arXiv subjects

Romeel Dave

Publications and source records attributed to Romeel Dave.

At least 55 records · Page 3Linked to original sources

arXiv2021

Detection of a Multiphase Intragroup Medium: Results from the COS-IGrM Survey

We present the results of the COS Intragroup Medium (COS-IGrM) Survey that used the Cosmic Origins Spectrograph on the Hubble Space Telescope to observe a sample of 18 UV bright quasars, each probing the intragroup medium (IGrM) of a galaxy group. We detect Ly$α$, C II, N V, Si II, Si III, and O VI in multiple sightlines. The highest ionization species detected in our data is O VI, which was detected in 8 out of 18 quasar sightlines. The wide range of ionization states observed provide evidence that the IGrM is patchy and multiphase. We find that the O VI detections generally align with radiatively cooling gas between $10^{5.8}$ and $10^6$ K. The lack of O VI detections in 10 of the 18 groups illustrates that O VI may not be the ideal tracer of the volume filling component of the IGrM. Instead, it either exists at trace levels in a hot IGrM or is generated in the boundary between the hotter IGrM and cooler gas.

astro-ph.GA↗

arXiv2021

The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence

We present the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) Multifield Dataset, CMD, a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from 2,000 distinct simulated universes at several cosmic times. The 2D maps and 3D grids represent cosmic regions that span $\sim$100 million light years and have been generated from thousands of state-of-the-art hydrodynamic and gravity-only N-body simulations from the CAMELS project. Designed to train machine learning models, CMD is the largest dataset of its kind containing more than 70 Terabytes of data. In this paper we describe CMD in detail and outline a few of its applications. We focus our attention on one such task, parameter inference, formulating the problems we face as a challenge to the community. We release all data and provide further technical details at https://camels-multifield-dataset.readthedocs.io.

cs.LG↗

arXiv2021

Robust marginalization of baryonic effects for cosmological inference at the field level

We train neural networks to perform likelihood-free inference from $(25\,h^{-1}{\rm Mpc})^2$ 2D maps containing the total mass surface density from thousands of hydrodynamic simulations of the CAMELS project. We show that the networks can extract information beyond one-point functions and power spectra from all resolved scales ($\gtrsim 100\,h^{-1}{\rm kpc}$) while performing a robust marginalization over baryonic physics at the field level: the model can infer the value of $Ω_{\rm m} (\pm 4\%)$ and $σ_8 (\pm 2.5\%)$ from simulations completely different to the ones used to train it.

astro-ph.CO↗

arXiv2021

Multifield Cosmology with Artificial Intelligence

Astrophysical processes such as feedback from supernovae and active galactic nuclei modify the properties and spatial distribution of dark matter, gas, and galaxies in a poorly understood way. This uncertainty is one of the main theoretical obstacles to extract information from cosmological surveys. We use 2,000 state-of-the-art hydrodynamic simulations from the CAMELS project spanning a wide variety of cosmological and astrophysical models and generate hundreds of thousands of 2-dimensional maps for 13 different fields: from dark matter to gas and stellar properties. We use these maps to train convolutional neural networks to extract the maximum amount of cosmological information while marginalizing over astrophysical effects at the field level. Although our maps only cover a small area of $(25~h^{-1}{\rm Mpc})^2$, and the different fields are contaminated by astrophysical effects in very different ways, our networks can infer the values of $Ω_{\rm m}$ and $σ_8$ with a few percent level precision for most of the fields. We find that the marginalization performed by the network retains a wealth of cosmological information compared to a model trained on maps from gravity-only N-body simulations that are not contaminated by astrophysical effects. Finally, we train our networks on multifields -- 2D maps that contain several fields as different colors or channels -- and find that not only they can infer the value of all parameters with higher accuracy than networks trained on individual fields, but they can constrain the value of $Ω_{\rm m}$ with higher accuracy than the maps from the N-body simulations.

astro-ph.CO↗

arXiv2021

Finding universal relations in subhalo properties with artificial intelligence

We use a generic formalism designed to search for relations in high-dimensional spaces to determine if the total mass of a subhalo can be predicted from other internal properties such as velocity dispersion, radius, or star-formation rate. We train neural networks using data from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project and show that the model can predict the total mass of a subhalo with high accuracy: more than 99% of the subhalos have a predicted mass within 0.2 dex of their true value. The networks exhibit surprising extrapolation properties, being able to accurately predict the total mass of any type of subhalo containing any kind of galaxy at any redshift from simulations with different cosmologies, astrophysics models, subgrid physics, volumes, and resolutions, indicating that the network may have found a universal relation. We then use different methods to find equations that approximate the relation found by the networks and derive new analytic expressions that predict the total mass of a subhalo from its radius, velocity dispersion, and maximum circular velocity. We show that in some regimes, the analytic expressions are more accurate than the neural networks. We interpret the relation found by the neural network and approximated by the analytic equation as being connected to the virial theorem.

astro-ph.CO↗

arXiv2021

The CAMELS project: Cosmology and Astrophysics with MachinE Learning Simulations

We present the Cosmology and Astrophysics with MachinE Learning Simulations --CAMELS-- project. CAMELS is a suite of 4,233 cosmological simulations of $(25~h^{-1}{\rm Mpc})^3$ volume each: 2,184 state-of-the-art (magneto-)hydrodynamic simulations run with the AREPO and GIZMO codes, employing the same baryonic subgrid physics as the IllustrisTNG and SIMBA simulations, and 2,049 N-body simulations. The goal of the CAMELS project is to provide theory predictions for different observables as a function of cosmology and astrophysics, and it is the largest suite of cosmological (magneto-)hydrodynamic simulations designed to train machine learning algorithms. CAMELS contains thousands of different cosmological and astrophysical models by way of varying $Ω_m$, $σ_8$, and four parameters controlling stellar and AGN feedback, following the evolution of more than 100 billion particles and fluid elements over a combined volume of $(400~h^{-1}{\rm Mpc})^3$. We describe the simulations in detail and characterize the large range of conditions represented in terms of the matter power spectrum, cosmic star formation rate density, galaxy stellar mass function, halo baryon fractions, and several galaxy scaling relations. We show that the IllustrisTNG and SIMBA suites produce roughly similar distributions of galaxy properties over the full parameter space but significantly different halo baryon fractions and baryonic effects on the matter power spectrum. This emphasizes the need for marginalizing over baryonic effects to extract the maximum amount of information from cosmological surveys. We illustrate the unique potential of CAMELS using several machine learning applications, including non-linear interpolation, parameter estimation, symbolic regression, data generation with Generative Adversarial Networks (GANs), dimensionality reduction, and anomaly detection.

astro-ph.CO↗

arXiv2021

The NEWFIRM HETDEX Survey: Photometric Catalog and a Conservative Sample of Massive Quiescent Galaxies at z=3-5 over 17.5 deg^2 in the SHELA Field

We present the results of a deep K_s-band (2.1 um) imaging survey of the Spitzer/HETDEX Exploratory Large Area (SHELA) field using the NEWFIRM near-infrared (NIR) camera on the KPNO Mayall 4-m telescope. This NEWFIRM HETDEX Survey (NHS) reaches a 5-sigma depth of 22.4 AB mag (2"-diameter apertures corrected to total), is ~50% and 90% complete at K~22.65 and K~22.15, respectively, and covers 22 deg^2 of the 24 deg^2 SHELA Spitzer/ IRAC footprint (within ``Stripe 82' of the Sloan Digital Sky Survey). We present a K_s-band-selected catalog which includes deep ugriz imaging from the Dark Energy Camera and 3.6 and 4.5 um imaging from Spitzer/IRAC, with forced-photometry of 1.7 million sources across 17.5 deg^2. The large area and moderate depth of this catalog enables the study of the most massive galaxies at high redshift, and minimizes uncertainties associated with counting statistics and cosmic variance. As a demonstration, we derive stellar masses (M*) and star-formation rates (SFRs) for candidate galaxies at 3 < z < 5, and select a conservative sample of nine candidate massive (M* > 10^11 Msol) quiescent galaxies, which have measured SFRs significantly below the main-sequence at this redshift. Five are ultra-massive with M* > 10^12, though uncertainties in IRAC blending, gravitational lensing, or AGN emission could result in true masses which are lower. Simulations predict that these galaxies should be extremely rare, thus we discuss what physical processes in models could be altered to allow the formation of such massive quiescent galaxies at such early times.

astro-ph.GA↗

arXiv2021

The Radio Galaxy Population in the SIMBA SImulations

We examine the 1.4GHz radio luminosities of galaxies arising from star formation and active galactic nuclei (AGN) within the state-of-the-art cosmological hydrodynamic simulation Simba. Simba grows black holes via gravitational torque limited accretion from cold gas and Bondi accretion from hot gas, and employs AGN feedback including jets at low Eddington ratios. We define a population of radio loud AGN (RLAGN) based on the presence of ongoing jet feedback. Within RLAGN we define high and low excitation radio galaxies (HERGs and LERGs) based on their dominant mode of black hole accretion: torque limited accretion representing feeding from a cold disk, or Bondi representing advection-dominated accretion from a hot medium. Simba predicts good agreement with the observed radio luminosity function (RLF) and its evolution, overall as well as separately for HERGs and LERGs. Quiescent galaxies with AGN-dominated radio flux dominate the RLF at > $\sim 10^{22-23}$ W Hz$^{-1}$, while star formation dominates at lower radio powers. Overall, RLAGN have higher black hole accretion rates and lower star formation rates than non-RLAGN at a given stellar mass or velocity dispersion, but have similar black hole masses. Simba predicts a LERG number density of 8.53 Mpc$^{-3}$, $\sim 10\times$ higher than for HERGs, broadly as observed. While LERGs dominate among most massive galaxies with the largest black holes and HERGs dominate at high specific star formation rates, they otherwise largely populate similar-sized dark matter halos and have similar host galaxy properties. Simba thus predicts that deeper radio surveys will reveal an increasing overlap between the host galaxy demographics of HERGs and LERGs.

astro-ph.GA↗

arXiv2020

The ThreeHundred: the structure and properties of cosmic filaments in the outskirts of galaxy clusters

Galaxy cluster outskirts are described by complex velocity fields induced by diffuse material collapsing towards filaments, gas and galaxies falling into clusters, and gas shock processes triggered by substructures. A simple scenario that describes the large-scale tidal fields of the cosmic web is not able to fully account for this variety, nor for the differences between gas and collisionless dark matter. We have studied the filamentary structure in zoom-in resimulations centred on 324 clusters from The ThreeHundred project, focusing on differences between dark and baryonic matter. This paper describes the properties of filaments around clusters out to five $R_{200}$, based on the diffuse filament medium where haloes had been removed. For this, we stack the remaining particles of all simulated volumes to calculate the average profiles of dark matter and gas filaments. We find that filaments increase their thickness closer to nodes and detect signatures of gas turbulence at a distance of $\sim 2 h^{-1}\rm{Mpc}$ from the cluster. These are absent in dark matter. Both gas and dark matter collapse towards filament spines at a rate of $\sim 200 h^{-1} \rm{km ~ s^{-1}} $. We see that gas preferentially enters the cluster as part of filaments, and leaves the cluster centre outside filaments. We further see evidence for an accretion shock just outside the cluster. For dark matter, this preference is less obvious. We argue that this difference is related to the turbulent environment. This indicates that filaments act as highways to fuel the inner regions of clusters with gas and galaxies.

astro-ph.GA↗

arXiv2020

Predictions of the L$_{\rm[CII]}$-SFR and [C$_{\rm II}$] Luminosity Function at the Epoch of Reionization

We present the first predictions for the $L_{\rm [CII]}$ - SFR relation and [CII] luminosity function (LF) in the Epoch of Reionization (EoR) based on cosmological hydrodynamics simulations using the SIMBA suite plus radiative transfer calculations via SÍGAME. The sample consists of 11,137 galaxies covering halo mass $\log M_{\rm halo}\in$[9, 12.4] $M_\odot$, star formation rate SFR$\in$[0.01, 330] $M_\odot$ yr$^{-1}$, and metallicity $ _{\rm SFR}\in$[0.1, 0.9] $Z_\odot$. The simulated $L_{\rm [CII]}$-SFR relation is consistent with the range observed, but with a spread of $\simeq$0.3 dex at the high end of SFR ($>$100 $M_\odot$ yr$^{-1}$) and $\simeq$0.6 dex at the lower end, and there is tension between our predictions and the values of $L_{\rm [CII]}$ above 10$^{8.5}$ $L_\odot$ observed in some galaxies reported in the literature. The scatter in the $L_{\rm [CII]}$-SFR relation is mostly driven by galaxy properties, such that at a given SFR, galaxies with higher molecular gas mass and metallicity have higher $L_{\rm [CII]}$. The [CII] LF predicted by SIMBA is consistent with the upper limits placed by the only existing untargeted flux-limited [CII] survey at the EoR (ASPECS) and those predicted by semi-analytic models. We compare our results with existing models and discuss differences responsible for the discrepant slopes in the $L_{\rm [CII]}$-SFR relatiion.

astro-ph.GA↗

arXiv2020

Protoclusters at z=5.7: A view from the MultiDark galaxies

Protoclusters, which will yield galaxy clusters at lower redshift, can provide valuable information on the formation of galaxy clusters. However, identifying progenitors of galaxy clusters in observations is not an easy task, especially at high redshift. Different priors have been used to estimate the overdense regions that are thought to mark the locations of protoclusters. In this paper, we use mimicked Ly$α$-emitting galaxies at $z=5.7$ to identify protoclusters in the MultiDark galaxies, which are populated by applying three different semi-analytic models to the 1 $Gpc h^{-1}$ MultiDark Planck2 simulation. To compare with observational results, we extend the criterion 1 (a Ly$α$ luminosity limited sample), to criterion 2 (a match to the observed mean galaxy number density). To further statistically study the finding efficiency of this method, we enlarge the identified protocluster sample (criterion 3) to about 3500 at $z=5.7$ and study their final mass distribution. The number of overdense regions and their selection probability depends on the semi-analytic models and strongly on the three selection criteria (partly by design). The protoclusters identified with criterion 1 are associated with a typical final cluster mass of $2.82\pm0.92 \times 10^{15} M_\odot$ which is in agreement with the prediction (within $\pm 1 σ$) of an observed massive protocluster at $z=5.7$. Identifying more protoclusters allows us to investigate the efficiency of this method, which is more suitable for identifying the most massive clusters: completeness ($\mathbb{C}$) drops rapidly with decreasing halo mass. We further find that it is hard to have a high purity ($\mathbb{P}$) and completeness simultaneously.

astro-ph.GA↗

arXiv2020

The Three Hundred Project: the stellar and gas profiles

Using the catalogues of galaxy clusters from The Three Hundred project, modelled with both hydrodynamic simulations, (Gadget-X and Gadget-MUSIC), and semi-analytic models (SAMs), we study the scatter and self-similarity of the profiles and distributions of the baryonic components of the clusters: the stellar and gas mass, metallicity, the stellar age, gas temperature, and the (specific) star formation rate. Through comparisons with observational results, we find that the shape and the scatter of the gas density profiles matches well the observed trends including the reduced scatter at large radii which is a signature of self-similarity suggested in previous studies. One of our simulated sets, Gadget-X, reproduces well the shape of the observed temperature profile, while Gadget-MUSIC has a higher and flatter profile in the cluster centre and a lower and steeper profile at large radii. The gas metallicity profiles from both simulation sets, despite following the observed trend, have a relatively lower normalisation. The cumulative stellar density profiles from SAMs are in better agreement with the observed result than both hydrodynamic simulations which show relatively higher profiles. The scatter in these physical profiles, especially in the cluster centre region, shows a dependence on the cluster dynamical state and on the cool-core/non-cool-core dichotomy. The stellar age, metallicity and (s)SFR show very large scatter, which are then presented in 2D maps. We also do not find any clear radial dependence of these properties. However, the brightest central galaxies have distinguishable features compared to the properties of the satellite galaxies.

astro-ph.GA↗

arXiv2020

The Origin and Evolution of Lyman-alpha Blobs in Cosmological Galaxy Formation Simulations

High-redshift Lyman-alpha blobs (LABs) are an enigmatic class of objects that have been the subject of numerous observational and theoretical investigations. It is of particular interest to determine the dominant power sources for the copious luminosity, as direct emission from HII regions, cooling gas, and fluorescence due to the presence of active galactic nuclei (AGN) can all contribute significantly. In this paper, we present the first theoretical model to consider all of these physical processes in an attempt to develop an evolutionary model for the origin of high-z LABs. This is achieved by combining a series of high-resolution cosmological zoom-in simulations with ionization and Lyman-alpha (Lya) radiative transfer models. We find that massive galaxies display a range of Lya luminosities and spatial extents (which strongly depend on the limiting surface brightness used) over the course of their lives, though regularly exhibit luminosities and sizes consistent with observed LABs. The model LABs are typically powered from a combination of recombination in star-forming galaxies, as well as cooling emission from gas associated with accretion. When AGN are included in the model, the fluorescence caused by AGN-driven ionization can be a significant contributor to the total Lya luminosity as well. We propose that the presence of an AGN may be predicted from the Gini coefficient of the blob's surface brightness. Within our modeled mass range, there are no obvious threshold physical properties that predict appearance of LABs, and only weak correlations of the luminosity with the physical properties of the host galaxy. This is because the emergent Lya luminosity from a system is a complex function of the gas temperature, ionization state, and Lya escape fraction.

astro-ph.GA↗

arXiv2019

Astro2020 APC White Paper: Theoretical Astrophysics 2020-2030

The past two decades have seen a tremendous investment in observational facilities that promise to reveal new and unprecedented discoveries about the universe. In comparison, the investment in theoretical work is completely dwarfed, even though theory plays a crucial role in the interpretation of these observations, predicting new types of phenomena, and informing observing strategies. In this white paper, we argue that in order to reach the promised critical breakthroughs in astrophysics over the next decade and well beyond, the national agencies must take a serious approach to investment in theoretical astrophysics research. We discuss the role of theory in shaping our understanding of the universe, and then we provide a multi-level strategy, from the grassroots to the national, to address the current underinvestment in theory relative to observational work.

astro-ph.IM↗

arXiv2019

Cosmological baryon transfer in the SIMBA simulations

We present a framework for characterizing the large scale movement of baryons relative to dark matter in cosmological simulations, requiring only the initial conditions and final state of the simulation. This is performed using the spread metric which quantifies the distance in the final conditions between initially neighbouring particles, and by analysing the baryonic content of final haloes relative to that of the initial Lagrangian regions defined by their dark matter component. Applying this framework to the SIMBA cosmological simulations, we show that 40% (10%) of cosmological baryons have moved $> 1h^{-1}~ {\rm Mpc}^{-1}$ ($3h^{-1}~ {\rm Mpc}^{-1}$) by $z=0$, due primarily to entrainment of gas by jets powered by AGN, with baryons moving up to $12h^{-1}~ {\rm Mpc}^{-1}$ away in extreme cases. Baryons decouple from the dynamics of the dark matter component due to hydrodynamic forces, radiative cooling, and feedback processes. As a result, only 60% of the gas content in a given halo at $z=0$ originates from its Lagrangian region, roughly independent of halo mass. A typical halo in the mass range $M_{\rm vir} = 10^{12}$--$10^{13}{\rm M}_\odot$ only retains 20% of the gas originally contained in its Lagrangian region. We show that up to 20% of the gas content in a typical Milky Way mass halo may originate in the region defined by the dark matter of another halo. This inter-Lagrangian baryon transfer may have important implications for the origin of gas and metals in the circumgalactic medium of galaxies, as well as for semi-analytic models of galaxy formation and "zoom-in" simulations.

astro-ph.GA↗

arXiv2019

The COS Absorption Survey of Baryon Harbors: The Galaxy Database and Cross-Correlation Analysis of OVI Systems

We describe the survey for galaxies in the fields surrounding 9 sightlines to far-UV bright, z~1 quasars that define the COS Absorption Survey of Baryon Harbors (CASBaH) program. The photometry and spectroscopy that comprise the dataset come from a mixture of public surveys (SDSS, DECaLS) and our dedicated efforts on private facilities (Keck, MMT, LBT). We report the redshifts and stellar masses for 5902 galaxies within ~10 comoving-Mpc (cMpc) of the sightlines with a median of z=0.28 and M_* ~ 10^(10.1) Msun. This dataset, publicly available as the CASBaH specDB, forms the basis of several recent and ongoing CASBaH analyses. Here, we perform a clustering analysis of the galaxy sample with itself (auto-correlation) and against the set of OVI absorption systems (cross-correlation) discovered in the CASBaH quasar spectra with column densities N(O^+5) >= 10^(13.5)/cm^2. For each, we describe the measured clustering signal with a power-law correlation function xi(r) = (r/r_0)^(-gamma) and find that (r_0,gamma) = (5.48 +/- 0.07 h_100^-1 Mpc, 1.33 +/- 0.04) for the auto-correlation and (6.00 +/- 1 h^-1 Mpc, 1.25 +/- 0.18) for galaxy-OVI cross-correlation. We further estimate a bias factor of b_gg = 1.3 +/- 0.1 from the galaxy-galaxy auto-correlation indicating the galaxies are hosted by halos with mass M_halo ~ 10^(12.1 +/- 0.05) Msun. Finally, we estimate an OVI-galaxy bias factor b_OVI = 1.0 +/- 0.1 from the cross-correlation which is consistent with OVI absorbers being hosted by dark matter halos with typical mass M_halo ~ 10^(11) Msun. Future works with upcoming datasets (e.g., CGM^2) will improve upon these results and will assess whether any of the detected OVI arises in the intergalactic medium.

astro-ph.GA↗

arXiv2019

And yet it flips: connecting galactic spin and the cosmic web

We study the spin alignment of galaxies and halos with respect to filaments and walls of the cosmic web, identified with DisPerSE, using the SIMBA simulation from z=0-2. Massive halos' spins are oriented perpendicularly to their closest filament's axis and walls, while low mass halos tend to have their spins parallel to filaments and in the plane of walls. A similar mass-dependent spin flip is found for galaxies, albeit with a weaker signal particularly at low mass and low-z, suggesting that galaxies' spins retain memory of their larger-scale environment. Low-z star-forming and rotation-dominated galaxies tend to have spins parallel to nearby filaments, while quiescent and dispersion-dominated galaxies show preferentially perpendicular orientation; the star formation trend can be fully explained by the stellar mass correlation, but the morphology trend cannot. There is a strong dependence on HI mass, such that high-HI galaxies tend to have parallel spins while low-HI galaxies are perpendicular, which persists even when matching samples in stellar mass, suggesting that HI content traces anisotropic infall more faithfully than the stellar component. Finally, at fixed stellar mass, the strength of spin alignments correlates with the filament's density, with parallel alignment for galaxies in high density environments. These findings are consistent with conditional tidal torque theory, and highlight a significant correlation between galactic spin and the larger scale tides that are important e.g. for interpreting weak lensing studies. SIMBA allows us to rule out numerical grid locking as the cause of previously-seen low mass alignment.

astro-ph.GA↗

arXiv2019

The case for a 'sub-millimeter SDSS': a 3D map of galaxy evolution to z~10

The Sloan Digital Sky Survey (SDSS) was revolutionary because of the extraordinary breadth and ambition of its optical imaging and spectroscopy. We argue that a 'sub-millimeter SDSS' - a sensitive large-area imaging+spectroscopic survey in the sub-mm window - will revolutionize our understanding of galaxy evolution in the early Universe. By detecting the thermal dust continuum emission and atomic and molecular line emission of galaxies out to z~10 it will be possible to measure the redshifts, star formation rates, dust and gas content of hundreds of thousands of high-z galaxies down to ~L*. Many of these galaxies will have counterparts visible in the deep optical imaging of the Large Synoptic Survey Telescope. This 3D map of galaxy evolution will span the peak epoch of galaxy formation all the way back to cosmic dawn, measuring the co-evolution of the star formation rate density and molecular gas content of galaxies, tracking the production of metals and charting the growth of large-scale structure.

astro-ph.GA↗