arXiv preprints from January 1, 2026 through September 26, 2026 — 10:17:09 EST
Many important problems in science and engineering involve inferring a signal from noisy and/or incomplete observations, where the observation process is known. Historically, this problem has been tackled using hand-crafted regularization (e.g., sparsity, total-variation) to obtain meaningful estimates. Recent data-driven methods...
$\mathsf{QAC}^0$ is the class of constant-depth polynomial-size quantum circuits constructed from arbitrary single-qubit gates and generalized Toffoli gates. It is arguably the smallest natural class of constant-depth quantum computation which has not been shown useful for computing any non-trivial Boolean function. Despite this, many...
Training data is a critical and often proprietary asset in Large Language Model (LLM) development, motivating the use of data watermarking to embed model-transferable signals for usage verification. We identify low coverage as a vital yet largely overlooked requirement for practicality, as individual data owners typically contribute...
We provide new insights into an open problem recently posed by Yuan-Sun [ISIT 2025], concerning the minimum individual key rate required in the vector linear secure aggregation problem. Consider a distributed system with $K$ users, where each user $k\in [K]$ holds a data stream $W_k$ and an individual key $Z_k$. A server aims to...
Line intensity mapping using atomic hydrogen (HI) has the potential to efficiently map large volumes of the universe if the signal can be successfully separated from overwhelmingly bright radio foreground emission. This motivates cross-correlations, to ascertain the cosmological nature of measured HI fluctuations, and to study their...
Within the last fifteen years, a program of establishing relationships between algorithmic randomness and almost-everywhere theorems in analysis and ergodic theory has developed. In harmonic analysis, Franklin, McNicholl, and Rute characterized Schnorr randomness using an effective version of Carleson's Theorem. We show here that, for...
The exact location of the solar dynamo remains uncertain--whether it operates primarily in the near-surface shear layer, throughout the entire convection zone, or near the tachocline, a region of sharp transition in the solar rotation, located at the base of the convection zone, approximately 200,000 km beneath the surface. Various...
Foundation vision, audio, and language models enable zero-shot performance on downstream tasks via their latent representations. Recently, unsupervised learning of data group structure with deep learning methods has gained popularity. TURTLE, a state of the art deep clustering algorithm, uncovers data labeling without supervision by...
Memory-Augmented Generation (MAG) extends Large Language Models with external memory to support long-context reasoning, but existing approaches largely rely on semantic similarity over monolithic memory stores, entangling temporal, causal, and entity information. This design limits interpretability and alignment between query intent...
Scalable hydrogen production using proton exchange membrane water electrolyzers depends on overcoming efficiency losses arising from coupled multiphase, multicomponent transport and interfacial phenomena across the membrane electrode assembly. Here, we demonstrate a multiscale computational framework that combines pore network...
This paper develops a systematic and geometric theory of optimal quantization on the unit sphere $\mathbb S^2$, focusing on finite uniform probability distributions supported on the spherical surface - rather than on lower-dimensional geodesic subsets such as circles or arcs. We first establish the existence of optimal sets of...
Quantum computing has long promised transformative advances in data analysis, yet practical quantum machine learning has remained elusive due to fundamental obstacles such as a steep quantum cost for the loading of classical data and poor trainability of many quantum machine learning algorithms designed for near-term quantum hardware....
This paper studies the transferability of altitude-dependent spectrum activity models and measurements across years. We introduce a physics-informed, mean-only stochastic-geometry model of aggregate interference to altitude-binned received power, yielding three interpretable parameters for a given band and campaign: 1) line-of-sight...
Recent text-to-video diffusion models can generate compelling video sequences, yet they remain silent -- missing the semantic, emotional, and atmospheric cues that audio provides. We introduce LTX-2, an open-source foundational model capable of generating high-quality, temporally synchronized audiovisual content in a unified manner....
Background: Reporting and Data Systems (RADS) standardize radiology risk communication but automated RADS assignment from narrative reports is challenging because of guideline complexity, output-format constraints, and limited benchmarking across RADS frameworks and model sizes. Purpose: To create RXL-RADSet, a radiologist-verified...
In the Standard Model, the Higgs potential develops an instability at high field values when the quartic self-coupling runs negative. Large quantum fluctuations during cosmic inflation could drive the Higgs field beyond the potential barrier, creating regions that would be catastrophic for our observable universe. We point out that...
We show that excitons coupled to cavity photons and phonons admit a generalized Bloch theorem when formulated for the conserved total crystal momentum. In minimal-coupling and Fröhlich representations, the interchange of momenta between fermions and bosons breaks crystalline excitons' translational symmetry. In our symmetry-adapted...
Correcting misinformation in public online spaces often exposes users to hostility and ad hominem attacks, discouraging participation in corrective discourse. This study presents empirical evidence that invoking Grok, the native large language model on X, rather than directly confronting other users, is associated with different...
Approximate Nearest Neighbor Search (ANNS) is a fundamental operation in vector databases, enabling efficient similarity search in high-dimensional spaces. While dense ANNS has been optimized using specialized hardware accelerators, sparse ANNS remains limited by CPU-based implementations, hindering scalability. This limitation is...
This paper develops our work on the consequences of the Regge calculus, where some edge length scale arises as an optimal starting point of the perturbative expansion with taking into account a bell-shaped form of the measure obtained using functional integration over connection. A "hypercubic" structure is considered (some...
Geo-localization aims to infer the geographic origin of a given signal. In computer vision, geo-localization has served as a demanding benchmark for compositional reasoning and is relevant to public safety. In contrast, progress on audio geo-localization has been constrained by the lack of high-quality audio-location pairs. To address...
We use real algebraic geometry to construct an affine $Λ$-building $B$ associated to the $\mathbb{F}$-points of a semisimple algebraic group, where $\mathbb{F}$ is a valued real closed field. We characterize the spherical building at infinity and the local building at a base point. We compute stabilizers of various subsets of $B$ and...
Although automated trucks have the potential to improve freight efficiency, reduce costs, and address driver shortages, organizing two or more trucks in a convoy has raised considerable concerns for pedestrian safety. This study conducted a controlled experiment to examine the influence of behavioral tendency, trust, and risk...
The coil in transcranial magnetic stimulation (TMS) determines the spatial shape of the electromagnetic field in the head, which structures are concurrently activated, and how focal stimulation is. Most of the readily available coils have been designed intuitively instead of systematic mathematical-physical optimization as there were...
Appropriate communication is crucial for efficient and safe interactions between pedestrians and autonomous vehicles (AVs). External human-machine interfaces (eHMIs) on AVs, which can be categorized as allocentric or egocentric, are considered a promising solution. While the effectiveness of eHMIs has been extensively studied, in...