arXiv subjects

Brent Tan

Publications and source records attributed to Brent Tan.

9 recordsLinked to original sources

arXiv2026

Clumps in a Cocoon: Geometry and Mixing Set the Universal X-ray to H$\alpha$ Surface Brightness Ratio

Recent observations reveal a universal X-ray to H$\alpha$ surface-brightness ratio, ${\rm SB}_{\rm X}/{\rm SB}_{\rm H\alpha}\sim 3$, in galactic winds, ram-pressure stripped tails, and cluster filaments. This is surprising because H$\alpha$ traces cold ($\sim 10^4$ K) gas while X-rays trace much hotter ($\sim 10^{6}$--$10^{7}$ K) gas. Plane-parallel mixing-layer models do not recover this ratio, and can be off by orders of magnitude. Motivated by recent work showing that geometry controls the temperature PDF of multiphase gas (Chen & Oh 2026), we run 3D wind-tunnel simulations in the high density contrast ($\chi\sim 10^3$) regime. In this limit, the cold phase shatters into many small H$\alpha$-emitting clumps, while X-ray-emitting gas forms a volume-filling cocoon around them. After smoothing on the tail-width scale, the measured surface-brightness ratio converges to the observed value, which can be understood theoretically. The H$\alpha$ luminosity fraction is set by atomic physics, whereas the X-ray luminosity fraction is set by the residence time of gas in the X-ray-emitting band. This residence time is much shorter than the cooling time at X-ray temperatures, but scales roughly inversely with pressure, suggesting that it is tied to the cooling time at a lower-temperature outlet of the mixing cascade. This framework naturally explains why the observed ratio is order unity, and robust to changes in gas pressure.

astro-ph.GA↗

arXiv2025

Tales of Tension: Magnetized Infalling Clouds and Cold Streams in the CGM

The observed star formation and wind outflow rates in galaxies suggest cold gas must be continually replenished via infalling clouds or streams. Previous studies have highlighted the importance of cooling-induced condensation on such gas, which enables survival, mass growth, and a drag force which typically exceeds hydrodynamic drag. However, the combined effects of magnetic fields, cooling, and infall remains unexplored. We conduct 3D magnetohydrodynamic (MHD) simulations of radiatively cooling infalling clouds and streams in uniform and stratified backgrounds. For infalling clouds, magnetic fields aligned with gravity do not impact cloud growth or dynamics significantly, although we see enhanced survival for stronger fields. By contrast, even weak transverse magnetic fields significantly slow cloud infall via magnetic drag, due to the development of strong draped fields which develop at peak infall velocity, before the cloud decelerates. Besides enhancing survival, long, slow infall increases total cloud mass growth compared to the hydrodynamic case, even if reduced turbulent mixing lowers the rate of mass growth. Streams often result in qualitatively different behavior. Mass growth and hence accretion drag are generally much lower in hydrodynamic streams. Unlike in clouds, aligned magnetic fields suppress mixing and thus both mass growth or loss. Transverse fields do apply magnetic drag and allow streams to grow, when the streams have a well-defined 'head' pushing through the surrounding medium. Overall, regardless of the efficacy of drag forces, streams are surprisingly robust in realistic potentials, as the destruction time when falling supersonically exceeds the infall time. We develop analytic models which reproduce cloud/stream trajectories.

astro-ph.GA↗

arXiv2024

Neural Infalling Cloud Equations (NICE): Increasing the Efficacy of Subgrid Models and Scientific Equation Discovery using Neural ODEs and Symbolic Regression

Galactic systems are inherently multiphase, and understanding the roles and interactions of the various phases is key towards a more complete picture of galaxy formation and evolution. For instance, these interactions play a pivotal role in the cycling of baryons which fuels star formation. The transport and dynamics of cold clouds in their surrounding hot environment are governed by complex small scale processes (such as the interplay of turbulence and radiative cooling) that determine how the phases exchange mass, momentum and energy. Large scale models thus require subgrid prescriptions in the form of models validated on small scale simulations, which often take the form of coupled differential equations. In this work, we explore using neural ordinary differential equations which embed neural networks as terms in the model to capture an uncertain physical process. We then apply Symbolic Regression to potentially discover new insights into the physics of cloud-environment interactions. We test this on both generated mock data and actual simulation data. We also extend the neural ODE to include a secondary neural term. We show that neural ODEs in tandem with Symbolic Regression can be used to enhance the accuracy and efficiency of subgrid models, and/or discover the underlying equations to improve generality and scientific understanding. We highlight the potential of this scientific machine learning approach as a natural extension to the traditional modelling paradigm, both for the development of semi-analytic models and for physically interpretable equation discovery in complex non-linear systems.

astro-ph.GA↗

arXiv2023

LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype

The accurate classification of lymphoma subtypes using hematoxylin and eosin (H&E)-stained tissue is complicated by the wide range of morphological features these cancers can exhibit. We present LymphoML - an interpretable machine learning method that identifies morphologic features that correlate with lymphoma subtypes. Our method applies steps to process H&E-stained tissue microarray cores, segment nuclei and cells, compute features encompassing morphology, texture, and architecture, and train gradient-boosted models to make diagnostic predictions. LymphoML's interpretable models, developed on a limited volume of H&E-stained tissue, achieve non-inferior diagnostic accuracy to pathologists using whole-slide images and outperform black box deep-learning on a dataset of 670 cases from Guatemala spanning 8 lymphoma subtypes. Using SHapley Additive exPlanation (SHAP) analysis, we assess the impact of each feature on model prediction and find that nuclear shape features are most discriminative for DLBCL (F1-score: 78.7%) and classical Hodgkin lymphoma (F1-score: 74.5%). Finally, we provide the first demonstration that a model combining features from H&E-stained tissue with features from a standardized panel of 6 immunostains results in a similar diagnostic accuracy (85.3%) to a 46-stain panel (86.1%).

cs.LG↗

arXiv2023

Cloud Atlas: Navigating the Multiphase Landscape of Tempestuous Galactic Winds

Galaxies comprise intricate networks of interdependent processes which together govern their evolution. Central among these are the multiplicity of feedback channels, which remain incompletely understood. One outstanding problem is the understanding and modeling of the multiphase nature of galactic winds, which play a crucial role in galaxy formation and evolution. We present the results of three dimensional magnetohydrodynamical tall box interstellar medium patch simulations with clustered supernova driven outflows. Fragmentation of the interstellar medium during superbubble breakout seeds the resulting hot outflow with a population of cool clouds. We focus on analyzing and modeling the origin and properties of these clouds. Their presence induces large scale turbulence, which in turn leads to complex cloud morphologies. Cloud sizes are well described by a power law distribution and mass growth rates can be modelled using turbulent radiative mixing layer theory. Turbulence provides significant pressure support in the clouds, while magnetic fields only play a minor role. We conclude that many of the physical insights and analytic scalings derived from idealized small scale simulations translate well to larger scale, more realistic turbulent magnetized winds, thus paving a path towards their necessary yet challenging inclusion in global-scale galaxy models.

astro-ph.GA↗

arXiv2023

Cloudy with A Chance of Rain: Accretion Braking of Cold Clouds

Understanding the survival, growth and dynamics of cold gas is fundamental to galaxy formation. While there has been a plethora of work on `wind tunnel' simulations that study such cold gas in winds, the infall of this gas under gravity is at least equally important, and fundamentally different since cold gas can never entrain. Instead, velocity shear increases and remains unrelenting. If these clouds are growing, they can experience a drag force due to the accretion of low momentum gas, which dominates over ram pressure drag. This leads to sub-virial terminal velocities, in line with observations. We develop simple analytic theory and predictions based on turbulent radiative mixing layers. We test these scalings in 3D hydrodynamic simulations, both for an artificial constant background, as well as a more realistic stratified background. We find that the survival criterion for infalling gas is more stringent than in a wind, requiring that clouds grow faster than they are destroyed ($t_{\rm grow} < 4\,t_{\rm cc} $). This can be translated to a critical pressure, which for Milky Way like conditions is $P \sim 3000 {\rm k}_B {\rm K}\,{\rm cm}^{-3}$ . Cold gas which forms via linear thermal instability ($t_{\rm cool}/t_{\rm ff} < 1$) in planar geometry meets the survival threshold. In stratified environments, larger clouds need only survive infall until cooling becomes effective. We discuss applications to high velocity clouds and filaments in galaxy clusters.

astro-ph.GA↗

arXiv2021

A Model for Line Absorption and Emission from Turbulent Mixing Layers

Turbulent mixing layers (TMLs) are ubiquitous in multiphase gas. They can potentially explain observations of high ions such as O VI, which have significant observed column densities despite short cooling times. Previously, we showed that global mass, momentum and energy transfer between phases mediated by TMLs is not sensitive to details of thermal conduction or numerical resolution. By contrast, we show here that observables such as temperature distributions, column densities and line ratios are sensitive to such considerations. We explain the reason for this difference. We develop a prescription for applying a simple 1D conductive-cooling front model which quantitatively reproduces 3D hydrodynamic simulation results for column densities and line ratios, even when the TML has a complex fractal structure. This enables sub-grid absorption and emission line predictions in large scale simulations. The predicted line ratios are in good agreement with observations, while observed column densities require numerous mixing layers to be pierced along a line of sight.

astro-ph.GA↗

arXiv2021

Radiative Mixing Layers: Insights from Turbulent Combustion

Radiative mixing layers arise wherever multiphase gas, shear, and radiative cooling are present. Simulations show that in steady state, thermal advection from the hot phase balances radiative cooling. However, many features are puzzling. For instance, hot gas entrainment appears to be numerically converged despite the scale-free, fractal structure of such fronts being unresolved. Additionally, the hot gas heat flux has a characteristic velocity $v_{\rm in} \approx c_{\rm s,cold} (t_{\rm cool}/t_{\rm sc,cold})^{-1/4}$ whose strength and scaling are not intuitive. We revisit these issues in 1D and 3D hydrodynamic simulations. We find that over-cooling only happens if numerical diffusion dominates thermal transport; convergence is still possible even when the Field length is unresolved. A deeper physical understanding of radiative fronts can be obtained by exploiting parallels between mixing layers and turbulent combustion, which has well-developed theory and abundant experimental data. A key parameter is the Damköhler number ${\rm Da} = τ_{\rm turb}/t_{\rm cool}$, the ratio of the outer eddy turnover time to the cooling time. Once ${\rm Da} > 1$, the front fragments into a multiphase medium. Just as for scalar mixing, the eddy turnover time sets the mixing rate, independent of small scale diffusion. For this reason, thermal conduction often has limited impact. We show that $v_{\rm in}$ and the effective emissivity can be understood in detail by adapting combustion theory scalings. Mean density and temperature profiles can also be reproduced remarkably well by mixing length theory. These results have implications for the structure and survival of cold gas in many settings, and resolution requirements for large scale galaxy simulations.

astro-ph.GA↗

arXiv2021

The Impact of Light Polarization Effects on Weak Lensing Systematics

A fraction of the light observed from edge-on disk galaxies is polarized due to two physical effects: selective extinction by dust grains aligned with the magnetic field, and scattering of the anisotropic starlight field. Since the reflection and transmission coefficients of the reflecting and refracting surfaces in an optical system depend on the polarization of incoming rays, this optical polarization produces both (a) a selection bias in favor of galaxies with specific orientations and (b) a polarization-dependent PSF. In this work we build toy models to obtain for the first time an estimate for the impact of polarization on PSF shapes and the impact of the selection bias due to the polarization effect on the measurement of the ellipticity used in shear measurements. In particular, we are interested in determining if this effect will be significant for WFIRST. We show that the systematic uncertainties in the ellipticity components are $8\times 10^{-5}$ and $1.1 \times 10^{-4}$ due to the selection bias and PSF errors respectively. Compared to the overall requirements on knowledge of the WFIRST PSF ellipticity ($4.7\times 10^{-4}$ per component), both of these systematic uncertainties are sufficiently close to the WFIRST tolerance level that more detailed studies of the polarization effects or more stringent requirements on polarization-sensitive instrumentation for WFIRST are required.

astro-ph.IM↗