arXiv preprints from January 1, 2026 through July 28, 2026 — 20:14:08 EST
We investigate algorithms with predictions in computational geometry, specifically focusing on the basic problem of computing 2D Delaunay triangulations. Given a set $P$ of $n$ points in the plane and a triangulation $G$ that serves as a "prediction" of the Delaunay triangulation, we would like to use $G$ to compute the correct...
Retrieval-augmented generation with tool-calling agents (agentic RAG) has become increasingly powerful in understanding, processing, and responding to user queries. However, the scope of the grounding knowledge is limited and asking questions that exceed this scope may lead to issues like hallucination. While guardrail frameworks aim...
The accurate identification and control of spatiotemporal chaos in reaction-diffusion systems remains a grand challenge in chemical engineering, particularly when the underlying catalytic surface possesses complex, unknown topography. In the \textit{Defect Turbulence} regime, system dynamics are governed by topological phase...
We present a measurement of Baryon Acoustic Oscillations (BAO) in the cross-correlation of triply ionized carbon C IV absorption with the positions of quasars (QSO) and Emission Line Galaxies (ELG). We use quasars and ELGs from the second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI) survey. Our data sample...
It is commonly thought that observers in distinct branches of an Everettian multiverse cannot communicate without violating the linearity of quantum theory. Here we show a counterexample, demonstrating that inter-branch communication is in fact possible, entirely within standard quantum theory. We do this by considering a...
Recently, the exciting new Fermilab (FNAL) Muon g-2 measurement impressively confirmed the final Brookhaven (BNL) result from 2004, and with a result four times more precise, has launched a new serious attack on the Standard Model (SM). On the theoretical side, ab initio lattice QCD (LQCD) calculations of hadronic vacuum polarization...
Understanding the generalization behavior of deep neural networks remains a fundamental challenge in modern statistical learning theory. Among existing approaches, PAC-Bayesian norm-based bounds have demonstrated particular promise due to their data-dependent nature and their ability to capture algorithmic and geometric properties of...
Electrical activity in fungal mycelium has been reported in numerous species and experimental contexts, yet its spatial organisation and propagation remain insufficiently characterised. In this study we investigate the spatiotemporal structure of electrical potential dynamics in oyster mushroom (\textit{Pleurotus ostreatus}) mycelium...
We derive a generalized Pohozhaev's identity for radial solutions of $p$-Laplace equations, by using the approach in [5], thus extending the work of H. Brézis and L. Nirenberg [2], where this identity was implicitly used for the Laplace equation.
Reward modeling is essential for aligning large language models with human preferences, yet predominant architectures rely on a static pooling strategy to condense sequences into scalar scores. This paradigm, however, suffers from two key limitations: a static inductive bias that misaligns with task-dependent preference signals, and a...
We prove the so-called second case of the fractional Korn inequality for uniform domains. We obtain this result as an application of a novel fractional Korn-type inequality formulated in terms of truncated seminorms, which turns out to be valid for the broader class of John domains. We also obtain weighted estimates in which the...
In this paper, we present an automated pipeline for generating domain-specific synthetic datasets with diffusion models, addressing the distribution shift between pre-trained models and real-world deployment environments. Our three-stage framework first synthesizes target objects within domain-specific backgrounds through controlled...
Subject-independent EEG emotion recognition is challenged by pronounced inter-subject variability and the difficulty of learning robust representations from short, noisy recordings. To address this, we propose a fusion framework that integrates (i) local, channel-wise descriptors and (ii) global, trial-level descriptors, improving...
On the framework of relativistic force-free magnetohydrodynamic (MHD) turbulence, we explore the fundamental properties of strong and weak turbulent cascades using high-resolution numerical simulations in the presence of a uniform background magnetic field. We find that (1) power spectra and scale-dependent anisotropies both for the...
Let $A$ be an associative algebra with a superinvolution $*$ over a field of characteristic zero, and let $c_n^*(A)$, $n = 1, 2, \ldots$, denote its sequence of $*$-codimensions. It is well known that this sequence is either polynomially bounded or grows exponentially. In the polynomial case, a central problem in PI-theory is the...
Firmware integrity is a foundational requirement for securing Cyber-Physical Systems (CPS), where malicious or compromised firmware can result in persistent backdoors, unauthorized control, or catastrophic system failures. Traditional verification mechanisms such as secure boot, digital signatures, and centralized hash databases are...
The exact solution of a two-dimensional (2D) Ising model with the next nearest interactions at zero magnetic field is derived. At first, the transfer matrices are analyzed in three representations, i.e., Clifford algebraic representation, transfer tensor representation and schematic representation, to inspect nontrivial topological...
The Light Dark Matter eXperiment (LDMX) is a proposed fixed-target missing momentum search for sub-GeV thermal relic dark matter. LDMX aims to probe thermal dark matter targets with 1016 electrons on target. Such an approach requires a high-repetition rate, low-current beam, with an average of one electron on target per event. These...
Public large language models (LLMs) are typically safety-aligned during pretraining, yet task-specific fine-tuning required for deployment often erodes this alignment and introduces safety risks. Existing defenses either embed safety recovery into fine-tuning or rely on fine-tuning-derived priors for post-hoc correction, leaving...
Discrete charge fluctuations, routinely observed in semiconductor quantum dot devices, may contribute significantly to device drift and errors resulting from qubit miscalibration. Understanding the nature and origins of these discrete charge fluctuations may provide insights into material improvements or means of mitigating charge...
Star clusters are well known for their dynamical interactions, an outcome of their high stellar densities; in this paper we use multiwavelength observations to search for the unique outcomes of these interactions in three nearby Galactic open clusters: IC 2602 (30 Myr), NGC 2632 (750 Myr) and M67 (4 Gyr). We compared X-ray...
Traditional 2D hydraulic models face significant computational challenges that limit their applications that are time-sensitive or require many model evaluations. This study presents a physics-informed Deep Operator Network (DeepONet) framework for computational hydraulics modeling that learns the solution operator of the 2D shallow...
Feedback-based quantum algorithms (FQAs) operate by iteratively growing a quantum circuit to optimize a given task. At each step, feedback from qubit measurements is used to inform the next quantum circuit update. In practice, the sampling cost associated with these measurements can be significant. Here, we ask whether FQA parameter...
Human Activity Recognition (HAR) in smart homes is critical for health monitoring and assistive living. While vision-based systems are common, they face privacy concerns and environmental limitations (e.g., occlusion). In this work, we present MobiDiary, a framework that generates natural language descriptions of daily activities...
Extended reality serious games for mental health are a promising research avenue to address the accessibility gap in mental health treatment by bringing therapy to patients in their homes, offering highly adaptable and immersive yet safe therapy opportunities, and increasing motivation and engagement with therapeutic exercises....