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Greg L. Bryan

Publications and source records attributed to Greg L. Bryan.

At least 91 records · Page 5Linked to original sources

Code Comparison in Galaxy Scale Simulations with Resolved Supernova Feedback: Lagrangian vs. Eulerian Methods

We present a suite of high-resolution simulations of an isolated dwarf galaxy using four different hydrodynamical codes: {\sc Gizmo}, {\sc Arepo}, {\sc Gadget}, and {\sc Ramses}. All codes adopt the same physical model which includes radiative cooling, photoelectric heating, star formation, and supernova (SN) feedback. Individual SN explosions are directly resolved without resorting to sub-grid models, eliminating one of the major uncertainties in cosmological simulations. We find reasonable agreement on the time-averaged star formation rates as well as the joint density-temperature distributions between all codes. However, the Lagrangian codes show significantly burstier star formation, larger supernova-driven bubbles, and stronger galactic outflows compared to the Eulerian code. This is caused by the behavior in the dense, collapsing gas clouds when the Jeans length becomes unresolved: gas in Lagrangian codes collapses to much higher densities than in Eulerian codes, as the latter is stabilized by the minimal cell size. Therefore, more of the gas cloud is converted to stars and SNe are much more clustered in the Lagrangian models, amplifying their dynamical impact. The differences between Lagrangian and Eulerian codes can be reduced by adopting a higher star formation efficiency in Eulerian codes, which significantly enhances SN clustering in the latter. Adopting a zero SN delay time reduces burstiness in all codes, resulting in vanishing outflows as SN clustering is suppressed.

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Efficient long-range AGN feedback affects the low redshift Lyman-$α$ forest

Active galactic nuclei (AGN) feedback models are generally calibrated to reproduce galaxy observables such as the stellar mass function and the bimodality in galaxy colors. We use variations of the AGN feedback implementations in the IllustrisTNG (TNG) and Simba cosmological hydrodynamic simulations to show that the low redshift Lyman-$α$ forest can provide constraints on the impact of AGN feedback. We show that TNG over-predicts the number density of absorbers at column densities $N_{\rm HI} < 10^{14}$ cm$^{-2}$ compared to data from the Cosmic Origins Spectrograph (in agreement with previous work), and we demonstrate explicitly that its kinetic feedback mode, which is primarily responsible for galaxy quenching, has a negligible impact on the column density distribution (CDD) of absorbers. In contrast, we show that the fiducial Simba model which includes AGN jet feedback is the preferred fit to the observed CDD of the $z = 0.1$ Lyman-$α$ forest across five orders of magnitude in column density. We show that the Simba results with jets produce a quantitatively better fit to the observational data than the Simba results without jets, even when the UVB is left as a free parameter. AGN jets in Simba are high speed, collimated, weakly-interacting with the interstellar medium (via brief hydrodynamic decoupling) and heated to the halo virial temperature. Collectively these properties result in stronger long-range impacts on the IGM when compared to TNG's kinetic feedback mode, which drives isotropic winds with lower velocities at the galactic radius. Our results suggest that the low redshift Lyman-$α$ forest provides plausible evidence for long-range AGN jet feedback.

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The structure and composition of multiphase galactic winds in a Large Magellanic Cloud mass simulated galaxy

We present the first results from a high resolution simulation with a focus on galactic wind driving for an isolated galaxy with a halo mass of $\sim 10^{11}$ M$_{\odot}$ (similar to the Large Magellanic Cloud) and a total gas mass of $\sim 6 \times 10^{8}$ M$_{\odot}$, resulting in $\sim 10^{8}$ gas cells at $\sim 4$ M$_{\odot}$ mass resolution. We adopt a resolved stellar feedback model with non-equilibrium cooling and heating, including photoelectric heating and photo-ionizing radiation, as well as supernovae (SNe), coupled to the second order meshless finite mass (MFM) method for hydrodynamics. These features make this the largest resolved-ISM galaxy model run to date. We find mean star formation rates around $0.05$ M$_{\odot}$ yr$^{-1}$ and evaluate typical time averaged loading factors for mass ($η_\mathrm{M}$ $\sim$ 1.0, in good agreement with recent observations) and energy ($η_\mathrm{E}$ $\sim$ 0.01). The bulk of the mass of the wind is transported by the warm ($T < 5 \times 10^5$K) phase, while there is a similar amount of energy transported in the warm and the hot phases ($T > 5 \times 10^5$K). We find an average opening angle of 30 degrees for the wind, decreasing with higher altitude above the midplane. The wind mass loading is decreasing (flat) for the warm (hot) phase as a function of the star formation surface rate density $Σ_{\rm SFR}$, while the energy loading shows inverted trends with $Σ_{\rm SFR}$, decreasing for the warm wind and increasing for the hot wind, although with very shallow slopes. These scalings are in good agreement with previous simulations of resolved wind driving in the multi-phase ISM.

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Calibrating cosmological simulations with implicit likelihood inference using galaxy growth observables

In a novel approach employing implicit likelihood inference (ILI), also known as likelihood-free inference, we calibrate the parameters of cosmological hydrodynamic simulations against observations, which has previously been unfeasible due to the high computational cost of these simulations. For computational efficiency, we train neural networks as emulators on ~1000 cosmological simulations from the CAMELS project to estimate simulated observables, taking as input the cosmological and astrophysical parameters, and use these emulators as surrogates to the cosmological simulations. Using the cosmic star formation rate density (SFRD) and, separately, stellar mass functions (SMFs) at different redshifts, we perform ILI on selected cosmological and astrophysical parameters (Omega_m, sigma_8, stellar wind feedback, and kinetic black hole feedback) and obtain full 6-dimensional posterior distributions. In the performance test, the ILI from the emulated SFRD (SMFs) can recover the target observables with a relative error of 0.17% (0.4%). We find that degeneracies exist between the parameters inferred from the emulated SFRD, confirmed with new full cosmological simulations. We also find that the SMFs can break the degeneracy in the SFRD, which indicates that the SMFs provide complementary constraints for the parameters. Further, we find that the parameter combination inferred from an observationally-inferred SFRD reproduces the target observed SFRD very well, whereas, in the case of the SMFs, the inferred and observed SMFs show significant discrepancies that indicate potential limitations of the current galaxy formation modeling and calibration framework, and/or systematic differences and inconsistencies between observations of the stellar mass function.

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If dark matter is fuzzy, the first stars form in massive pancakes

Fuzzy dark matter (FDM) is a proposed modification for the standard cold dark matter (CDM) model motivated by small-scale discrepancies in low-mass galaxies. Composed of ultra-light (mass $\sim 10^{-22}$ eV) axions with kpc-scale de Broglie wavelengths, this is one of a class of candidates that predicts that the first collapsed objects form in relatively massive dark matter halos. This implies that the formation history of the first stars and galaxies would be very different, potentially placing strong constraints on such models. Here we numerically simulate the formation of the first stars in an FDM cosmology, following the collapse in a representative volume all the way down to primordial protostar formation including a primordial non-equilibrium chemical network and cooling for the first time. We find two novel results: first, the large-scale collapse results in a very thin and flat gas "pancake"; second, despite the very different cosmology, this pancake fragments until it forms protostellar objects indistinguishable from those in CDM. Combined, these results indicate that the first generation of stars in this model are also likely to be massive and, because of the sheet morphology, do not self-regulate, resulting in a massive Pop III starburst. We estimate the total number of first stars forming in this extended structure to be $10^4$ over 20 Myr using a simple model to account for the ionizing feedback from the stars, and should be observable with JWST. These predictions provide a potential smoking gun signature of FDM and similar dark matter candidates.

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Regulation of Star Formation by a Hot Circumgalactic Medium

Galactic outflows driven by supernovae (SNe) are thought to be a powerful regulator of a galaxy's star-forming efficiency. Mass, energy, and metal outflows ($η_M$, $η_E$, and $η_Z$, here normalized by the star formation rate, the SNe energy and metal production rates, respectively) shape galaxy properties by both ejecting gas and metals out of the galaxy and by heating the circumgalactic medium (CGM), preventing future accretion. Traditionally, models have assumed that galaxies self-regulate by ejecting a large fraction of the gas which enters the interstellar medium (ISM), even though such high mass-loadings are in growing tension with observations. To better understand how the relative importance of ejective (i.e. high mass-loading) vs preventative (i.e. high energy-loading) feedback affects the present-day properties of galaxies, we develop a simple gas-regulator model of galaxy evolution, where the stellar mass, ISM, and CGM are modeled as distinct reservoirs which exchange mass, metals, and energy at different rates within a growing halo. Focusing on the halo mass range from $10^{10}$ to $10^{12} M_{\odot}$, we demonstrate that, with reasonable parameter choices, we can reproduce the stellar-to-halo mass relation and the ISM-to-stellar mass relation with low mass-loaded ($η_M \sim 0.1-10$) but high energy-loaded ($η_E \sim 0.1-1$) winds, with self-regulation occurring primarily through heating and cooling of the CGM. We show that the model predictions are robust against changes to the mass-loading of outflows but are quite sensitive to our choice of the energy-loading, preferring $η_E \sim 1$ for the lowest mass halos and $\sim 0.1$ for Milky Way-like halos.

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Robust field-level inference with dark matter halos

We train graph neural networks on halo catalogues from Gadget N-body simulations to perform field-level likelihood-free inference of cosmological parameters. The catalogues contain $\lesssim$5,000 halos with masses $\gtrsim 10^{10}~h^{-1}M_\odot$ in a periodic volume of $(25~h^{-1}{\rm Mpc})^3$; every halo in the catalogue is characterized by several properties such as position, mass, velocity, concentration, and maximum circular velocity. Our models, built to be permutationally, translationally, and rotationally invariant, do not impose a minimum scale on which to extract information and are able to infer the values of $Ω_{\rm m}$ and $σ_8$ with a mean relative error of $\sim6\%$, when using positions plus velocities and positions plus masses, respectively. More importantly, we find that our models are very robust: they can infer the value of $Ω_{\rm m}$ and $σ_8$ when tested using halo catalogues from thousands of N-body simulations run with five different N-body codes: Abacus, CUBEP$^3$M, Enzo, PKDGrav3, and Ramses. Surprisingly, the model trained to infer $Ω_{\rm m}$ also works when tested on thousands of state-of-the-art CAMELS hydrodynamic simulations run with four different codes and subgrid physics implementations. Using halo properties such as concentration and maximum circular velocity allow our models to extract more information, at the expense of breaking the robustness of the models. This may happen because the different N-body codes are not converged on the relevant scales corresponding to these parameters.

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LYRA III: The smallest Reionization survivors

The dividing line between galaxies that are quenched by reionization ("relics") and galaxies that survive reionization (i.e. continue forming stars) is commonly discussed in terms of a halo mass threshold. We probe this threshold in a physically more complete and accurate way than has been possible to date, using five extremely high resolution ($M_\mathrm{target}=4M_\odot$) cosmological zoom-in simulations of dwarf galaxies within the halo mass range $1-4\times10^9M_\odot$. The employed LYRA simulation model features resolved interstellar medium physics and individual, resolved supernova explosions. In our results, we discover an interesting intermediate population of dwarf galaxies close to the threshold mass but which are neither full reionization relics nor full reionization survivors. These galaxies initially quench at the time of reionization but merely remain quiescent for ~500Myr. At $z\approx5$ they recommence star formation in a synchronous way, and remain star-forming until the present day. These results demonstrate that the halo mass at $z=0$ is not a good indicator of survival close to the threshold. While the star formation histories we find are diverse, we show that they are directly related to the ability of a given halo to retain and cool gas. Whereas the latter is most strongly dependent on the mass (or virial temperature) of the host halo at the time of reionization, it also depends on its growth history, the UV background (and its decrease at late times) and the amount of metals retained within the halo.

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HIFlow: Generating Diverse HI Maps and Inferring Cosmology while Marginalizing over Astrophysics using Normalizing Flows

A wealth of cosmological and astrophysical information is expected from many ongoing and upcoming large-scale surveys. It is crucial to prepare for these surveys now and develop tools that can efficiently extract most information. We present HIFlow: a fast generative model of the neutral hydrogen (HI) maps that is conditioned only on cosmology ($Ω_{m}$ and $σ_{8}$) and designed using a class of normalizing flow models, the Masked Autoregressive Flow (MAF). HIFlow is trained on the state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project. HIFlow has the ability to generate realistic diverse maps without explicitly incorporating the expected 2D maps structure into the flow as an inductive bias. We find that HIFlow is able to reproduce the CAMELS average and standard deviation HI power spectrum (Pk) within a factor of $\lesssim$ 2, scoring a very high $R^{2} > 90\%$. By inverting the flow, HIFlow provides a tractable high-dimensional likelihood for efficient parameter inference. We show that the conditional HIFlow on cosmology is successfully able to marginalize over astrophysics at the field level, regardless of the stellar and AGN feedback strengths. This new tool represents a first step toward a more powerful parameter inference, maximizing the scientific return of future HI surveys, and opening a new avenue to minimize the loss of complex information due to data compression down to summary statistics.

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Reorientation Rates of Structural and Kinematic Axes in Simulated Massive Galaxies and the Origins of Prolate Rotation

In this work, we analyze a sample of $\sim$4000 massive ($M_*\geq 10^{11} M_\odot$ at $z=0$) galaxies in TNG300, the $(300 \mathrm{Mpc})^3$ box of the IllustrisTNG simulation suite. We characterize the shape and kinematics of these galaxies with a focus on the kinematic misalignment ($Ψ_\mathrm{int}$) between the angular momentum (AM) and morphological major axis. We find that the traditional purely shape- or kinematics-based classifications are insufficient to characterize the diversity of our sample and define a new set of classes based on the rates of change of the galaxies' morphological and kinematic axes. We show that these classes are mostly stable over time and correspond to six distinct populations of galaxies: the rapid AM reorienters (58% of our sample), unsettled galaxies (10%), spinning disks (10%), twirling cigars (16%), misaligned slow reorienters (3%), and regular prolate rotators (galaxies that display major axis rotation; 2%). We demonstrate that the most-recent significant (mass-ratio $μ>1/10$) mergers of these galaxies are the primary cause for their present-day properties and find that these mergers are best characterized at the point of the satellite's final infall -- that is, much closer to the final coalescence than has been previously thought. We show that regular prolate rotators evolve from spinning disk progenitors that experience a radial merger along their internal AM direction. Finally, we argue that these regular prolate rotators are distinct from the similarly-sized population of rapid AM reorienters with large $Ψ_\mathrm{int}$, implying that a large $Ψ_\mathrm{int}$ is not a sufficient condition for major axis rotation.

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Self-regulation of black hole accretion via jets in early protogalaxies

The early growth of black holes (BHs) in high-redshift galaxies is likely regulated by their feedback on the surrounding gas. While radiative feedback has been extensively studied, the role of mechanical feedback has received comparatively less scrutiny to date. Here we use high-resolution parsec-scale hydrodynamical simulations to study jet propagation and its effect on BH accretion onto 100 ${\rm M_\odot}$ BHs in the dense, low-metallicity gas expected in early protogalaxies. As the jet propagates, it shocks the surrounding gas and forms a jet cocoon. The cocoon consists of a rapidly-cooling cold phase at the interface with the background gas and an over-pressured subsonic phase of reverse shock-heated gas filling the cocoon interior. We systematically vary the background gas density and temperature, BH feedback efficiency, and the jet model. We found that the jet cocoon width roughly follows a scaling derived by assuming momentum conservation in the jet propagation direction, and energy conservation in the lateral directions. Depending on the assumed gas and jet properties, the cocoon either stays elongated out to a large radius or isotropizes before reaching the Bondi radius, forming a nearly spherical bubble. Lower jet velocities and higher background gas densities result in self-regulation to higher momentum fluxes and elongated cocoons. In all cases, the outward momentum flux of the cocoon balances the inward momentum flux of the inflowing gas near the Bondi radius, which ultimately regulates BH accretion. The larger the distance the jet cocoon reaches, the longer the variability timescale of the BH accretion rate. Overall, the average accretion rate always remains below the Bondi rate, and exceeds the Eddington rate only if the ambient medium is dense and cold, and/or the jet is weak. We derive the combination of jet and ambient gas parameters yielding super-Eddington growth.

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The low redshift Lyman-$α$ Forest as a constraint for models of AGN feedback

We study the sensitivity of the $z=0.1$ Lyman-$α$ Forest observables, such as the column density distribution function (CDD), flux PDF, flux power spectrum, and line width distribution, to sub-grid models of active galactic nuclei (AGN) feedback using the Illustris and IllustrisTNG (TNG) cosmological simulations. The two simulations share an identical Ultraviolet Background (UVB) prescription and similar cosmological parameters, but TNG features an entirely reworked AGN feedback model. Due to changes in the AGN radio mode model, the original Illustris simulations have a factor of 2-3 fewer Lyman-$α$ absorbers than TNG at column densities $N_{\rm HI}< 10^{15.5}$ cm$^{-2}$. We compare the simulated forest statistics to UV data from the Cosmic Origins Spectrograph (COS) and find that neither simulation can reproduce the slope of the absorber distribution. Both Illustris and TNG also produce significantly smaller line width distributions than observed in the COS data. We show that TNG is in much better agreement with the observed $z=0.1$ flux power spectrum than Illustris. We explore which statistics can disentangle the effects of AGN feedback from alternative UVB models by rescaling the UVB of Illustris to produce a CDD match to TNG. While this UVB rescaling is degenerate with the effect of AGN feedback on the CDD, the amplitude and shape of the flux PDF and 1D flux power spectrum change in a way distinct from a scaling of the UVB. Our study suggests that the $z=0.1$ Lyman-$α$ forest observables can be used as a diagnostic of AGN feedback models.

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On the impact of runaway stars on dwarf galaxies with resolved interstellar medium

About ten to 20 percent of massive stars may be kicked out of their natal clusters before exploding as supernovae. These "runaway stars" might play a crucial role in driving galactic outflows and enriching the circumgalactic medium with metals. To study this effect, we carry out high resolution dwarf galaxy simulations that include velocity kicks to massive O/B stars above 8 M$_{\odot}$. We consider two scenarios, one that adopts a power law velocity distribution for kick velocities, resulting in more stars with high velocity kicks, and a more moderate scenario with a Maxwellian velocity distribution. We explicitly resolve the multi-phase interstellar medium (ISM), and include non-equilibrium cooling and chemistry channels. We adopt a resolved feedback scheme (\textsc{Griffin}) where we sample individual massive stars from an IMF. We follow the lifetime of these stars and add their photoionising radiation, their UV radiation field, and their photoelectric heating rate to the surrounding gas. At the end of their lifetime we explode the massive population as core collapse supernovae (CCSN). In the simulations with runaway massive stars, we add additional (natal) velocity kicks that mimic two and three body interactions that cannot be fully resolved in our simulations. We find that the inclusion of runaway or walkaway star scenarios has an impact on mass, metal, momentum and energy outflows as well as the respective loading factors. We find an increase in mass, metal and momentum loading by a factor of 2-3, whereas we find an increase in the mean energy loading by a factor of 5 in the runaway case and a factor of 3 in the walkaway case. However, we find that the peak values are increased by a factor of up to 10, independent of the adopted velocity kick model. We conclude that the inclusion of runaway stars could have a significant impact on the global outflow properties of dwarf galaxies.

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Formation and evolution of young massive clusters in galaxy mergers: the SMUGGLE view

Galaxy mergers are known to host abundant young massive cluster (YMC) populations, whose formation mechanism is still not well-understood. Here, we present a high-resolution galaxy merger simulation with explicit star formation and stellar feedback prescriptions to investigate how mergers affect the properties of the interstellar medium and YMCs. Compared with a controlled simulation of an isolated galaxy, the mass fraction of dense and high-pressure gas is much higher in mergers. Consequently, the mass function of both molecular clouds and YMCs becomes shallower and extends to higher masses. Moreover, cluster formation efficiency is significantly enhanced and correlates positively with the star formation rate surface density and gas pressure. We track the orbits of YMCs and investigate the time evolution of tidal fields during the course of the merger. At an early stage of the merger, the tidal field strength correlates positively with YMC mass, $λ_{\rm tid}\propto M^{0.71}$, which systematically affects the shape of the mass function and age distribution of the YMCs. At later times, most YMCs closely follow the orbits of their host galaxies, gradually sinking into the center of the merger remnant due to dynamical friction, and are quickly dissolved via efficient tidal disruption. Interestingly, YMCs formed during the first passage, mostly in tidal tails and bridges, are distributed over a wide range of galactocentric radii, greatly increasing their survivability because of the much weaker tidal field in the outskirts of the merger system. These YMCs are promising candidates for globular clusters that survive to the present day.

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Gas Accretion Can Drive Turbulence in Galaxies

The driving of turbulence in galaxies is deeply connected with the physics of feedback, star formation, outflows, accretion, and radial transport in disks. The velocity dispersion of gas in galaxies therefore offers a promising observational window into these processes. However, the relative importance of each of these mechanisms remains controversial. In this work we revisit the possibility that turbulence on galactic scales is driven by the direct impact of accreting gaseous material on the disk. We measure this effect in a disk-like star-forming galaxy in IllustrisTNG, using the high-resolution cosmological magnetohydrodynamical simulation TNG50. We employ Lagrangian tracer particles with a high time cadence of only a few Myr to identify accretion and other events, such as star formation, outflows, and movement within the disk. The energies of particles as they arrive in the disk are measured by stacking the events in bins of time before and after the event. The average effect of each event is measured on the galaxy by fitting explicit models for the kinetic and turbulent energies as a function of time in the disk. These measurements are corroborated by measuring the cross-correlation of the turbulent energy in the different annuli of the disk with other time series, and searching for signals of causality, i.e. asymmetries in the cross-correlation across zero time lag. We find that accretion contributes to the large-scale turbulent kinetic energy even if it is not the dominant driver of turbulence in this $\sim 5 \times 10^{9} M_\odot$ stellar mass galaxy. Extrapolating this finding to a range of galaxy masses, we find that there are regimes where energy from direct accretion may dominate the turbulent energy budget, particularly in disk outskirts, galaxies less massive than the Milky Way, and at redshift $\sim 2$.

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The Circumgalactic Medium from the CAMELS Simulations: Forecasting Constraints on Feedback Processes from Future Sunyaev-Zeldovich Observations

The cycle of baryons through the circumgalactic medium (CGM) is important to understand in the context of galaxy formation and evolution. In this study we forecast constraints on the feedback processes heating the CGM with current and future Sunyaev-Zeldovich (SZ) observations. To constrain these processes, we use a suite of cosmological simulations, the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS), that varies four different feedback parameters of two previously existing hydrodynamical simulations, IllustrisTNG and SIMBA. We capture the dependencies of SZ radial profiles on these feedback parameters with an emulator, calculate their derivatives, and forecast future constraints on these feedback parameters from upcoming experiments. We find that for a DESI-like (Dark Energy Spectroscopic Instrument) galaxy sample observed by the Simons Observatory all four feedback parameters are able to be constrained (some within the $10\%$ level), indicating that future observations will be able to further restrict the parameter space for these sub-grid models. Given the modeled galaxy sample and forecasted errors in this work, we find that the inner SZ profiles contribute more to the constraining power than the outer profiles. Finally, we find that, despite the wide range of AGN feedback parameter variation in the CAMELS simulation suite, we cannot reproduce the tSZ signal of galaxies selected by the Baryon Oscillation Spectroscopic Survey as measured by the Atacama Cosmology Telescope.

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The CAMELS project: public data release

The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4,233 cosmological simulations, 2,049 N-body and 2,184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogues, power spectra, bispectra, Lyman-$α$ spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over one thousand catalogues that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz Semi-Analytic Model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies and summary statistics. We provide further technical details on how to access, download, read, and process the data at \url{https://camels.readthedocs.io}.

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A Comparison of Circumgalactic MgII Absorption between the TNG50 Simulation and the MEGAFLOW Survey

The circumgalactic medium (CGM) contains information on gas flows around galaxies, such as accretion and supernova-driven winds, which are difficult to constrain from observations alone. Here, we use the high-resolution TNG50 cosmological magnetohydrodynamical simulation to study the properties and kinematics of the CGM around star-forming galaxies in $10^{11.5}-10^{12}\;M_{\odot}$ halos at $z\simeq$ 1 using mock MgII absorption lines, which we generate by postprocessing halos to account for photoionization in the presence of a UV background. We find that the MgII gas is a very good tracer of the cold CGM, which is accreting inward at inflow velocities of up to 50 km s$^{-1}$. For sight lines aligned with the galaxy's major axis, we find that MgII absorption lines are kinematically shifted due to the cold CGM's significant corotation at speeds up to 50% of the virial velocity for impact parameters up to 60 kpc. We compare mock MgII spectra to observations from the MusE GAs FLow and Wind (MEGAFLOW) survey of strong MgII absorbers ($\rm{EW}^{2796Å}_{0}>0.5 \; Å$). After matching the equivalent-width (EW) selection, we find that the mock MgII spectra reflect the diversity of observed kinematics and EWs from MEGAFLOW, even though the sight lines probe a very small fraction of the CGM. MgII absorption in higher-mass halos is stronger and broader than in lower-mass halos but has qualitatively similar kinematics. The median-specific angular momentum of the MgII CGM gas in TNG50 is very similar to that of the entire CGM and only differs from non-CGM components of the halo by normalization factors of $\lesssim$ 1 dex.

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