arXiv subjects

Ethan O. Nadler

Publications and source records attributed to Ethan O. Nadler.

At least 55 records · Page 3Linked to original sources

arXiv2024

The SAGA Survey. IV. The Star Formation Properties of 101 Satellite Systems around Milky Way-mass Galaxies

We present the star-forming properties of 378 satellite galaxies around 101 Milky Way analogs in the Satellites Around Galactic Analogs (SAGA) Survey, focusing on the environmental processes that suppress or quench star formation. In the SAGA stellar mass range of 10^6 to 10^10 solar masses, we present quenched fractions, star-forming rates, gas-phase metallicities, and gas content. The fraction of SAGA satellites that are quenched increases with decreasing stellar mass and shows significant system-to-system scatter. SAGA satellite quenched fractions are highest in the central 100 kpc of their hosts and decline out to the virial radius. Splitting by specific star formation rate (sSFR), the least star-forming satellite quartile follows the radial trend of the quenched population. The median sSFR of star-forming satellites increases with decreasing stellar mass and is roughly constant with projected radius. Star-forming SAGA satellites are consistent with the star formation rate--stellar mass relationship determined in the Local Volume, while the median gas-phase metallicity is higher and median HI gas mass is lower at all stellar masses. We investigate the dependence of the satellite quenched fraction on host properties. Quenched fractions are higher in systems with larger host halo mass, but this trend is only seen in the inner 100 kpc; we do not see significant trends with host color or star formation rate. Our results suggest that lower mass satellites and satellites inside 100 kpc are more efficiently quenched in a Milky Way-like environment, with these processes acting sufficiently slowly to preserve a population of star-forming satellites at all stellar masses and projected radii.

astro-ph.GA↗

arXiv2024

Tidal evolution of cored and cuspy dark matter halos

The internal structure and abundance of dark matter halos and subhalos are powerful probes of the nature of dark matter. In order to compare observations with dark matter models, accurate theoretical predictions of these quantities are needed. We present a fast and accurate method to describe the tidal evolution of subhalos within their parent halo, based on a semi-analytic approach. We first consider idealized N-body simulations of subhalos within their host halo, using a generalized mass density profile that describes their properties in a variety of dark matter models at infall, including popular warm, cold, and self-interacting ones. Using these simulations we construct tidal "tracks" for the evolution of subhalos based on their conditions at infall. Second, we use the results of these simulations to build semi-analytic models for tidal effects, including stripping and heating and implement them within the code GALACTICUS. Our semi-analytic models can accurately predict the tidal evolution of both cored and cuspy subhalos, including the bound mass and density profiles, providing a powerful and efficient tool for studying the post-infall properties of subhalos in different dark matter models.

astro-ph.GA↗

arXiv2024

Forecasts for Galaxy Formation and Dark Matter Constraints from Dwarf Galaxy Surveys

The abundance of faint dwarf galaxies is determined by the underlying population of low-mass dark matter (DM) halos and the efficiency of galaxy formation in these systems. Here, we quantify potential galaxy formation and DM constraints from future dwarf satellite galaxy surveys. We generate satellite populations using a suite of Milky Way (MW)--mass cosmological zoom-in simulations and an empirical galaxy--halo connection model, and assess sensitivity to galaxy formation and DM signals when marginalizing over galaxy--halo connection uncertainties. We find that a survey of all satellites around one MW-mass host can constrain a galaxy formation cutoff at peak virial masses of $M_{50}=10^8~M_{\mathrm{\odot}}$ at the $1σ$ level; however, a tail toward low $M_{50}$ prevents a $2σ$ measurement. In this scenario, combining hosts with differing bright satellite abundances significantly reduces uncertainties on $M_{50}$ at the $1σ$ level, but the $2σ$ tail toward low $M_{50}$ persists. We project that observations of one (two) complete satellite populations can constrain warm DM models with $m_{\mathrm{WDM}}\approx 10~\mathrm{keV}$ ($20~\mathrm{keV}$). Subhalo mass function (SHMF) suppression can be constrained to $\approx 70\%$, $60\%$, and $50\%$ that in cold dark matter (CDM) at peak virial masses of $10^8$, $10^9$, and $10^{10}~M_{\mathrm{\odot}}$, respectively; SHMF enhancement constraints are weaker ($\approx 20$, $4$, and $2$ times that in CDM, respectively) due to galaxy--halo connection degeneracies. These results motivate searches for faint dwarf galaxies beyond the MW and indicate that ongoing missions like Euclid and upcoming facilities including the Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope will probe new galaxy formation and DM physics.

astro-ph.GA↗

arXiv2024

A Parametric Model for Self-Interacting Dark Matter Halos

We propose a parametric model for studying self-interacting dark matter (SIDM) halos. The model uses an analytical density profile, calibrated using a controlled N-body SIDM simulation that covers the entire gravothermal evolution, including core-forming and -collapsing phases. By normalizing the calibrated density profile, we obtain a universal description for SIDM halos at any evolution phase. The model allows us to infer properties of SIDM halos based on their cold dark matter (CDM) counterparts. As a basic application, we only require two characteristic parameters of an isolated CDM halo at $z=0$. We then extend the model to incorporate effects induced by halo mass changes, such as major mergers or tidal stripping, making it applicable to both isolated halos and subhalos. The parametric model is tested and validated using cosmological zoom-in SIDM simulations available in the literature.

astro-ph.CO↗

arXiv2024

A comprehensive model for the formation and evolution of the faintest Milky Way dwarf satellites

In this study, we modify the semi-analytic model Galacticus in order to accurately reproduce the observed properties of dwarf galaxies in the Milky Way. We find that reproducing observational determinations of the halo occupation fraction and mass-metallicity relation for dwarf galaxies requires us to include H$_2$ cooling, an updated UV background radiation model, and to introduce a model for the metal content of the intergalactic medium. By fine-tuning various model parameters and incorporating empirical constraints, we have tailored the model to match the statistical properties of Milky Way dwarf galaxies, such as their luminosity function and size$-$mass relation. We have validated our modified semi-analytic framework by undertaking a comparative analysis of the resulting galaxy-halo connection. We predict a total of $300 ^{+75} _{-99}$ satellites with an absolute $V$-band magnitude (M$_{V}$) less than $0$ within $300$ kpc from our Milky Way-analogs. The fraction of subhalos that host a galaxy at least this bright drops to $50\%$ by a halo peak mass of $\sim 8.9 \times 10^{7}$ M$_{\odot}$, consistent with the occupation fraction inferred from the latest observations of Milky Way satellite population.

astro-ph.GA↗

arXiv2024

SAGAbg I: A Near-Unity Mass Loading Factor in Low-Mass Galaxies via their Low-Redshift Evolution in Stellar Mass, Oxygen Abundance, and Star Formation Rate

Measuring the relation between star formation and galactic winds is observationally difficult. In this work we make an indirect measurement of the mass loading factor (the ratio between mass outflow rate and star formation rate) in low-mass galaxies using a differential approach to modeling the low-redshift evolution of the star-forming main sequence and mass-metallicity relation. We use the SAGA (Satellites Around Galactic Analogs) background galaxies, those spectra observed by the SAGA survey that are not associated with the main SAGA host galaxies, to construct a sample of 11925 spectroscopically confirmed low-mass galaxies from $0.01\lesssim z \leq 0.21$ and measure a auroral line metallicity for 120 galaxies. The crux of the method is to use the lowest redshift galaxies as the boundary condition of our model, and to infer a mass-loading factor for the sample by comparing the expected evolution of the low redshift reference sample in stellar mass, gas-phase metallicity, and star formation rate against the observed properties of the sample at higher redshift. We infer a mass-loading factor of $η_{\rm m}=0.92^{+1.76}_{-0.74}$, which is in line with direct measurements of the mass-loading factor from the literature despite the drastically different set of assumptions needed for each approach. While our estimate of the mass-loading factor is in good agreement with recent galaxy simulations that focus on resolving the dynamics of the interstellar medium, it is smaller by over an order of magnitude than the mass-loading factor produced by many contemporary cosmological simulations.

astro-ph.GA↗

arXiv2023

Dynamical friction in self-interacting ultralight dark matter

We explore how dynamical friction in an ultralight dark matter (ULDM) background is affected by dark matter self-interactions. We calculate the force of dynamical friction on a point mass moving through a uniform ULDM background with self-interactions, finding that the force of dynamical friction vanishes for sufficiently strong repulsive self-interactions. Using the pseudospectral solver $\texttt{UltraDark.jl}$, we show with simulations that reasonable values of the ULDM self-interaction strength and particle mass cause $\mathcal{O}(1)$ differences in the acceleration of an object like a supermassive black hole (SMBH) traveling near the center of a soliton, relative to the case with no self-interactions. For example, repulsive self-interactions with $λ= 10^{-90}$ yield a deceleration due to dynamical friction $\approx70\%$ smaller than a model with no self-interactions. We discuss the observational implications of our results for SMBHs near soliton centers and for massive satellite galaxies falling into ultralight axion halos and show that outcomes are dependent on whether a self-interaction is present or not.

astro-ph.CO↗

arXiv2023

A Self-interacting Dark Matter Solution to the Extreme Diversity of Low-mass Halo Properties

The properties of low-mass dark matter (DM) halos appear to be remarkably diverse relative to cold, collisionless DM predictions, even in the presence of baryons. We show that self-interacting DM (SIDM) can simultaneously explain observations of halo diversity at two opposite extremes$-$the inner density profile of the dense substructure perturbing the strong lens galaxy SDSSJ0946+1006 and the rotation curves of isolated, gas-rich ultradiffuse galaxies (UDGs). To achieve this, we present the first cosmological zoom-in simulation featuring strong DM self-interactions in a galaxy group environment centered on a $10^{13}~M_{\mathrm{\odot}}$ host halo. In our SIDM simulation, most surviving subhalos of the group-mass host are deeply core-collapsed, yielding excellent candidates for the observed dense strong-lens perturber. Self-interactions simultaneously create kiloparsec-scale cores in low-concentration isolated halos, which could host the observed UDGs. Our scenario can be further tested with observations of DM structure and galaxies over a wide mass range.

astro-ph.GA↗

arXiv2023

Can Neutrino Self-interactions Save Sterile Neutrino Dark Matter?

Sterile neutrinos only interact with the Standard Model through the neutrino sector, and thus represent a simple dark matter (DM) candidate with many potential astrophysical and cosmological signatures. Recently, sterile neutrinos produced through self-interactions of active neutrinos have received attention as a particle candidate that can yield the entire observed DM relic abundance without violating the most stringent constraints from X-ray observations. We examine consistency of this production mechanism with the abundance of small-scale structure in the universe, as captured by the population of ultra-faint dwarf galaxies orbiting the Milky Way, and derive a lower bound on the sterile-neutrino particle mass of $37$ keV. Combining these results with previous limits from particle physics and astrophysics excludes $100\%$ sterile neutrino DM produced by strong neutrino self-coupling, mediated by a heavy ($\gtrsim 1~\mathrm{GeV}$) scalar particle; however, data permits sterile-neutrino DM production via a light mediator.

astro-ph.CO↗

arXiv2023

Divergences in Color Perception between Deep Neural Networks and Humans

Deep neural networks (DNNs) are increasingly proposed as models of human vision, bolstered by their impressive performance on image classification and object recognition tasks. Yet, the extent to which DNNs capture fundamental aspects of human vision such as color perception remains unclear. Here, we develop novel experiments for evaluating the perceptual coherence of color embeddings in DNNs, and we assess how well these algorithms predict human color similarity judgments collected via an online survey. We find that state-of-the-art DNN architectures $-$ including convolutional neural networks and vision transformers $-$ provide color similarity judgments that strikingly diverge from human color judgments of (i) images with controlled color properties, (ii) images generated from online searches, and (iii) real-world images from the canonical CIFAR-10 dataset. We compare DNN performance against an interpretable and cognitively plausible model of color perception based on wavelet decomposition, inspired by foundational theories in computational neuroscience. While one deep learning model $-$ a convolutional DNN trained on a style transfer task $-$ captures some aspects of human color perception, our wavelet algorithm provides more coherent color embeddings that better predict human color judgments compared to all DNNs we examine. These results hold when altering the high-level visual task used to train similar DNN architectures (e.g., image classification versus image segmentation), as well as when examining the color embeddings of different layers in a given DNN architecture. These findings break new ground in the effort to analyze the perceptual representations of machine learning algorithms and to improve their ability to serve as cognitively plausible models of human vision. Implications for machine learning, human perception, and embodied cognition are discussed.

cs.CV↗

arXiv2023

Novel Conservative Methods for Adaptive Force Softening in Collisionless and Multi-Species N-Body Simulations

Modeling self-gravity of collisionless fluids (e.g. ensembles of dark matter, stars, black holes, dust, planetary bodies) in simulations is challenging and requires some force softening. It is often desirable to allow softenings to evolve adaptively, in any high-dynamic range simulation, but this poses unique challenges of consistency, conservation, and accuracy, especially in multi-physics simulations where species with different softening laws may interact. We therefore derive a generalized form of the energy-and-momentum conserving gravitational equations of motion, applicable to arbitrary rules used to determine the force softening, together with consistent associated timestep criteria, interaction terms between species with different softening laws, and arbitrary maximum/minimum softenings. We also derive new methods to maintain better accuracy and conservation when symmetrizing forces between particles. We review and extend previously-discussed adaptive softening schemes based on the local neighbor particle density, and present several new schemes for scaling the softening with properties of the gravitational field, i.e. the potential or acceleration or tidal tensor. We show that the tidal softening scheme not only represents a physically-motivated, translation and Galilean invariant and equivalence-principle respecting (and therefore conservative) method, but imposes negligible timestep or other computational penalties, ensures that pairwise two-body scattering is small compared to smooth background forces, and can resolve outstanding challenges in properly capturing tidal disruption of substructures (minimizing artificial destruction) while also avoiding excessive N-body heating. We make all of this public in the GIZMO code.

astro-ph.GA↗

arXiv2023

Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program

We introduce the DESI LOW-Z Secondary Target Survey, which combines the wide-area capabilities of the Dark Energy Spectroscopic Instrument (DESI) with an efficient, low-redshift target selection method. Our selection consists of a set of color and surface brightness cuts, combined with modern machine learning methods, to target low-redshift dwarf galaxies ($z$ < 0.03) between $19 < r < 21$ with high completeness. We employ a convolutional neural network (CNN) to select high-priority targets. The LOW-Z survey has already obtained over 22,000 redshifts of dwarf galaxies (M$_* < 10^9$ M$_\odot$), comparable to the number of dwarf galaxies discovered in SDSS-DR8 and GAMA. As a spare fiber survey, LOW-Z currently receives fiber allocation for just ~50% of its targets. However, we estimate that our selection is highly complete: for galaxies at $z < 0.03$ within our magnitude limits, we achieve better than 95% completeness with ~1% efficiency using catalog-level photometric cuts. We also demonstrate that our CNN selections $z<0.03$ galaxies from the photometric cuts subsample at least ten times more efficiently while maintaining high completeness. The full five-year DESI program will expand the LOW-Z sample, densely mapping the low-redshift Universe, providing an unprecedented sample of dwarf galaxies, and providing critical information about how to pursue effective and efficient low-redshift surveys.

astro-ph.GA↗

arXiv2023

Strong Dark Matter Self-interactions Diversify Halo Populations within and surrounding the Milky Way

We perform a high-resolution cosmological zoom-in simulation of a Milky Way (MW)--like system, which includes a realistic Large Magellanic Cloud analog, using a large differential elastic dark matter self-interaction cross section that reaches $\approx 100~\mathrm{cm}^2\ \mathrm{g}^{-1}$ at relative velocities of $\approx 10~\mathrm{km\ s}^{-1}$, motivated by the diverse and orbitally dependent central densities of dwarf galaxies within and surrounding the MW. We explore the effects of dark matter self-interactions on satellite, splashback, and isolated halos through their abundance, central densities, maximum circular velocities, orbital parameters, and correlations between these variables. We use an effective constant cross section model to analytically predict the stages of our simulated halos' gravothermal evolution, demonstrating that deviations from the collisionless $R_{\rm max}$--$V_{\rm max}$ relation can be used to select deeply core-collapsed halos, where $V_{\rm max}$ is a halo's maximum circular velocity, and $R_{\rm max}$ is the radius at which it occurs. We predict that a sizable fraction ($\approx 20\%$) of subhalos with masses down to $\approx 10^8~M_{\odot}$ is deeply core collapsed in our SIDM model. Core-collapsed systems form $\approx 10\%$ of the isolated halo population down to the same mass; these isolated, core-collapsed halos would host faint dwarf field galaxies with extremely steep central density profiles. Finally, most halos with masses above $\approx 10^9~M_{\odot}$ are core-forming in our simulation. Our study thus demonstrates how self-interactions diversify halo populations in an environmentally dependent fashion within and surrounding MW-mass hosts, providing a compelling avenue to address the diverse dark matter distributions of observed dwarf galaxies.

astro-ph.GA↗

arXiv2023

Non-thermal warm dark matter limits from small-scale structure

We present small-scale structure constraints on sterile dark matter produced from a heavy mediator particle, inspired by models of moduli decay. Dark matter particles produced through this mechanism can contribute to the entire dark matter energy density but the particles have a non-thermal phase-space distribution; however, we show that the resulting linear matter power spectra can be mapped to effective thermal-relic warm dark matter models. This production mechanism is therefore subject to warm dark matter constraints from small-scale structure as probed by ultra-faint dwarf galaxy abundances and strong gravitational lensing flux ratio statistics. We use the correspondence to thermal-relic models to derive a lower bound on the non-thermal particle mass of $107\ \mathrm{keV}$, at $95\%$ confidence. These are the first and most stringent constraints derived on sterile dark matter produced via the heavy mediator decay scenario we consider.

astro-ph.CO↗

arXiv2023

Snowmass2021 Cosmic Frontier White Paper: Dark Matter Physics from Halo Measurements

The non-linear process of cosmic structure formation produces gravitationally bound overdensities of dark matter known as halos. The abundances, density profiles, ellipticities, and spins of these halos can be tied to the underlying fundamental particle physics that governs dark matter at microscopic scales. Thus, macroscopic measurements of dark matter halos offer a unique opportunity to determine the underlying properties of dark matter across the vast landscape of dark matter theories. This white paper summarizes the ongoing rapid development of theoretical and experimental methods, as well as new opportunities, to use dark matter halo measurements as a pillar of dark matter physics.

hep-ph↗

arXiv2023

Growing the First Galaxies' Merger Trees

Modelling the growth histories of specific galaxies often involves generating the entire population of objects that arise in a given cosmology and selecting systems with appropriate properties. This approach is highly inefficient when targeting rare systems such as the extremely luminous high-redshift galaxy candidates detected by JWST. Here, we present a novel framework for generating merger trees with branches that are guaranteed to achieve a desired halo mass at a chosen redshift. This method augments extended Press Schechter theory solutions with constrained random processes known as Brownian bridges and is implemented in the open-source semi-analytic model $\texttt{Galacticus}$. We generate ensembles of constrained merger trees to predict the growth histories of seven high-redshift JWST galaxy candidates, finding that these systems most likely merge $\approx 2~\mathrm{Gyr}$ after the observation epoch and occupy haloes of mass $\gtrsim 10^{14}~M_{\mathrm{\odot}}$ today. These calculations are thousands of times more efficient than existing methods, are analytically controlled, and provide physical insights into the evolution of haloes with rapid early growth. Our constrained merger tree implementation is publicly available at http://github.com/galacticusorg/galacticus.

astro-ph.GA↗

arXiv2023

Symphony: Cosmological Zoom-in Simulation Suites over Four Decades of Host Halo Mass

We present Symphony, a compilation of $262$ cosmological, cold-dark-matter-only zoom-in simulations spanning four decades of host halo mass, from $10^{11}$$-$$10^{15}~M_{\mathrm{\odot}}$. This compilation includes three existing simulation suites at the cluster and Milky Way$-$mass scales, and two new suites: $39$ Large Magellanic Cloud-mass ($10^{11}~M_{\mathrm{\odot}}$) and $49$ strong-lens-analog ($10^{13}~M_{\mathrm{\odot}}$) group-mass hosts. Across the entire host halo mass range, the highest-resolution regions in these simulations are resolved with a dark matter particle mass of $\approx 3\times 10^{-7}$ times the host virial mass and a Plummer-equivalent gravitational softening length of $\approx 9\times 10^{-4}$ times the host virial radius, on average. We measure correlations between subhalo abundance and host concentration, formation time, and maximum subhalo mass, all of which peak at the Milky Way host halo mass scale. Subhalo abundances are $\approx 50\%$ higher in clusters than in lower-mass hosts at fixed sub-to-host halo mass ratios. Subhalo radial distributions are approximately self-similar as a function of host mass and are less concentrated than hosts' underlying dark matter distributions. We compare our results to the semianalytic model $\mathrm{\texttt{Galacticus}}$, which predicts subhalo mass functions with a higher normalization at the low-mass end and radial distributions that are slightly more concentrated than Symphony. We use $\mathrm{\texttt{UniverseMachine}}$ to model halo and subhalo star formation histories in Symphony, and we demonstrate that these predictions resolve the formation histories of the halos that host nearly all currently observable satellite galaxies in the universe. To promote open use of Symphony, data products are publicly available at http://web.stanford.edu/group/gfc/symphony.

astro-ph.CO↗

arXiv2023

From Images to Dark Matter: End-To-End Inference of Substructure From Hundreds of Strong Gravitational Lenses

Constraining the distribution of small-scale structure in our universe allows us to probe alternatives to the cold dark matter paradigm. Strong gravitational lensing offers a unique window into small dark matter halos ($<10^{10} M_\odot$) because these halos impart a gravitational lensing signal even if they do not host luminous galaxies. We create large datasets of strong lensing images with realistic low-mass halos, Hubble Space Telescope (HST) observational effects, and galaxy light from HST's COSMOS field. Using a simulation-based inference pipeline, we train a neural posterior estimator of the subhalo mass function (SHMF) and place constraints on populations of lenses generated using a separate set of galaxy sources. We find that by combining our network with a hierarchical inference framework, we can both reliably infer the SHMF across a variety of configurations and scale efficiently to populations with hundreds of lenses. By conducting precise inference on large and complex simulated datasets, our method lays a foundation for extracting dark matter constraints from the next generation of wide-field optical imaging surveys.

astro-ph.CO↗