arXiv preprints from January 1, 2026 through July 28, 2026 — 05:29:16 EST
We consider a family $\{(u_\varepsilon, v_\varepsilon)\}_{\varepsilon>0}$ of critical points of the Ambrosio-Tortorelli functional. Assuming a uniform energy bound, the sequence $\{(u_\varepsilon, v_\varepsilon)\}_{\varepsilon>0}$ converges in $L^2(Ω)$ to a limit $(u, 1)$ as $\varepsilon \to 0$, where $u$ is in $SBV^2(Ω)$. It was...
We study d-way balanced allocation, which assigns each incoming job to the lightest loaded among d randomly chosen servers. While prior work has extensively studied the performance of the basic scheme, there has been less published work on adapting this technique to many aspects of large-scale systems. Based on our experience in...
Deep neural networks constructed from linear maps and positively homogeneous nonlinearities (e.g., ReLU) possess a fundamental gauge symmetry: the network function is invariant to node-wise diagonal rescalings. However, standard gradient descent is not equivariant to this symmetry, causing optimization trajectories to depend heavily...
Differential abundance (DA) analysis in microbiome studies has recently been used to uncover a plethora of associations between microbial composition and various health conditions. While current approaches to DA typically apply only to cross-sectional data, many studies feature a longitudinal design to better understand the underlying...
In this work, we apply topic modeling to detect new physics in proton-proton collisions at the LHC in an unsupervised way. We investigate three new physics scenarios where fully leptonic $t\bar{t}\to b\bar{b}\ell^+\ell^-ν_\ell\barν_\ell$ is the main source of background without relying on jet substructure variables. We demonstrate...
Since the alternating sign matrix conjecture, proposed by Mills, Robbins, and Rumsey in 1982, was proved by Zeilberger and Kuperberg, several refined enumerations have been considered. In particular, Behrend et al. obtained a quadruply refined enumeration by adding certain parameters. In this paper, we revisit the doubly refined...
This paper develops a generalized finite horizon recursive solution to the discrete time stage bound disturbance attenuation regulator (StDAR) for state feedback control. This problem addresses linear dynamical systems subject to stage bound disturbances, i.e., disturbance sequences constrained independently at each time step through...
Surface wettability, governed by both topography and chemistry, plays a critical role in applications such as heat transfer, lubrication, microfluidics, and surface coatings. In this study, we present a machine learning (ML) framework capable of accurately predicting the wettability of laser-textured metal alloys using experimentally...
This paper establishes convergence and steady-state properties for the signal bound disturbance attenuation regulator (SiDAR). Building on the finite horizon recursive solution developed in a companion paper, we introduce the steady-state SiDAR and derive its tractable linear matrix inequality (LMI) with $O(n^3)$ complexity. Systems...
This paper develops a generalized finite horizon recursive solution to the discrete time signal bound disturbance attenuation regulator (SiDAR) for state feedback control. This problem addresses linear dynamical systems subject to signal bound disturbances, i.e., disturbance sequences whose squared signal two-norm is bounded by a...
We study the problem of adaptive privacy budgeting under generalized differential privacy. Consider the setting where each user $i\in [n]$ holds a tuple $x_i\in U:=U_1\times \dotsb \times U_T$, where $x_i(l)\in U_l$ represents the $l$-th component of their data. For every $l\in [T]$ (or a subset), an untrusted analyst wishes to...
Static Application Security Testing (SAST) tools using taint analysis are widely viewed as providing higher-quality vulnerability detection results compared to traditional pattern-based approaches. However, performing static taint analysis for JavaScript poses two major challenges. First, JavaScript's dynamic features complicate data...
In this expository article, we summarize what is known about maximum likelihood thresholds of Gaussian models, paying special attention to connections with rigidity theory.
Traditional time series forecasting methods optimize for accuracy alone. This objective neglects temporal consistency, in other words, how consistently a model predicts the same future event as the forecast origin changes. We introduce the forecast accuracy and coherence score (forecast AC score for short) for measuring the quality of...
How do evaluation systems compress multidimensional performance information into summary ratings? Using expert assessments of 9,669 professional soccer players on 28 attributes, we characterize the dimensional structure of evaluation outputs. The first principal component explains 40.6% of attribute variance, indicating a strong...
Real-time image segmentation is a key enabler for AR/VR, robotics, drones, and autonomous systems, where tight accuracy, latency, and energy budgets must be met on resource-constrained edge devices. While U-Net offers a favorable balance of accuracy and efficiency compared to large transformer-based models, achieving real-time...
The transition to electric vehicles (EVs) depends heavily on the reliability of charging infrastructure, yet approximately 1 in 5 drivers report being unable to charge during station visits due to inoperable equipment. While regulatory efforts such as the National Electric Vehicle Infrastructure (NEVI) program have established uptime...
We determine the post-perihelion rotation period of 3I/ATLAS using two independent diagnostics: the temporal modulation of the position angle (PA) of a persistent jet-like feature, and a time-series photometric light curve in the Gr (R) band. For the jet morphology, we measure the PA at multiple epochs by applying the Larson-Sekanina...
Inverse design tools such as Topology Optimization (TO) can achieve new levels of improvement for high-performance engineered structures. However, widespread use is hindered by high computational times and a black-box nature that inhibits user interaction. Human-in-the-loop TO approaches are emerging that integrate human intuition...
Sea ice mechanical properties are involved in dynamical processes acting from the scale of meters to several hundred kilometers. The current rapid changes in the state of polar sea ice require a better understanding and modeling of these processes and, therefore, accurate measurements of properties including sea ice thickness,...
This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd context including the previewed Behemoth teacher model, (ii) architectural characteristics beyond a high-level MoE description covering routed/shared-expert...
This paper describes the thirteen ensembles, named NME, generated with 2+1-flavor Wilson-clover fermions by the JLab/W\&M/LANL/MIT/Marseille collaborations, and presents an analysis of the meson and baryon spectrum, decay constants $f_π$ and $f_K$, flow scales $t_0$ and $w_0$, and time histories of the $Θ$ and Weinberg operators under...
Let W be a Weyl group. We define a class of irreducible representations of W that we call antispecial. They are in bijection with the constructible representations of W. We define an oriented graph structure on the set of antispecial representations or equivalently on the set of constructible representations of W. We describe...
We study the propagation and stability of electromagnetic vortex beams in relativistically de generate plasmas. We show that such plasmas support localized vortex solitons carrying orbital angular momentum and analyze their linear and nonlinear stability. Vortex solitons undergo az imuthal symmetry-breaking instabilities whose growth...
Human action recognition has become an important research focus in computer vision due to the wide range of applications where it is used. 3D Resnet-based CNN models, particularly MC3, R3D, and R(2+1)D, have different convolutional filters to extract spatiotemporal features. This paper investigates the impact of reducing the captured...