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Tom Abel

Publications and source records attributed to Tom Abel.

At least 19 recordsLinked to original sources

The AGORA High-resolution Galaxy Simulations Comparison Project. IX - Part 1: Effects of a Major Galaxy Merger on Star Formation of a Milky Way-mass Galaxy Progenitor

Given their highly nonlinear dynamics and sensitivity to initial conditions, galaxy mergers are a compelling area to conduct a simulation code comparison. We perform a comparative study of a major galaxy merger at $z \approx 4.5$ in cosmological zoom-in hydrodynamic simulations of a Milky Way-mass galaxy progenitor. The comparison employs the AGORA CosmoRun suite of nine well-calibrated, state-of-the-art numerical codes, each adopting a different stellar feedback scheme. We find that the evolution of the star formation rate (SFR) during the interaction is strongly shaped by the stellar feedback type. Using kinetic feedback in the feedback model drives a pronounced merger-induced starburst that starts to subside before coalescence; using thermal feedback without kinetic feedback yields prolonged SFR growth even after coalescence; and using delayed cooling or radiation pressure results in highly fluctuating SFR. Tracking gas particles in particle-based codes reveals that kinetic feedback facilitates gas inflow from the secondary galaxy onto the primary galaxy between the first periapsis and apoapsis, thus producing an earlier and more prominent starburst. In contrast, thermal feedback, augmented by superbubble or delayed-cooling feedback, suppresses gas cooling, creates a more extended gas distribution, and hinders strong starbursts during the merger. We also observe an inverse correlation between burst fraction and pre-merger gas fraction that is independent of feedback models. Overall, these results highlight the sensitivity of simulated galaxy mergers' star formation response to stellar feedback prescriptions. This study indicates that galaxy mergers may serve as a good testbed for stellar feedback processes in cosmological simulations.

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The AGORA High-resolution Galaxy Simulations Comparison Project. IX - Part 2: Effects of a Major Galaxy Merger on the Stellar Morphology of a Milky Way-mass Galaxy Progenitor

Galaxy mergers, with their high sensitivity to initial conditions, provide a valuable setting for comparative studies of galaxy simulation codes. Following our first paper focusing on merger-driven star formation, we present a code comparison examining the morphological transformation impact of a major galaxy merger at $z \approx 4.5$ on a Milky Way-mass galaxy progenitor. Our analysis employs nine state-of-the-art codes from the AGORA CosmoRun cosmological zoom-in simulation suite. For this merger, we show that the adopted stellar feedback type influences the galaxy's compaction and stellar disc formation. Codes with purely thermal feedback produce a merger remnant that forms a disc and becomes compact primarily during and after coalescence; codes that include kinetic feedback begin disc formation and compaction around the first periapsis; and codes with strong delayed cooling or superbubble feedback suppress disc formation and produce a more extended remnant. In contrast, the orientation of the remnant disc is code-independent. In all codes, the rotational angular momentum of the remnant disc aligns with the interaction's orbital angular momentum rather than the pre-merger rotational axis, implying that the infalling gas preserves its orbital angular momentum to form a new disc. Comparisons with the Santa Cruz semi-analytic model show reasonable agreement in stellar mass and half-mass radius, yet the model underpredicts (overpredicts) the dark matter fraction and velocity dispersion for codes exhibiting strong compaction (expansion). The systematic dependence of our remnants' morphology on feedback schemes demonstrates that merger remnant morphology may serve as a powerful probe of stellar feedback processes.

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RAMSES-GPU: Cell-by-Cell Adaptive Mesh Refinement with Magneto-Hydrodynamics and Self-Gravity on Graphics Processing Units

We present the implementation and optimization of the cosmological simulation code RAMSES on Graphics Processing Units (GPUs) using CUDA Fortran. This accelerated version ports the main computational routines, including hydrodynamics, particle dynamics, and self-gravity, to multi-GPU architectures. We detail our strategy for managing cell-by-cell Adaptive Mesh Refinement (AMR) on the GPU, utilizing bucket sort with prefix sums for AMR level sorting, radix sort via the CUB library for Hilbert key ordering, and an fnv64 hash table with linear probing for fast spatial indexing. Portability across diverse hardware architectures is achieved via a dispatcher and C-Fortran wrappers, calling CUDA, HIP, and Metal kernels directly translated from the CUDA Fortran framework. Hydrodynamics updates are executed via a Godunov MUSCL-Hancock HLLC Riemann solver managed through a three-tier shared-memory kernel architecture (named rock, paper, and scissor). Particle mass deposition uses Cloud-in-Cell (CIC) interpolation optimized with atomic additions or prefix sums, combined with a kick-drift-kick time integration pusher. Self-gravity is handled via a Multigrid (MG) Poisson solver performing hierarchical V-cycles on individual levels. Performance benchmarks conducted on NVIDIA A100 and H200 GPUs demonstrate substantial accelerations compared to multi-core CPUs, yielding 10x up to a 100x speedup for standard test problems such as the Sedov blast wave, molecular core collapse, and cosmological simulations. Finally, we briefly discuss additional accelerated physics modules, including equilibrium cooling, polytropic equations of state, ideal and non-ideal magneto-hydrodynamics (MHD), and stellar feedback.

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The AGORA High-resolution Galaxy Simulations Comparison Project. XI: Solving the Non-Spherical Morphology and Evolution of Dark Matter Halos with Haskap Pie

We introduce a halo solving and tracking procedure that intrinsically treats dark matter halos as non-spherical objects by leveraging the bound particle searching techniques used in Haskap Pie. The AGORA Collaboration's hydrodynamic simulation CosmoRun}project provides a useful laboratory to explore trends in dark matter halo morphology that are revealed by our new procedure in the context of any dispersions or similarities between the codes. We find that several morphological and shape measures were very responsive to high mass ratio mergers. The greatest difference in these measures between the simulation codes were related to timing discrepancies and the dynamical state of the halos prior to the mergers. Most other quantities were similar across codes, including several secular and redshift-dependent trends in various dynamical quantities that showed a departure from Virial Theorem (e.g., overdensity and halo mass). We find that halo spin and the ratio between the semi-major and the semi-minor axis peaked at 4>z>2 before declining at low redshift. Also, halo overdensity is both mass-dependent and redshift-dependent, diverging for low mass halos at low redshift. Our method contributes a new perspective on these trends that have not been fully replicated in other works due to our emphasis on fundamentally non-spherical halos and measures of morphology that correspondingly do not assume spherical symmetry.

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It\^o tracers: continuous-trajectory Lagrangian particles for Eulerian hydrodynamics

Lagrangian tracer particles have long been used to track the history of individual gas parcels in hydrodynamical codes. Particles advected by the cell-centered velocity carry no representation of underlying numerical diffusion, and thus exhibit systematic bias. The Monte-Carlo (MC) tracer resolves this with discrete probabilistic cell-to-cell, flux-based jumps, at the cost of trajectories that are discontinuous in time. We introduce the It\^o tracer, a continuous-time Lagrangian particle with moments matched to the advection, diffusion, and dispersion of the gas. A subgrid-scale variant (SGS-It\^o) replaces the numerical diffusion with a Smagorinsky--Lilly turbulent diffusivity, illustrating that the form of the diffusion matters less than its magnitude. We validate these methods with a 1D square-pulse advection test and 3D decaying turbulence at $\sigma_{\rm rms} = 15\,c_{\rm s}$. We compare the different tracer particle methods using several statistical tests. It\^o tracers largely reproduce or improve upon MC tracers statistics across column-density maps, joint density histograms, log-density-ratio PDFs, and density power spectra. In the turbulence test, It\^o tracers improve the correlation between tracers and gas over the MC tracers by >3\%, and reduce the width of the log-density ratio PDF by nearly 50\%. Relative to classical tracers, these improvements are $\gtrsim$30\% and 230\%, respectively. Because It\^o tracers follow a stochastic differential equation, the method maps onto other continuous-trajectory Lagrangian processes (e.g. dust grains, charged particles, cosmic rays), admits variance-reduction techniques, higher-order integrators, and GPU-friendly implementations -- all of which are unavailable to discrete-jump schemes.

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Learning Cosmology from Nearest Neighbour Statistics

Extracting cosmological parameters from galaxy/halo catalogues with sub-percent level accuracy is an important aspect of modern cosmology, especially in view of ongoing and upcoming surveys such as Euclid, DESI, and LSST. While traditional two-point statistics have been known to be suboptimal for this task, recently proposed k-Nearest Neighbour (kNN) based summary statistics have demonstrated tighter constraining power. Building on the kNN statistics, we introduce a new field-level representation of discrete halo catalogues - NN distance maps. We employ this technique on the halo catalogues obtained from Quijote N-body simulation suites. By combining these maps with kNN-based summary statistics, we train a hybrid neural network to infer cosmological parameters, showing that the resulting constraints achieve state-of-the-art, if not the best, accuracy. In addition, our hybrid framework is 5-10 times more computationally efficient than some of the existing point-cloud-based ML methods.

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The AGORA High-resolution Galaxy Simulations Comparison Project. X: Formation and Evolution of Galaxies at the High-redshift Frontier

Recent observations from JWST have revealed unexpectedly luminous galaxies, exhibiting stellar masses and luminosities significantly higher than predicted by theoretical models at Cosmic Dawn. In this study, we present a suite of cosmological zoom-in simulations targeting high-redshift ($z \geq 10$) galaxies with dark matter halo masses in the range $10^{10} - 10^{11}\ {\rm M}_{\odot}$ at $z=10$, using state-of-the-art galaxy formation simulation codes (Enzo, Ramses, Changa, Gadget-3, Gadget-4, and Gizmo). This study aims to evaluate the convergence of the participating codes and their reproducibility of high-redshift galaxies with the galaxy formation model calibrated at relatively low redshift, without additional physics for high-redshift environments. The subgrid physics follows the AGORA CosmoRun framework, with adjustments to resolution and initial conditions to emulate similar physical environments in the early universe. The participating codes show consistent results for key galaxy properties (e.g., stellar mass), but also reveal notable differences (e.g., metallicity), indicating that galaxy properties at high redshifts are highly sensitive to the feedback implementation of the simulation. Massive halos (${\rm M}_{\rm halo}\geq5\times10^{10}\,{\rm M}_{\odot}$ at $z=10$) succeed in reproducing observed stellar masses, metallicities, and UV luminosities at $10\leq z\leq12$ without requiring additional subgrid physics, but tend to underpredict those properties at higher redshift. We also find that varying the dust-to-metal ratio modestly affects UV luminosity of simulated galaxies, whereas the absence of dust significantly enhances it. In future work, higher-resolution simulations will be conducted to better understand the formation and evolution of galaxies at Cosmic Dawn.

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The AGORA High-Resolution Galaxy Simulations Comparison Project VII: Satellite quenching in zoom-in simulation of a Milky Way-mass halo

Context: Satellite galaxies experience multiple physical processes when interacting with their host halos, often leading to the quenching of star formation. In the Local Group (LG), satellite quenching has been shown to be highly efficient, affecting nearly all satellites except the most massive ones. While recent surveys are studying Milky Way (MW) analogs to assess how representative our LG is, the dominant physical mechanisms behind satellite quenching in MW-mass halos remain under debate. Aims: We analyze satellite quenching within the same MW-mass halo, simulated using various widely-used astrophysical codes, each using different hydrodynamic methods and implementing different supernovae feedback recipes. The goal is to determine whether quenched fractions, quenching timescales and the dominant quenching mechanisms are consistent across codes or if they show sensitivity to the specific hydrodynamic method and supernovae (SNe) feedback physics employed. Methods: We use a subset of high-resolution cosmological zoom-in simulations of a MW-mass halo from the multiple-code AGORA CosmoRun suite. Results: We find that the quenched fraction is consistent with the latest SAGA survey results within its 1$\sigma$ host-to-host scatter across all the models. Regarding quenching timescales, all the models reproduce the trend observed in the ELVES survey, LG observations, and previous simulations: the less massive the satellite, the shorter its quenching timescale. All our models converge on the dominant quenching mechanisms: strangulation halts cold gas accretion and ram pressure stripping is the predominant mechanism for gas removal, particularly effective in satellites with $M_* < 10^8\, M_\odot$. Nevertheless, the efficiency of the stripping mechanisms differs among the codes, showing a strong sensitivity to the different SNe feedback implementations and/or hydrodynamic methods employed.

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The AGORA High-resolution Galaxy Simulations Comparison Project. VIII: Disk Formation and Evolution of Simulated Milky Way Mass Galaxy Progenitors at $1<z<5$

We investigate how differences in the stellar feedback produce disks with different morphologies in Milky Way-like progenitors over 1 $\leq z \leq 5$, using eight state-of-the-art cosmological hydrodynamics simulation codes in the \textit{AGORA} project. In three of the participating codes, a distinct, rotation-dominated inner core emerges with a formation timescale of $\lesssim 300$ Myr, largely driven by a major merger event, while two other codes exhibit similar signs of wet compaction -- gaseous shrinkage into a compact starburst phase -- at earlier epochs. The remaining three codes show only weak evidence of wet compaction. Consequently, we divide the simulated galaxies into two groups: those with strong compaction signatures and those with weaker ones. Galaxies in these two groups differ in size, stellar age gradients, and disk-to-total mass ratios. Specifically, codes with strong wet compaction build their outer disks in an inside-out fashion, leading to negative age gradients, whereas codes with weaker compaction feature flat or positive age gradients caused primarily by outward stellar migration. Although the stellar half-mass radii of these two groups diverge at $z \sim 3$, the inclusion of dust extinction brings their sizes and shapes in mock observations closer to each other and to observed galaxies. We attribute the observed morphological differences primarily to variations in the stellar feedback implementations -- such as delayed cooling timescales, and feedback strengths -- that regulate both the onset and duration of compaction. Overall, our results suggest that disk assembly at high redshifts is highly sensitive to the details of the stellar feedback prescriptions in simulations.

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Hints of Primordial Magnetic Fields at Recombination and Implications for the Hubble Tension

Primordial Magnetic Fields (PMFs), long studied as relics of the early Universe, accelerate recombination and have been proposed as a way to relieve the Hubble tension. However, previous studies relied on simplified toy models. Here we use recent evaluations of recombination with PMFs, incorporating full magnetohydrodynamic (MHD) simulations and detailed Lyman-alpha radiative transfer, to test PMF-enhanced recombination ($b\Lambda$CDM) against observational data from the cosmic microwave background (CMB), baryon acoustic oscillations (BAO), and Type Ia supernovae (SN). Focusing on non-helical PMFs with a Batchelor spectrum, we find a preference for present-day total field strengths of approximately 5-10 pico-Gauss. Depending on the dataset combination, this preference ranges from mild ($\sim 1.8\sigma$ with Planck + DESI) to moderate ($\sim 3\sigma$ with Planck + DESI + SH0ES-calibrated SN) significance. The $b\Lambda$CDM has Planck + DESI $\chi^2$ values equal to or better than $\Lambda$CDM while predicting a higher Hubble constant. Future high-resolution CMB temperature and polarization measurements will be crucial for confirming or further constraining PMFs at recombination. Field strengths of 5-10 pico-Gauss align closely with those required for cluster magnetic fields to originate entirely from primordial sources, without the need for additional dynamo amplification.

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Geometric Interpretations of the $k$-Nearest Neighbour Distributions

The $k$-Nearest Neighbour Cumulative Distribution Functions are measures of clustering for discrete datasets that are fast and efficient to compute. They are significantly more informative than the 2-point correlation function. Their connection to $N$-point correlation functions, void probability functions and Counts-in-Cells is known. However, the connections between the CDFs and other geometric and topological spatial summary statistics are yet to be fully explored in the literature. This understanding will be crucial to find optimally informative summary statistics to analyse data from stage 4 cosmological surveys. We explore quantitatively the geometric interpretations of the $k$NN CDF summary statistics. We establish an equivalence between the 1NN CDF at radius $r$ and the volume of spheres with the same radius around the data points. We show that higher $k$NN CDFs are equivalent to the volumes of intersections of $\ge k$ spheres around the data points. We present similar geometric interpretations for the $k$NN cross-correlation joint CDFs. We further show that the volume, or the CDFs, have information about the angles and arc lengths created at the intersections of spheres around the data points, which can be accessed through the derivatives of the CDF. We show this information is very similar to that captured by Germ Grain Minkowski Functionals. Using a Fisher analysis we compare the information content and constraining power of various data vectors constructed from the $k$NN CDFs and Minkowski Functionals. We find that the CDFs and their derivatives and the Minkowski Functionals have nearly identical information content. However, $k$NN CDFs are computationally orders of magnitude faster to evaluate. Finally, we find that there is information in the full shape of the CDFs, and therefore caution against using the values of the CDF only at sparsely sampled radii.

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A Parameter-Masked Mock Data Challenge for Beyond-Two-Point Galaxy Clustering Statistics

The last few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge "Beyond-2pt", initiated during the Aspen 2022 Summer Program "Large-Scale Structure Cosmology beyond 2-Point Statistics," whose first round of results we present here. The challenge dataset consists of high-precision mock galaxy catalogs for clustering in real space, redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown ("masked") cosmological parameters of the underlying $\Lambda$CDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available and we welcome future submissions from methods that are not yet represented.

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The SAGA Survey. V. Modeling Satellite Systems around Milky Way-mass Galaxies with Updated UniverseMachine

Environment plays a critical role in shaping the assembly of low-mass galaxies. Here, we use the UniverseMachine (UM) galaxy-halo connection framework and the Data Release 3 of the Satellites Around Galactic Analogs (SAGA) Survey to place dwarf galaxy star formation and quenching into a cosmological context. UM is a data-driven forward model that flexibly parameterizes galaxy star formation rates (SFR) using only halo mass and assembly history. We add a new quenching model to UM, tailored for galaxies with stellar masses $\lesssim 10^9$ solar masses, and constrain the model down to a stellar mass $\gtrsim 10^7$ solar masses using new SAGA observations of 101 satellite systems around Milky Way (MW)-mass hosts and a sample of isolated field galaxies in a similar mass range from the Sloan Digital Sky Survey (SDSS). The new best-fit model, 'UM-SAGA,' reproduces the satellite stellar mass functions, average SFRs, and quenched fractions in SAGA satellites while keeping isolated dwarfs mostly star forming. The enhanced quenching in satellites relative to isolated field galaxies leads the model to maximally rely on halo assembly to explain the observed environmental quenching. Extrapolating the model down to a stellar mass $\sim 10^{6.5}$ solar masses yields a quenched fraction of $\gtrsim$ 30% for isolated field galaxies and $\gtrsim$ 80% for satellites of MW-mass hosts at this stellar mass. This specific prediction can soon be tested by spectroscopic surveys to reveal the relative importance of internal feedback, cessation of mass and gas accretion, satellite-specific gas processes, and reionization for the evolution of faint low-mass galaxies.

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The AGORA High-resolution Galaxy Simulations Comparison Project IV: Halo and Galaxy Mass Assembly in a Cosmological Zoom-in Simulation at $z\le2$

In this fourth paper from the AGORA Collaboration, we study the evolution down to redshift $z=2$ and below of a set of cosmological zoom-in simulations of a Milky Way mass galaxy by eight of the leading hydrodynamic simulation codes. We also compare this CosmoRun suite of simulations with dark matter-only simulations by the same eight codes. We analyze general properties of the halo and galaxy at $z=4$ and 3, and before the last major merger, focusing on the formation of well-defined rotationally-supported disks, the mass-metallicity relation, the specific star formation rate, the gas metallicity gradients, and the non-axisymmetric structures in the stellar disks. Codes generally converge well to the stellar-to-halo mass ratios predicted by semi-analytic models at $z\sim$2. We see that almost all the hydro codes develop rotationally-supported structures at low redshifts. Most agree within 0.5 dex with the observed MZR at high and intermediate redshifts, and reproduce the gas metallicity gradients obtained from analytical models and low-redshift observations. We confirm that the inter-code differences in the halo assembly history reported in the first paper of the collaboration also exist in CosmoRun, making the code-to-code comparison more difficult. We show that such differences are mainly due to variations in code-dependent parameters that control the time-stepping strategy of the gravity solver. We find that variations in the early stellar feedback can also result in differences in the timing of the low-redshift mergers. All the simulation data down to $z=2$ and the auxiliary data will be made publicly available.

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The AGORA High-resolution Galaxy Simulations Comparison Project. V: Satellite Galaxy Populations In A Cosmological Zoom-in Simulation of A Milky Way-mass Halo

We analyze and compare the satellite halo populations at $z\sim2$ in the high-resolution cosmological zoom-in simulations of a $10^{12}\,{\rm M}_{\odot}$ target halo ($z=0$ mass) carried out on eight widely-used astrophysical simulation codes ({\sc Art-I}, {\sc Enzo}, {\sc Ramses}, {\sc Changa}, {\sc Gadget-3}, {\sc Gear}, {\sc Arepo-t}, and {\sc Gizmo}) for the {\it AGORA} High-resolution Galaxy Simulations Comparison Project. We use slightly different redshift epochs near $z=2$ for each code (hereafter ``$z\sim2$') at which the eight simulations are in the same stage in the target halo's merger history. After identifying the matched pairs of halos between the {\it CosmoRun} simulations and the DMO simulations, we discover that each {\it CosmoRun} halo tends to be less massive than its DMO counterpart. When we consider only the halos containing stellar particles at $z\sim2$, the number of satellite {\it galaxies} is significantly fewer than that of dark matter halos in all participating {\it AGORA} simulations, and is comparable to the number of present-day satellites near the Milky Way or M31. The so-called ``missing satellite problem' is fully resolved across all participating codes simply by implementing the common baryonic physics adopted in {\it AGORA} and the stellar feedback prescription commonly used in each code, with sufficient numerical resolution ($\lesssim100$ proper pc at $z=2$). We also compare other properties such as the stellar mass$-$halo mass relation and the mass$-$metallicity relation. Our work highlights the value of comparison studies such as {\it AGORA}, where outstanding problems in galaxy formation theory are studied simultaneously on multiple numerical platforms.

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The AGORA High-resolution Galaxy Simulations Comparison Project. VI. Similarities and Differences in the Circumgalactic Medium

We analyze the circumgalactic medium (CGM) for eight commonly-used cosmological codes in the AGORA collaboration. The codes are calibrated to use identical initial conditions, cosmology, heating and cooling, and star formation thresholds, but each evolves with its own unique code architecture and stellar feedback implementation. Here, we analyze the results of these simulations in terms of the structure, composition, and phase dynamics of the CGM. We show properties such as metal distribution, ionization levels, and kinematics are effective tracers of the effects of the different code feedback and implementation methods, and as such they can be highly divergent between simulations. This is merely a fiducial set of models, against which we will in the future compare multiple feedback recipes for each code. Nevertheless, we find that the large parameter space these simulations establish can help disentangle the different variables that affect observable quantities in the CGM, e.g., showing that abundances for ions with higher ionization energy are more strongly determined by the simulation's metallicity, while abundances for ions with lower ionization energy are more strongly determined by the gas density and temperature.

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Cosmic Recombination in the Presence of Primordial Magnetic Fields

Primordial magnetic fields (PMFs) may explain observations of magnetic fields on extragalactic scales. They are most cleanly constrained by measurements of cosmic microwave background radiation (CMB) anisotropies. Their effects on cosmic recombination may even be at the heart of the resolution of the Hubble tension. We present the most detailed analysis of the effects of PMFs on cosmic recombination to date. To this end we extend the public magneto-hydrodynamic code {\sl ENZO} with a new cosmic recombination routine, Monte-Carlo simulations of Lyman-$\alpha$ photon transport, and a Compton drag term in the baryon momentum equation. The resulting code allows us, for the first time, to realistically predict the impact of PMFs on the cosmic ionization history and the clumping of baryons during cosmic recombination. Our results identify the importance of mixing of Lyman-$\alpha$ photons between overdense- and underdense- regions for small PMF strength. This mixing speeds up recombination beyond the speed-up due to clumping. We also investigate the effects of pecuilar flows on the recombination rate and find it to be small for small PMF strengths. For non-helical PMFs with a Batchelor spectrum we find a surprising dependency of results on ultra-violet magnetic modes. We further show that the increase in the ionization fraction at low redshift by hydrodynamic baryon heating due to PMF dissipation is completely compensated by the faster recombination from baryon clumping. The present study shall serve as a theoretical foundation for a future precise comparison of recombination with PMFs to CMB data.

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The classical field approximation of ultra light dark matter: quantum breaktimes, corrections, and decoherence

The classical field approximation is widely used to better understand the predictions of ultra-light dark matter. Here, we use the truncated Wigner approximation method to test the classical field approximation of ultra-light dark matter. This method approximates a quantum state as an ensemble of independently evolving realizations drawn from its Wigner function. The method is highly parallelizable and allows the direct simulation of quantum corrections and decoherence times in systems many times larger than have been previously studied in reference to ultra-light dark matter. Our study involves simulation of systems in 1, 2, and 3 spatial dimensions. We simulate three systems, the condensation of a Gaussian random field in three spatial dimensions, a stable collapsed object in three spatial dimensions, and the merging of two stable objects in two spatial dimensions. We study the quantum corrections to the classical field theory in each case. We find that quantum corrections grow exponentially during nonlinear growth with the timescale being approximately equal to the system dynamical time. In stable systems the corrections grow quadratically. We also find that the primary effect of quantum corrections is to reduce the amplitude of fluctuations on the deBroglie scale in the spatial density. Finally, we find that the timescale associated with decoherence due to gravitational coupling to Baryonic matter is at least as fast as the quantum corrections due to gravitational interactions. These results strongly imply that quantum corrections do not impact the predictions of the classical field theory.

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