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Lina Necib

Publications and source records attributed to Lina Necib.

At least 19 recordsLinked to original sources
arXiv2026

Baryon-Accelerated Core Collapse in SIDM Halos and its Imprint on Galactic Disks

The gravitational coupling between dark matter (DM) halos and the baryonic structures they host is one of the most powerful windows into the particle nature of DM. Self-interacting dark matter (SIDM) presents a minimal, well-motivated extension to the dark sector with dramatic consequences for the structure of galaxies and their halos. However, the impact of baryons on SIDM halo evolution and the resulting galactic structure has been underexplored in Milky Way (MW)-size galaxies. In this paper, we demonstrate that the inclusion of a baryonic component in a MW-size galaxy causes accelerated core collapse to begin within the MW's lifetime for a cross section as low as $\sigma/m = 1 \, \rm{cm}^2/\rm{g}$. We present a suite of $N$-body simulations of cold dark matter and SIDM MW-size galaxies with and without a baryonic component for cross sections $\sigma/m =[1.0, 2.5, 5.0]$ cm$^2$/g. We find numerically, and semi-analytically, that the presence of a stellar disk and bulge shortens the predicted core collapse timescales from the DM only simulations by a factor of $\sim 40$. Further, as the core collapse begins within the lifetime of the galaxy, the subsequent density increase strengthens the mid-plane restoring force exerted on stellar disk orbits, leading the disk to flare. This work quantifies both directions of the baryon--SIDM coupling: baryons accelerate core collapse in MW-sized halos, and the resulting halo evolution reshapes the disk through thinning and flaring. Both processes open new observational windows into DM.

astro-ph.GA↗
arXiv2026

Dark Matter in Draco and Bo\"otes I: Hints of a Core in an Ultra-Faint Dwarf from Simulation-Based Inference

The density profiles of dwarf spheroidal galaxies are among the most sensitive probes of dark matter physics, yet extracting them from noisy stellar kinematics remains a fundamental obstacle. We present GraphNPE, a simulation-based inference method for dynamical mass modeling that incorporates measurement uncertainties and spectroscopic selection functions in the forward model. Using mock data, we show that methods relying solely on line-of-sight velocity dispersion are biased toward cuspy density profiles, even in the absence of the mass-anisotropy degeneracy. By accessing higher-order velocity moments, particularly line-of-sight kurtosis, GraphNPE breaks key degeneracies and recovers density profiles with substantially less bias. We apply GraphNPE to Draco and Bo\"otes I using MMT/Hectochelle and DESI for Draco, and the S5 survey for Bo\"otes I. For each, we report density profiles and dark matter $J$- and $D$-factors. For Draco, GraphNPE yields consistent results across datasets, marginally preferring a cuspy inner profile ($\rho_{150} \sim 1.6-1.9 \times 10^8\,\mathrm{M}_\odot\,\mathrm{kpc}^{-3}$) in agreement with literature. On DESI, however, second-order Jeans modeling fits the dispersion but fails to reproduce the kurtosis, demonstrating higher-order moments are essential. For Bo\"otes I, limited statistical power prevents definitive determination of the inner slope. GraphNPE recovers $\rho_{150} = 0.36^{+0.15}_{-0.11} \times 10^8\,\mathrm{M}_\odot\,\mathrm{kpc}^{-3}$, significantly lower than literature and consistent with a cored inner profile. This places Bo\"otes I among the lowest density dwarfs at comparable stellar masses.

astro-ph.GA↗
arXiv2026

Reconstructing Galactic Gravitational Potentials from Stellar Kinematics with Physics-Informed Neural Networks

The gravitational potential of a galaxy encodes its mass distribution, formation history, and dark matter halo structure. Accurate potential models are therefore critical for interpreting stellar kinematics, orbital dynamics, and the influence of satellite systems like the Large Magellanic Cloud. Analytic potential models offer interpretability and efficiency but struggle to capture complex, non-axisymmetric structure and time-dependent perturbations. Neural network-based methods can capture this complexity but offer little interpretability. We introduce a physics-informed neural network (PINN) framework that combines data-driven learning with embedded physical constraints, available as the open-source package GalactoPINNS. Trained on acceleration measurements, the framework captures complex, small-scale features while preserving global physical consistency. We test on systems of increasing complexity, from controlled analytic halos to cosmological simulations of Milky Way-like galaxies, achieving sub-percent acceleration errors with orbit reconstruction that consistently outperforms analytic baselines. Additionally, we implement a Bayesian neural network to provide spatially calibrated uncertainty estimates, and a time-dependent extension to capture smooth temporal evolution. By treating an analytic model as a structured prior and learning corrections on top of it, the method retains physical interpretability while gaining the flexibility to represent realistic galactic potentials, making it well suited for Milky Way modeling and dynamical inference in the era of current and upcoming large-scale surveys.

astro-ph.GA↗
arXiv2026

The Dynamics of Old Inner Galaxy Stars in Milky Way-mass Galaxies Using FIRE-2 Simulations

Understanding how galaxies like the Milky Way assembled over cosmic time remains a central question in astrophysics. Understanding the processes that shaped their formation and evolution is greatly enhanced by the joint use of observational data and high-resolution cosmological simulations. Old stars in the inner regions of galaxies serve as powerful tracers of early dynamical events, having formed during the initial stages of galaxy assembly and retaining the kinematic imprints of those formative periods. We investigate the kinematic properties of old (age $>10$ Gyr) inner galaxy ($r_\mathrm{GC}<5$ kpc) stars in thirteen Milky Way-mass galaxies from the FIRE-2 cosmological zoom-in simulations, focusing on their origin, orbital structure, and kinematic alignment with the disk. Our analysis reveals that old stars in the inner galaxy are more likely to have been formed in their host galaxy, although accretion is seen most prominently during the earliest stages of galaxy formation. Many of these accreted stars tend to occupy kinematically hot orbits compared to their counterparts formed in the host galaxy, although some stars formed in-galaxy also retain kinematically hot orbits. Disk-like dynamics are present throughout all age bins, and are most prominent as age decreases. Although some old stellar populations retain disk-like structure, the prominence of this rotational component varies significantly across galaxies and between star populations. These results emphasize the diversity of early galaxy assembly histories and suggest that coherent angular momentum in accreted material can leave detectable kinematic signatures in present-day stellar halos.

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arXiv2026

Mergers Matter: Gravothermal Collapse in Dwarf Halos with Self-Interacting Dark Matter

Self-Interacting Dark Matter (SIDM) models with large cross sections at relative velocities below $\sim100\,{\rm km \, s}^{-1}$ can be tested with dwarf galaxy observations. We analyze six dark-matter-only zoom-in $\sim10^{10}\,{\rm M}_\odot$ halos with diverse assembly histories, adopting a cross section over mass of $\sigma/m = 70\,cm^2 \, g^{-1}$. We find that mergers inject orbital kinetic energy into the halo, altering the heat transport and the gravothermal evolution of the core. Three of the six halos -- those with the most quiescent merger histories -- show clear signs of core collapse in these simulations. Halos with sustained mergers do not collapse. Furthermore, merger-induced heat transport drives two non-collapsing halos to central densities well below the predictions of the gravothermal fluid model. These findings suggest a novel mechanism for producing dark-matter-deficient galaxies and expanding the diversity of rotation curves beyond what halo concentration alone predicts. Merger histories are thus essential for understanding central density distributions of dwarf galaxy halos in SIDM.

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arXiv2026

Galactic Amnesia: The Information Washout of the Milky Way Merger History

The merger history of a galaxy leaves imprints on its present-day stellar chemodynamics, yet dynamical processes progressively erase this record. We ask: how far back in time, and from which observables, can a galaxy's assembly history still be recovered? We provide a quantitative framework to address this question, using Mutual Information normalized by Shannon entropy to measure how much present-day stellar chemodynamics retains about each past merger's stellar mass $M_\star$ and infall time $t_{\rm infall}$. This framework is applied to TNG50 Milky Way -- like galaxies, with comparison to FIRE-2. We find that the gravitational potential and total energy are the most informative and longest-lived tracers of merger properties, highlighting the need for accurately measuring the Milky Way's potential. The information carried by the radial velocity decays to the noise floor within $\sim$5 Gyr, angular momentum carries low information overall with a mass-dependent decay, and chemical abundances retain a flat, low information floor. Information washout depends on three key factors: (1) radial position -- stars in the inner galaxy lose information faster due to shorter orbital times; (2) infall time -- old mergers are largely phase-mixed; and (3) merger mass -- larger mergers sink to the bottom of the potential well via dynamical friction, inducing violent relaxation that erases dynamical information. At each galactocentric radius, we map the observational horizon in the $(M_\star,\; t_{\rm infall})$ plane beyond which past mergers can no longer be recovered from that observable. By recasting merger reconstruction into this quantitative, observable-by-observable map of what is and is not recoverable, our results provide a foundation for interpreting chemodynamical signatures of past mergers and for guiding surveys and modeling toward the observables that maximize merger information recovery.

astro-ph.GA↗
arXiv2026

Formation and Redshift Evolution of Dark Matter Spikes

Dark matter density spikes forming around adiabatically growing black holes can dramatically enhance indirect and direct detection signals. Canonical predictions, however, assume a zero-mass seed in a purely dark matter environment and do not track the long-term dynamical impact of surrounding stars. We present a semi-analytic framework that first generalizes adiabatic spike formation to include finite seed masses, stellar cusps, and non-circular orbits, and then studies the subsequent cosmic evolution by solving coupled Fokker-Planck equations for the dark matter and stellar phase-space distributions, with a heating rate modulated by the cosmic star formation rate. Starting conservatively from canonical Gondolo-Silk spikes and marginalizing over astrophysical uncertainties, we find that stellar gravitational heating drives the inner slope towards $\gamma_\chi \simeq 1.5$ within a few Gyrs (e.g by $z \lesssim 2$ for spikes formed at $z\simeq 10$), yielding overdensities two to four orders of magnitude below canonical expectations but still well above an NFW-like cusp. We provide redshift-dependent benchmarks for the column density and $J$-factor relevant to scattering, decay and annihilation signatures. Any robust interpretation of indirect dark matter signals from galactic nuclei must account for this evolution.

astro-ph.CO↗
arXiv2026

Set the Night on FIRE: Building an Empirical Local Dark Matter Velocity Distribution

The majority of terrestrial direct detection experiments for Dark Matter (DM) rely on the Standard Halo Model (SHM), which assumes the local DM velocity distribution follows a Maxwell-Boltzmann distribution. However, galaxy mergers can deposit DM that remains kinematically clustered today, inducing deviations from the smooth SHM prediction. Previous studies have suggested that the local stellar velocity distribution may serve as a tracer for DM populations originating from the same progenitor systems. In this work, we systematically investigate how merger mass and accretion time affect the correlation between local stellar and DM velocity distributions in Milky Way-like galaxies from the FIRE-2 simulations. We find a strong correlation between traceable DM components and their stellar counterparts, with the tightest correspondence arising from lower-mass mergers accreted at earlier cosmic times. For the remaining DM that lacks an identifiable stellar counterpart, which dominate the full DM fraction, we find that its velocity distribution is well described by a component-wise generalized Gaussian. Combining these two ingredients, we reconstruct the full local DM velocity distribution. This framework captures merger-induced features-such as co-rotation of accreted material with the galactic disk-that are entirely absent in the SHM. Finally, we propagate uncertainties through the reconstruction and show that they are dominated by the stellar mass-halo mass relation, which is unlikely to improve substantially in the near term. We therefore argue that this framework approaches the current limit of our ability to characterize the local DM velocity distribution.

astro-ph.GA↗
arXiv2026

Probing Atomic Dark Matter with Stellar Streams in Milky Way-Mass Galaxies

We present the first detailed analysis of the effects of dissipative dark matter on stellar streams. As a concrete example, we generate a cosmological hydrodynamic zoom-in simulation of a Milky Way-mass galaxy, assuming that the dark matter consists of Cold Dark Matter (CDM) with a sub-component ($\sim6\%$) of Atomic Dark Matter (ADM). The ADM subcomponent behaves as collisional, efficiently dissipative gas and allows for the formation of dense compact objects that enhance the central density of satellite galaxies, making them more resistant to tidal disruption. We show that stellar streams with stellar mass $M_{\rm{tot}, \star} \gtrsim 10^{5.5} \ \text{M}_\odot$ form later and exhibit prolonged star formation throughout their evolution, as compared to their CDM counterparts. Changes to star formation history are reflected on the chemical tracks of the stellar stream stars, where the youngest have enhanced [Fe/H] and [Mg/Fe] in the presence of ADM. Furthermore, a population of low-mass satellites with high ADM mass fractions is identified at low pericenter distances, which may affect the population of streams at $M_{\rm{tot}, \star} \lesssim 10^{5.5} \ \text{M}_\odot$. The results of this study should generalize to other dark matter models that lead to inner-density enhancements in satellites, such as elastic self-interacting dark matter in the gravothermal collapse regime.

astro-ph.GA↗
arXiv2026

The erasure of Galactic bar resonances by dark matter subhaloes

In the context of increasing appreciation for the coupling between the Galactic bar and the halo, we introduce a new framework using stars trapped in resonance with the bar to probe the Galactic dark matter subhalo population. Since resonant stars occupy a finite width in action space, perturbations from subhaloes can shift a star's actions beyond this width, causing them to circulate out of resonance. Physically, the dark substructure in the Milky Way may dissolve, puff-up, or re-order the resonance features in the stellar halo. To explore the utility of this framework, we treat individual encounters in the impulse approximation and model their cumulative effect as diffusion in the relevant action. The resulting diffusion coefficient allows us to link the survival of resonant populations to the subhalo mass function, whose properties depend on the particle nature of dark matter. Test particle integration validates the impulse treatment for low-mass subhaloes and quantifies its regime of applicability. For a Milky Way-like bar, we find individual subhaloes with $M<10^7$ M$_{\odot}$ have negligible impact on stars in co-rotation resonance, where as the full cold dark matter (CDM) population could erase the resonance over the bar's lifetime. The persistence of resonances therefore implies a suppression of the local subhalo density to less than 1/3 of CDM expectations, consistent with tidal disruptions and previous literature. The narrow widths of higher-order resonances will increase the constraining power of this framework, and therefore motivates searches for bar-resonant halo features in observational data.

astro-ph.GA↗
arXiv2026

Physics-Informed Neural Networks for Modeling Galactic Gravitational Potentials

We introduce a physics-informed neural framework for modeling static and time-dependent galactic gravitational potentials. The method combines data-driven learning with embedded physical constraints to capture complex, small-scale features while preserving global physical consistency. We quantify predictive uncertainty through a Bayesian framework, and model time evolution using a neural ODE approach. Applied to mock systems of varying complexity, the model achieves reconstruction errors at the sub-percent level ($0.14\%$ mean acceleration error) and improves dynamical consistency compared to analytic baselines. This method complements existing analytic methods, enabling physics-informed baseline potentials to be combined with neural residual fields to achieve both interpretable and accurate potential models.

astro-ph.GA↗
arXiv2025

The DREAMS Project: Disentangling the Impact of Halo-to-Halo Variance and Baryonic Feedback on Milky Way Dark Matter Speed Distributions

Direct detection experiments require information about the local dark matter speed distribution to produce constraints on dark matter candidates, or infer their properties in the event of a discovery. In this paper, we analyze how the uncertainty in the dark matter speed distribution near the Sun is affected by baryonic feedback, halo-to-halo variance, and halo mass. To do so, we harness the statistical power of the new DREAMS Cold Dark Matter simulation suite, which is comprised of 1024 zoom-in Milky Way-mass halos with varied initial conditions as well as cosmological and astrophysical parameters. Applying a normalizing flows emulator to these simulations, we find that the uncertainty in the local DM speed distribution is dominated by halo-to-halo variance and, to a lesser extent, uncertainty in host halo mass. Uncertainties in supernova and black hole feedback (from the IllustrisTNG model in this case) are negligible in comparison. Using the DREAMS suite, we present a state-of-the-art prediction for the DM speed distribution in the Milky Way. Although the Standard Halo Model is contained within the uncertainty of this prediction, individual galaxies may have distributions that differ from it. Lastly, we apply our DREAMS results to the XENON1T experiment and demonstrate that the astrophysical uncertainties are comparable to the experimental ones, solidifying previous results in the literature obtained with a smaller sample of simulated Milky Way-mass halos.

astro-ph.GA↗
arXiv2025

The DREAMS Project: Disentangling the Impact of Halo-to-Halo Variance and Baryonic Feedback on Milky Way Dark Matter Density Profiles

In this work, we utilize a new suite of Milky Way-mass halos from the DREAMS Project, simulated with Cold Dark Matter (CDM), to quantify the influence of baryon feedback and intrinsic halo-to-halo variance on dark matter density profiles. Our suite of 1024 halos varies over supernova and black hole feedback parameters from the IllustrisTNG model, as well as variations in two cosmological parameters. We find that, for the DREAMS parameter variations, Milky Way-mass dark matter density profiles in the IllustrisTNG model are largely insensitive to astrophysics and cosmology variations, with the dominant source of scatter instead arising from halo-to-halo variance. However, most of the (comparatively minor) feedback-driven variations come from the changes to supernova prescriptions. By comparing to dark matter-only simulations, we find that the strongest supernova wind energies are so effective at preventing galaxy formation that the halos are nearly entirely collisionless dark matter. Finally, regardless of physics variation, all the DREAMS halos are roughly consistent with a halo contracting adiabatically from the presence of baryons, unlike models that have bursty stellar feedback. This work represents a step toward assessing the uncertainty in Milky Way dark matter profiles, with direct implications for dark matter searches where systematic uncertainty in the density profile remains a major challenge.

astro-ph.GA↗
arXiv2025

The DREAMS Project: Disentangling the Impact of Halo-to-Halo Variance and Baryonic Feedback on Milky Way Satellite Galaxies

We analyze the properties of satellite galaxies around 1,024 Milky Way-mass hosts from the DREAMS Project, simulated within a $\Lambda$CDM cosmology. Utilizing the TNG galaxy-formation model, the DREAMS simulations incorporate both baryonic physics and cosmological uncertainties for a large sample of galaxies with diverse environments and formation histories. We investigate the relative impact of the physical uncertainty from the galaxy-formation model on predicted satellite properties using four metrics: the satellite stellar mass function, radial distribution, inner slope of dark matter density profile, and stellar half-light radius. We compare these predictions to observations from the SAGA Survey and the DREAMS N-body simulations and find that uncertainties from baryonic physics modeling are subdominant to the scatter arising from halo-to-halo variance. Where baryonic modeling does affect satellites, the supernova wind energy has the largest effect on the satellite properties that we investigate. Specifically, increased supernova wind energy suppresses the stellar mass of satellites and results in more extended stellar half-light radii. The adopted wind speed has only a minor impact, and other astrophysical and cosmological parameters show no measurable effect. Our findings highlight the robustness of satellite properties against uncertainties in baryonic physics modeling.

astro-ph.GA↗
arXiv2025

Searching for Exoplanets Born Outside the Milky Way: VOYAGERS Survey Design

Observations over the past few decades have found that planets are common around nearby stars in our Galaxy, but little is known about planets that formed outside the Milky Way. We describe the design and early implementation of a survey to test whether planets also exist orbiting the remnant stars of ancient dwarf galaxies that merged with the Milky Way, and if so, how they differ from their Milky Way counterparts. VOYAGERS (Views Of Yore - Ancient Gaia-enceladus Exoplanet Revealing Survey) is a radial velocity (RV) search using precision spectrographs to discover exoplanets orbiting very low metallicity ($-2.8 < [\mathrm{Fe/H}] \leq -0.8$) stars born in the dwarf galaxy Enceladus, which merged with the Milky Way galaxy about 10 Gyr ago. A sample of 22 candidates have been screened from a catalog of Gaia-Enceladus-Sausage (GES) members using a combination of stellar properties and reconnaissance observations from the TRES spectrograph. Precision RV measurements have been initiated using the NEID, HARPS-N, and CARMENES spectrographs. We plan to focus most upcoming observations on 10 main sequence targets. Data collection is well underway, with 778 observations on 22 candidates (385 of which are 10 focus targets), but far from complete. This survey is designed to be sensitive to sub-Neptune mass planets with periods up to hundreds of days. We note that the RV analysis gives mass multiplied by $\sin (inclination)$ or the minimum mass for exoplanets. The expected survey yield is three planets, assuming that occurrence rates are similar to those in the Milky Way and taking into account the degeneracy with inclination in our yield models. Our survey is designed to detect at least one exoplanet if occurrence rates are similar to known Milky Way exoplanets or, if no exoplanets are discovered, to rule out a Milky Way-like planet population in GES with 95% confidence level.

astro-ph.EP↗
arXiv2025

How to Build an Empirical Speed Distribution for Dark Matter in the Solar Neighborhood

The dark matter flux in a direct detection experiment depends on its local speed distribution. This distribution has been inferred from simulations of Milky Way-like galaxies, but such models serve only as proxies, given that no simulation directly captures the detailed evolution of our own Galaxy. This motivates alternative approaches that obtain this distribution directly from observations. In this work, we utilize 98 Milky Way analogues from the TNG50 simulation to develop and validate a procedure for inferring the dark matter speed distribution using the kinematics of nearby stars. We find that the dark matter that originated from old mergers, plus that from recent nonluminous accretions, is well described by a Maxwell-Boltzmann speed distribution centered at the local standard-of-rest velocity. Meanwhile, recently accreted dark matter from massive mergers has speeds that can be traced from the associated stellar debris of these events. The stellar populations systematically underestimate the velocity dispersion of their dark matter counterparts, but a simple kinematic boost brings the two into good alignment. Using the TNG50 host galaxies, we demonstrate that combining these two contributions provides an accurate reconstruction of the local dark matter speeds. As an application of the procedure to our own Galaxy, we utilize stellar kinematic data from Gaia to quantify how the dark matter remnants from the Milky Way's last major merger impact its speed distribution in the solar neighborhood.

astro-ph.GA↗
arXiv2025

Galactic Center Gamma-Ray Emission in MHD Galaxy Formation Simulations with Full Cosmic Ray Spectra

The Milky Way's galactic center is a highly dynamical, crowded environment. Gamma ray observations of this region, such as the excess of GeV scale gamma rays observed by Fermi LAT, have been of tremendous interest to both the high energy astrophysics and particle physics communities. However, nearly all past studies of gamma ray emission make simplifying assumptions about cosmic ray (CR) propagation that may not be valid in the galactic center. Recent numerical breakthroughs now enable fully time dependent dynamical evolution of CRs in magnetohydrodynamic simulations with resolved, multi phase small scale structure in the interstellar medium (ISM), allowing self consistent comparisons to the Milky Way cosmic ray spectrum. We model diffuse gamma ray emission from cosmic ray interactions for a set of Feedback in Realistic Environments (FIRE) simulations of Milky Way mass galaxies run with spectrally resolved cosmic ray spectra for multiple species at MeV to TeV energies. We find that the galactic center gamma ray spectrum can vary by order of magnitude amounts in normalization, and by approx. 10 percent in spectral slope at high energies, driven by both injection from highly variable star formation and losses from variable structure in the turbulent ISM. Gamma ray emission from inverse Compton scattering and relativistic nonthermal Bremsstrahlung is particularly variable on Myr timescales. We argue that features of the observed Milky Way gamma ray spectrum may arise from such transient phenomena in gamma rays produced from CR interactions.

astro-ph.HE↗
arXiv2025

Second public data release of the FIRE-2 cosmological zoom-in simulations of galaxy formation

We describe the second data release (DR2) of the FIRE-2 cosmological zoom-in simulations of galaxy formation, from the Feedback In Realistic Environments (FIRE) project, available at http://flathub.flatironinstitute.org/fire. DR2 includes all snapshots for most simulations, starting at z ~ 99, with all snapshot time spacings <~ 25 Myr. The Core suite -- comprising 14 Milky Way-mass galaxies, 5 SMC/LMC-mass galaxies, and 4 lower-mass galaxies -- includes 601 snapshots to z = 0. For the Core suite, we also release resimulations with physics variations: (1) dark-matter-only versions; (2) a modified ultraviolet background with later reionization at z = 7.8; (3) magnetohydrodynamics, anisotropic conduction, and viscosity in gas; and (4) a model for cosmic-ray injection, transport, and feedback (assuming a constant diffusion coefficient). The Massive Halo suite now includes 8 massive galaxies with 278 snapshots to z = 1. The High Redshift suite includes 34 simulations: in addition to the 22 simulations run to z = 5, we now include 12 additional simulations run to z = 7 and z = 9. We also release 4 dark-matter-only cosmological boxes used to generate zoom-in initial conditions for many FIRE simulations. Most simulations include catalogs of (sub)halos and galaxies at all available snapshots, and most Core simulations to z = 0 include full halo merger trees.

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