arXiv subjects

Lina Necib

Publications and source records attributed to Lina Necib.

At least 73 records · Page 4Linked to original sources

arXiv2022

FIRE-3: Updated Stellar Evolution Models, Yields, & Microphysics and Fitting Functions for Applications in Galaxy Simulations

Increasingly, uncertainties in predictions from galaxy formation simulations (at sub-Milky Way masses) are dominated by uncertainties in stellar evolution inputs. In this paper, we present the full set of updates from the FIRE-2 version of the Feedback In Realistic Environments (FIRE) project code, to the next version, FIRE-3. While the transition from FIRE-1 to FIRE-2 focused on improving numerical methods, here we update the stellar evolution tracks used to determine stellar feedback inputs, e.g. stellar mass-loss (O/B and AGB), spectra (luminosities and ionization rates), and supernova rates (core-collapse and Ia), as well as detailed mass-dependent yields. We also update the low-temperature cooling and chemistry, to enable improved accuracy at $T \lesssim 10^{4}\,$K and densities $n\gg 1\,{\rm cm^{-3}}$, and the meta-galactic ionizing background. All of these synthesize newer empirical constraints on these quantities and updated stellar evolution and yield models from a number of groups, addressing different aspects of stellar evolution. To make the updated models as accessible as possible, we provide fitting functions for all of the relevant updated tracks, yields, etc, in a form specifically designed so they can be directly 'plugged in' to existing galaxy formation simulations. We also summarize the default FIRE-3 implementations of 'optional' physics, including spectrally-resolved cosmic rays and supermassive black hole growth and feedback.

astro-ph.GA↗

arXiv2022

Chasing Accreted Structures within Gaia DR2 using Deep Learning

In previous work, we developed a deep neural network classifier that only relies on phase-space information to obtain a catalog of accreted stars based on the second data release of Gaia (DR2). In this paper, we apply two clustering algorithms to identify velocity substructure within this catalog. We focus on the subset of stars with line-of-sight velocity measurements that fall in the range of Galactocentric radii $r \in [6.5, 9.5]$ kpc and vertical distances $|z| < 3$ kpc. Known structures such as Gaia Enceladus and the Helmi stream are identified. The largest previously-unknown structure, Nyx, is a vast stream consisting of at least 90 stars in the region of interest. This study displays the power of the machine learning approach by not only successfully identifying known features, but also discovering new kinematic structures that may shed light on the merger history of the Milky Way.

astro-ph.GA↗

arXiv2022

Evidence for a Vast Prograde Stellar Stream in the Solar Vicinity

Massive dwarf galaxies that merge with the Milky Way on prograde orbits can be dragged into the disk plane before being completely disrupted. Such mergers can contribute to an accreted stellar disk and a dark matter disk. We present evidence for Nyx, a vast new stellar stream in the vicinity of the Sun, that may provide the first indication that such an event occurred in the Milky Way. We identify about 500 stars that have coherent radial and prograde motion in this stream using a catalog of accreted stars built by applying deep learning methods to the second Gaia data release. Nyx is concentrated within $\pm 2$ kpc of the Galactic midplane and spans the full radial range studied (6.5-9.5 kpc). The kinematics of Nyx stars are distinct from those of both the thin and thick disk. In particular, its rotational speed lags the disk by $\sim 80$ km/s and its stars follow more eccentric orbits. A small number of Nyx stars have chemical abundances or inferred ages; from these, we deduce that Nyx stars have a peak metallicity of [Fe/H] $\sim -0.5$ and ages $\sim $10-13 Gyr. Taken together with the kinematic observations, these results strongly favor the interpretation that Nyx is the remnant of a disrupted dwarf galaxy. To further justify this interpretation, we explicitly demonstrate that metal-rich, prograde streams like Nyx can be found in the disk plane of Milky Way-like galaxies using the FIRE hydrodynamic simulations. Future spectroscopic studies will be able to validate whether Nyx stars originate from a single progenitor.

astro-ph.GA↗

arXiv2021

Via Machinae: Searching for Stellar Streams using Unsupervised Machine Learning

We develop a new machine learning algorithm, Via Machinae, to identify cold stellar streams in data from the Gaia telescope. Via Machinae is based on ANODE, a general method that uses conditional density estimation and sideband interpolation to detect local overdensities in the data in a model agnostic way. By applying ANODE to the positions, proper motions, and photometry of stars observed by Gaia, Via Machinae obtains a collection of those stars deemed most likely to belong to a stellar stream. We further apply an automated line-finding method based on the Hough transform to search for line-like features in patches of the sky. In this paper, we describe the Via Machinae algorithm in detail and demonstrate our approach on the prominent stream GD-1. Though some parts of the algorithm are tuned to increase sensitivity to cold streams, the Via Machinae technique itself does not rely on astrophysical assumptions, such as the potential of the Milky Way or stellar isochrones. This flexibility suggests that it may have further applications in identifying other anomalous structures within the Gaia dataset, for example debris flow and globular clusters.

astro-ph.GA↗

arXiv2021

Dissipative Dark Matter on FIRE: I. Structural and kinematic properties of dwarf galaxies

We present the first set of cosmological baryonic zoom-in simulations of galaxies including dissipative self-interacting dark matter (dSIDM). These simulations utilize the Feedback In Realistic Environments (FIRE-2) galaxy formation physics, but allow the dark matter to have dissipative self-interactions analogous to Standard Model forces, parameterized by the self-interaction cross-section per unit mass, $(σ/m)$, and the dimensionless degree of dissipation, $0<f_{\rm diss}<1$. We survey this parameter space, including constant and velocity-dependent cross-sections, and focus on structural and kinematic properties of dwarf galaxies with $M_{\rm halo} \simeq 10^{10-11} {\rm M}_{\odot}$. Central density profiles of simulated dwarfs become cuspy when $(σ/m)_{\rm eff} \gtrsim 0.1\,{\rm cm^{2}\,g^{-1}}$ (and $f_{\rm diss}=0.5$ as fiducial). The power-law slopes asymptote to $α\approx -1.5$ in low-mass dwarfs independent of cross-section, which arises from a dark matter "cooling flow". Through comparisons with dark matter only simulations, we find the profile in this regime is insensitive to the inclusion of baryons. However, when $(σ/m)_{\rm eff} \ll 0.1\,{\rm cm^{2}\,g^{-1}}$, baryonic effects can produce cored density profiles comparable to non-dissipative cold dark matter (CDM) runs but at smaller radii. Simulated galaxies with $(σ/m) \gtrsim 10\,{\rm cm^{2}\,g^{-1}}$ develop significant coherent rotation of dark matter, accompanied by halo deformation, but this is unlike the well-defined thin "dark disks" often attributed to baryon-like dSIDM. The density profiles in this high cross-section model exhibit lower normalizations given the onset of halo deformation. For our surveyed dSIDM parameters, halo masses and galaxy stellar masses do not show appreciable difference from CDM, but dark matter kinematics and halo concentrations/shapes can differ.

astro-ph.GA↗

arXiv2021

Substructure at High Speed II: The Local Escape Velocity and Milky Way Mass with Gaia DR2

Measuring the escape velocity of the Milky Way is critical in obtaining the mass of the Milky Way, understanding the dark matter velocity distribution, and building the dark matter density profile. In Necib $\&$ Lin (2021), we introduced a strategy to robustly measure the escape velocity. Our approach takes into account the presence of kinematic substructures by modeling the tail of the stellar distribution with multiple components, including the stellar halo and the debris flow called the Gaia Sausage (Enceladus). In doing so, we can test the robustness of the escape velocity measurement for different definitions of the "tail" of the velocity distribution, and the consistency of the data with different underlying models. In this paper, we apply this method to the second data release of Gaia and find that a model with at least two components is preferred. Based on a fit with three bound components to account for the disk, relaxed halo, and the Gaia Sausage, we find the escape velocity of the Milky Way at the solar position to be $v_{\rm{esc}}= 484.6^{+17.8}_{-7.4}$ km/s. Assuming a Navarro-Frenck-White dark matter profile, and taken in conjunction with a recent measurement of the circular velocity at the solar position of $v_c = 230 \pm 10$ km/s, we find a Milky Way concentration of $c_{200} = 13.8^{+6.0}_{-4.3}$ and a mass of $M_{200} = 7.0^{+1.9}_{-1.2} \times 10^{11} M_{\odot}$, which is considerably lighter than previous measurements.

astro-ph.GA↗

arXiv2021

An extended halo around an ancient dwarf galaxy

The Milky Way is surrounded by dozens of ultra-faint (< $10^5$ solar luminosities) dwarf satellite galaxies. They are the surviving remnants of the earliest galaxies, as confirmed by their ancient (~13 billion years old) and chemically primitive stars. Simulations suggest that these systems formed within extended dark matter halos and experienced early galaxy mergers and supernova feedback. However, the signatures of these events would lie outside their core regions (>2 half-light radii), which are spectroscopically unstudied due to the sparseness of their distant stars. Here we identify members of the Tucana II ultra-faint dwarf galaxy in its outer region (up to 9 half-light radii), demonstrating the system to be dramatically more spatially extended and chemically primitive than previously found. These distant stars are extremely metal-poor (<[Fe/H]>=-3.02; less than ~1/1000th of the solar iron abundance), affirming Tucana II as the most metal-poor known galaxy. We observationally establish, for the first time, an extended dark matter halo surrounding an ultra-faint dwarf galaxy out to one kiloparsec, with a total mass of >$10^7$ solar masses. This measurement is consistent with the expected ~2x$10^7$ solar masses using a generalized NFW density profile. The extended nature of Tucana II suggests that it may have undergone strong bursty feedback or been the product of an early galactic merger. We demonstrate that spatially extended stellar populations, which other ultra-faint dwarfs hint at hosting as well, are observable in principle and open the possibility for detailed studies of the stellar halos of relic galaxies.

astro-ph.GA↗

arXiv2021

Substructure at High Speed I: Inferring the Escape Velocity in the Presence of Kinematic Substructure

The local escape velocity provides valuable inputs to the mass profile of the Galaxy, and requires understanding the tail of the stellar speed distribution. Following Leonard $\&$ Tremaine (1990), various works have since modeled the tail of the stellar speed distribution as $\propto (v_{\rm{esc}} -v)^k$, where $v_{\rm{esc}}$ is the escape velocity, and $k$ is the slope of the distribution. In such studies, however, these two parameters were found to be largely degenerate and often a narrow prior is imposed on $k$ in order to constrain $v_{\rm{esc}}$. Furthermore, the validity of the power law form is likely to break down in the presence of multiple kinematic substructures. In this paper, we introduce a strategy that for the first time takes into account the presence of kinematic substructure. We model the tail of the velocity distribution as a sum of multiple power laws without imposing strong priors. Using mock data, we show the robustness of this method in the presence of kinematic structure that is similar to the recently-discovered Gaia Sausage. In a companion paper, we present the new measurement of the escape velocity and subsequently the mass of the Milky Way using Gaia DR2 data.

astro-ph.GA↗

arXiv2020

Prospects for Detecting Boosted Dark Matter in DUNE through Hadronic Interactions

Boosted dark matter (BDM) is a well-motivated class of dark matter (DM) candidates in which a small component of DM is relativistic at the present time. We lay the foundation for BDM searches via hadronic interactions in large liquid-argon time-projection chambers (LArTPCs), such as DUNE. We investigate BDM-nucleus scattering in detail by developing new event generation techniques with a parameterized detector simulation. We study the discovery potential in a DUNE-like experiment using the low threshold and directionality of hadron detection in LArTPCs and compare with other experiments.

hep-ph↗

arXiv2020

Dark Matter Density Profiles in Dwarf Galaxies: Linking Jeans Modeling Systematics and Observation

The distribution of dark matter in dwarf galaxies can have important implications on our understanding of galaxy formation as well as the particle physics properties of dark matter. However, accurately characterizing the dark matter content of dwarf galaxies is challenging due to limited data and complex dynamics that are difficult to accurately model. In this paper, we apply spherical Jeans modeling to simulated stellar kinematic data of spherical, isotropic dwarf galaxies with the goal of identifying the future observational directions that can improve the accuracy of the inferred dark matter distributions in the Milky Way dwarf galaxies. We explore how the dark matter inference is affected by the location and number of observed stars as well as the line-of-sight velocity measurement errors. We use mock observation to demonstrate the difficulty in constraining the inner core/cusp of the dark matter distribution with datasets of fewer than 10,000 stars. We also demonstrate the need for additional measurements to make robust estimates of the expected dark matter annihilation signal strength. For the purpose of deriving robust indirect detection constraints, we identify Ursa Major II, Ursa Minor, and Draco as the systems that would most benefit from additional stars being observed.

astro-ph.CO↗

arXiv2020

Cataloging Accreted Stars within Gaia DR2 using Deep Learning

The goal of this study is to present the development of a machine learning based approach that utilizes phase space alone to separate the Gaia DR2 stars into two categories: those accreted onto the Milky Way from those that are in situ. Traditional selection methods that have been used to identify accreted stars typically rely on full 3D velocity, metallicity information, or both, which significantly reduces the number of classifiable stars. The approach advocated here is applicable to a much larger portion of Gaia DR2. A method known as "transfer learning" is shown to be effective through extensive testing on a set of mock Gaia catalogs that are based on the FIRE cosmological zoom-in hydrodynamic simulations of Milky Way-mass galaxies. The machine is first trained on simulated data using only 5D kinematics as inputs and is then further trained on a cross-matched Gaia/RAVE data set, which improves sensitivity to properties of the real Milky Way. The result is a catalog that identifies around 767,000 accreted stars within Gaia DR2. This catalog can yield empirical insights into the merger history of the Milky Way and could be used to infer properties of the dark matter distribution.

astro-ph.GA↗

arXiv2019

Inferred Evidence For Dark Matter Kinematic Substructure with SDSS-Gaia

We use the distribution of accreted stars in SDSS-Gaia DR2 to demonstrate that a non-trivial fraction of the dark matter halo within Galactocentric radii of 7.5-10 kpc and $|z| > 2.5$ kpc is in substructure, and thus may not be in equilibrium. Using a mixture likelihood analysis, we separate the contributions of an old, isotropic stellar halo and a younger anisotropic population. The latter dominates and is uniform within the region studied. It can be explained as the tidal debris of a disrupted massive satellite on a highly radial orbit, and is consistent with mounting evidence from recent studies. Simulations that track the tidal debris from such mergers find that the dark matter traces the kinematics of its stellar counterpart. If so, our results indicate that a component of the nearby dark matter halo that is sourced by luminous satellites is in kinematic substructure referred to as debris flow. These results challenge the Standard Halo Model, which is discrepant with the distribution recovered from the stellar data, and have important ramifications for the interpretation of direct detection experiments.

astro-ph.GA↗

arXiv2019

Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope

Astrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST) will provide necessary guidance for the experimental dark matter program. This white paper represents a community effort to summarize the science case for studying the fundamental physics of dark matter with LSST. We discuss how LSST will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational couplings to the Standard Model, and compact object abundances. Additionally, we discuss the ways that LSST will complement other experiments to strengthen our understanding of the fundamental characteristics of dark matter. More information on the LSST dark matter effort can be found at https://lsstdarkmatter.github.io/ .

astro-ph.CO↗

arXiv2019

Astrophysical Tests of Dark Matter with Maunakea Spectroscopic Explorer

We discuss how astrophysical observations with the Maunakea Spectroscopic Explorer (MSE), a high-multiplexity (about 4300 fibers), wide field-of-view (1.5 square degree), large telescope aperture (11.25 m) facility, can probe the particle nature of dark matter. MSE will conduct a suite of surveys that will provide critical input for determinations of the mass function, phase-space distribution, and internal density profiles of dark matter halos across all mass scales. N-body and hydrodynamical simulations of cold, warm, fuzzy and self-interacting dark matter suggest that non-trivial dynamics in the dark sector could have left an imprint on structure formation. Analysed within these frameworks, the extensive and unprecedented datasets produced by MSE will be used to search for deviations away from cold and collisionless dark matter model. MSE will provide an improved estimate of the local density of dark matter, critical for direct detection experiments, and will improve estimates of the J-factor for indirect searches through self-annihilation or decay into Standard Model particles. MSE will determine the impact of low mass substructures on the dynamics of Milky Way stellar streams in velocity space, and will allow for estimates of the density profiles of the dark matter halos of Milky Way dwarf galaxies using more than an order of magnitude more tracers. In the low redshift Universe, MSE will provide critical redshifts to pin down the luminosity functions of vast numbers of satellite systems, and MSE will be an essential component of future strong lensing measurements to constrain the halo mass function. Across nearly all mass scales, the improvements offered by MSE, in comparison to other facilities, are such that the relevant analyses are limited by systematics rather than statistics.

astro-ph.CO↗

arXiv2019

The Metal-Poor Stellar Halo in RAVE-TGAS and its Implications for the Velocity Distribution of Dark Matter

The local velocity distribution of dark matter plays an integral role in interpreting the results from direct detection experiments. We previously showed that metal-poor halo stars serve as excellent tracers of the virialized dark matter velocity distribution using a high-resolution hydrodynamic simulation of a Milky Way--like halo. In this paper, we take advantage of the first \textit{Gaia} data release, coupled with spectroscopic measurements from the RAdial Velocity Experiment (RAVE), to study the kinematics of stars belonging to the metal-poor halo within an average distance of $\sim 5$ kpc of the Sun. We study stars with iron abundances [Fe/H]$ < -1.5$ and $-1.8$ that are located more than $1.5$ kpc from the Galactic plane. Using a Gaussian mixture model analysis, we identify the stars that belong to the halo population, as well as some kinematic outliers. We find that both metallicity samples have similar velocity distributions for the halo component, within uncertainties. Assuming that the stellar halo velocities adequately trace the virialized dark matter, we study the implications for direct detection experiments. The Standard Halo Model, which is typically assumed for dark matter, is discrepant with the empirical distribution by $\sim6σ$ and predicts fewer high-speed particles. As a result, the Standard Halo Model overpredicts the nuclear scattering rate for dark matter masses below $\sim 10$ GeV. The kinematic outliers that we identify may potentially be correlated with dark matter substructure, though further study is needed to establish this correspondence.

astro-ph.GA↗

arXiv2018

Comment on the paper "On the correlation between the local dark matter and stellar velocities"

We briefly comment on the paper "On the correlation between the local dark matter and stellar velocities" (Bozorgnia et al. 2018), which purports to test our previous claims regarding the correlation of stellar and dark matter kinematics (Herzog-Arbeitman et al. 2017; Necib et al. 2018). The conclusions of these papers are not accurately presented in Bozorgnia et al. (2018), and we thus clarify them here.

astro-ph.GA↗

arXiv2018

Under the Firelight: Stellar Tracers of the Local Dark Matter Velocity Distribution in the Milky Way

The Gaia era opens new possibilities for discovering the remnants of disrupted satellite galaxies in the Solar neighborhood. If the population of local accreted stars is correlated with the dark matter sourced by the same mergers, one can then map the dark matter distribution directly. Using two cosmological zoom-in hydrodynamic simulations of Milky Way-mass galaxies from the Latte suite of Fire-2 simulations, we find a strong correlation between the velocity distribution of stars and dark matter at the solar circle that were accreted from luminous satellites. This correspondence holds for dark matter that is either relaxed or in kinematic substructure called debris flow, and is consistent between two simulated hosts with different merger histories. The correspondence is more problematic for streams because of possible spatial offsets between the dark matter and stars. We demonstrate how to reconstruct the dark matter velocity distribution from the observed properties of the accreted stellar population by properly accounting for the ratio of stars to dark matter contributed by individual mergers. After demonstrating this method using the Fire-2 simulations, we apply it to the Milky Way and use it to recover the dark matter velocity distribution associated with the recently discovered stellar debris field in the Solar neighborhood. Based on results from Gaia, we estimate that $42 ^{+26}_{-22}\%$ of the local dark matter that is accreted from luminous mergers is in debris flow.

astro-ph.GA↗

arXiv2018

Recursive Soft Drop

We introduce a new jet substructure technique called Recursive Soft Drop, which generalizes the Soft Drop algorithm to have multiple grooming layers. Like the original Soft Drop method, this new recursive variant traverses a jet clustering tree to remove soft wide-angle contamination. By enforcing the Soft Drop condition N times, Recursive Soft Drop improves the jet mass resolution for boosted hadronic objects like W bosons, top quarks, and Higgs bosons. We further show that this improvement in mass resolution persists when including the effects of pileup, up to large pileup multiplicities. In the limit that N goes to infinity, the resulting groomed jets formally have zero catchment area. As an alternative approach, we present a bottom-up version of Recursive Soft Drop which, in its local form, is similar to Recursive Soft Drop and which, in its global form, can be used to perform event-wide grooming.

hep-ph↗