arXiv preprints from January 1, 2026 through October 1, 2026 — 00:34:21 EST
This perspective explores the evolution of materials informatics, from its foundational roots in physics and information theory to its maturation through artificial intelligence (AI). We trace the field's trajectory from early milestones to the transformative impact of the Materials Genome Initiative and the recent advent of large...
We perform high-resolution, grid-based hydrodynamics simulations of gaseous rings viscously spreading into disks around equal-mass, circular binaries. We find that all systems suppress accretion onto the binary when the gas is relatively cold. Circumbinary rings (CBRs) display weak variability above the binary orbital frequency $Ω_b$...
We compute the thermodynamic phase diagram of seventeen elemental metals with hexagonal close-packed (hcp), face-centered cubic (fcc), and body-centered cubic (bcc) crystal structures using finite-temperature density functional theory. Helmholtz free-energy differences between competing hcp, fcc, and bcc phases are evaluated as...
This article develops a continuous-time asymptotic framework for analyzing adaptive experiments -- settings in which data collection and treatment assignment evolve dynamically in response to incoming information. A key challenge in analyzing fully adaptive experiments, where the assignment policy is updated after each observation, is...
This paper examines the impact of reducing Ethereum slot time on decentralized exchange activity, with a focus on CEX-DEX arbitrage behavior. We develop a trading model where the agent's DEX transaction is not guaranteed to land, and the agent explicitly accounts for this execution risk when deciding whether to pursue arbitrage...
Off-policy actor-critic methods in reinforcement learning train a critic with temporal-difference updates and use it as a learning signal for the policy (actor). This design typically achieves higher sample efficiency than purely on-policy methods. However, critic networks tend to overestimate value estimates systematically. This is...
Identifying relevant text spans is important for several downstream tasks in NLP, as it contributes to model explainability. While most span identification approaches rely on relatively smaller pre-trained language models like BERT, a few recent approaches have leveraged the latest generation of Large Language Models (LLMs) for the...
Nielsen's geometric approach to quantum circuit complexity provides a Riemannian framework for quantifying the cost of implementing unitary (closed--system) dynamics. For open dynamics, however, the reduced evolution is described by quantum channels and admits many inequivalent Stinespring realizations, so any meaningful complexity...
Curved reconfigurable intelligent surfaces (RISs) represent a promising frontier for next-generation wireless communication, enabling adaptive wavefront control on nonplanar platforms such as unmanned aerial vehicles and urban infrastructure. This work presents a systematic investigation of cylindrical RISs, progressing from idealized...
For a Tychonoff space $X$, $B_1(X)$ denotes the space of all Baire-one functions on $X$ endowed with the pointwise topology. We prove that the following assertions are equivalent: (1) $B_1(X)$ is a (semi-)Montel space, (2) $B_1(X)$ is a (semi-)reflexive space, (3) $B_1(X)$ is a (quasi-)complete space, (4) $B_1(X)=\mathbb{R}^X$, (5)...
Urban transportation networks face significant challenges due to traffic congestion, leading to adverse environmental and socioeconomic impacts. Vehicular admission control (VAC) strategies have emerged as a promising solution to alleviate congestion. By leveraging information and communication technologies, VAC strategies regulate...
Complex organic molecules (COMs), the building blocks of life, have been extensively detected under various physical conditions, from quiescent clouds to star-forming regions. They therefore serve as excellent tracers for the local physical and chemical properties of these environments. Proper models that are capable of grasping the...
Liquid chromatography mass spectrometry (LC-MS)-based metabolomics and exposomics aim to measure detectable small molecules in biological samples. The results facilitate hypothesis-generating discovery of metabolic changes and disease mechanisms and provide information about environmental exposures and their effects on human health....
Liquids like water, wine and medicine are everywhere. However, limited attention has been given to the task of segmenting liquids, hindering the ability of robots to safely avoid and interact with them. The segmentation of liquids is difficult because liquids come in diverse appearances and shapes; moreover, they can be both...
Handwritten STEM exams capture open-ended reasoning and diagrams, but manual grading is slow and difficult to scale. We present an end-to-end workflow for grading scanned handwritten engineering quizzes with multimodal large language models (LLMs) that preserves the standard exam process (A4 paper, unconstrained student handwriting)....
This paper presents a comprehensive overview of several multidimensional reduction methods focusing on Multidimensional Principal Component Analysis (MPCA), Multilinear Orthogonal Neighborhood Preserving Projection (MONPP), Multidimensional Locally Linear Embedding (MLLE), and Multidimensional Laplacian Eigenmaps (MLE). These...
We propose a reinforcement learning (RL) framework for adaptive precision tuning for linear solvers, which can be extended to general algorithms. The framework is formulated as a contextual bandit problem and solved using incremental action-value estimation with a discretized state space to select optimal precision configurations for...
This article proves that there are no self-intersections in the dragon curve when the unfolding angle is greater than 98.195°. This is shown by constructing a hull for the dragon curve that is mapped onto itself by the generating mappings for the dragon curve. The treatment is purely geometric. The proof is supplemented by a...
We present a high-order implicit large eddy simulation (ILES) approach for simulating flows at the nearly incompressible regime. Our methodology based on utilization of a nodal discontinuous Galerkin (DG) discretization of the Boltzmann equations. The compactness and low-dissipative nature of the discontinuous Galerkin method are...
Deep neural networks show great potential for automating various visual quality inspection tasks in manufacturing. However, their applicability is limited in more volatile scenarios, such as remanufacturing, where the inspected products and defect patterns often change. In such settings, deployed models require frequent adaptation to...
We present an AI-driven approach to discover compounds with optimal properties for CO2 capture from flue gas-refinery emissions' primary source. Focusing on ionic liquids (ILs) as alternatives to traditional amine-based solvents, we successfully identify new IL candidates with high working capacity, manageable viscosity, favorable...
We investigate the solidification of a water rivulet flowing over a cold inclined substrate and the resulting formation of three-dimensional ice structures. Using a controlled hydraulic and thermal setup, combined with spatiotemporal phase-shifting profilometry and infrared thermography, we characterize both the transient evolution...
The interplay among electronic nematicity, charge density wave, and superconductivity in correlated electronic systems has induced extensive research interest. Here, we discover the existence of nematic fluctuations in TiSe2 single crystal and investigate its evolution with Cu intercalation. It is observed that the elastoresistivity...
High-energy colliders, such as the Large Hadron Collider (LHC) at CERN, are genuine quantum machines, so, in line with Richard Feynman's original motivation for Quantum Computing, the scattering processes that take place there are natural candidates to be simulated on a quantum system. Potential applications range from quantum machine...
This paper focuses on symbolic integration of differential forms, with a particular emphasis on historical and modern developments, from Abel's addition theorems for Abelian integrals to Zeilberger's creative telescoping for parameterized integrals. It explores closed rational $p$-forms and provides algorithmic approaches for their...