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Lile Wang

Publications and source records attributed to Lile Wang.

At least 19 recordsLinked to original sources

From Inspiral to Expansion: The Wake-Driven Torque on Binary Black Holes in Gaseous Medium

Binary black holes (BBHs) in gaseous medium, such as active galactic nucleus (AGN) disks, are important gravitational-wave sources, yet the gas-driven torque that governs their orbital evolution remains to be fully understood. Most existing studies of BBHs in gas often approximate the net torque as the sum of independent dynamical friction (DF) forces exerted on each black hole by its own wake, neglecting the mutual gravitational coupling between the two wakes. We perform three-dimensional hydrodynamic simulations of circular BBHs in a uniform flow and find the torque is determined by the wake-wake interactions. The net torque is controlled by a single parameter $\eta \equiv v_g/v_o$, the ratio of the gas flow velocity to the binary orbital velocity. At small $\eta$, the wakes merge into a single overdense envelope and the time-averaged torque is negative; as $\eta$ increases, the wakes separate and the torque becomes positive. In AGN disks, capture-channel binaries in a disk model naturally produce $\eta$ in the positive-torque regime; the expansion timescale is comparable to or shorter than the disk lifetime, suggesting that gas-driven expansion can compete with gravitational-wave inspiral and suppress the capture-channel merger rate.

astro-ph.HE

Energy Partitioning in Dust-catalyzed $\mathrm{H_2}$ and HD Formation Revealed by Molecular Simulations Considering Nuclear Quantum Effects

Molecular hydrogen formation on interstellar dust grains is a key surface process in the interstellar medium, but the redistribution of the recombination energy between the substrate and the nascent molecule remains poorly understood. Here, we use ring-polymer molecular dynamics (RPMD) with a machine-learning force field to investigate energy partitioning during $\mathrm{H_2}$ and $\mathrm{HD}$ formation on graphene at $T=25, 50$ and $100 \mathrm{K}$. We focus on the chemisorbed-H recombination pathway previously identified as the dominant low-temperature channel on bare graphitic surfaces when nuclear quantum effects are included. The desorbing molecule retains the major fraction of the effective surface-mediated released energy, while graphene absorbs a smaller but non-negligible part. This molecular retention fraction is nearly temperature-independent over the investigated range. In contrast, the post-formation molecular kinetic-energy distribution changes more strongly with temperature: rovibrational motion dominates at low temperature, whereas center-of-mass translation becomes increasingly important at $100 \mathrm{K}$. $\mathrm{H_2}$ and $\mathrm{HD}$ exhibit broadly similar total energy retention, with only modest isotope-dependent differences in their internal kinetic-energy partitioning. These results provide an energy-resolved microscopic picture of surface-mediated energy redistribution in $\mathrm{H_2}$/$\mathrm{HD}$ formation, with implications for formation-pumping signatures in high-excitation $\mathrm{H_2}$ lines, vibrationally excited $\mathrm{H_2}$ chemistry, and collisional excitation of coexisting molecules by translationally hot nascent $\mathrm{H_2}$ in cold interstellar gas.

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Kratos-linerad: GPU-accelerated Monte Carlo radiative transfer of lines with efficient imaging

Spectral lines encode the velocity, the temperature, and the chemical structure of astrophysical gas; interpreting them requires radiative transfer that is accurate at high optical depth, consistent with the local excitation, and efficient enough to synthesize velocity-resolved images. We present Kratos-linerad, a GPU-accelerated Monte Carlo radiative transfer code for spectral lines. The level populations can be iterated to statistical equilibrium together with the escaping photon distribution, treating angle-dependent partial frequency redistribution through constant-memory sampling tables. The code adopts the two-step imaging scheme to line transfer, in which a Monte Carlo pass samples a velocity-resolved scattering emissivity, and a deterministic ray-tracing pass synthesizes channel maps decoupled from the scattering geometry. Validation reproduces the analytic scaling of escaped spectra and the imaging double-peak profiles. GPU parallelism enables both stages sufficiently fast for routine application to astrophysically realistic models.

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HOTDISK. Finding Massive Protostellar Disks with Water and Refractory Molecular Species

We present high-angular-resolution ($\sim0.05^{\prime\prime}$, $\sim 60-250$ au) ALMA Band~6 observations from the HOTDISK project (Hot-Origin Tracer survey of DISKs of massive protostars) aimed at investigating the "hot-disk" chemical pattern traced by vibrationally excited water, NaCl, SiS, and SiO in the innermost regions around massive protostars. Ten targets were selected based on strong CH$_3$CN emission exhibiting clear rotational signatures and centrally concentrated SiO emission from lower-resolution observations. We detect vibrationally excited water emission toward 7 of the 10 sources. In all detections, the blueshifted and redshifted components are compact and located on opposite sides of the 1.3 mm continuum peak, with velocity gradients approximately perpendicular to the outflow axes, consistent with rotation on disk scales. Emission from NaCl and SiS is detected toward 5 of these 7 sources and exhibits similar kinematics, further supporting the presence of compact rotating structures. In contrast, commonly used hot-core tracers (e.g., CH$_3$CN and SO$_2$) primarily probe larger-scale envelope gas. These results demonstrate that vibrationally excited water, NaCl, and SiS are powerful tracers of disk structures on $\sim$100 au scales, when observed at sufficient angular resolution and sensitivity. The high detection rate suggests that hot-disk chemical patterns -- and thus compact rotating disks -- are common in massive star-forming regions, at least among sources with well-developed rotating envelopes.

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Modeling the Dynamics and Thermochemistry for the Outer Atmospheres of the Ultra-hot Jupiter WASP-121b

We present three-dimensional simulations of the ultra-hot Jupiter (UHJ) WASP-121b from the planetary surface to extended outflows, coupling hydrodynamics with consistent non-equilibrium thermochemistry, ray-tracing radiative transfer, and hydrodynamics using the GPU-accelerated Kratos framework. The fiducial model exhibits several atmospheric layers, including the lower atmospheres controlled by day-night circulation, and transonic photoevaporative outflows at higher altitudes shaped into two spiral arms by the stellar gravity and orbital motion effects. Different species could trace different regions: Fe probes rotation-dominated inner layers, Na maps dense spiral arms where recombination balances photoionization, and H$\alpha$ and He 10830 A features trace progressively more extended, ionized gas. With spiral arm velocities reaching ~ 40 km/s projected along the line of sight, this morphology naturally reproduces the velocity pattern of observed high-velocity Na and H$\alpha$ absorption features without requiring significant super-rotation jet streams, although the absolute absorption amplitudes could carry uncertainties from stellar UV luminosity and trace elemental abundances. Parametric studies reveal complex dependencies on stellar irradiation: enhanced FUV intensifies outflows and extends spiral arms spatially and kinematically, while EUV and X-ray expands spiral structures into attenuated, ionized regions. Stellar wind confinement compresses the dayside outflow and enhances metastable helium absorption. This work demonstrates that current and future transmission spectral observations that probe multiple species can provide important constraints on astrophysical environments of UHJs by comparing state-of-the-art simulations.

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The effects of star-gas interactions on binary evolution in open clusters

Star-gas interactions can provide gravitational feedback that influences the dynamical evolution of stellar clusters, through processes such as dynamical friction (DF) and its non-dissipative counterpart, negative dynamical friction (NDF). Using the \texttt{PeTar} code, we perform direct $N$-body simulations of an open cluster initially containing $10^4$ stars, evolving within a gaseous medium spanning a range of ambient densities. Our results demonstrate that NDF associated with stellar outflows interacting with the surrounding gas can enhance the rate of cluster expansion, preferentially transporting stars toward the cluster outskirts. This behavior is accompanied by a more rapid decline in the number of binaries composed of a neutron star and a main-sequence star. A statistical analysis of binary orbital parameters further indicates that, compared to DF-dominated evolution, NDF tends to retain systems with larger semi-major axes and lower eccentricities. Outflow-ambient gas interactions can modify the dynamical processing of binaries in star clusters, leading to changes in the survival fraction and composition of the remaining binary population.

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Kratos-polrad: Novel GPU system for Monte-Carlo simulations with consistent polarization calculations

Polarized radiation serves as a vital diagnostic tool in astrophysics, providing unique insights into magnetic field geometries, scattering processes, and three-dimensional structures in diverse astrophysical scenarios. To address these applications, we present Kratos-polrad, a novel GPU-accelerated Monte Carlo Radiative Transfer code built upon the heterogeneous computing framework of Kratos, designed for self-consistent and efficient polarization calculations. It utlizes comprehensive treatment of Stokes parameters throughout photon propagation, featuring transforms the grain-lab frame transforms using quaternion algebra and consistent non-linear polarization extinction in cells, which are useful in modeling radiative transfer processes with scatterings by aligned dust grains. The code implements two-step polarimetry imaging that decouples Monte Carlo sampling of scattering physics from imaging geometry, enabling efficient synthesis maximizing the utilization of photon packets. Extensive validation against analytical solutions and established codes demonstrates accurate treatment of diverse polarization phenomena, including self-scattering polarization, dichroic extinction in aligned dust grains, and complex polarization patterns in twisted magnetic field configurations. By leveraging massive GPU parallelism, optimized memory access patterns, and analytical approaches for optically thick cells, Kratos-polrad achieves performance improvements of $\sim 10^{2}$ times compared to CPU-based methods, enabling previously prohibitive studies in polarimetric astrophysics.

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Adsorption of volatiles on dust grains in protoplanetary disks

The adsorption of volatile molecules onto dust grain surfaces fundamentally influences dust-related processes, including condensation of gas-phase molecules, dust coagulation, and planet formation in protoplanetary disks. Using advanced ab-initio density functional theory with r$^2$SCAN+rVV10 van der Waals functionals, we calculate adsorption energies of H$_2$, H$_2$O, and CO on carbonaceous (graphene, amorphous carbon) and silicate (MgSiO$_3$) surfaces. Results reveal fundamentally different adsorption mechanisms: weak physisorption on carbonaceous surfaces ($|\Delta\epsilon_{\rm ad}|\sim 0.1-0.2~{\rm eV}$) versus strong chemisorption on silicates ($|\Delta\epsilon_{\rm ad}|\sim 0.5-1.5~{\rm eV}$) via coordination bonds. Kinetic Monte Carlo simulations incorporating these energies demonstrate divergent surface evolution: carbonaceous grains exhibit distinct condensation radius compared to silicates, while the cocrystal of H$_2$O and CO significantly increases the desorption temperature of CO. The actual radii of gas-phase molecule depletion could thus be a comprehensive result of temperatures, chemical compositions, and even evolution tracks. Meanwhile, silicates maintain chemisorbed molecular coatings throughout most disk regions. Such dichotomy in surface coverage could also provide a natural mechanism for carbon depletion in inner planetary systems.

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Direct Numerical Simulations of Oxygen-Flame-Driven Deflagration-to-Detonation Transition in Type Ia Supernovae

We present direct numerical simulations demonstrating deflagration-to-detonation transition (DDT) driven by oxygen flames in Type Ia supernova progenitors. Using the Castro hydrodynamics code coupled with the ``aprox13'' 13-isotope nuclear network, we simulate combustion in isolated fuel regions where oxygen flames trail carbon flames. In a fiducial one-dimensional run at $\rho_{0}=3.5\times10^{7}\ \mathrm{g\ cm^{-3}}$ we observe spontaneous DDT of the oxygen flame via the Zel'dovich gradient mechanism when the carbon-oxygen separation reaches $\sim 10\ \mathrm{km}$. The oxygen detonation then captures the carbon flame and triggers a stable carbon detonation. Systematic one-dimensional parameter scans show that successful carbon DDT requires upstream densities in the range $(3.1$--$3.6)\times10^{7}\ \mathrm{g\ cm^{-3}}$ and a minimum carbon-flame thickness of $\gtrsim 20\ \mathrm{m}$. Two-dimensional simulations confirm DDT and demonstrate that the multidimensional cellular structure of the oxygen detonation can promote carbon detonation at somewhat lower densities than in one dimension. These results provide direct numerical evidence that oxygen-flame-driven DDT is physically plausible in turbulent white-dwarf environments and underscore the importance of multidimensional effects for Type Ia supernova explosion modeling.

astro-ph.HE

Interstellar Dust-Catalyzed Molecular Hydrogen Formation Enabled by Nuclear Quantum Effects

Molecular hydrogen (H$_2$) is one of the key chemical species that controls and shapes a wide spectrum of astrophysical processes from galaxy evolution to planet formation. Although catalyzation on dust grain surfaces is the dominant formation channel of H$_2$ in the interstellar medium, its efficiency across $20-200~\rm K$ has remained not fully understood. Here, using multiscale simulations combining ab-initio-level machine learning force fields, constrained path-integral Monte Carlo, and kinetic Monte Carlo, we perform a systematic, quantum-mechanical study of the full H$_2$ formation sequence, including hydrogen adsorption, diffusion, association and desorption. We explicitly consider the decoupling of gas and dust temperatures, making our results applicable to photon-dominated regions (PDRs) and dense cold clouds. Our results show that on the bare, crystalline surfaces studied here (graphitic and silicate grains), physisorbed hydrogen is negligible, and nuclear quantum effects (NQEs) in chemisorbed hydrogen atoms are essential for efficient formation at low temperatures, overcoming the classical Boltzmann suppression. This work presents a quantitative NQEs-inclusive study on silicate surfaces (exemplified by enstatite) and graphitic grains, revealing surface-specific adsorption behavior. These findings provide a first-principles quantum foundation for interstellar H$_2$ formation, complementing empirical multipliers, and enable new observational constraints on dust composition and molecular cloud evolution. The framework also extends to other astrochemical reactions on dust grains under full NQEs.

astro-ph.GA

Neural Networks as Surrogate Solvers for Time-Dependent Accretion Disk Dynamics

Accretion disks are ubiquitous in astrophysics, appearing in diverse environments from planet-forming systems to X-ray binaries and active galactic nuclei. Traditionally, modeling their dynamics requires computationally intensive (magneto)hydrodynamic simulations. Recently, Physics-Informed Neural Networks (PINNs) have emerged as a promising alternative. This approach trains neural networks directly on physical laws without requiring data. We for the first time demonstrate PINNs for solving the two-dimensional, time-dependent hydrodynamics of non-self-gravitating accretion disks. Our models provide solutions at arbitrary times and locations within the training domain, and successfully reproduce key physical phenomena, including the excitation and propagation of spiral density waves and gap formation from disk-companion interactions. Notably, the boundary-free approach enabled by PINNs naturally eliminates the spurious wave reflections at disk edges, which are challenging to suppress in numerical simulations. These results highlight how advanced machine learning techniques can enable physics-driven, data-free modeling of complex astrophysical systems, potentially offering an alternative to traditional numerical simulations in the future.

astro-ph.EP

Consistent Modeling of Non-equilibrium Dust Sublimation and the Interactions with Dust Evolution in the Inner Regions of Protoplanetary Disks

The inner regions of protoplanetary disks are host to the sublimation of dust grains, a process traditionally modeled using equilibrium thermodynamics. We demonstrate through ab-initio density functional theory (DFT) and kinetic Monte Carlo (KMC) simulations that silicate dust sublimation is inherently a non-equilibrium kinetic process. The binding energies and vibrational frequencies governing desorption, calculated for MgSiO3 and other compositions, reveal that sublimation timescales far exceed local dynamical times, allowing grains to persist in a superheated state. This kinetic inhibition results in a broad, dynamic sublimation front whose location and morphology are strongly regulated by radial advection and dust coagulation. Our coupled simulations, integrating sublimation with advection and grain evolution, show that the front varies radially by a factor of four with accretion rate and exhibits a vertically stratified, bowl-shaped structure. These findings imply that the inner disk dust distribution, thermal structure, and subsequent planet formation are profoundly influenced by the kinematics and kinetics of dust grains, necessitating a departure from equilibrium prescriptions in disk models and interpretations of inner rim observations.

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Dense Molecular Ring-like structure in gaseous CO depletion region G34.74-0.12

We report the discovery of a dense molecular ring-like structure in a dense (10$^5$ cm$^{-3}$), cold (pc-scale CO depletion at a factor of 5), and young (10$^4$ year) star-forming region G34.74-0.12, revealed by C$^{18}$O (2-1), HNC (1-0), and N$_2$H$^+$ (1-0) observations with the Atacama Large Millimeter/submillimeter Array (ALMA). The ring-like structure is redshifted with respect to the clump, spanning from $V_{\rm sys,lsr} + 0.9$ to $V_{\rm sys,lsr} + 2.9$ km s$^{-1}$, with a total mass of 109 $M_{\odot}$. It is spatially coincident with 1.3 mm and 3.0 mm dust continuum emission from cores, and several protostellar outflows. However, no free-free emission or H\textsc{ii} region is detected in association with this structure. With a slow expansion speed indicated by the position-velocity diagram, this ring structure differs from rings previously identified in more evolved star-forming regions. Possible explanations for the ring-like structure include a relic wind-blown bubble produced by a deeply embedded young stellar object, a hollow cavity formed by cloud-cloud interactions, a gas ring resulting from a temperature gradient, or a line-of-sight superposition of multiple outflows or dense clouds. This discovery offers a rare observational glimpse into the earliest dynamical processes involved in massive star formation.

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The ALMA Survey of 70 $\mu$m Dark High-mass Clumps in Early Stages (ASHES). XII. Unanchored Forked Stream in the Propagating Path of a Protostellar Outflow

Outflows are key indicators of ongoing star formation. We report the discovery of an unanchored forked stream within the propagating path of an extremely young protostellar outflow in the 70 $\mu$m-dark clump G34.74-0.12, based on ALMA 1.3 mm observations with an angular resolution of 1''.6 (~ 5000 au). This outflow originate from a 9.7 $M_{\odot}$ core, exhibits a fork-shaped stream structure in its red-shifted lobe, which is traced by CO (2-1), SiO (5-4), and H$_2$CO (3$_{0,3}$-2$_{0,2}$). It has a momentum of 13 $M_{\odot}$ km s$^{-1}$, an energy of 107 $M_{\odot}$ km$^{2}$ s$^{-2}$, and a dynamical timescale of ~10$^{4}$ yr. Significantly, the enhanced relative abundances of SiO, H$_2$CO, and CH$_3$OH with respect to CO, along with the increased temperature at the forked point, indicate a collisional origin. The forked point does not coincide with any dust continuum core > 0.1 $M_{\odot}$. Moreover, CO (2-1) emission also traces three other outflows in this region, characterized by their masses (0.40, 0.02 and 0.15 $M_{\odot}$) and momenta (5.2, 0.2, 1.8 $M_{\odot}$ km s$^{-1}$), as part of the ALMA Survey of 70 $\mu$m dark High-mass clumps in Early Stages (ASHES) project. All the newly discovered morphological and kinematic features associated with these extremely young protostellar outflows (with timescales of 10$^3$ - 10$^4$ years) suggest that the initial stages of star formation are more complicated than previously understood.

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AGN star dynamics under the Influence of Outflow-Ambient Interactions

Stars with outflows interacting with ambient gas experience accelerations arising from the gravitational feedback induced by the interaction structure. In this work, three-dimensional (3D) local shearing box simulations are performed to investigate the dynamical evolution of a star with outflows embedded in the outer regions of an active galactic nucleus (AGN) disk. Two types of stellar wind are considered: isotropic winds and axisymmetric jets, along with variations in the radial pressure gradient profile. The results show that anti-friction enables AGN stars to acquire angular momentum from the ambient gas, resulting in outward migration away from the disk center. The formation and stability of the head-wind structure, which is crucial for maintaining anti-friction, are sensitive to both the strength of the stellar outflow and the radial pressure gradient of the disk gas. Once the head-wind structure is disrupted, the anti-friction effect ceases to operate effectively. A case study is also presented, focusing on a stellar-mass black hole (sBH) in an AGN disk. It is shown that jet material launched along the z-axis is confined to the trailing side of the object's motion by high gas inflow velocities, thereby activating anti-friction and inducing outward migration. If such an sBH migrates inward initially, the interplay between inward and outward migration may trap it at an equilibrium radius, potentially facilitating the formation and merger of black hole binaries.

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The H2 Glow of a Quiescent Molecular Cloud Observed with JWST

We report JWST MIRI/MRS observations of the H2 S(1) 17.04 micron transition in two regions in the boundary of the Taurus Molecular Cloud. The two regions, denoted Edge (near the relatively sharp boundary of the 13CO J=1-0 emission) and Peak (the location of the strongest H2 emission observed with Spitzer), have average intensities of 14.5 MJy/sr and 32.1 MJy/sr, respectively. We find small scale structures of characteristic size 1.0 to 2.5 arcseconds, corresponding to 140 AU to 350 AU, with characteristic intensity above the extended background of 10 MJy/sr, corresponding to a J = 3 column density of 1.6x1017/cm2. The most plausible explanation for the observed intensities from level 845 K above the J = 1 ortho-H2 ground state level is excitation by collisions with H2 molecules (the hydrogen in this region being predominantly molecular). Two mechanisms, turbulent dissipation and shocks, have been proposed for heating of localized regions of the ISM to temperatures ~1000 K to explain abundances of and emission from particular molecules. While we cannot determine unique values of density and kinetic temperature, the solutions in best agreement with predictions of shock models are H2 density = 370 /cm3 and kinetic temperature = 1000 K. The total H2 column density of the small-scale structures under these conditions is ~8x1017/cm2. This first direct detection of heated tiny scale structure in the quiescent molecular interstellar medium has significant implications for the physical structure of this phase of the ISM and maintaining supersonic motions within it.

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Deep Neural Networks for Modeling Astrophysical Nuclear Reacting Flows

In astrophysical simulations, nuclear reacting flows pose computational challenges due to the stiffness of reaction networks. We introduce neural network-based surrogate models using the DeePODE framework to enhance simulation efficiency while maintaining accuracy and robustness. Our method replaces conventional stiff ODE solvers with deep learning models trained through evolutionary Monte Carlo sampling from zero-dimensional simulation data, ensuring generalization across varied thermonuclear and hydrodynamic conditions. Tested on 3-species and 13-species reaction networks, the models achieve $\lesssim 1\%$ accuracy relative to semi-implicit numerical solutions and deliver a $\sim 2.6\times$ speedup on CPUs. A temperature-thresholded deployment strategy ensures stability in extreme conditions, sustaining neural network utilization above 75\% in multi-dimensional simulations. These data-driven surrogates effectively mitigate stiffness constraints, offering a scalable approach for high-fidelity modeling of astrophysical nuclear reacting flows.

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The Kratos Framework for Heterogeneous Astrophysical Simulations: Ray Tracing, Reacting Flow and Thermochemistry

Thermochemistry, ray-tracing radiation, and radiation-matter interactions are important processes which are computationally difficult to model in astrophysical simulations, addressed by introducing novel algorithms optimized for heterogeneous architectures in the Kratos framework. Key innovations include a stoichiometry-compatible reconstruction scheme for consistent chemical species advection, which ensures element conservation while avoiding matrix inversions, and a LU decomposition method specifically designed for multi-thread parallelization in order to solve stiff thermochemical ordinary differential equations with high efficiency. The framework also implements efficient ray-tracing techniques for radiation transport for radiation-matter interactions. Various verification tests, spanning from chemical advection, combustion, Str\"omgren spheres, and detonation dynamics, are conducted to demonstrate the accuracy and robustness of Kratos, with results closely matching semi-analytic solutions and benchmarks such as Cantera and the Shock and Detonation Toolbox. The modular design and performance optimizations position it as a versatile tool for studying coupled microphysical processes in the diverse environments of contemporary astrophysical studies.

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