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We present jFoF, a fully GPU-native Friends-of-Friends (FoF) halo finder designed for both high-performance simulation analysis and differentiable modeling. Implemented in JAX, jFoF achieves …

We present a comprehensive data-driven spectroscopic analysis of 357,415 red giant stars using Gaia DR3 Radial Velocity Spectrometer (RVS) spectra (8460-8700 A; R≈11,500 …

Machine learning enables powerful cosmological inference but typically requires many high-fidelity simulations covering many cosmological models. Transfer learning offers a way to reduce the simulation cost by …

The "ringdown" radiation emitted by oscillating black holes has great scientific potential. By carefully predicting the frequencies and amplitudes of black hole quasinormal modes and comparing them with …

We present gas-phase radial metallicity profiles for 20 main-sequence galaxies at 4

In the nearby universe, quasars are well known to exhibit variability in their brightness over time, offering a powerful tool to probe the physics of accretion onto the …

The first stars formed out of pristine gas, causing them to be so massive that none are expected to have survived until today. If their direct descendants were …

The tidal field of a black hole can turn a star into a gas stream whose orbit can precess, especially if the a black hole is rapidly spinning …

Reinforcement Learning (RL) has long served as a model for goal-directed animal behavior in neuroscience. Modern deep RL has shown remarkable success across many domains, further strengthening …

Generative diffusion models have demonstrated an ability to produce novel images sampled from the learned underlying data distribution. These models are able to infer system characteristics for parameter …

Training loss and accuracy are the standard signals used to monitor generalization during deep neural network training. Two well-documented phenomena complicate this picture: in grokking, train loss …

Generative diffusion models can provide powerful prior probability models for inverse problems in imaging, but existing implementations suffer from two key limitations: (i) the prior density is represented …

Data augmentation is widely recognized for improving generalization in deep networks, yet its impact on the geometry of learned representations remains poorly understood. In this work, we characterize …

Internal neural representations can systematically deviate from externally measured sensory and behavioral variables, yet neuroscientists lack a principled statistical framework to quantify these mismatches. Here we introduce a …

Hot Neptunes in the sub-Jovian desert offer unique insights into planetary system evolution, retaining signatures of dynamical processes that shaped their present-day architectures. Many of these …

Star formation occurs within dense regions of giant molecular clouds (GMCs), however, exactly how gas collects and evolves to form individual stars and what role dense cores play …

One of JWST's most unexpected discoveries is the emergence of "Little Red Dots" (LRDs): compact sources at z≳3 with blue rest-frame UV continua, red optical …

Galaxies are often modelled as composites of separable components with distinct spectral signatures, implying that different wavelength ranges are only weakly correlated. They are not. We present a …

Galaxies evolve in tandem with their environments -- mergers and gas inflows drive galaxy growth while galactic outflows launched by supernovae may seed the galactic environment with gas, metals …

The circumgalactic medium (CGM) is known to contain multiphase gas in various stages of evolution and interaction with the galaxy. In order to characterize its detailed behavior on …

Young star-forming clumps (SFCs) emit strongly in the ultraviolet (UV), making UV imaging ideal for detecting them. The Ultraviolet Imaging Telescope (UVIT) onboard AstroSat, with 1.5arcsec …

Relativistic magnetic reconnection is a key mechanism for dissipating magnetic energy and accelerating particles in astrophysics. In the absence of radiative cooling, recent particle-in-cell (PIC) simulations …

Over the last two decades, the Sun has been observed to be depleted in refractory elements as a function of elemental condensation temperature (\(T_{\rm c}\)) relative to …

Satellite galaxies undergo ram pressure stripping, in which their gas is directly removed by a hydrodynamical interaction with the surrounding host halo gas. In clusters, ram pressure stripped …

We study the effects of varying different Active Galactic Nuclei (AGN) feedback parameters on the Lyman-\(\alpha\) (Ly\(\alpha\)) forest 1D transmitted flux power spectrum (P1D). We use …

In recent years, the existence of a gap in the mass spectrum of compact objects formed from stellar collapse, between the heaviest neutron stars and the lightest black …

The discovery of joint sources of high-energy neutrinos and gravitational waves has been a primary target for the LIGO, Virgo, KAGRA, and IceCube observatories. The joint detection …

We extend the time-dependent convection treatment in MESA by introducing eddy-viscous damping. This software change brings MESA-TDC into closer alignment with the radial stellar pulsation …

Cosmic filaments form the backbone of the cosmic web, yet their properties and evolution remain uncertain. Using the EAGLE hydrodynamical simulations, we investigate the dark matter density profiles …

The growing number of gravitational wave (GW) detections and the increasing sensitivity of GW detectors have enabled precision tests of General Relativity (GR) in the strong-field regime …

Protoplanetary discs contain a wide range of dust sizes that influence their thermal structure and planet formation processes such as planetesimal formation and pebble accretion. Dust evolution models …

Galaxy mergers have long been proposed as a mechanism for funneling gas toward galactic centres, potentially triggering accretion onto supermassive black holes (SMBHs) and igniting active galactic nuclei …

The recent discovery of a large number of massive black holes within the first two billion years after the Big Bang, as well as their peculiar properties, have …

Superluminous supernovae (SLSNe) are a rare class of transients with peak luminosities 10-100 times greater than those of standard core-collapse supernovae (SNe). The mechanisms powering their …

IceCube observations point to Active Galactic Nuclei (AGN) as promising contributors to the observed astrophysical neutrino flux. Close to the central black hole, protons can be accelerated through …

Modern large language models (LLMs) excel at tasks that require storing and retrieving knowledge, such as factual recall and question answering. Transformers are central to this capability because …

… learning mechanics should aspire to be its physics, mirroring the complementary relationship between biology and physics in the natural sciences. We also review and address common arguments …

Neural networks exhibit a remarkable degree of representational convergence across diverse architectures, training objectives, and even data modalities. This convergence is predictive of alignment with brain representation. A …

Measuring representational similarity between neural recordings and computational models is challenging due to constraints on the number of neurons that can be recorded simultaneously. In this work, we …

Connectome-constrained neural network models aim to link anatomical connectivity with functional computation by training networks whose architectures reflect biological circuits. Because such models are increasingly used to …

Randomized methods, such as the randomized SVD (singular value decomposition) and Nyström approximation, are an effective way to compute low-rank approximations of large matrices. Motivated by applications …

Representational similarity metrics typically force all units to be matched, making them susceptible to noise and outliers common in neural representations. We extend the soft-matching distance to …

This paper introduces quasi-Monte Carlo latent variable models (QLVMs): a class of deep generative models that are specialized for finding extremely low-dimensional and interpretable embeddings of …

The global dimensionality of a neural representation manifold provides rich insight into the computational process underlying both artificial and biological neural networks. However, all existing measures of global …

Black hole X-ray binaries (BHXRBs) have traditionally been discovered by X-ray surveys with cadences of hours to days. However, large optical time-domain surveys now provide …

A substantial fraction of metal-poor stars in the local Milky Way halo exhibit large overabundances of carbon. These stars, dubbed Carbon-Enhanced Metal-Poor (CEMP) stars, provide …

Zeeman observations provide the only direct probe of line-of-sight (LOS) magnetic fields in the interstellar medium. To evaluate their accuracy and limitations, we generate synthetic HI …

We update and expand the MESA Isochrones and Stellar Tracks (MIST) database to include variations in the alpha-capture elements, specifically [alpha/Fe]=-0.2, 0, +0.2 …