April 2026 arXiv papers — page 41

Yifan Zhang, Xiaohan Wang, Yueke Zhang, Yu Huang

Decompilation -- recovering source code from compiled binaries -- is essential for security analysis, malware reverse engineering, and legacy software maintenance. However, existing decompilers produce code that often fails to compile or execute correctly, limiting their practical utility. We present a multi-agent framework that transforms decompiled code in

Chen Wang, Guoqiang Wu

Let $(M^n, g, f)$ be an $n$-dimensional complete noncompact gradient shrinking Ricci soliton with the equation $Ric+\nabla^2f= \frac{1}{2}g$. 1. If its scalar curvature is $\frac{k}{2}$, Ricci curvature is nonnegative and sectional curvature has upper bound $\frac{1}{2(k-1)}$, we prove that the Ricci shrinker is isometric to a finite quotient of $\mathbb{R}^

Yu Kitabeppu, Naoto Nishida

In this paper, we obtain the limit formula of the observable diameter with non-Euclidean screen. In order to treat a sequence of observable diameters with varying screens, we define new types of observable diameters with errors.

Zhiyu Wang, Xudong Kang, Shutao Li

Audio-based video object segmentation aims to locate and segment objects in videos conditioned on audio cues, requiring precise understanding of both appearance and motion. Recent audio-driven video segmentation methods extend MLLMs by fusing audio and visual features for end-to-end localization. Despite their promise, these approaches are computationally in

Qingwen Pu, Kun Xie, Yuxiang Liu

Autonomous driving systems often infer pedestrian yielding behavior from geometric and kinematic cues alone, limiting their ability to reason about visual scene context and age-dependent behavioral variability. This limitation can produce delayed interventions in safety-critical encounters and unnecessary braking in benign interactions. This work introduces

Nicholas R. Rasmussen, Longwei Wang, Rodrigue Rizk, Md Rezwanul Akter Pallab

Developing robust and clinically reliable EEG biomarkers requires evaluation frameworks that explicitly address cross population generalization in multi site settings such as Parkinsons disease (PD) detection. Models trained under i.i.d. assumptions often capture population specific artifacts rather than disease relevant neural structure, leading to poor gen

Jun Dai, Xiaorun Wang, Xingde Li, Zheng Yang

We propose MatchRDMA, a proactive, segmented, and rate-matched long-haul RDMA scheme for geo-distributed LLM training over OTN. By coordinating source and destination OTN rates, it improves inter-DC throughput by up to 20x compared with conventional RDMA, and reduces destination-OTN buffer occupancy by up to 62.7%.

Min Yang, Wei Zheng, John Stufken, Ming-Chung Chang

When, in terms of the number of data points, the size of a dataset exceeds available computing resources, or when labeling is expensive, an attractive solution consists of selecting only some of the data points (subdata) for further consideration. A central question for selecting subdata of size $n$ from $N$ available data points is which $n$ points to selec

Ismael Mireles, Solène Ulmer-Moll, Donald Liveoak, Diana Dragomir

Studying planetary interactions in exoplanet systems informs theories of planet formation and evolution, providing essential context for understanding our own solar system. We combine spectroscopy, transit photometry, transit timing variations, and astrometry to characterize the TOI-201 system. The co-transiting system consists of a super-Earth, warm Jupiter

Dongzhou Huang, Tianyi Jiang, Haonan Wang

In this paper, we establish sharp upper and lower bounds on the convergence rate of the empirical measures of point processes under the Wasserstein distance. To this end, we first introduce a new metric on the space of counting measures and, based on this metric, define a Wasserstein distance between point processes. We then employ it to study the convergenc

Yisu Yan, Jifeng Guo

This paper investigates the cross-frequency structure of background clutter induced by random dispersive media in single-snapshot FDA-MIMO-GPR. Representative media are modeled by the Cole--Cole formulation to relate dispersive constitutive behavior to the reference propagation environment and observation-domain statistics. A normalized incremental contrast

Hung N. Do, Jessica Z. Kubicek-Sutherland, Oscar A. Negrete, S. Gnanakaran

We instruct an AI agent to construct two separate agentic AI platforms: one for autonomous training of predictive ML models for human-human and virus-human PPI, and the other for inducing explicit general rules governing human-human and virus-human PPI. The first agentic AI platform for autonomous training of predictive ML models for PPI is designed to consi

Minjie Ye, Yuzi Yang, Jiangtao Wei, Weilong Qin

High-energy-resolution GaN $\alpha$-particle detectors have significant potential for space radiation, nuclear instrumentation, and harsh-environment applications. However, existing GaN $\alpha$-particle detectors still face several key challenges, including reducing the dead-layer thickness, suppressing leakage current under high reverse bias, improving ene

Xi Shen, Bowen Qi, Tabassom Hamidfar, Selim M. Shahriar

Three-dimensional convolutional neural networks (3D CNNs) have demonstrated remarkable performance in video recognition tasks by processing both spatial and temporal features. However, the cubic scaling of computational complexity poses significant time and energy efficiency challenges for conventional silicon-based hardware. To address this, we propose a hy

John Chiang

In this paper, we introduce the Quasi-Quadratic Gradient (QQG), a novel search direction designed to accelerate the BFGS method within the quasi-Newton framework. By defining the QQG as the product of the inverse Hessian approximation and the current gradient, we explicitly leverage local second-order curvature to rectify the search path. Theoretical analysi

Stavros Gerolymatos, J. Kyle Brubaker, Martin J. A. Schuetz, Vladimir V. Gusev

Crystalline materials are widely used in technological applications, yet their discovery remains a significant challenge. As their properties are driven by structure, crystal structure prediction (CSP) methods play a central role in computational approaches aiming to accelerate this process. Previously, CSP has been approached from a combinatorial optimizati

João Henrique Andrade, Stefano Nardulli, Raoní Ponciano

We present a survey on multiplicity results for the Allen--Cahn equation and systems in the singular perturbation regime, emphasizing their geometric interpretation through $\Gamma$-convergence and isoperimetric theory. In the scalar case, the Allen--Cahn functional converges to perimeter, giving rise to minimal and constant-mean-curvature hypersurfaces, whi

Sihong Liu, Bocheng Jiang

High harmonic generation by an undulator is a key issue for extending the photon energy range of synchrotron light sources. In this work, we propose a biharmonic planar undulator operating in the low-K regime (K<1) to enhance high-harmonic radiation. By superimposing a 1/3 subharmonic undulator field onto a short-period superconducting undulator, a biharmoni

Peng Gao

The Gauss circle problem concerns with the evaluation of $\sum_{n \leq x}r(n)$, where $r(n)$ denotes the number of representations of $n$ as sums of two squares and $x \geq 2$. Let $\Psi_G(x,y)$ denote the sum of $y$-smooth numbers below $x$ weighted by $r(n)$. In this paper, we evaluate $\Psi_G(x,y)$ asymptotically for certain ranges of $x \geq y \geq 2$.

Bitan Sarkar, Yang Ni

Cell--cell communication (CCC) is commonly inferred from ligand--receptor co-expression, an associational paradigm that cannot distinguish causal signaling from shared regulation or confounding. We propose MR-CCC, a Bayesian Mendelian randomization framework that uses cis-eQTLs as instruments for ligand and receptor expression and explicitly models receptor-

Hai Hai Fu

We develop a formal framework for constructing canonical interpretations from plural structure theories. A structure theory is a triple T = (Σ, A, I) consisting of a signature, axioms, and an inference policy, whose admissible interpretation family collects all globally consistent assignments of structural conclusions. We distinguish three levels of canonica

Alokendu Mazumder, Arnab Roy, Punit Rathore

The subdominant (minmax) ultrametric is a canonical tree-structured summary of a dissimilarity matrix, arising equivalently as the ultrametric induced by single-linkage clustering. While its classical stability theory is usually formulated in $\ell_\infty$ or Gromov--Hausdorff terms, such bounds are poorly suited to sparse perturbations that alter only a few

Minjie Hua, Ning Wang, Peijun Yang, Kai Wang

OpenClaw requests are dominated by long, tool-augmented prefixes, including system prompts, conversation history, and tool outputs fed back into the context window. For this workload, with about 28k-30k input tokens and 500 output tokens per request, serving quality is governed by throughput, TTFT, and tail latency rather than short-prompt throughput alone.

Hua Zheng, Yuhang Guo, Kuanishbay Sadatdiynov, Cheng Wen

The recovery of high-level type information from stripped binaries-executables devoid of symbol tables and debugging information-is a cornerstone of software reverse engineering, vulnerability analysis, and decompilation. This survey tracks the evolution of binary type inference from early rule-based heuristics and static analysis to modern deep learning arc

Zihuai Xu, Ruofei Hou, Yang Xu, Hongli Xu

In agent-driven question answering (QA) applications, retrieval-augmented generation (RAG) is commonly introduced to enhance the response accuracy of large language models (LLMs) by providing additional context. Due to the inherent noise in retrieval results and the coarse granularity of document-level retrieval, the retrieved context often contains substant

Xinyan Zhu, Yaoqi Liu, Yue Gao, Huadong Ma

Knowledge graph (KG) reasoning infers new knowledge from existing facts and is widely applied in question answering, recommendation, and decision support. With the rapid development of large language models (LLMs), LLM-based KG reasoning frameworks have become increasingly popular by leveraging retrieved KG information. However, hallucinations in LLMs remain

Amogh Sheth, Biruk Assefa, Yi Wen Huang, Andrew Lin

Large language models (LLMs) excel at multi-step reasoning but incur substantial inference cost. We introduce Causal Attribution Pruning (CAP), a training-free method that identifies critical attention heads by measuring their causal impact on reasoning tasks and uses these head-level scores to guide fine-grained weight pruning. For each attention head, CAP

Jiexiang Huang

Huybrechts proved the finiteness of constant cycle curves of fixed order in any linear system $|L|$ on a K3 surface. In this paper, we study constant cycle surfaces on the Fano variety of lines $F(X)$ of a smooth cubic fourfold $X$. Fano surfaces $F(Y) \subset F(X)$ of hyperplane sections $Y \subset X$ are higher-dimensional analogues of curves on K3 surface

Belle Li, Lily Tan, Wei Zakharov, Qiang Qiu

Generative AI tutors hold significant promise for higher education, yet designing systems that scaffold learning without undermining academic integrity remains an open design challenge. This paper presents PeteChat, a course-aligned AI tutor developed and deployed at Purdue University, documented through the lens of design-based research (DBR). Drawing on li

Felipe Chavarro Polania

Budget-constrained micro-pretraining often requires triaging many candidate recipes on a shared accelerator before larger search budgets are spent. We study whether a staged fractional-factorial workflow can recover stable early effect structure in this setting. On a fixed autoresearch-derived single-GPU training loop, we run 613 experiments across pilot and

Andrea Ferrario, Joshua Hatherley

Machine learning models embedded in deployed AI systems are routinely updated to maintain correct functioning over time. Yet such updates can generate update opacity: users may not be able to understand why the same input now yields a different output. We argue that update opacity is best understood as a diachronic failure of epistemic accessibility: the pro

Dong Liu, Yanxuan Yu, Ying Nian Wu

The success of large language models (LLMs) across diverse NLP tasks has elevated the importance of reasoning chain optimization as a critical step in aligning model behavior with task objectives. Existing reasoning chain tuning methods often rely on black-box heuristics or gradient-free search, which lack interpretability, generalization, and sample efficie

Kevin Carrillo-Reina, Jean C. Cortissoz

We establish an explicit maximum principle for the Dirichlet problem associated with the $p$-Laplacian ($p>1$), where the constant depends on both $p$ and the geometry of the domain. From this result we derive two main applications. First, we obtain a new lower bound for the first nontrivial eigenvalue of the $p$-Laplacian, which improves upon existing estim

JunFeng Zhang

In industrial design, N-sided hole filling is typically formulated as the construction of a single trimmed B-spline surface by minimizing a fairness energy subject to geometric boundary constraints. This formulation requires an accurate parameter-space representation of the trimming curve on the filling surface. Most existing methods project the hole boundar

Sonu Kumar, Gaël Bastien, Maxim Savinov, Małgorzata Śliwińska-Bartkowiak

We report dielectric spectroscopy of single-crystalline \ce{NdMgAl11O19}, a magnetoplumbite hexaaluminate in which localized \ce{Nd^{3+}} moments coexist with a polarizable \ce{AlO5} bipyramidal network. The real part of the permittivity, $\varepsilon&#39;_{c}(T)$, measured along the crystallographic $c$ axis, increases as the temperature is lowered from 275

R. Seppi, D. Eckert, J. Schaye, J. Braspenning

The impact of AGN feedback on the hot gas content of galaxy groups remains a key uncertainty in galaxy formation and its connection to the large scale structure of the Universe. We aim to compare the XMM-Newton Group AGN Project (X-GAP) sample to the hydrodynamical FLAMINGO simulations, which span a wide range of AGN feedback prescriptions. We construct X-GA

R. Pascale, G. Battaglia, J. M. Arroyo-Polonio, E. Vasiliev

Dwarf spheroidal galaxies (dSphs) are prime laboratories for studying dark matter (DM) and the black hole demographics in the low-mass regime. These systems are also often flattened; nevertheless most studies rely on spherical models, potentially affecting dynamical inferences. We introduce the first multi-component, axisymmetric dynamical models of dSphs ba

Mounir Abdkrimi, Olivier Rossetto, O. Bourrion, Christophe Vescovi

CONCERTO is a millimeter-wave imaging instrument that operated on the Atacama Pathfinder Experiment (APEX) telescope from April 2021 to May 2023. Its primary scientific objectives include the study of galaxy clusters through the Sunyaev-Zel&#39;dovich (SZ) effects, the observation of Galactic star-forming regions, and the first measurements constraining the

J. Lois-Fuentes, B. Fernández-Domínguez, T. Roger, F. Delaunay

We present the first direct measurement of the Z=6 shell gap in the neutron-rich 20O nucleus. The one-proton removal transfer reaction 2H(20O,3He)19N has been studied using the ACTAR TPC setup at GANIL. The use of ACTAR TPC enabled the measurement of low-cross section proton-removal reactions while preserving resolution. Eight p-hole states with l=1 were ide

Yingqian Min, Kun Zhou, Yifan Li, Yuhuan Wu

Recent advancements in reinforcement learning with verifiable rewards (RLVR) have significantly improved the complex reasoning ability of vision-language models (VLMs). However, its outcome-level supervision is too coarse to diagnose and correct errors within the reasoning chain. To this end, we propose Perceval, a process reward model (PRM) that enables tok

Christophe Chareton, Jad Issa, Mathieu Nguyen, Nicolas Blanco

As quantum computing becomes an emerging reality, designing efficient quantum programming capabilities is becoming more and more important. Particularly, the debugging and validation of quantum programs is of paramount importance, as these programs are by definition hard to test. Static analysis and formal verification methods for quantum programs started to

Pablo Andújar Guerrero

A subset of a topological space is constructible if it is a finite Boolean combination of closed sets. We prove that every NTP$_2$ expansion of $(\mathbb{R},<,+)$ by constructible sets defines only constructible sets, and that definable functions are generically piecewise continuous. The result also holds for all NTP$_2$ expansions of $(\mathbb{Q}_p,+,\cdot)

Jeong Yun Choi, Francisca Espinoza-Rojas, Saskia Hekker

Light curves of oscillating stars provide valuable insights into the stellar interiors. When oscillations from a pair of stars are captured within a single photometric aperture, they can be considered as potential asteroseismic binaries (ABs). If the two stars oscillate at similar frequency ranges, the superpositioned oscillation patterns appear as if from a

Paweł Kryszkiewicz, Łukasz Kułacz, Marcin Pakuła, Marcin Dryjanski

With growing mobile-network complexity, management and optimization have become increasingly difficult. Centralized algorithms face high control-data overhead and computational load, while distributed approaches often perform far from optimally. The O-RAN architecture introduces two tiers of RAN Intelligent Controllers (RICs), enabling hierarchical network-m

Wadhah Zai El Amri, Nicolás Navarro-Guerrero

Training machine learning models for robotic tactile sensing requires vast amounts of data, yet obtaining realistic interaction data remains a challenge due to physical complexity and variability. Simulating tactile sensors is thus a crucial step in accelerating progress. This paper presents SPLIT, a novel method for simulating image-based tactile sensors, w

Osvaldo M. Moreschi

This work introduces a geometrical method for analyzing transient gravitational waves recorded at interferometric observatories. This approach is intended to aid in assessing the performance and sensitivity of next-generation detector configurations, such as Cosmic Explorer, Einstein Telescope, and the South American Gravitational-wave Observatory.

Ziqi Ma, Si-Yue Yu, Taotao Fang, Jinyi Shangguan

The upcoming imaging survey of the Chinese Space-station Survey Telescope (CSST) will deliver high-resolution imaging of an unprecedented number of galaxies for galaxy studies. To understand CSST&#39;s capability, and to support the preparation of early-science programs, we generate 470,526 mock CSST images for 22,406 simulated galaxies with $M_*>10^9 M_\odo

Pedram Abdolghader, Rana Jafari, Abinash Das, Bilol Banerjee

We present a method for quantifying pulse-shape instability in a train of pulses using multi-shot Second-Harmonic-Generation Frequency-Resolved Optical Gating (SHG FROG). All versions of multi-shot FROG have previously shown the ability to distinguish stable from unstable pulse trains, as systematic differences appear between measured and retrieved traces wh

Adrian Kelly, Rony Keppens, Jordi De Jonghe

Cool, dense condensations such as coronal rain and prominences suggest that coronal plasma can undergo runaway radiative cooling. Connecting this behaviour to linear thermal modes requires us to fully understand the deeper connection between eigenvalue spectra and actual time-dependent evolution. We aim to clarify this intricate link for a simplified, corona

Davide Ricci, Bernardo Salasnich, Andrea Baruffolo, Jani Achrén

SOXS (Son Of X-Shooter) is a new spectrograph for the European Southern Observatory (ESO), recently installed at the New Technology Telescope (NTT) at the La Silla Observatory, Chile. The main instrument goal consists in the characterization of transient sources, based on alerts. It covers from (partially) ultra-violet to visible and near-infrared bands, wit

Jacobus Conradi, Ivor van der Hoog, Frederikke Uldahl, Eva Rotenberg

The Fréchet distance is a popular distance measure between trajectories or curves in space, or between walks in graphs. We study computing the Fréchet distance between walks in the $d$-dimensional grid graphs, i.e. $\mathbb{Z}^d$ where points share an edge if they differ by one in one coordinate. We give an algorithm, that for two simple paths on $n$ vertice

Xinran Zhang

Safety benchmarks such as HarmBench rely on LLM judges to classify model responses as harmful or safe, yet the judge configuration, namely the combination of judge model and judge prompt, is typically treated as a fixed implementation detail. We show this assumption is problematic. Using a 2 x 2 x 3 factorial design, we construct 12 judge prompt variants alo

Hiroki Nakano, Toru Sakai

The spin-S Heisenberg antiferromagnet on the two-dimensional lattice is investigated for S=1/2 and S=1. We consider interaction at isolated dimers ($J_{\rm d}$) and interaction bonds that form the bounce lattice ($J_{\rm b}$). For $J_{\rm d}=J_{\rm b}$, the system is reduced to the maple-leaf-lattice antiferromagnet. We primarily conduct highly parallelized

Si-wen Li

Using the gauge-gravity duality, we construct the anisotropic D3/D7 approach as a three-dimensional QCD-like theory, then investigate systematically the hadronic mass spectra, the dragging terms and the lowest hadronic interactions in the presence of the anisotropy in holography. Our derivation illustrates the dragging terms in the effective action are very

Nan Xue, Zuoye Liu, Ziwen Li, Adriana Pálffy

We investigate theoretically a nuclear excitation mechanism involving absorption of non-resonant photons leveraged by the coupling to the atomic shell. The nuclear non-resonant photoexcitation is assisted by electron recombination which compensates the energy mismatch between photon and nuclear transition energies, reminiscent of parametric up-conversion in

Junchi Liu, Zijun Wang, Shawn Tsai, Rui Zhang

The shift to the radiative near field region due to large antenna arrays necessitates beamforming that accounts for both angle and range, evolving mobility management into a joint angular range tracking challenge. Conventional schemes rely on rigid pilot payload structures with dedicated training slots, which interrupt data transmission and degrade spectral

Minhyeong Yu, Wonduk Seo

Product mapping, the task of deciding whether two e-commerce listings refer to the same product, is a core problem for price monitoring and channel visibility. In real marketplaces, however, sellers frequently inject promotional keywords, platform-specific tags, and bundle descriptions into titles, causing the same product to appear under many different name

Xiao-Yun Zhao, Jiang He, Shi-Jie Zheng, Ping Wang

The SVOM mission is specifically designed to for the detection and localization of Gamma-Ray Bursts (GRBs) and subsequent follow-up observations. Among the four telescopes installed on the SVOM satellite, the Gamma-Ray Monitor (GRM) plays a crucial role in capturing the prompt emission of GRBs due to its wide field of view (FOV) and broad energy range. Accur

Sara Tahery, Qin Chang

We investigate the holographic Schwinger effect in a confining background with a step dilaton profile, which induces a sharp transition between ultraviolet and infrared regimes and provides a qualitatively distinct realization of confinement. Within this framework, the quark--antiquark potential is extracted from the classical configuration of a fundamental

Thomas Martin Müller, Silvia Pappalardi, Rosario Fazio

Closed chaotic quantum systems relax after a quench into a Gibbs ensemble. At late times, the relaxation speed is determined by their conservation laws and hydrodynamics. As a result, there exist pairs of initial states which thermalize to the same ensemble, yet exhibit drastically different hydrodynamic relaxation. We show in two chaotic spin chains how thi

Yuki Furukawa

In this work, we study exotic theta terms in the 2+1d $ϕ$-theory, which provides a continuum description of the XY-plaquette model. The $ϕ$-theory can be viewed as a fractonic analogue of the 1+1d compact boson and exhibits momentum and winding subsystem symmetries. In this theory, discontinuous field configurations play a crucial role. Although such configu

Takashi Okamoto

Accurate modeling of supernova (SN) feedback in galaxy formation simulations is complicated by energy conservation violations arising from the vector nature of momentum injection. We present a mechanical feedback scheme addressing two key sources: the relative motion between gas elements and the SN-hosting star particle, and multiple momentum injections into

Benjamin Davies

A forward-looking agent observes signals of a state that follows a Gaussian AR(1) process. He balances the cost of having imprecise beliefs with the cost of acquiring more precise signals. I characterize his optimal information acquisition policy, and analyze how his steady-state beliefs and costs depend on persistence (the AR(1) parameter) and patience (the

Xinkai Ji, Pan Liu, Ying Yang, Yu Han

In Part I of this companion paper series, we introduced SWIFTraj, a new open-source vehicle trajectory dataset collected using a unmanned aerial vehicle (UAV) swarm. The dataset has two distinctive features. First, by connecting trajectories across consecutive UAV videos, it provides long-distance continuous trajectories, with the longest exceeding 4.5 km. S

Antonio Franchi

In robotics and biomechanics, trading metabolic cost for kinematic readiness is a well-established principle. This paper formalizes this concept for aerial multirotors through the introduction of aerodynamic promptness -- a dynamic metric analogous to dynamic manipulability in robotics. By formulating redundancy resolution as a geometric multi-objective opti

Joakim Skarding, Pavel Sanda

The OpenAIRE graph contains a large citation graph dataset, with over 200 million publications and over 2 billion citations. The current graph is available as a dump with metadata which, when uncompressed, totals $\sim$2.5 TB. This makes it hard to process on conventional computers. To make this network more accessible for the community, we provide a process

Tiziano Schiavone, Mariaveronica De Angelis, Luis A. Escamilla, Giovanni Montani

The Hubble tension and the unknown origin of dark energy motivate the exploration of alternative mechanisms for late-time cosmic acceleration. We investigate gravitationally induced particle creation (PC) as a non-equilibrium process that can effectively mimic dynamical dark energy. Within the thermodynamic framework of open systems, we adopt an agnostic app

Petr Kolman, Hans Raj Tiwary

A cut in a graph $G$ is called a {\em bond} if both parts of the cut induce connected subgraphs in $G$, and the {\em bond polytope} is the convex hull of all bonds. Computing the maximum weight bond is an NP-hard problem even for planar graphs. However, the problem is solvable in linear time on $(K_5 \setminus e)$-minor-free graphs, and in more general, on g

Jie Zhu, Hao Li

This work systematically investigates the post-Newtonian behavior of general quadratic gravity in the weak-field regime. By extending the Einstein-Hilbert action to include quadratic curvature terms as $\mathcal{L}\propto R-λC^2+μR^2$, the theory introduces two massive modes: a scalar mode and a ghost tensor mode. Using the post-Newtonian expansion method, w

Julia Pfitzer, Martin Uecker, Hermann Scharfetter

Electromagnetic interference (EMI) is a significant challenge for low-field MRI systems operating without conventional Faraday-shielded rooms. Traditional EMI mitigation approaches include external shields, subject grounding via electrodes, or active noise cancellation requiring synchronized receive channels. These methods either limit portability, introduce

Shivnandan Kaushik, Mahesh Madhav, Nagi Aboulenein, Jason Bessette

Memory-safety escapes continue to form the launching pad for a wide range of security attacks, especially for the substantial base of deployed software that is coded in pointer-based languages such as C/C++. Although compiler and Instruction Set Architecture (ISA) extensions have been introduced to address elements of this issue, the overhead and/or comprehe

Brandon Pries, John H. Wise

The nature of the origins of supermassive black holes remains uncertain. Multiple possible seeding pathways have been proposed across a variety of mass scales, each with their own strengths and weaknesses. One such channel is a direct collapse black hole (DCBH), thought to form from the deaths of supermassive stars in pristine atomic cooling halos in the ear

Swaraj Pratim Sarmah, Umananda Dev Goswami

We examine whether Flat Spectrum Radio Quasars (FSRQs) and BL Lacertae objects (BL Lacs) can act as plausible astrophysical sources of diffuse ultra-high-energy cosmic rays (UHECRs). Using realistic luminosity-dependent density evolution (LDDE) functions derived from observed gamma-ray luminosity functions for FSRQs and BL Lacs, we calculate the redshift evo

Matthew Patkowski, Onat Ayyildiz, Matjaž Kebrič, Katharine L. C. Hunt

Robust and efficient eigenstate preparation is a central challenge in quantum simulation. The Rodeo Algorithm (RA) offers exponential convergence to a target eigenstate but suffers from poor performance when the initial state has low overlap with the desired eigenstate, hindering the applicability of the original algorithm to larger systems. In this work, we

Leron Borsten, Hyungrok Kim

We argue that a field theory with a $\mathbb Z_N$ $p$-form symmetry generically admits, in addition to a Higgs phase and a &#39;confining&#39; phase, a Coulomb phase in which the infrared theory contains Abelian $p$-form electrodynamics, similar to the behaviour of Yang-Mills theory coupled to adjoint or fundamental matter. We illustrate our claim with conti

Zhirui Dai, Hojoon Shin, Yulun Tian, Ki Myung Brian Lee

Dense reconstruction and differentiable rendering are fundamental tightly connected operations in 3D vision and computer graphics. Recent neural implicit representations demonstrate compelling advantages in reconstruction fidelity and differentiability over conventional discrete representations such as meshes, point clouds, and voxels. However, many neural i

David Loeffler, Sarah Livia Zerbes

In our earlier work with Christopher Skinner (J. Eur. Math. Soc 24 (2022), no. 2; DOI 10.4171/JEMS/1124; Arxiv 1706.00201), we constructed Euler systems for the 4-dimensional spin Galois representations corresponding to automorphic forms for GSp(4). This construction depended on various arbitrary choices of local test data. In this paper, we use multiplicity

Yan-Qi Wang, Zhi-Qiang Gao, Hui Yang

We propose a minimal model starting from a parent Chern band with quartic dispersion that can describe the spin-valley polarized electrons in rhombohedral tetralayer graphene. The interplay between repulsive and attractive interactions on top of that parent Chern band is studied. We conduct standard self-consistent mean-field calculations, and find a rich ph

Nicola Agnew, David Lowit, Aidan S. Arnold

In a wide range of quantum technology applications, ranging from atomic clocks to the creation of ultracold or quantum degenerate samples for atom interferometry, optimal laser sources are critical. In particular, two phase-locked laser sources with a precise difference frequency are needed for efficient coherent population trapping (CPT) clocks, gray molass

Vicente Iligaray, Danilo Aballay, Federico Fuentes

This work provides new lower bounds on the global (nonlinear) stability limit of pressure-driven two-dimensional plane Poiseuille flow, improving on the energy stability limit, $Re_E$, originally computed by Orr in 1907. Using a computer we carefully construct quartic Lyapunov functionals of the velocity perturbations about the laminar profile, which certify

Haoning Xue, Yue Li, Benjamin A. Lyons, Andy J. King

Make America Healthy Again (MAHA) is a health-related campaign slogan proposed by Robert F. Kennedy Jr. and later incorporated into the political coalition of President Trump. While #MAHA quickly circulated beyond the campaign itself and became a prominent hashtag for public discussion, it remains unclear whether this public discourse reflected, reshaped, or

Kaiyuan Feng, Debin Zou, Bo Cui, Shukai He

We report on an experimental demonstration of efficient neutron generation based on direct laser acceleration in microwire-array targets irradiated by ultrashort (tens of femtoseconds) laser pulses. The optimal array period was identified, at which the maximum proton energy and the number of protons with energies exceeding $1~\mathrm{MeV}$ were significantly

Rafael Pereira Eufrazio, Eduardo Fernandes Montesuma, Charles Casimiro Cavalcante

Learning low-dimensional representations from multi-view relational data is challenging when underlying geometries differ across views. We propose Bary-GWMDS, a Gromov-Wasserstein-based method that operates directly on distance matrices to learn a consensus embedding preserving shared relational structure. By leveraging intrinsic distances, the approach natu

Georgii V. D&#39;yakonov

We establish spectral conditions under which a first-order energy linearization of a projected Feshbach Hamiltonian is controlled. When the support of the induced self-energy spectral measure lies entirely above or below the target energy window, the self-energy curvature and linearization remainder have fixed sign in the semidefinite (Löwner) order. The rem

Benjamin Klein, Kazi Ruslan Rahman, Sanchita Ghose

Navigational aids for blind and low vision individuals struggle conveying dynamic real-world environments, leading to cognitive overload from continuous, undifferentiated feedback. We present AMAVA, a novel real-time video-to-audio framework that converts mobile device video into contextually relevant sound effects or text-to-speech descriptions. We propose

Wei Lu, Jay Wang, Dingli Duan, Ding Mao

Short term electricity price forecast is essential in competitive power markets, yet electricity price series exhibit high volatility, irregularity, and non-stationarity. This phenomenon is pronounced in the South Australian region of the National Electricity Market, where high renewable penetration drives price volatility and frequent negative price interva

Alcides Buss, Pradyut Karmakar

We introduce a notion of the Rapid Decay Property (RDP) for Fell bundles over locally compact Hausdorff \'etale groupoids, extending earlier rapid decay theories for \'etale groupoids and twists. Our approach yields analytic control on convolution norms and leads to the existence of dense Schwartz-type $*$-subalgebras of the reduced cross-sectional $C^*$-alg

Touch Sungkawichai, Tanupat Trakulthongchai

Wills conjectured that, for any non-zero integers $u_1,\ldots,u_k$, there is a real number $t$ such that, for all $i=1,\ldots,k$, \[\lVert tu_i\rVert\geq\frac{1}{k+1},\] where $\lVert x\rVert$ is the distance from $x$ to the closest integer. This statement is known as the Lonely Runner Conjecture. A computational method developed by Rosenfeld and the second

RoÝah Radaideh, Ali Khreis

Threat modeling for cyber-physical systems (CPS) remains a largely manual exercise. This project presents SMSI (System Model Security Inference), a hybrid neuro-symbolic pipeline that starts from a SysML architecture model and produces a prioritized list of NIST 800-53 security controls. The prototype has three main stages: a deterministic parser mapping sys

Il Memming Park, Ayesha Vermani, Gonzalo G. de Polavieja, Juan Álvaro Gallego

Large-scale neuroscience is generating rich datasets across animals, brain areas and behavioral contexts, yet our modeling efforts remains fragmented across isolated experiments. We argue that understanding behavior requires integrative neurocybernetic models: understandable dynamical models that capture the closed-loop coupling of brain, body and environmen

Jiazhao Shi

Traffic signal control is a critical task in intelligent transportation systems, yet conventional fixed-time and rule-based methods often struggle to adapt to dynamic traffic demand and provide limited decision interpretability. This study proposes an LLM-augmented traffic signal control framework that integrates LSTM-based short-term traffic state predictio

Jinbao Li, Jiancheng An, Hao Liu, Lu Gan

Semantic communications (SemCom) is a promising paradigm that prioritizes the transmission of task-relevant information, thereby enabling superior communication efficiency over traditional bit-centric systems. However, most existing SemCom systems face critical limitations in computational efficiency and spatial flexibility. To overcome these limitations, we

Sayan Ghosh, Pratim Mitra

Let $\pi$ be an irreducible, cuspidal automorphic representation of $GL_n(\mathbb{A}_\mathbb{Q})$ ($n\geq 3$), which is tempered only for $n=3$. Let $s$ be a complex number such that $\Re(s)\notin \left[1/n, 1-1/n\right]$ if $n\neq 4$; $\Re(s)\notin\left[1/5, 4/5\right]$ if $n=4$, then we show that there are infinitely many primitive cubic Dirichlet characte

Helder Oliveira

Breast cancer is a leading cause of cancer-related mortality among women worldwide, with mammography as the primary screening tool. While deep learning models have shown strong performance in lesion segmentation, most rely on computationally intensive architectures that limit their use in resource-constrained environments. This study evaluates the performanc

Ali Can Günhan, Semahi Serhat Aksoy, Zafer Gedik

We place several known indicators of Kochen--Specker contextuality -- the KCBS correlator $\chi$, the contextual fraction $\CF$, the Shannon-entropic $n$-cycle inequality of Chaves and Fritz, and the operational commutator witness $D$ of Paper~I -- into a single projector-geometric framework organized around the overlap matrix $\Tcal_{ij} = d^{-1}\tr[(\hat P

Andrey Fradkin, Rohit Krishnan

Markets are a promising way to coordinate AI agent activity for similar reasons to those used to justify markets more broadly. In order to effectively participate in markets, agents need to have informative signals of their own ability to successfully complete a task and the cost of doing so. We propose MarketBench, a benchmark for assessing whether AI agent

Muhammad Raees, Konstantinos Papangelis

While human-AI decision-making research has primarily used trust measurements to assess the practical usage of AI systems by their end-users, recent empirical evidence suggests that trust measurements do not inform users' appropriate reliance on AI systems. While examining the human-AI decision-making literature, in this work, we review empirical studies tha

Ralph Sabbagh, Tryphon T. Georgiou

We study the controllability of the differential Lyapunov equation under isospectral rotation of a linear gradient field. Specifically, control is effected by a symmetric time-varying gain-matrix constrained to have fixed eigenvalues; that is, by exclusively modulating the eigen-vectors of the state matrix and not its eigenvalues. Motivation for this problem

Andrew Au

We prove that any algorithm for detecting cycles in an $m \times n$ grid graph, where cells are colored and adjacency is defined by matching colors, must read all $mn$ cells in the worst case for all grids with $m \geq 2$ and $n \geq 2$. The proof is by adversary argument: we construct an adaptive adversary that maintains ambiguity -- one completion containi

Tomasz Stachowiak

The binary EML operator yields all (transcendental) elementary functions by recursive application, or a binary tree. The structure of the operator itself carries two distinct ingredients: that of an abelian group, and of functional inverse, which reveal a constructive path to many distinct functional families.