arXiv preprints from January 1, 2026 through September 23, 2026 — 11:58:10 EST
We prove strong well-posedness results for the stochastic 2D Euler equations in vorticity form and generalized SQG equations, with $L^p$ initial data and driven by a spatially rough, incompressible transport noise of Kraichnan type. Previous works addressed this problem with noise of spatial regularity $α\in (0,1/2)$, in a setting...
Deformable multi-contrast image registration is a challenging yet crucial task due to the complex, non-linear intensity relationships across different imaging contrasts. Conventional registration methods typically rely on iterative optimization of the deformation field, which is time-consuming. Although recent learning-based...
Embedded vision systems need efficient and robust image processing algorithms to perform real-time, with resource-constrained hardware. This research investigates image processing algorithms, specifically edge detection, corner detection, and blob detection, that are implemented on embedded processors, including DSPs and FPGAs. To...
Despite progress in the observations of stellar magnetic fields, their physical mechanisms remain poorly understood. During the pre-main sequence (PMS) phase, the inner layers of stars contract and a radiative core gradually develops. In contrast, the convective envelope is gradually braked through magnetic interactions with the...
This study focuses on developing a metal-dielectric sensor structure with optimized unit cell geometry for determination of protein Immunoglobulin G (IgG) concentration in aqueous solutions. The research combines both experimental and theoretical investigations, utilizing the differential microwave dielectrometry method and numerical...
In this work, we present a conditional denoising-diffusion surrogate for electromagnetic calorimeter showers that is trained to generate high-fidelity energy-deposition maps conditioned on key detector and beam parameters. The model employs efficient inference using Denoising Diffusion Implicit Model sampling and is pre-trained on...
Millimeter-wave (mmWave) links are increasingly utilized in wireless x-haul transport to meet growing service demands. However, the inherent susceptibility of mmWave links to weather-related attenuation creates uncertainty about future network capacity which can significantly affect Quality of Service (QoS). This creates a critical...
The article Nuclear Fusion \textbf{66}, 016012 (2026) by Richard Fitzpatrick is based on fundamental errors in the physics of the evolution of the poloidal magnetic flux in tokamaks. This paper was inspired by an article $\big<$arxiv.org/abs/2507.05456$\big>$ by Allen Boozer, which was posted on arXiv in various versions. The...
We present a rotational velocity (vsini) survey of 32 stellar/substellar objects and giant planets using Keck/KPIC high-resolution spectroscopy, including 6 giant planets (2-7 M$_\mathrm{Jup}$) and 25 substellar/stellar companions (12-88 M$_\mathrm{Jup}$). Adding companions with spin measurements from the literature, we construct a...
As hardware and software systems have grown in complexity, formal methods have been indispensable tools for rigorously specifying acceptable behaviors, synthesizing programs to meet these specifications, and validating the correctness of existing programs. In the field of robotics, a similar trend of rising complexity has emerged,...
We propose DeePM (Deep Portfolio Manager), a structured deep-learning macro portfolio manager trained end-to-end to maximize a robust, risk-adjusted utility. DeePM addresses three fundamental challenges in financial learning: (1) it resolves the asynchronous "ragged filtration" problem via a Directed Delay (Causal Sieve) mechanism...
Automated decision systems increasingly rely on human oversight to ensure accuracy in uncertain cases. This paper presents a practical framework for optimizing such human-in-the-loop classification systems using a double-threshold policy. Conventional classifiers usually produce a confidence score and apply a single cutoff, but our...
Among variational quantum algorithms designed for NISQ devices, ADAPT-VQE stands out for its robustness against barren plateaus, particularly in estimating molecular ground states. On the other hand, counterdiabatic algorithms have shown advantages in both performance and circuit depth when compared to standard adiabatic approaches....
NVIDIA's CUTLASS library provides a robust and expressive set of methods for describing and manipulating multi-dimensional tensor data on the GPU. These methods are conceptually grounded in the abstract notion of a CuTe layout and a rich algebra of such layouts, including operations such as composition, logical product, and logical...
In a game of permutation wordle, a player attempts to guess a secret permutation in the fewest number of guesses possible. Previously, Samuel Kutin and Lawren Smithline (arXiv:2408.00903) introduced this game and proposed a strategy called cyclic shift, which they conjecture performs optimally. We continue our investigation of this...
We study ballistic electron transport through electrostatic barriers in AB-stacked bilayer graphene within a full four-band framework. A mode-resolved analysis reveals how propagating and evanescent channels couple across electrostatic interfaces and how channel selectivity governs transport at normal incidence. We show that perfect...
In this work, we investigate the feasibility of event-by-event primary mass discrimination using radio observables only. Although the analysis does not require an explicit reconstruction of the shower maximum ($X_{max}$), the discrimination power still arises from the sensitivity of the radio observables to the longitudinal...
We present BSkG5, the latest entry in the Brussels-Skyrme-on-a-Grid (BSkG) series and the first large-scale nuclear structure model based on next-to-next-to-leading order (N2LO) Skyrme energy density functional (EDF). By extending the traditional Skyrme EDF ansatz with central terms containing up to four gradients, we are able to...
The linear point, a purely geometric feature in the monopole of the two-point correlation function, has been proposed as an alternative standard ruler. Compared to the peak in the correlation function, it is more robust to late-time nonlinear effects at the percent level. In light of improved simulations and high quality data, we...
Recent advances in video generation have been dominated by diffusion and flow-matching models, which produce high-quality results but remain computationally intensive and difficult to scale. In this work, we introduce VideoAR, the first large-scale Visual Autoregressive (VAR) framework for video generation that combines multi-scale...
We study the typical structure of games in terms of their connectivity properties. A game is `connected' if it has a pure Nash equilibrium and there is a best-response path from every action profile which is not a pure Nash equilibrium to every pure Nash equilibrium; a game is generic if it has no indifferences. In previous work we...
Prediction of outstanding claims has been done via nonparametric models (chain ladder), semiparametric models (overdispersed poisson) or fully parametric models. In this paper, we propose models based on negative binomial distributions for the prediction of outstanding number of claims, which are particularly useful to account for...
Despite recent advances in integrating Large Language Models (LLMs) into social robotics, two weaknesses persist. First, existing implementations on platforms like Pepper often rely on cascaded Speech-to-Text (STT)->LLM->Text-to-Speech (TTS) pipelines, resulting in high latency and the loss of paralinguistic information. Second, most...
Synchronization transition in oscillatory networks manifests itself as the appearance of a periodic global mode. While perfect in the thermodynamic limit, this mode fluctuates for finite ensembles. We characterize the coherence of this mode in terms of the phase diffusion constant. In several examples, we always observed normal...
While in pristine bilayer graphene the Berry curvature dipole (BCD), a necessary ingredient for the nonlinear anomalous Hall effect, is zero, uniaxial strain can give rise to finite BCD. We investigate this by using a tight-binding (TB) approach build on the Slater-Koster parameterization to capture lattice deformation effects often...