: Shear–Gravity Transition Determines the Steep Velocity Dispersion–Size Relation in Molecular Clouds: Confronting Analytical Formula with Observations
Authors: Yi-Heng Xie, Guang-Xing Li
Figure caption: Map of gravity-dominated and shear-dominated gas. Left panel: gravity-dominated gas (﹩{\lambda }_{1}{\sigma }_{{{\rm{v}}}_{{\rm{g}}}}\gt {\lambda }_{2}{\sigma }_{{{\rm{v}}}_{{\rm{shear}}}}﹩); right panel: shear-dominated gas (﹩{\lambda }_{1}{\sigma }_{{{\rm{v}}}_{{\rm{g}}}}\lt {\lambda }_{2}{\sigma }_{{{\rm{v}}}_{{\rm{shear}}}}﹩). The clouds are projected on the mid-plane of the Galactic disk. The color of clouds refers to the velocity dispersion contribution ratio between gravity and shear from Equation (8).
Paper: Shear–Gravity Transition Determines the Steep Velocity Dispersion–Size Relation in Molecular Clouds: Confronting Analytical Formula with Observations
Authors: Yi-Heng Xie, Guang-Xing Li
Figure caption: Gravity-weighted gas density at Galactic mid-plane (z = 0).
Paper: Shear–Gravity Transition Determines the Steep Velocity Dispersion–Size Relation in Molecular Clouds: Confronting Analytical Formula with Observations
Authors: Yi-Heng Xie, Guang-Xing Li
Figure caption: Shear-weighted gas density at Galactic mid-plane (z = 0).
Paper: A Constraint on Superheavy Elements of the GRB–Kilonova AT 2023vfi
Authors: Zhengyan Liu, Ji-an Jiang, Wen Zhao
Figure caption: Abundance distributions at 1e+9 s simulated by the SkyNet nucleosynthesis code with various initial conditions. The initial temperature Tini is fixed to 6 GK. The entropy is selected as (10, 50, 100, 200) kB baryon−1. For the lines with the same color, the higher transparency represents the larger entropy set.
Paper: A Constraint on Superheavy Elements of the GRB–Kilonova AT 2023vfi
Authors: Zhengyan Liu, Ji-an Jiang, Wen Zhao
Figure caption: Abundance distributions at 1e+9 s simulated by the SkyNet nucleosynthesis code for the models with different EoSs. The black dots represent solar r-process element abundances from M. Arnould et al. (2007).
Paper: A Constraint on Superheavy Elements of the GRB–Kilonova AT 2023vfi
Authors: Zhengyan Liu, Ji-an Jiang, Wen Zhao
Figure caption: Lightcurves derived from the heating rates of the BNS merger models. The dark and red dots represent the bolometric luminosity lightcurves of the KN of GRB 230307A and AT 2017gfo, respectively. The red triangles are the lower limits of bolometric luminosity for AT 2017gfo.
Paper: A Constraint on Superheavy Elements of the GRB–Kilonova AT 2023vfi
Authors: Zhengyan Liu, Ji-an Jiang, Wen Zhao
Figure caption: Lightcurves derived from heating rates with different abundances of 223Ra and 225Ac. The black solid line is the lightcurve calculated based on the solar r-process abundance.
Paper: A Constraint on Superheavy Elements of the GRB–Kilonova AT 2023vfi
Authors: Zhengyan Liu, Ji-an Jiang, Wen Zhao
Figure caption: Heating rates produced by the β-decay and α-decay of r-process elements for lanthanide-rich ejecta. The solid and dashed lines represent LS220_M140140_LK and DD2_M140140_LK, respectively.
Paper: A Constraint on Superheavy Elements of the GRB–Kilonova AT 2023vfi
Authors: Zhengyan Liu, Ji-an Jiang, Wen Zhao
Figure caption: Heating rates of lanthanide-poor and lanthanide-rich ejecta of different models. The dashed black line represents a power-law function with an index of −1.3.
Paper: A Constraint on Superheavy Elements of the GRB–Kilonova AT 2023vfi
Authors: Zhengyan Liu, Ji-an Jiang, Wen Zhao
Figure caption: Fractions of heating rate for the superheavy elements: 222Rn, 223Ra, 224Ra, and 225Ac, in the case of LS220_M140140_LK.
Paper: A Constraint on Superheavy Elements of the GRB–Kilonova AT 2023vfi
Authors: Zhengyan Liu, Ji-an Jiang, Wen Zhao
Figure caption: Lightcurves derived from the heating rates with the varying abundances of the 254Cf.
Paper: Angular Momentum Transport by Internal Gravity Waves across Age
Authors: T. M. Rogers, R. P. Ratnasingam
Figure caption: Brunt–Väisälä frequency as a function of radius for all ages simulated. The inset shows the zoom-in of the evolution of the near-core spike.
Paper: Angular Momentum Transport by Internal Gravity Waves across Age
Authors: T. M. Rogers, R. P. Ratnasingam
Figure caption: Time snapshots of all simulations, aging from left to right. Images are of vorticity with positive (prograde) vorticity white (saturated at 2 × 10−5) and negative (retrograde) vorticity black (saturated at −2 × 10−5). Note the varying radial scale as the star ages. The top row shows the full simulated domain, while the bottom row shows zoomed-in images of the convective core and Brunt–Väisälä spike.
Paper: Angular Momentum Transport by Internal Gravity Waves across Age
Authors: T. M. Rogers, R. P. Ratnasingam
Figure caption: Ratio of the divergence of the Reynolds stress (second term on left-hand side of (4)) to viscous stress (RHS of (4)). Blue demonstrates regions that are dominated by Reynolds stress, while red shows regions that are dominated by viscous stress. Horizontal white lines denote the convective–radiative interface (for Xc = 0.69) and the extent of the Brunt–Väisälä spike for all other ages. Note the varying ordinate axis to reflect the vast expansion in radius across the main-sequence lifetime.
Paper: From Misaligned Sub-Saturns to Aligned Brown Dwarfs: The Highest Mp/M* Systems Exhibit Low Obliquities, Even around Hot Stars 
Authors: Jace Rusznak, Xian-Yu Wang, Malena Rice, Songhu Wang
Figure caption: Upper panel: spectral energy distribution, TESS transit photometry, out-of-transit RV, and in-transit Rossiter–McLaughlin data sets and associated best-fit EXOFASTv2 models for XO-3 b. NEID radial velocity measurements are represented by inverted orange triangles, and previous measurements (G. Hébrard et al. 2008; C. M. Johns-Krull et al. 2008; J. N. Winn et al. 2009; T. Hirano et al. 2011a; H. A. Knutson et al. 2014; A. S. Bonomo et al. 2017; Z. Garai et al. 2017; K. Worku et al. 2022) are shown in gray. Lower panel: Doppler tomography signal for XO-3, obtained during transit. Our spectra captured by NEID produce the Doppler tomography seen in the left panel, while the best-fit model and associated residuals are shown in the middle and right panels, respectively.
Paper: From Misaligned Sub-Saturns to Aligned Brown Dwarfs: The Highest Mp/M* Systems Exhibit Low Obliquities, Even around Hot Stars 
Authors: Jace Rusznak, Xian-Yu Wang, Malena Rice, Songhu Wang
Figure caption: Upper panel: the sky-projected spin–orbit angle (∣λ∣) distribution for cool-star systems (Teff ≤ 6100 K) as a function of planet-to-star mass ratio. The contours represent the kernel density estimation of stellar obliquity measurements in the MP/M* − ∣λ∣ space. The vertical blue dashed line marks the most likely boundary between the misalignment of low MP/M* systems and the alignment of high MP/M* systems. Lower panel: similar to the upper panel, but for hot-star systems (Teff > 6100 K). The location of XO-3 is indicated by a curved gray arrow. The left-oriented arrow, marked as “1,” indicates that dynamical excitation can lead to misalignment in both cool-star and hot-star systems with  MP/M* < 2 × 10−3. However, for cool stars with thick convective envelopes, misaligned systems with 3 × 10−4 <  MP/M* < 2 × 10−3 are tidally damped, as shown by arrows marked as “2.” In systems with high mass ratios, represented by the “3” arrow, primordial alignment dominates the stellar obliquity distribution, with no dynamical excitation causing misalignment. We note that there is a second target with a similar measured obliquity, CoRoT-3 b, ﹩\lambda =3{7}_{-22.3}^{+10.0}﹩a°. However, we define misalignment as a >3σ deviation from 0°. CoRoT-3 b is only 1.66σ from 0°, and therefore we consider it to be consistent with alignment.(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)
Paper: Spin–Orbit Alignment in Merging Binary Black Holes Following Collisions with Massive Stars
Authors: Fulya Kıroğlu, James C. Lombardi, Kyle Kremer, Hans D. Vanderzyden, Frederic A. Rasio
Figure caption: Comparison of the GW inspiral timescale (black dashed lines) of a BBH with semimajor axis a and total mass MBBH (assuming equal-mass components) to the dynamical encounter timescale (blue dashed lines) in a typical dense star cluster with a central density of n ∼ 106 pc−3 and velocity dispersion 10 km s−1. The shaded gray region displays the parameter space where tGW < tenc, indicating that BBHs merge via GW emission before they have a chance to dynamically interact with a star. Above this region, the points denote all BBH–star collisions identified in the cluster models of F. Kıroğlu et al. (2025), with colors representing their orbital eccentricity at the time of the collision. Different symbols indicate collisions between BHs and stars of different mass ratios (q = M⋆/MBH).
Paper: Spin–Orbit Alignment in Merging Binary Black Holes Following Collisions with Massive Stars
Authors: Fulya Kıroğlu, James C. Lombardi, Kyle Kremer, Hans D. Vanderzyden, Frederic A. Rasio
Figure caption: From top to bottom, time evolution of the eccentricity, instantaneous effective spin parameter (χeff), and separation between BBHs after their collision with a 10 M⊙ star. Models with initial BBH semimajor axes ranging from 0.02 to 0.2 au are shown in different colors (cases 1, 16, 23, and 38 in Table 2, respectively). For cases with a ≥ 0.1 au, χeff starts negative and transitions to positive during the closest approach between the BHs. This transition is consistently accompanied by a decrease in the semimajor axis, driven by angular momentum transfer from the BBH to the stellar debris. In contrast, for a < 0.1 au, the instantaneous χeff is initially positive and remains so throughout the evolution. As the stellar debris approaches a steady state, the BBH orbit continues to shrink and circularize, ejecting a significant fraction of the mass in the common envelope around the orbit (see column (12) in Table 2).
Paper: Spin–Orbit Alignment in Merging Binary Black Holes Following Collisions with Massive Stars
Authors: Fulya Kıroğlu, James C. Lombardi, Kyle Kremer, Hans D. Vanderzyden, Frederic A. Rasio
Figure caption: The final inspiral timescale vs. final effective spin of BBHs after colliding with a 10 M⊙ star. In all cases, the BBH achieves a positive χeff value as a consequence of angular momentum exchange between the BBH orbit and stellar debris. Initially compact BBHs (ai < 0.1 au; represented by triangles) generally attain relatively short postcollision inspiral times (≲10 Myr) and therefore are expected to merge before subsequent dynamical interactions can randomize their positive spin–orbit alignment. For initially wide BBHs (ai ≥ 0.1 au; represented by circles), the postcollision spin–orbit alignment may ultimately be randomized by subsequent encounters within their host cluster, unless the binaries are ejected from their host following the collision. The color of each point indicates the final center-of-mass velocity of the BBH, which arises from linear momentum kicks imparted by ejected stellar material.
Paper: Spin–Orbit Alignment in Merging Binary Black Holes Following Collisions with Massive Stars
Authors: Fulya Kıroğlu, James C. Lombardi, Kyle Kremer, Hans D. Vanderzyden, Frederic A. Rasio
Figure caption: The density and mass profiles of the MESA stellar models (dashed lines) in comparison to their SPH models at the end of relaxation (solid lines).