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How developmental timings are regulated is a fundamental open question. Two widely considered mechanisms are the clock, in which an internal timer determines when each stage occurs, and …

How developmental timings are regulated is a fundamental open question. Two widely considered mechanisms are the clock, in which an internal timer determines when each stage occurs, and …

The growing scale of deep learning models has rendered exhaustive hyperparameter (HP) optimization prohibitively expensive. A promising solution is the use of scale-aware HPs, which can enable …

We model sensory streams as observations from high-dimensional stochastic dynamical systems and conceptualize sensory neurons as self-supervised learners of compact representations of such dynamics. From prior …

Unsupervised source separation involves unraveling an unknown set of source signals recorded through a mixing operator, with limited prior knowledge about the sources, and only access to a …

Stochastic gradient descent (SGD) is central to deep learning, yet the dynamical origin of its preference for flatter, more generalizable solutions remains unclear. Here, by analyzing SGD learning …

Learning probability models from data is at the heart of many machine learning endeavors, but is notoriously difficult due to the curse of dimensionality. We introduce a new …

Increasing quantities of genomic data present an opportunity for uncovering functional and mechanistic insights. However, given the complexity and scale of the data, sophisticated analytical frameworks and integrative …

Efficient Monte Carlo (MC) sampling of many-body systems with long-range electrostatics is often limited by the cost of per-move energy-difference evaluation under periodic boundary …

Network remodeling, or adaptation, in the presence of periodically driven forcings has hereto remained largely unexplored, despite the fact that a broad class of biological transport networks, e …

Flagellar motors enable bacteria to navigate their environments by switching rotation direction in response to external cues with high sensitivity. Previous work indicated that the ultrasensitivity of the …

Simulating the dynamics of charged particles in quasi-two-dimensional (quasi-2D) nanoconfined systems presents a significant computational challenge due to the long-range nature of electrostatic interactions …

The Poisson Generalized Linear Model (GLM) is a foundational tool for analyzing neural spike train data. However, standard implementations rely on discretizing spike times into binned count data …

Passively collected wearable data offers scalable sleep phenotyping in autism spectrum disorder. We address domain shift and compliance challenges to establish reliable machine-learning biomarkers of sleep disruption …

Acute kidney injury (AKI) and chronic kidney disease (CKD) are two interconnected clinical conditions, both defined by degree of functional impairment, but with heterogeneous clinical trajectories. Using new …

Accurate and parsimonious quantification of baryonic feedback on matter distribution is of crucial importance for understanding both cosmology and galaxy formation from observational data. This is, however, challenging …

We present an extensive photometric and spectroscopic ultraviolet-optical-infrared campaign on the luminous fast blue optical transient (LFBOT) AT 2024wpp over the first ~100 d. AT 2024wpp …

White dwarfs which explode by the double-detonation mechanism may have a binary white dwarf donor which is subsequently ignited by its collision with the ejecta. This results …

Little red dots (LRDs), high-redshift, compact, red objects with V-shaped spectra, are one of the most exciting and perplexing discoveries made by the James Webb Space …

The next generation of weak gravitational lensing surveys has the potential to place stringent constraints on cosmological parameters. However, their analysis is limited by systematics such as the …

The complex astrophysical processes leading to the formation of binary black holes and their eventual merger are imprinted on the spins of the individual black holes. We revisit …

Coagulation of dust particles in protoplanetary disks is the first step on the journey to the formation of planets. The surface free energy (SFE) of the dust particles …

We present the tightest cosmic microwave background (CMB) lensing constraints to date on the growth of structure by combining CMB lensing measurements from the Atacama Cosmology Telescope (ACT …

The binary black hole signal GW250114, the loudest gravitational wave detected to date, offers a unique opportunity to test Einstein's general relativity (GR) in the high-velocity …

The Milky Way is known to contain a stellar bar, as are a significant fraction of disc galaxies across the universe. Our understanding of bar evolution, both theoretically …

Active galactic nuclei (AGNs) drive powerful, multiphase outflows that are thought to play a key role in galaxy evolution. The hot, shocked phase of these outflows ( …

The dark siren method exploits the complementarity between gravitational-wave binary coalescence signals and galaxy catalogs originating from the same regions of space. However, all galaxy catalogs are …

The ALMA survey to Resolve exoKuiper belt Substructures (ARKS) was recently completed to cover the lack of high-resolution observations of debris discs and to investigate the prevalence …

We investigate the impacts of the evolution of dust mass and grain size distribution within a Milky Way-like (MW-like) galaxy simulation on global attenuation curves, focusing …

The brown dwarf desert describes a range of orbital periods (

We present an NPT extension of Ewald summation with prolates (ESP), a spectrally accurate and scalable particle-mesh method for molecular dynamics simulations of periodic, charged systems. Building …

We introduce a size-consistent and orbital-invariant formalism for constructing correlation functionals based on the adiabatic connection for density functional theory (DFT). By constructing correlation energy matrices …

Machine learning interatomic potentials (MLIPs) have become powerful tools to extend molecular simulations beyond the limits of quantum methods, offering near-quantum accuracy at much lower computational cost …

The growing availability of biological data resources has transformed research, yet their effective use remains challenging: selecting appropriate sources requires domain knowledge, data are fragmented across databases, and …

Women are consistently underrepresented in astrophysics yet are simultaneously subject to disproportionate attrition at every career stage. This disparity between demonstrated efficacy in job performance and ultimate career …

Women are consistently underrepresented in astrophysics yet are simultaneously subject to disproportionate attrition at every career stage. This disparity between demonstrated efficacy in job performance and ultimate career …

Women are consistently underrepresented in astrophysics yet are simultaneously subject to disproportionate attrition at every career stage. This disparity between demonstrated efficacy in job performance and ultimate career …

Quantum geometry has been shown to make an important contribution to the superfluid stiffness of flatband superconductors including moiré materials. In this Letter we use mean-field theory …

We formulate a quantum embedding algorithm in real-space for the simultaneous theoretical treatment of nonlocal electronic correlations and disorder, the coherent cellular dynamical mean-field theory (C …

Cryogenic electron microscopy (cryo-EM) has emerged as a powerful method for resolving the structure of biological macromolecules. Recently, several computational methods have been developed to study the …

Cryogenic electron microscopy (cryo-EM) has emerged as a powerful method for resolving the structure of biological macromolecules. Recently, several computational methods have been developed to study the …

We introduce a new suite of 1,024 cosmological and hydrodynamical zoom-in simulations of Milky Way-mass halos, run with Cold Dark Matter, as part of the …

Many tasks in single-particle cryo-electron microscopy (cryo-EM), such as 2D/3D classification and homo/heterogeneous reconstruction, require optimizing model parameters to minimize the discrepancy between …

Many tasks in single-particle cryo-electron microscopy (cryo-EM), such as 2D/3D classification and homo/heterogeneous reconstruction, require optimizing model parameters to minimize the discrepancy between …

Simulations of quantum matter rely mainly on Kohn-Sham density functional theory (DFT), which often fails for strongly correlated systems. Quantum embedding (QE) theories address this limitation by …

More than a century after discovery, the theory of conventional superconductivity remains incomplete. While the importance of electron-phonon coupling is understood, a controlled first-principles treatment of …