arXiv subjects

Blakesley Burkhart

Publications and source records attributed to Blakesley Burkhart.

At least 37 records · Page 2Linked to original sources

arXiv2025

Reconstructing galactic feedback history via the Lyman-$α$ forest with Habitable Worlds Observatory

Recent studies have focused on the low-$z$ Ly$α$ forest as a potential constraint on galactic feedback, as different AGN and stellar feedback models in hydrodynamic simulations produce varying intergalactic medium (IGM) statistics. However, existing low-$z$ Ly$α$ forest data provide insufficient observational constraints for simulations due to their low precision and the lack of observations from $z \sim 0.4$ to $1.8$. The Habitable Worlds Observatory, equipped with an ultraviolet (FUV / NUV) spectrograph, could provide transformative data for this science by increasing both absorbers in the redshift range where current data are lacking and increasing the precision of the Ly$α$ forest observational data at $z \leq 0.4$. This spectrograph should cover the wavelengths $1215-3402$ Å~and have a spectral resolution of $R =$~40,000. Distinguishing between certain active-galactic nuclei feedback models requires high precision ($\sim 5-10$\%) measurements of the Ly$α$ forest 1D transmitted flux power spectrum for $z\leq 1.8$. This requires $\sim 830$ QSO spectra with S/N~$\geq5$ - $25$ depending on redshift. This data would also enable a comprehensive study on the thermal state of the IGM across time, and address the tension between the observed and simulated Ly$α$ forest $b$-value distribution.

astro-ph.GA↗

arXiv2025

Correlations, mean-field limits, and transition to the concentrated regime in motile particle suspensions

Suspensions of swimming particles exhibit complex collective behaviors driven by hydrodynamic interactions, showing persistent large-scale flows and long-range correlations. While heavily studied, it remains unclear how such structures depend on the system size and swimmer concentration. To address these issues, we simulate very large systems of suspended swimmers across a range of system sizes and volume fractions. For this we use high-performance simulation tools that build on slender body theory and implicit resolution of steric interactions. At low volume fractions and long times, the particle simulations reveal dynamic flow structures and correlation functions that scale with the system size. These results are consistent with a mean-field limit and agree well with a corresponding kinetic theory. At higher concentrations, the system departs from mean-field behavior. Flow structures become cellular, and correlation lengths scale with the particle size. Here, translational motion is suppressed, while rotational dynamics dominate. These findings highlight the limitations of dilute mean-field models and reveal new behaviors in dense active suspensions.

cond-mat.soft↗

arXiv2025

A data-driven approach for star formation parameterization using symbolic regression

Star formation (SF) in the interstellar medium (ISM) is fundamental to understanding galaxy evolution and planet formation. However, efforts to develop closed-form analytic expressions that link SF with key influencing physical variables, such as gas density and turbulence, remain challenging. In this work, we leverage recent advancements in machine learning (ML) and use symbolic regression (SR) techniques to produce the first data-driven, ML-discovered analytic expressions for SF using the publicly available FIRE-2 simulation suites. Employing a pipeline based on training the genetic algorithm of SR from an open software package called PySR, in tandem with a custom loss function and a model selection technique which compares candidate equations to analytic approaches to describing SF, we produce symbolic representations of a predictive model for the star formation rate surface density ($Σ_\mathrm{SFR}$) averaged over both 10 Myr and 100 Myr based on eight extracted variables from FIRE-2 galaxies. The resulting model that PySR finds best describes SF, on both averaging timescales, features equations that incorporates the surface density of gas, $Σ_\mathrm{gas}$, the velocity dispersion of gas $σ_{\mathrm{gas,~z}}$ and the surface density of stars $Σ_\mathrm{*}$. Furthermore, we find that the equations found for the longer SFR timescale all converge to a scaling-relation-like equation, all of which also closely capture the intrinsic physical scatter of the data within the Kennicutt-Schmidt (KS) plane. This observed convergence to physically interpretable scaling relations at longer SFR timescales demonstrates that our method successfully identifies robust physical relationships rather than fitting to stochastic fluctuations.

astro-ph.GA↗

arXiv2025

Searching for star formation towards the Eos molecular cloud

The Eos cloud, recently discovered in the far ultraviolet via H$_2$ fluorescence, is one of the nearest known dark molecular clouds to the Sun, with a distance spanning from $\sim94-136$pc. However, with a mass ($\sim5.5\times10^3$M$_\odot$) just under $40$ per cent that of star forming clouds like Taurus and evidence for net molecular dissociation, its evolutionary and star forming status is uncertain. We use Gaia data to investigate whether there is evidence for a young stellar population that may have formed from the Eos cloud. Comparing isochrones and pre-main sequence evolutionary models there is no clear young stellar population in the region. While there are a small number of $<10$Myr stars, that population is statistically indistinguishable from those in similar search volumes at other Galactic latitudes. We also find no unusual spatial or kinematic clustering toward the Eos cloud over distances $70-150$pc. Overall we conclude that the Eos cloud has most likely not undergone any recent substantial star formation, and further study of the dynamics of the cloud is required to determine whether it will do so in the future.

astro-ph.GA↗

arXiv2025

The Stellar Initial Mass Function of Early Dark Matter-free Gas Objects

Among the remarkable strides made by JWST is the discovery of the earliest star clusters found to date. These have been proposed as early progenitors of globular clusters, which are known to come from the early stages of star formation in the Universe. This is an exciting development in modern astronomy, as it offers an opportunity to connect theoretical models of globular cluster formation to actual observations of these high-redshift structures. In this work, we aim to develop observational signatures of a star cluster formation route known as supersonically induced gas objects, which are dark matter-less gas clouds in the early Universe proposed as a potential origin of some globular clusters. For the first time, we follow the star formation process of these early Universe objects using high-resolution hydrodynamical simulations, including mechanical feedback. Our results suggest that the first dark matter-less star clusters are top-heavy, meaning that they have a flatter IMF slope compared to very young low-metallicity star clusters in the local Universe, and they also have extremely high stellar mass surface densities compared to their local counterparts.

astro-ph.GA↗

arXiv2025

Magnetic fields limit the mass of Population III stars even before the onset of protostellar radiation feedback

The masses of Population III stars are largely unconstrained since no simulations exist that take all relevant primordial star formation physics into account. We perform the first suite of radiation magnetohydrodynamics (RMHD) simulations of Population III star formation, with the POPSICLE project. Compared to control simulations that only include magnetic fields (MHD), protostellar ionizing and dissociating feedback, or neither, the RMHD simulation best resembles the MHD simulation during the earliest stages of collapse and star formation. In $5000\,\rm{yrs}$, the mass of the most massive star is $65\,\rm{M_{\odot}}$ in the RMHD simulation, compared to $120\,\rm{M_{\odot}}$ in simulations without magnetic fields. This difference arises because magnetic fields act against gravity, suppress mass transport, and reduce compressional heating. The maximum stellar mass of Population III stars is thus already limited by magnetic fields, even before accretion rates drop to allow significant protostellar radiative feedback. Following classical main sequence stellar evolution with MESA reveals that it is difficult to create Population III stars with masses larger than $600\,\rm{M_{\odot}}$ in typical dark matter minihaloes at $z \gtrsim 20$, with maximum stellar masses $\sim 100\,\rm{M_{\odot}}$ more likely due to expected negative feedback from both magnetic fields and stellar radiation. This work lays the first step in building a full physics-informed mass function of Population III stars.

astro-ph.GA↗

arXiv2025

A Nearby Dark Molecular Cloud in the Local Bubble Revealed via H$_2$ Fluorescence

A longstanding prediction in interstellar theory posits that significant quantities of molecular gas, crucial for star formation, may be undetected due to being ``dark" in commonly used molecular gas tracers, such as carbon monoxide. We report the discovery of Eos, the closest dark molecular cloud, located just 94 parsecs from the Sun. This cloud is the first molecular cloud ever to be identified using H$_2$ far ultra-violet (FUV) fluorescent line emission, which traces molecular gas at the boundary layers of star-forming and supernova remnant regions. The cloud edge is outlined along the high-latitude side of the North Polar Spur, a prominent x-ray/radio structure. Our distance estimate utilizes 3D dust maps, the absorption of the soft X-ray background, and hot gas tracers such as O\,{\sc vi}; these place the cloud at a distance consistent with the Local Bubble's surface. Using high-latitude CO maps we note a small amount (M$_{\rm{H}_2}\approx$20-40\,M$_\odot$) of CO-bright cold molecular gas, in contrast with the much larger estimate of the cloud's true molecular mass (M$_{\rm{H}_2}\approx3.4\times 10^3$\,M$_\odot$), indicating most of the cloud is CO-dark. Combining observational data with novel analytical models and simulations, we predict this cloud will photoevaporate in 5.7 million years, placing key constraints on the role of stellar feedback in shaping the closest star-forming regions to the Sun.

astro-ph.GA↗

arXiv2025

The Effects of AGN Feedback on the Lyman-$α$ Forest Flux Power Spectrum

We study the effects of AGN feedback on the Lyman-$α$ forest 1D flux power spectrum (P1D). Using the Simba cosmological-hydrodynamic simulations, we examine the impact that adding different AGN feedback modes has on the predicted P1D. We find that, for Simba, the impact of AGN feedback is most dramatic at lower redshifts ($z<1$) and that AGN jet feedback plays the most significant role in altering the P1D. The effects of AGN feedback can be seen across a large range of wavenumbers ($1.5\times10^{-3} 2.0$), AGN feedback has a $2\%$ effect on the P1D for $k<5\times10^{-2}$ s/km and an $8\%$ effect for $k>5\times10^{-2}$ s/km. We show that the small scale effect is reduced when normalizing the simulation to the observed mean flux. On large scales, the effect of AGN feedback appears via a change in the IGM temperature and is thus unlikely to bias cosmological parameters. The strong AGN jets in the Simba simulation can reproduce the $z>2$ Lyman-$α$ forest. We stress that analyses comparing different AGN feedback models to future higher precision data will be necessary to determine the full extent of this effect.

astro-ph.CO↗

arXiv2025

$Λ$CDM star clusters at cosmic dawn: stellar densities, environment, and equilibrium

The James Webb Space Telescope (JWST) has opened a window on many new puzzles in the early Universe, including a population of high-redshift star clusters with extremely high stellar surface density, suggesting unique star formation conditions in the Universe's early evolution. We study the formation and evolution of these first star clusters and galaxies using an AREPO cosmological simulation box designed to resolve the intricate environments of the smallest halos hosting Population III star clusters at $z \geq 12$. Our approach, which prioritizes baryonic structure identification through a friends-of-friends algorithm, provides new insights into early star cluster formation and delivers predictions directly relevant to observations. We investigate the dynamical properties of these first star clusters and use numerical and analytical methods to understand the populations of virialized and non-virialized systems. Our findings indicate that high-$z$ star clusters in a feedback-free regime can achieve extreme surface densities, consistent with the systems detected by JWST. These results imply that JWST may have the opportunity to uncover stellar systems at high redshift whose dynamical state preserves evidence of the hierarchical structure formation process.

astro-ph.GA↗

arXiv2025

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning

Machine learning based surrogate models offer researchers powerful tools for accelerating simulation-based workflows. However, as standard datasets in this space often cover small classes of physical behavior, it can be difficult to evaluate the efficacy of new approaches. To address this gap, we introduce the Well: a large-scale collection of datasets containing numerical simulations of a wide variety of spatiotemporal physical systems. The Well draws from domain experts and numerical software developers to provide 15TB of data across 16 datasets covering diverse domains such as biological systems, fluid dynamics, acoustic scattering, as well as magneto-hydrodynamic simulations of extra-galactic fluids or supernova explosions. These datasets can be used individually or as part of a broader benchmark suite. To facilitate usage of the Well, we provide a unified PyTorch interface for training and evaluating models. We demonstrate the function of this library by introducing example baselines that highlight the new challenges posed by the complex dynamics of the Well. The code and data is available at https://github.com/PolymathicAI/the_well.

cs.LG↗

arXiv2025

The Molecular Cloud Lifecycle I: Constraining H2 formation and dissociation rates with observations

Molecular clouds (MCs) are the birthplaces of new stars in galaxies. A key component of MCs are photodissociation regions (PDRs), where far-ultraviolet radiation plays a crucial role in determining the gas's physical and chemical state. Traditional PDR models assume chemical steady state (CSS), where the rates of H$_2$ formation and photodissociation are balanced. However, real MCs are dynamic and can be out of CSS. In this study, we demonstrate that combining H$_2$ emission lines observed in the far-ultraviolet or infrared with column density observations can be used to derive the rates of H$_2$ formation and photodissociation. We derive analytical formulae that relate these rates to observable quantities, which we validate using synthetic H$_2$ line emission maps derived from the SILCC-Zoom hydrodynamical simulation. Our method estimates integrated H$_2$ formation and dissociation rates with an accuracy $\approx 30$ % (on top of uncertainties in observed H$_2$ emission maps and column densities). Our simulations, valid for column densities $N \leq 2 \times 10^{22}$ cm$^{-2}$, cover a wide dynamic range in H$_2$ formation and photodissociation rates, showing significant deviations from CSS, with 74 % of the MC's mass deviating from CSS by a factor greater than 2. Our analytical formulae can effectively distinguish between regions in and out of CSS. When applied to actual H$_2$ line observations, our method can assess the chemical state of MCs, providing insights into their evolutionary stages and lifetimes. A NASA Small Explorer mission concept, Eos, will be proposed in 2025 and is specifically designed to conduct the types of observations outlined in this study.

astro-ph.GA↗

arXiv2024

Tracing 3-D Magnetic Field Structure Using Dust Polarization and the Zeeman Effect

The characterization of magnetic fields within molecular clouds is fundamental to understanding star formation processes. Accurately gauging the three-dimensional structure of these fields presents a challenge, as observational techniques such as dust polarization and the Zeeman effect each provide only partial information on the orientation and line-of-sight strength, respectively. By analyzing a suite of AREPO simulations, this paper investigates how observables can relate to underlying physical properties to derive a more comprehensive picture of the magnetic field's inclination angle and strength, specifically in regions where both dust polarization and Zeeman data are available. To demonstrate the method, we produce synthetic observations of the polarization angle dispersion and line-of-sight Alfvén Mach Number and explore the behavior of the inclination angle, $γ$, and strength of the magnetic field in regions where both Zeeman and dust polarization data are available. We find that dust polarization data can be used to determine the inclination angle if the cloud is known to be trans-Alfvénic or sub-Alfvénic. The strength of the magnetic field relative to turbulence can be estimated by comparing polarization observations to Zeeman observations. Comparing the dispersion of the polarization angle to the estimated line-of-sight Alfvén Mach Number provides clues about the strength of the magnetic field and, consequently, the orientation of the magnetic field.

astro-ph.GA↗

arXiv2024

Bursts of star formation and radiation-driven outflows produce efficient LyC leakage from dense compact star clusters

The escape of LyC photons emitted by massive stars from the dense interstellar medium of galaxies is one of the most significant bottlenecks for cosmological reionization. The escape fraction shows significant scatter between galaxies, and anisotropic, spatial variation within them, motivating further study of the underlying physical factors responsible for these trends. We perform numerical radiation hydrodynamic simulations of idealized clouds with different gas surface densities (compactness) $Σ\sim 10^2$--$10^5 \, M_{\odot} \rm{pc}^{-2}$, meant to emulate star cluster-forming clumps ranging from conditions typical of the local Universe to the high ISM-pressure conditions more frequently encountered at high redshift. Our results indicate that dense compact star clusters with $Σ\gtrsim 10^4 \, M_{\odot} \rm{pc}^{-2}$ efficiently leak LyC photons, with cloud-scale luminosity-weighted average escape fractions $\gtrsim 80\%$ as opposed to $\lesssim 10\%$ for $Σ\sim 100 \, M_{\odot} \rm{pc}^{-2}$. This occurs due to higher star formation efficiencies and shorter dynamical timescales at higher $Σ$; the former results in higher intrinsic LyC emission, and the latter implies rapid evolution, with a burst of star formation followed by rapid gas dispersal, permitting high LyC escape well before the intrinsic LyC emission of stellar populations drop ($\sim 4 \, \mathrm{Myr}$). LyC escape in dense clouds is primarily facilitated by highly ionized outflows driven by radiation pressure on dust with velocities $ \sim 3$ times the cloud escape velocity. We also vary the (assumed) dust abundances ($Z_{\rm{d}}$) and find a very mild increase ($\sim 10%$) in the escape fraction for $\sim 100$ lower $Z_{\mathrm{d}}$. Our results suggest a scenario in which localized compact bursts of star formation in galaxies are disproportionately productive sites of LyC leakage.

astro-ph.GA↗

arXiv2024

Objects May Be Closer Than They Appear: Significant Host Galaxy Dispersion Measures of Fast Radio Bursts in Zoom-in Simulations

We investigate the contribution of host galaxies to the overall Dispersion Measures (DMs) for Fast Radio Bursts (FRBs) using the Feedback in Realistic Environments (FIRE-2) cosmological zoom-in simulation suite. We calculate DMs from every star particle in the simulated L* galaxies by ray-tracing through their multi-phase interstellar medium (ISM), summing the line-of-sight free thermal electron column for all gas elements within $\pm$20 kpc of the galactic mid-plane. At $z=0$, we find average (median) host-galaxy DMs of 74 (43) and 210 (94) pc cm$^{-3}$ for older ($\gtrsim$10 Myr) and younger ($\lesssim$10 Myr) stellar populations, respectively. Inclination raises the median DM measured for older populations ($\gtrsim$10 Myr) in the simulations by a factor of $\sim$2, but generally does not affect the younger stars deeply embedded in H{\small II} regions except in extreme edge-on cases (inclination $\gtrsim 85^\circ$). In kinematically disturbed snapshots ($z = 1$ in FIRE), the average (median) host-galaxy DMs are higher: 80 (107) and 266 (795) pc cm$^{-3}$ for older ($\gtrsim$10 Myr) and younger ($\lesssim$10 Myr) stellar populations, respectively. FIRE galaxies tend to have higher DM values than cosmological simulations such as IllustrisTNG\rev{, with larger tails in their distributions to high DMs}. As a result, FRB host galaxies may be closer (lower redshift) than previously inferred. Furthermore, constraining host-galaxy DM distributions may help significantly constrain FRB progenitor models.

astro-ph.GA↗

arXiv2024

The Supersonic Project: Early Star Formation with the Streaming Velocity

At high redshifts ($z\gtrsim12$), the relative velocity between baryons and dark matter (the so-called streaming velocity) significantly affects star formation in low-mass objects. Streaming substantially reduces the abundance of low-mass gas objects while simultaneously allowing for the formation of supersonically-induced gas objects (SIGOs) and their associated star clusters outside of dark matter halos. Here, we present a study of the population-level effects of streaming on star formation within both halos and SIGOs in a set of simulations with and without streaming. Notably, we find that streaming actually enhances star formation within individual halos of all masses at redshifts between $z=12$ and $z=20$. This is demonstrated both as an increased star formation rate per object as well as an enhancement of the Kennicutt-Schmidt relation for objects with streaming. We find that our simulations are consistent with some observations at high redshift, but on a population level, they continue to under-predict star formation relative to the majority of observations. Notably, our simulations do not include feedback, and so can be taken as an upper limit on the star formation rate, exacerbating these differences. However, simulations of overdense regions (both with and without streaming) agree with observations, suggesting a strategy for extracting information about the overdensity and streaming velocity in a given survey volume in future observations.

astro-ph.GA↗

arXiv2024

Any Way the Wind Blows: Quantifying Superbubbles and their Outflows in Simulated Galaxies across $z \approx 0-3$

We present an investigation of clustered stellar feedback in the form of superbubbles identified within eleven galaxies from the FIRE-2 (Feedback in Realistic Environments) cosmological zoom-in simulation suite, at both cosmic noon (1 < z < 3) and in the local Universe. We study the spatially-resolved multiphase outflows that these supernovae drive, comparing our findings with recent theory and observations. These simulations consist of five LMC-mass galaxies and six Milky Way-mass progenitors (with a minimum baryonic particle mass of $m_{b.min} = 7100 M_{\odot}$), for which we calculate the local mass and energy loading factors on 750~pc scales from the identified outflows. We also characterize the multiphase morphology and properties of the identified superbubbles, including the `shell' of cool ($T<10^5$ K) gas and break out of energetic hot ($T>10^5$ K) gas when the shell bursts. For all galaxies, the outflow mass, momentum, and energy fluxes appear to reach their peak during the identified superbubbles, and we investigate the effects on the interstellar medium (ISM), circumgalactic medium (CGM), and subsequent star formation rates. We find that these simulations, regardless of redshift, have mass-loading factors and momentum fluxes in the cool gas that largely agree with recent observations. Lastly, we also investigate how methodological choices in measuring outflows can affect loading factors for galactic winds.

astro-ph.GA↗

arXiv2024

The Interplay between the IMF and Star Formation Efficiency through Radiative Feedback at High Stellar Surface Densities

The observed rest-UV luminosity function at cosmic dawn ($z \sim 8-14$) measured by JWST revealed an excess of UV-luminous galaxies relative to many pre-launch theoretical predictions. A high star-formation efficiency (SFE) and a top-heavy initial mass function (IMF) are among the mechanisms proposed for explaining this excess. Although a top-heavy IMF has been proposed for its ability to increase the light-to-mass ratio ($Ψ_{\mathrm{UV}}$), the resulting enhanced radiative pressure from young stars could decrease the star formation efficiency (SFE), potentially driving galaxy luminosities back down. In this Letter, we use idealized radiation hydrodynamic simulations of star cluster formation to explore the effects of a top-heavy IMF on the SFE of clouds typical of the high pressure conditions found at these redshifts. We find that the SFE in star clusters with solar neighbourhood-like dust abundance decreases with increasingly top-heavy IMF's -- by $\sim 20 \%$ for an increase of factor 4 in $Ψ_{\mathrm{UV}}$, and by $50 \%$ for a factor $ \sim 10$ in $Ψ_{\mathrm{UV}}$. However, we find that an expected decrease in the dust-to-gas ratio ($\sim 0.01 \times \mathrm{Solar}$) at these redshifts can completely compensate for the enhanced light output. This leads to a (cloud-scale; $\sim 10 \, \mathrm{pc}$) SFE that is $\gtrsim 70\%$ even for a factor 10 increase in $Ψ_{\mathrm{UV}}$, implying that highly efficient star formation is unavoidable for high surface density and low metallicity conditions. Our results suggest that a top-heavy IMF, if present, likely coexists with efficient star formation in these galaxies.

astro-ph.GA↗

arXiv2024

Arkenstone I: A Novel Method for Robustly Capturing High Specific Energy Outflows In Cosmological Simulations

Arkenstone is a new model for multiphase, stellar feedback driven galactic winds designed for inclusion in coarse resolution cosmological simulations. In this first paper of a series, we describe the features that allow Arkenstone to properly treat high specific energy wind components and demonstrate them using idealised non-cosmological simulations of a galaxy with a realistic CGM, using the Arepo code. Hot, fast gas phases with low mass loadings are predicted to dominate the energy content of multiphase outflows. In order to treat the huge dynamic range of spatial scales involved in cosmological galaxy formation at feasible computational expense, cosmological volume simulations typically employ a Lagrangian code or else use adaptive mesh refinement with a quasi-Lagrangian refinement strategy. However, it is difficult to inject a high specific energy wind in a Lagrangian scheme without incurring artificial burstiness. Additionally, the low densities inherent to this type of flow result in poor spatial resolution. Arkenstone addresses these issues with a novel scheme for coupling energy into the ISM/CGM transition region which also provides the necessary level of refinement at the base of the wind. In the absence of our improvements, we show that poor spatial resolution near the sonic point of a hot, fast outflow leads to an underestimation of gas acceleration as the wind propagates. We explore the different mechanisms by which low and high specific energy winds can regulate the SFR of galaxies. In future work, we will demonstrate other aspects of the Arkenstone model.

astro-ph.GA↗