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Peter Behroozi

Publications and source records attributed to Peter Behroozi.

At least 19 recordsLinked to original sources

Galaxies at z > 10: {\Lambda}CDM predicts increased Star Formation Efficiency

We show that the rest-frame UV statistics and global properties of galaxies at 7 <= z <= 14 are naturally reproduced within the standard {\Lambda}CDM framework when galaxy formation is modeled with UniverseMachine applied to the high-resolution Uchuu N-body simulation. Our model matches the UV luminosity functions over five magnitudes and reproduces the evolution of the UV (and inferred star formation rate) density once internal dust attenuation is included. Comparisons with spectroscopically confirmed JWST/HST galaxies show good agreement with the stellar mass-SFR and stellar mass-UV luminosity relations. In contrast, earlier claims of insufficient stellar masses at z=8 are inconsistent with our model and are likely driven by systematic uncertainties, including AGN contamination, dust attenuation, and the lack of JWST/MIRI constraints. A key prediction is that the star-formation efficiency increases with redshift at fixed halo mass, reaching 2-3 percent of baryons converted into stars by z=10-12. These results demonstrate that current JWST observations of early galaxy populations can be explained within the {\Lambda}CDM framework.

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PANORAMIC: The Dawn of Massive Quiescent Galaxies I. Number Density and Cosmic Variance from 1000 arcmin$^2$ NIRCam Imaging

We measure the number density and field-to-field variance of massive quiescent galaxies at $z\sim3$ - 8 using the JWST/NIRCam pure-parallel imaging survey PANORAMIC together with archival observations, covering an area of 0.28 deg$^2$ ($\sim1000$ arcmin$^2$) in at least six filters. We identify quiescent galaxy candidates at $z\gtrsim3$ with $M_\ast \gtrsim 10^{10}\,M_\odot$, comprising 101 galaxies in a gold sample of high-confidence candidates and 137 in a more inclusive silver sample. We measure their evolving comoving number density, finding $(1.5$ vs. $3.1)\times10^{-5}\,\mathrm{Mpc}^{-3}$ at $z=3$ - 4 for the gold and silver samples, respectively, and a decline by more than a factor of 20 by $z\sim6$. Comparisons with empirical models and cosmological simulations show that widely used frameworks underpredict the abundance of massive quiescent galaxies at $z\gtrsim4$ by $\gtrsim1$ dex, indicating that current implementations of early star formation, feedback, and quenching do not produce enough early quenched systems. With 34 independent sightlines, we present the first direct empirical measurement of field-to-field variance for quiescent galaxies at $z>3$, finding a high cosmic variance of $\sigma_{\rm CV}\approx0.7\pm0.3$. This exceeds predictions from abundance-matched mock catalogs, suggesting that early quiescent galaxies are more strongly clustered, and more likely to be found near one another or in more biased regions, than expected in current galaxy-formation models. Any successful model for the emergence of early massive quiescent galaxies must reproduce both their abundance evolution and their imprint on the large-scale distribution.

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The stellar-to-halo mass relation of central galaxies across three orders of halo mass

The stellar content of galaxies is tightly connected to the mass and growth of their host dark matter halos. Observational constraints on this relation remain limited, particularly for low-mass groups, leaving uncertainties in how galaxies assemble their stars across halo mass scales. Accurately measuring the brightest central galaxy (BCG) stellar-to-halo mass relation (SHMR) over a wide mass range is therefore crucial for understanding galaxy formation and the role of feedback processes. Here we present the SHMR spanning $M_{\rm halo} \sim 10^{12}$-$10^{15}\,M_\odot$, using halo masses derived from eROSITA eRASS1 X-ray data and BCG stellar masses based on SDSS photometry. By stacking X-ray spectra of optically selected groups, we recover robust average halo gas temperatures for each bin, which are then converted to halo masses via the $M$-$T_X$ relation. We find that the SHMR peaks near $M_{\rm halo} \sim 10^{12}\,M_\odot$, with a declining stellar fraction at higher masses. This trend reflects a combination of processes that reduce the efficiency of stellar mass growth in massive halos, such as AGN feedback, reduced cooling efficiency, and the increasing dominance of ex-situ assembly, while halos continue to grow through mergers and accretion. Our measurements are consistent over the full mass range with previous observational studies, including weak lensing, X-ray analyses of individual clusters, and kinematical and dynamical methods. Comparisons with hydrodynamical simulations show good agreement at low masses but reveal significant discrepancies in the normalization at cluster scales, highlighting the sensitivity of BCG stellar growth to feedback prescriptions and halo assembly history. These results provide the first X-ray-based observational SHMR covering three orders of magnitude in halo mass, establish a robust benchmark for testing galaxy formation models.

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DREAMS.II. Galaxy Demographics from Direct Te-Based Metallicities at z~2-10: Tracing the Evolution of the Mass-Metallicity and Fundamental Relations

We present the statistics of line ratios and direct Te-based metallicities from JWST medium-resolution spectra of 292 galaxies at z=2-10, combining DREAMS observations with those of JADES and CEERS. To remove systematics caused by stellar mass (M*) and star formation rate (SFR), we construct stacked spectra binned by redshift within fixed M* and SFR ranges, as well as across the full ranges. We find that the [OII]3727/Hb ratio drops by a factor of five from z~3 to 8 at fixed M* and SFR, in contrast to the nearly constant [OIII]5007/Hb ratio. We derive metallicities via the direct Te method using the [OIII]4363 line, and identify that high-z galaxies lie on the low-metallicity end of the anti-correlation between ionization parameter and metallicity at z~0. Photoionization modeling demonstrates that the redshift evolution, where metallicity decreases and ionization parameter increases, self-consistently explains the observed line ratios. We then examine the mass-metallicity (MZ) and fundamental (MZ-SFR) relations. Including additional galaxies at z~10-12, we find that the MZ relation monotonically decreases from z~3 to 10 at fixed M*, while the MZ-SFR relation shows a significant decline at z>8. Based on the ChemicalUniverseMachine model, this evolutionary trend can be explained by enhanced gas inflow (outflow) by a factor of ~5 (~1.7) at z>8.

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The Ray Tracing Sampler: Bayesian Sampling of Neural Networks for Everyone

We derive a family of Markov Chain Monte Carlo (MCMC) sampling methods based on following ray paths in a medium where the refractive index $n(x)$ is a function of the desired likelihood $\mathcal{L}(x)$, extending past work on isokinetic sampling. The simplest ray tracing method propagates rays at constant speed through parameter space, leading to orders of magnitude higher resilience to heating for stochastic gradients as compared to both Hamiltonian Monte Carlo (HMC) and Stochastic Gradient HMC, as well as the ability to cross any likelihood barrier, including holes in parameter space. Using the simplest ray tracing method, we sample the posterior distributions of neural network outputs for a variety of different architectures, including a preliminary exploration of the 1.5 billion-parameter GPT-2 (Generative Pre-trained Transformer 2) architecture, all on a single consumer-level GPU. We also show that prior samplers including traditional HMC, the original microcanonical HMC, Metropolis, Gibbs, and even Monte Carlo integration are special cases within a generalized ray tracing framework, which can sample according to an arbitrary weighting function. Public code and documentation for C, JAX, and PyTorch are available at https://bitbucket.org/pbehroozi/ray-tracing-sampler/src

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Halo Properties from Observable Measures of Environment: II. Central versus Satellite Classification

A physical understanding of galaxy formation and evolution benefits from an understanding of the connections between galaxies, their host dark matter halos, and their environments. In particular, interactions with more-massive neighbors can leave lasting imprints on both galaxies and their hosts. Distinguishing between populations of galaxies with differing environments and interaction histories is therefore essential for isolating the role of environment in shaping galaxy properties. We present a novel neural-network based method, which takes advantage of observable measures of a galaxy and its environment to recover whether it (1) is a central or a satellite, (2) has experienced an interaction with a more massive neighbor, and (3) is currently orbiting or infalling onto such a neighbor. We find that projected distances to, redshift separations of, and relative stellar masses with respect to a galaxy's 25 nearest neighbors are sufficient to distinguish central from satellite halos in $> 90\%$ of cases, with projection effects accounting for most classification errors. Our method also achieves high accuracy in recovering interaction history and orbital status, though the network struggles to distinguish between splashback and infalling systems in some cases due to the lack of velocity information. With careful treatment of the uncertainties introduced by projection and other observational limitations, this method offers a new avenue for studying the role of environment in galaxy formation and evolution.

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Machine Learning the Dark Matter Halo Mass of the Milky Way

Although numerous dynamical techniques have been developed to estimate the total dark matter halo mass of the Milky Way, it remains poorly constrained, with typical systematic uncertainties of 0.3 dex. In this study, we apply a neural network-based approach that achieves high mass precision without several limitations that have affected past approaches; for example, we do not assume dynamical equilibrium, nor do we assume that neighboring galaxies are bound satellites. Additionally, this method works for a broad mass range, including for halos that differ significantly from the Milky Way. Our model relies solely on observable dynamical quantities, such as satellite orbits, distances to larger nearby halos, and the maximum circular velocity of the most massive satellite. In this paper, we measure the halo mass of the Milky Way to be log_10 M_vir / M_Sun = 12.20^{+0.163}_{-0.138}. Future studies in this series will extend this methodology to estimate the dark matter halo mass of M31, and develop new neural networks to infer additional halo properties including concentration, assembly history, and spin axis.

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Characterizing the host galaxies and delay times of Ca-rich gap transients vs 91bg-like SNe and normal Type Ia SNe

Calcium-rich gap transients are a faint, fast-evolving class of supernovae that show strong nebular Ca emission lines. Their progenitor systems are uncertain, but they are often associated with old and quiescent host galaxies. In this work, we compare the properties of the hosts of hydrogen-poor Ca-rich gap transients to the hosts of 3 other classes of supernova (SNe): normal Type Ia, 91bg-like, and Type II. We use data from the Zwicky Transient Facility (ZTF) Census of the Local Universe (CLU) experiment to build up our 4 SNe samples and identify the host galaxies. A combination of precomputed host properties from the CLU catalog and those derived from SED fitting are used to characterize each host's stellar mass, star formation rate, and specific star formation rate (sSFR). We find that the hosts of Ca-rich gap transients and 91bg-like SNe occupy a similar parameter space of mass and sSFR, and are more massive and quiescent compared to the hosts of Type Ia and Type II SNe. Additionally, we construct delay time distributions (DTDs) for our 4 samples, finding that Ca-rich gap transients and 91bg-like SNe have the longest peak delay times $\sim 10^4$ Myr, compared to the peak delay times of Type Ia SNe ($\sim 10^3$ Myr) and Type II SNe ($\sim 10$ Myr). The similarity of host environment and DTDs for Ca-rich gap transients and 91bg-like SNe motivates further analysis of the relationship of these two transient classes.

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A Promise for the JWST era: Massive black holes directly collapsed from wave dark matter haloes, and Star formation in and around their accretion flows

There are several puzzling phenomena from recent JWST observations, which seem to push the standard {\Lambda}CDM cosmology over the edge. All those puzzles can be understood in a coherent way if we assume that first massive black holes (MBHs, the "heavy eggs") formed by directly collapsing from wave CDM haloes, which can be even earlier than the formation of first galaxies (the "chickens"). We elucidate two false obstacles that have been believed to prevent wave CDM haloes from collapsing into black holes (namely "maximum stable mass" and "bosenova") and point out that general-relativistic instabilities (e.g., the non-axisymmetric instability numerically found in spinning scalar-field boson stars) could serve as the concrete mechanisms for direct-collapse black holes (DCBHs) born from wave dark matter. Once the MBHs formed, star formation bursts in and around the accretion flows, characteristic of a special mode in compact regions of high gravitational accelerations.

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Trinity VII. Predictions for the Observable Correlation Functions of Accreting Black Holes

The quasar correlation function assesses the occurrence of quasar pairs as a function of separation, which is strongly influenced by quasar host halo masses. The empirical Trinity model recently inferred the redshift-dependent relationship between supermassive black hole (SMBH) mass, galaxy mass, and halo mass, using constraints other than correlation functions (e.g., quasar luminosity functions, active galactic nuclei occupation fractions, and SMBH mass-bulge mass relations). Hence, comparing the predicted quasar correlation functions from Trinity to real observations is an important test of Trinity's inferred SMBH -- halo relation. In this work, we use a compilation of observed two-point projected and redshift-space correlation functions from $0 \leq z \leq 3.5$. We find that Trinity accurately predicts quasar correlation functions within observed error bars, although observations do not have much constraining power at lower redshifts due to smaller observable volumes and lower quasar number densities. This finding is consistent with Trinity having the correct placement of quasars within their host galaxies and dark matter halos, without requiring quasar clustering constraints during model fitting. Using Trinity, we also predict the clustering as a function of quasar bolometric luminosity, finding that existing survey uncertainties are too large to show measurable differences ($\lesssim 0.3$ dex change in bias for $10^{42}$ erg s$^{-1}$ compared to $10^{46}$ erg s$^{-1}$ SMBHs across redshifts). This fact arises because most SMBH growth (and hence quasar luminosity) occurs in halos in a similar mass range ($10^{12}-10^{13} M_\odot$).

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Lonely Little Red Dots: Challenges to the AGN-nature of little red dots through their clustering and spectral energy distributions

Observations with the James Webb Space Telescope (JWST) reveal a previously unseen population of compact red objects, known as ``little red dots`` (LRDs). We study a new photometrically selected sample of 124 LRDs in the redshift range $z$ $\sim$ 3 - 10 selected from NIRCam coverage of the CEERS, NEP-TDF, JADES and JEMS surveys. For JADES, the NEP-TDF and CEERS, we compare SED models with and without AGN components and analyse the impact of an AGN component on the goodness of fit using the Bayesian information criterion (BIC). We find that whilst the $\chi^{2}$ of the majority of models containing AGN components is improved compared to models without AGN components, we show that the BIC suggests models without AGN are a more appropriate fit to LRD SEDs, especially when MIRI data is available. We also measure LRD clustering in the CEERS field, JADES field, and NEP-TDF, where we compare the spatial distribution of LRDs and galaxies with Kolmogorov-Smirnov tests of equality of distribution. We find that the neighbourhood of LRDs tends to be less dense compared to galaxies at all selections and masses and at similar redshifts. We further measure upper limit estimates for the halo masses of LRDs using abundance matching. Whilst the population of LRDs could be a mixture of several different inherent populations, as a whole it does appear that these systems are mostly hosting compact galaxies or star clusters in formation.

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Insights into the dependence of galaxy properties on the environment with explainable machine learning models

Galaxies reside within dark matter halos, but their properties are influenced not only by their halo properties but also by the surrounding environment. We construct an interpretable neural network framework to characterize the surrounding environment of galaxies and investigate the extent to which their properties are affected by neighboring galaxies in IllustrisTNG300 data ($z=0$). Our models predict galaxy properties (stellar mass and star formation rate) given dark matter subhalo properties of both host subhalo and of surrounding galaxies, which serve as an explainable, flexible galaxy-halo connection model. We find that prediction accuracy peaks when incorporating only the nearest neighboring galaxy for stellar mass prediction, while star formation rate prediction benefits from information from up to the third-nearest neighbor. We determine that environmental influence follows a clear hierarchical pattern, with the nearest neighbor providing the dominant contribution that diminishes rapidly with additional neighbors. We confirm that central and satellite galaxies, as well as different galaxy categories based on mass and star-forming activity, exhibit distinct environmental dependencies. Environmental dependence for low-mass galaxies ($\log(M_*/M_\odot) < 10$) shows 35-50% environmental contribution compared to just 8-30% for massive centrals, while satellite galaxies experience consistently stronger environmental effects than centrals across all populations. Furthermore, we find that the most significant attribute from neighboring subhalos for predicting target galaxy properties is its distance to the nearest neighboring galaxy. These quantitative results offer guidance for constructing more sophisticated empirical and semi-analytic models of galaxy formation that explicitly include environmental dependence as a function of galaxy type and mass.

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SAPPHIRES: A Galaxy Over-Density in the Heart of Cosmic Reionization at $z=8.47$

We report the discovery of a galaxy proto-cluster candidate (dubbed MACS0416-OD-z8p5) at a spectroscopic redshift of $z\sim8.47$, dating back to $\sim550$Myr after the Big Bang. The observations are part of the JWST Cycle-3 treasury program, Slitless Areal Pure-Parallel HIgh-Redshift Emission Survey (SAPPHIRES) with NIRCam-grism. Using wide field slitless spectroscopy (WFSS) obtained in the MACS0416 parallel field, we robustly confirm nine galaxies at $z_{\rm spec}\sim8.47$ via emission line detections of [OIII]5008A (with $>5\,\sigma$) and tentatively confirm one additional galaxy (at $\sim3\,\sigma$). This discovery represents the highest-redshift, spectroscopically confirmed galaxy over-density known to date, which is $\sim6$--$8$ times more dense than the average volume density of galaxies at the same redshift. Furthermore, a galaxy hosting a low-mass active galactic nucleus (``Little-Red-Dot'') is found as a member, suggesting an early emergence of active, massive black holes and feedback between these black holes and their surrounding environments. We also discuss the spatial structures connecting the galaxy over-density to nearby massive star-forming galaxies (separated by $\sim 5$pMpc, including MACS0416-Y1 and MACS0416-JD. This finding of a massive dark matter halo hosting a galaxy over-density at $z\sim8.5$ is surprising given that our survey covered only a small, random field ($16.5\,{\rm arcmin^2}$) as part of a pure parallel observation. The comparison with cosmological simulations shows that the likelihood of finding such a large-scale structure is $<5\,\%$ under the current galaxy formation scenario and the observed survey volume. Our results demonstrate the power of WFSS observations to build a complete line-emitter sample and suggest an important role for over-densities in enhancing galaxy formation by funneling large-scale gas supplies into small cosmological volumes.

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ChemicalUniverseMachine I: Uncovering the Cosmic Evolution of Metals in the Galaxy-ISM-CGM Ecosystem

We present an empirical chemical evolution model that explains the distribution of metals in the interstellar medium (ISM) and the circumgalactic medium (CGM) of galaxies based on the UniverseMachine and NeutralUniverseMachine models in the framework of $\Lambda$CDM structure formation. We parameterize the fractions of outflowing metals returned and mixed into the multi-phase ISM of the star-forming regions ($f_{\rm H2}$) and into the neutral gas regions ($f_{\rm HI}$); metal production, transfer, and dilution are caused by star formation, galaxy mergers, and gas inflow from the inter-galactic medium, respectively, with rates determined by the (Neutral)UniverseMachine models. Using a Markov Chain Monte Carlo algorithm, we explore the posterior distributions of metal return and mixing consistent with observed mass-metallicity relations in HII regions (at $0<z<5$), HI damped Lyman-alpha systems (at $1<z<4$), and the CGM (at $z=0$). We find that the fraction of metals present in the ISM, $f_{\rm H2}+f_{\rm HI}$, increases with halo mass from $\sim20$\% at $10^{10}M_\odot$ to $\sim80$\% at $10^{13}M_\odot$. These fractions increase mildly at higher redshifts, to $\sim30$\% at $10^{10}M_\odot$ and $\sim80$\% at $10^{13}M_\odot$ at $z=5$. Interestingly, there is no significant redshift evolution of $f_{\rm H2}+f_{\rm HI}$ at fixed circular velocity, suggesting that metal distribution between the ISM and CGM is universally determined by the halo potential well depth. CGM metal enrichment is thus slow in high-$z$ halos with deep potential wells. While $f_{\rm H2}$ monotonically increases with halo mass, $f_{\rm HI}$ peaks at $\sim10^{12}-10^{13} M_\odot$, suggesting that reinfall may be inefficient in larger-mass halos.

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Where do High-Velocity Dark Matter Particles come from in the Milky Way?

High-velocity particles ( $v>v_\mathrm{esc}$) in the Milky Way are rare but nonetheless important to characterize due to their impact on dark matter (DM) direct detection experiments. We select halos similar in mass to the Milky Way in a large-volume dark matter simulation and measure the incidence of high-velocity particles, finding that an average fraction $\sim 1.3\times 10^{-5}$ of the DM particles have $\Delta v > 600$ km/s within 5-11 kpc of the halo centers. However, some systems have dramatically higher fractions. Milky Way-like systems with high-speed satellites can have high-velocity DM fractions of order $\sim 100\times$ higher than average. The environment also affects high-velocity DM fractions; massive nearby halos ( $>10^{13} M_{\odot}$) can boost high-velocity DM density by $\sim 10\times$, although there is little effect for nearby Andromeda-like systems. We confirm previous predictions from zoom-in simulations that the high-velocity particles in the Milky Way with heliocentric speeds $>700$ km/s primarily originate from the Large Magellanic Cloud, and provide a table of expected high-velocity DM densities at different heliocentric velocity thresholds.

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MPI-Rockstar: a Hybrid MPI and OpenMP Parallel Implementation of the Rockstar Halo finder

MPI-Rockstar is a massively parallel halo finder based on the Rockstar phase-space temporal halo finder code, which is one of the most extensively used halo finding codes. Compared to the original code, parallelized by a primitive socket communication library, we parallelized it in a hybrid way using MPI and OpenMP, which is suitable for analysis on the hybrid shared and distributed memory environments of modern supercomputers. This implementation can easily handle the analysis of more than a trillion particles on more than 100,000 parallel processes, enabling the production of a huge dataset for the next generation of cosmological surveys. As new functions to the original Rockstar code, MPI-Rockstar supports HDF5 as an output format and can output additional halo properties such as the inertia tensor.

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TRINITY VI: Connection between Galaxy Star Formation Rates and Supermassive Black Hole Accretion Rates from z=0-10

We infer supermassive black hole (SMBH) accretion rates and Eddington ratios as a function of SMBH/host galaxy mass and redshift with the empirical TRINITY model of dark matter halo--galaxy--SMBH connection. The galaxy--SMBH mass and growth rate connection from TRINITY matches galaxy observables from $0 6$: at these redshifts, dark matter halos grow with an $e$-folding time of $\sim 45$ Myrs, driving similar growth rates in both galaxies and SMBHs.

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Optical alignment of contamination-sensitive Far-Ultraviolet spectrographs for Aspera SmallSat mission

Aspera is a NASA Astrophysics Pioneers SmallSat mission designed to study diffuse OVI emission from the warm-hot phase gas in the halos of nearby galaxies. Its payload consists of two identical Rowland Circle-type long-slit spectrographs, sharing a single MicroChannel plate detector. Each spectrograph channel consists of an off-axis parabola primary mirror and a toroidal diffraction grating optimized for the 1013-1057 Angstroms bandpass. Despite the simple configuration, the optical alignment/integration process for Aspera is challenging due to tight optical alignment tolerances, driven by the compact form factor, and the contamination sensitivity of the Far-Ultraviolet optics and detectors. In this paper, we discuss implementing a novel multi-phase approach to meet these requirements using state-of-the-art optical metrology tools. For coarsely positioning the optics we use a blue-laser 3D scanner while the fine alignment is done with a Zygo interferometer and a custom computer-generated hologram. The detector focus requires iterative in-vacuum alignment using a Vacuum UV collimator. The alignment is done in a controlled cleanroom facility at the University of Arizona.

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