December 2025 arXiv papers — page 13

Luca Falorsi, Gianni V. Vinci, Maurizio Mattia

We study the joint dynamics of membrane potential and time since the last spike in a population of integrate-and-fire neurons using a population density framework. This leads to a two-dimensional Fokker-Planck equation that captures the evolution of the full neuronal state, along with a one-dimensional hierarchy of equations for the moments of the inter-spik

John Cullinan, Nathan Kaplan

Let l be a prime number and let E and E' be l-isogenous elliptic curves defined over Q. In this paper we determine the proportion of primes p for which E(F_p) is isomorphic to E'(F_p). Our techniques are based on those developed in \cite{ck} and \cite{rnt}.

Yipei Wang, Qianye Yang, Lior Drukker, Aris T. Papageorghiou

Traditionally, ultrasound skill assessment has relied on expert supervision and feedback, a process known for its subjectivity and time-intensive nature. Previous works on quantitative and automated skill assessment have predominantly employed supervised learning methods, often limiting the analysis to predetermined or assumed factors considered influential

Boleslaw K. Szymanski, Yongtao Zhang, Brian Uzzi, Mohammed Shahid Modi

In the scientific community, prizes play a pivotal role in shaping research trajectories by conferring credibility and offering financial incentives to researchers. Yet, we know little about the relationship between academic collaborations and prizewinning. By analyzing over 100 scientific prizes and the collaboration behaviors of over 5,000 prizewinners in

Tingting Shi, Xiaoling Cui

We propose to measure the dispersions of Fermi polaron and molecule by engineering spin-orbit coupling (SOC) on the impurity, which induces spin flip with finite momentum transfer. The polaron dispersion can be probed at small SOC momentum from the linear response of impurity spin. For molecule, we show that it can be prepared through an adiabatic steady-sta

Rong-Yang Sun, Tomonori Shirakawa, Hidehiko Kohshiro, D. N. Sheng

Tensor networks (TNs) are a central computational tool in quantum science and artificial intelligence. However, the lack of unified software interface across tensor-computing frameworks severely limits the portability of TN applications, coupling algorithmic development to specific hardware and software back ends. To address this challenge, we introduce the

Xia Chen

Conventional deep learning prioritizes unconstrained optimization, yet biological systems operate under strict metabolic constraints. We propose that these physical constraints shape dynamics to function not as limitations, but as a temporal inductive bias that breeds generalization. Through a phase-space analysis of signal propagation, we reveal a fundament

Russell Beale

We reflect on the life and influence of the academic journal, charting their history and contributions, discussing how their influence changed society, and examining how in death they will be mourned for what they initially stood for but in the end had moved so far from that they will less missed than they might have been.

Bin Xu, Ayan Banerjee, Sandeep Gupta

Neural networks have become dominant computational workloads across cloud and edge platforms, but their rapid growth in model size and deployment diversity has exposed hardware bottlenecks increasingly dominated by memory movement, communication, and irregular operators rather than peak arithmetic throughput. This survey reviews the current technology landsc

Yaacov Kopeliovich

We express the branch points cross ratio of cyclic Mumford curves as quotients of $p$-adic theta functions evaluated at the p-adic period matrix

Ruei-Jiun Hung, Matthew Weingarten, Shuo Ma, Steven M. Day

Hydrologic observations and experimental studies indicate that inelastic dilation from coseismic fault damage can cause substantial pore pressure reduction, yet most near-fault hydromechanical models ignore such inelastic effects. Here, we present a 3-D groundwater flow model incorporating the effects of inelastic dilation based on an earthquake dynamic rupt

Xuanlong Fu

We present a relation between stable rank one and real rank zero via the method of tracial oscillation. Let $A$ be a simple separable $C^*$-algebra of stable rank one. We show that $A$ has tracial approximate oscillation zero and, as a consequence, the tracial sequence algebra $l^\infty(A)/J_A$ has real rank zero, where $J_A$ is the trace-kernel ideal with r

Qihao Duan, Alexandre B. Simas, David Bolin, Raphaël Huser

The Dynamic Nelson--Siegel (DNS) model is a widely used framework for term structure forecasting. We propose a novel extension that models DNS residuals as a Gaussian random field, capturing dependence across both time and maturity. The residual field is represented via a stochastic partial differential equation (SPDE), enabling flexible covariance structure

Anton M. Zeitlin

We investigate the moduli space of holomorphic $GL(1|1)$ Higgs bundles over a compact Riemann surface. The supergroup $GL(1|1)$, the simplest non-trivial example beyond abelian cases, provides an ideal setting for developing supergeometric analogues of classical results in Higgs bundle theory. We derive an explicit description of the moduli space and we stud

Mykola Dedushenko, Daniel Resnick

We study the Coulomb-branch sector of 3D $\mathcal{N}=4$ gauge theories with half-hypermultiplets in general pseudoreal representations $\mathbf{R}$ ("noncotangent" theories). This yields (short) quantization of the Coulomb branch and correlators of the Coulomb branch operators captured by the 1d topological sector. This is done by extending the hemisphere p

Paul Englefield, Russell Beale

In a world of information overload, understanding how we can most effectively manage information is crucial to success. We set out to understand how people view deletion, the removal of material no longer needed: does it help by reducing clutter and improving the signal to noise ratio, or does the effort required to decide to delete something make it not wor

Wendong Yao, Binhua Huang, Soumyabrata Dev

Near-real-time regional-scale monitoring of ground deformation is increasingly required to support urban planning, critical infrastructure management, and natural hazard mitigation. While Interferometric Synthetic Aperture Radar (InSAR) and continental-scale services such as the European Ground Motion Service (EGMS) provide dense observations of past motion,

Peter Farag

Dense linear layers are a dominant source of computational and parametric cost in modern machine learning models, despite their quadratic complexity and often being misaligned with the compositional structure of learned representations. We introduce Stagewise Pairwise Mixers (SPM), a structured linear operator that replaces dense matrices with a composition

Himanshu Mavani, Mohamed Elekhtiar, Kai Huang, Naafis Ahnaf Shahed

Antiferromagnetic (AFM) spintronics offers a pathway toward electrically controllable spin-based devices beyond ferromagnets. Here, we identify wurtzite MnX (X = S, Se, Te) as a family of multiferroic materials hosting competing AFM phases, including altermagnetic, where nonrelativistic spin splitting can be controlled by ferroelectric polarization. Using de

Prasiddha Siwakoti, Atefeh Khoshkhahtinat, Piyush M. Mehta, Barbara J. Thompson

High-fidelity compression of multispectral solar imagery remains challenging for space missions, where limited bandwidth must be balanced against preserving fine spectral and spatial details. We present a learned image compression framework tailored to solar observations, leveraging two complementary modules: (1) the Inter-Spectral Windowed Graph Embedding (

Camille L Latune

After a brief historical perspective, we introduce the key notions of work and heat for quantum systems, to then apply them to quantum engines operating on quantum Otto and Carnot cycles. The irreversible and dissipative character of the quantum Otto cycle is briefly analyzed, contrasting with the energetic optimality of the quantum Carnot cycle. The central

Maurice Genevieva Almeida

For a simple graph G = (V, E), a coloring of vertices of G using two colors, say red and blue, is called a quasi neighborhood balanced coloring if, for every vertex of the graph, the number of red neighbors and the number of blue neighbors differ by at most one. In addition, there must be at least one vertex in G for which this difference is exactly one. If

Joonhee Lee, Kichang Lee, Jeonggil Ko

Wilderness monitoring tasks, such as poaching surveillance and forest fire detection, require pervasive and high-accuracy sensing. While AIoT offers a promising path, covering vast, inaccessible regions necessitates the massive deployment of maintenance-free, battery-less nodes with limited computational resources. However, these constraints create a critica

Mehdi Baharizadeh, Mohammad Sadegh Golsorkhi, Neda Keshavarzi, Thomas Ebel

DC microgrids provide an efficient framework for the interconnection of DC distributed energy resources (DERs) and DC loads. To continue to supply legacy single-phase AC loads, DC/AC converters can be integrated in the DC microgrid. The oscillatory instantaneous power of the single-phase AC load translates into a harmonic current on the converter's DC si

Kristóf Benedek, Géza Ódor

We present a numerical study on the synchronization and cascade failure behaviour by solving the adaptive second-order Kuramoto model on a large high voltage (HV) European power-grid. This non-perturbative analysis takes into account non-linear effects, which occur even when phase differences are large, when the system is away from the steady state, and even

Rößler Nicolas, Khan Irfan, Schade Thomas, Wellmann Christoph

This paper investigates the economic and technical feasibility of integrating Vehicle-to-Grid (V2G) technology in the Non-Road Mobile Machinery (NRMM) sector. These often-idling assets, with their substantial battery capacities, present a unique opportunity to participate in energy markets, providing grid services and generating additional revenue. A novel m

Suresh Chand, Avnish, Poulose Poulose

We propose a novel framework for low-scale leptogenesis within an extension of the Standard Model (SM) that includes three SU(2) singlet right-handed neutrinos, a singlet charged neutral fermion, and a real scalar field. In this setup, the CP asymmetry arises through a rich interplay of mechanisms, including two-body decays of the lightest right-handed neutr

Tae Ha Park, Simone D'Amico

This work presents a novel pipeline to recover the 3D structure of an unknown target spacecraft from a sequence of images captured during Rendezvous and Proximity Operations (RPO) in space. The target's geometry and appearance are represented as a 3D Gaussian Splatting (3DGS) model. However, learning 3DGS requires static scenes, an assumption in contrast

Haoran Ge, Zhen Chen, Yijia Wu, X. C. Xie

Jackiw-Rebbi zero modes were first proposed in 1976 as topologically protected zero-energy states localized at domain walls in one-dimensional Dirac systems. They have attracted widespread attention in the field of topological quantum computing, as they serve as non-superconducting analogs of Majorana zero modes and support non-Abelian statistics in topologi

Ruixin Yang, Songbai Chen, Jiliang Jing

The Blandford-Znajek (BZ) process is a pivotal mechanism to efficiently extract the energy from a rotating black hole (BH) via its plasma-filled magnetosphere in relativistic astrophysics. Within the framework of extended BZ monopole expansion, we have studied BZ process in the Randall-Sundrum braneworld BH spacetime and analyzed effects of the tidal charge

Nevidu Jayatilleke, Nisansa de Silva

SiDiaC, the first comprehensive Sinhala Diachronic Corpus, covers a historical span from the 5th to the 20th century CE. SiDiaC comprises 58k words across 46 literary works, annotated carefully based on the written date, after filtering based on availability, authorship, copyright compliance, and data attribution. Texts from the National Library of Sri Lanka

Souradeep Purkayastha, Zishen Qu, Ali Zahabi

We study asymptotics of the $d=4$, $\mathcal{N}=1$ superconformal index for toric quiver gauge theories. Using graph-theoretic and algebraic factorization techniques, we obtain a cycle expansion for the large-$N$ index in terms of the $R$-charge-weighted adjacency matrix. Applying saddle-point techniques at the on-shell $R$-charges, we determine the asymptot

Yu-Chan Chang, Jerónimo García-Mejía, Matteo Migliorini

We prove that the Dehn function of every finitely presented Bestvina-Brady group grows as a linear, quadratic, cubic, or quartic polynomial. In fact, we provide explicit criteria on the defining graph to determine the degree of this polynomial. As a consequence, we identify an obstruction that prevents certain Bestvina-Brady groups from admitting a CAT(0) st

Konstantin Avrachenkov, Vivek S. Borkar, Pratik Shah

We study the Lagrangian Index Policy (LIP) for restless multi-armed bandits with long-run average reward. In particular, we compare the performance of LIP with the performance of the Whittle Index Policy (WIP), both heuristic policies known to be asymptotically optimal under certain natural conditions. Even though in most cases their performances are very si

Michael Wiemeler

We prove vanishing results for Witten genera of string generalized complete intersections in homogeneous $\text{Spin}^c$-manifolds and in other $\text{Spin}^c$-manifolds with Lie group actions. By applying these results to Fano manifolds with second Betti number equal to one we get new evidence for a conjecture of Stolz.

Charith Wickrema, Eliza Mace, Hunter Brown, Heidys Cabrera

We explore the scaling behaviors of artificial intelligence to establish practical techniques for training foundation models on high-resolution electro-optical (EO) datasets that exceed the current state-of-the-art scale by orders of magnitude. Modern multimodal machine learning (ML) applications, such as generative artificial intelligence (GenAI) systems fo

Hesam Khoshkbari, Georges Kaddoum, Omid Abbasi, Bassant Selim

This paper presents a distributed beamforming framework for a constellation of airborne platform stations (APSs) in a massive Multiple-Input and Multiple-Output (MIMO) non-terrestrial network (NTN) that targets the downlink sum-rate maximization under imperfect local channel state information (CSI). We propose a novel entropy-based multi-agent deep reinforce

Milos Stankovic, Ella Hirche, Sarah Kollatzsch, Julia Nadine Doetsch

Recently published work titled Your Brain on ChatGPT: Accumulation of Cognitive Debt When Using an AI Assistant for Essay Writing Task by Kosmyna et al. (2025) has sparked a vivid debate on the topic of artificial intelligence (AI) and human performance. We sincerely congratulate Kosmyna et al. for initiating such important research, collecting a valuable da

Joseph Oche Agada, Andrew McAninch, Haley Day, Yasemin Tanyu

Physical properties and functionalities of materials are dictated by global crystal structures as well as local defects. To establish a structure-property relationship, not only the crystallographic symmetry but also quantitative knowledge about defects are required. Here we present a hybrid Machine Learning framework that integrates a physically-constrained

Bradley Fang, Michael Roger

WiFi allows for the connection of devices and people around the globe. It has proven to be a monumental and revolutionary tool that keeps the world connected. However, recent WiFi advancements are numerous and at times confusing. WiFi has grown significantly over the years, yet few understand the scope and scale of WiFi progression as a whole. This paper tac

Hesam Khoshkbari, Georges Kaddoum, Bassant Selim, Omid Abbasi

Non-terrestrial base stations (NTBSs), including high-altitude platform stations (HAPSs) and hot-air balloons (HABs), are integral to next-generation wireless networks, offering coverage in remote areas and enhancing capacity in dense regions. In this paper, we propose a distributed beamforming framework for a massive MIMO network with a constellation of aer

Reza Ansari, Gabriela A. Marques, John P. Marriner, Olivier Perdereau

We present the results of a small, low redshift spectroscopic survey of galaxies within 3 degrees of the North Celestial Pole (NCP) selected using V-band photometry obtained from the North Celestial Cap Survey (NCCS) (Gorbikov & Brosch 2014). The purpose of the current survey is to create a redshift space template for 21 cm emission from neutral hydrogen wit

Tin Hoang

Reliable forecasting of Global Horizontal Irradiance (GHI) is essential for mitigating the variability of solar energy in power grids. This study presents a comprehensive benchmark of ten deep learning architectures for short-term (1-hour ahead) GHI time series forecasting in Ho Chi Minh City, leveraging high-resolution NSRDB satellite data (2011-2020) to co

Mohammad Farzanullah, Han Zhang, Akram Bin Sediq, Ali Afana

The emergence of multimodal foundation models has revolutionized learning paradigms by enabling joint understanding across diverse data types. In the context of next-generation wireless networks, integrating sensing and communication modalities presents a unique opportunity to develop generalizable and data-efficient models. In this work, we introduce the co

Shivali Agrawal, Hsin-Wei S. Huang, Debaditya Bhattacharya, Madhav Ramesh

UV-C LEDs pseudomorphically grown by MBE on bulk AlN substrates emitting at 265 nm are demonstrated. High current density up to 800 A/cm$^2$, 5 orders of on/off ratio, and low differential on-resistance of 2.6 m$\Omega\cdot$cm$^2$ at the highest current density is achieved. The LED heterostructure has a high refractive index waveguide core surrounded by n- a

Ankur Jain

Fluid flow past one or more solid bodies is a fundamental problem of much practical importance. Standard solutions of simplified problems involving incompressible inviscid irrotational flow past common geometries such as circular cylinders and airfoils are commonly available. This work presents exact analysis of a potential flow problem involving fluid flow

Krithika Iyer, Austin Tapp, Athelia Paulli, Gabrielle Dickerson

Quantifying normative pediatric cranial development and suture ossification is crucial for diagnosing and treating growth-related cephalic disorders. Computed tomography (CT) is widely used to evaluate cranial and sutural deformities; however, its ionizing radiation is contraindicated in children without significant abnormalities. Magnetic resonance imaging

Thibaut K Kemayo, Justin Courter, Vishal Srikanth, Chadwick Jetti

When a turbulent vortex impinges on a porous layer, it creates a complex multiscale interaction: the wake structures that form in the free fluid engage with the intricate geometry of the pores, and this interplay governs both the turbulent energy budget and the rate of heat transfer. Here we use interface-resolved two-dimensional direct numerical simulations

Fanglei Hu, Jiachen Guo, Stephen Niezgoda, Wing Kam Liu

We present JAX-PF, an open-source, GPU-accelerated, and differentiable Phase Field (PF) software package, supporting both explicit and implicit time stepping schemes. Leveraging the modern computing architecture JAX, JAX-PF achieves high performance through array programming and GPU acceleration, delivering ~5x speedup over PRISMS-PF with MPI (24 CPU cores)

Manuel de Atocha Rodríguez Fernández, Alexander I. Nesterov, Gennady P. Berman, C. Moreno-González

While the Unruh effect has traditionally been studied under the assumption of uniform acceleration, a simplification motivated by experimental considerations, it is not necessarily true for all non-inertial motions. We propose a novel approach for the indirect detection of the Unruh effect without relying on the former restriction. Previous studies have show

A. Murat Maga, Steve Pieper, Cassandra Donatelli, Paul M Gignac

The increasing use of 3D imaging technologies in biological sciences is generating vast repositories of anatomical data, yet significant barriers prevent this data from reaching its full potential in educational and collaborative contexts. While sharing raw CT and MRI scans has become routine, distributing value-added segmented datasets, where anatomical str

Manuel Delgado, Neeraj Kumar

We present an algorithm to explore various properties of the numerical semigroups with a given maximum primitive. In particular, we count the number of such numerical semigroups and verify that there is no counterexample to Wilf's conjecture among the numerical semigroups with maximum primitive up to \(60\).

A. Alonso-Izquierdo, A. J. Balseyro Sebastian, M. A. Gonzalez Leon

In this work, families of kinks are analytically identified in multifield theories with either polynomial or deformed sine-Gordon-type potentials. The underlying procedure not only allows us to obtain analytical solutions for these models, but also provides a framework for constructing more general families of field theories that inherit certain analytical i

Sola Kim, Jieshu Wang, Marco A. Janssen, John M. Anderies

Federal agencies and researchers increasingly use large language models to analyze and simulate public opinion. When AI mediates between the public and policymakers, accuracy across intersecting identities becomes consequential; inaccurate group-level estimates may mislead outreach, consultation, and policy design. While research examines intersectionality i

Manuel de Atocha Rodríguez Fernández, Alexander I. Nesterov, Gennady P. Berman, C. Moreno-González

The Unruh effect remains a central topic in quantum field theory, although its direct experimental verification continues to be challenging. Recent efforts have therefore focused on indirect detection strategies in which the Unruh effect emerges through measurable physical processes. In this work, we extend a previously introduced detector model, originally

Maria Chudnovsky, Jadwiga Czyżewska, Marcin Pilipczuk, Paweł Rzążewski

We prove that for every fixed integer $s$ and every planar graph $H$, the class of $H$-induced-minor-free and $K_{1,s}$-induced-subgraph-free graphs has polylogarithmic tree-independence number. This is a weakening of a conjecture of Dallard, Krnc, Kwon, Milani\v{c}, Munaro, \v{S}torgel, and Wiederrecht.

Yin Wang, Chunlin Gong, Zhuozhen Xu, Lehan Zhang

Sea Surface Temperature (SST) prediction plays a vital role in climate modeling and disaster forecasting. However, it remains challenging due to its nonlinear spatiotemporal dynamics and extended prediction horizons. To address this, we propose OptFormer, a novel encoder-decoder model that integrates phase-space reconstruction with a motion-aware attention m

Sylwia Antoniuk, Andrzej Dudek, Andrzej Ruciński

We study the question of the least number of random edges that need to be added to a P\'osa-Seymour graph, that is, a graph with minimum degree exceeding $\frac k{k+1}n$, to secure the existence of the $m$-th power of a Hamiltonian cycle, $m>k$. It turns out that, depending on $k$ and $m$, this quantity may be captured by two types of thresholds, with one of

S. Bartocci, R. Battiston, S. Beolè, F. Benotto

The High Energy Particle Detector (HEPD-02) is a payload of the second China Seismo-Electromagnetic Satellite (CSES-02), designed and built by the Italian Limadou collaboration. Its purpose is to detect cosmic rays and trapped particles of radiation belts, in the kinetic energy range 3-100 MeV for electrons, 30-200 MeV for protons. HEPD-02 is the first space

Hunor Csala, Sebastian De Pascuale, Paul Laiu, Jeremy Lore

Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes such as SOLPS-ITER capture SOL physics with high accuracy, but their computational cost limits broad parameter scans and long transient studies. We present transformer-based, autoregr

Achyut Tiwari, Maxim Wenzel, Renjith Mathew Roy, Christian Prange

The commensurate charge-density-wave phase of the prototypical transition metal dichalcogenide $1T$-TaS$_2$ is investigated by temperature- and polarization-dependent infrared spectroscopy, revealing distinct charge dynamics parallel and perpendicular to the layers. Supported by density-functional-theory calculations, we show that the in-plane electronic str

Roee Ziv, Raz Lapid, Moshe Sipper

Audio-language models combine audio encoders with large language models to enable multimodal reasoning, but they also introduce new security vulnerabilities. We propose a universal targeted latent space attack, an encoder-level adversarial attack that manipulates audio latent representations to induce attacker-specified outputs in downstream language generat

Xu Huang, Junwu Chen, Yuxing Fei, Zhuohan Li

Large language model (LLM) agents currently depend on predefined tools or early-stage tool generation, limiting their adaptability and scalability to complex scientific tasks. We introduce CASCADE, a self-evolving agentic framework representing an early instantiation of the transition from "LLM + tool use" to "LLM + skill acquisition". CASCADE enables agents

Andrew Zhu, Poramas Komonvasee, Arman Nejad, David P. Tew

We apply periodic domain-based local pair natural orbital second-order M{\o}ller--Plesset perturbation theory (DLPNO-MP2) to probe the adsorption energy of CO on MgO(001), the consensus toy model system for surface adsorption. A number of robust correlated wavefunction methods now achieve excellent agreement with experiment for the adsorption of a single CO

A. Mironov, A. Morozov, Sh. Shakirov

The best way to represent generic conformal blocks is provided by the free-field formalism, where they acquire a form of multiple Dotsenko-Fateev-like integrals of the screening operators. Degenerate conformal blocks can be described by the same integrals with special choice of parameters. Integrals satisfy various recurrent relations, which for the special

Vincent Beguin, Jean Grétillat, Kornelija Kaminskaitė, Simonas Juzenas

Polymerase chain reaction (PCR) underpins modern molecular biology, yet its deployment in emerging domains such as DNA data storage and distributed diagnostics remains constrained by bulky thermocyclers, complex thermal hardware, and contamination-prone workflows. Here, we present an autonomous robotic PCR platform that redefines thermocycling as a motion-co

Gennaro Infante, Paola Rubbioni

We study the existence of positive eigenvalues with associated nonnegative mild eigenfunctions for a class of abstract initial value problems in Banach spaces with functional, possibly nonlocal, initial conditions. The framework includes periodic, multipoint, and integral average conditions. Our approach relies on nonlinear analysis, topological methods, and

Mohsen Hesamolhokama, Behnam Rohani, Amirahmad Shafiee, MohammadAmin Fazli

Much of the reported progress in file-level software defect prediction (SDP) is, in reality, nothing but an illusion of accuracy. Over the last decades, machine learning and deep learning models have reported increasing performance across software versions. However, since most files persist across releases and retain their defect labels, standard evaluation

Şenol Tarhan, Gabriel Goetten de Lima

This work has investigated the Magneto-Optical Trap (MOT) system used to produce Bose-Einstein Condensate (BEC). A primary challenge addressed in this study concerns the geometric limitations of traditional single-pair anti-Helmholtz coil configurations, where the magnetic field peaks occur outside the accessible inter-coil region. To overcome this limitatio

Alan Kostelecky

This talk at the CPT'25 meeting presents an overview of some recent results in Lorentz and CPT violation. Topics covered include the geometry of Finsler spaces associated with Lorentz violation, the resolution of the concordance problem in Lorentz-violating effective field theories, the relativistic evolution of a spin in background fields, and the phenomeno

Amadeus Brandes

Thermodynamic systems that preserve information against thermal fluctuations face a tradeoff distinct from transmission (Shannon) or erasure (Landauer). We formalize the preservation problem by defining the preservation stiffness $S_\kappa$, a response function analogous to magnetic susceptibility, and derive the Stiffness-Odds Identity: at optimal allocatio

Emily McMillon, Kathryn Haymaker

We introduce the first example of algebraically constructed hierarchical quasi-cyclic codes. These codes are built from Reed-Solomon codes using a 1964 construction of superimposed codes by Kautz and Singleton. We show both the number of levels in the hierarchy and the index of these Reed-Solomon derived codes are determined by the field size. We show that t

Sidney Natzuka Junior

We calculate, up to the first-order in the black hole spin, the perihelion precession of a test particle in the equatorial plane of a Kerr black hole using the perturbative Laplace-Runge-Lenz (LRL) vector method. To account for the dragging of inertial frames, we modify the LRL vector by incorporating a counteracting term in the angular momentum, which prese

Yuyang Zhang, Yang Hu, Bo Dai, Na Li

Soft actor-critic (SAC) is a popular algorithm for max-entropy reinforcement learning. In practice, the energy-based policies in SAC are often approximated using simple policy classes for efficiency, sacrificing the expressiveness and robustness. In this paper, we propose a variant of the SAC algorithm that parameterizes the policy with flow-based models, le

Tristan Barkman

A discrete binomial random-walk description of molecular collisions is used to quantify the variance of coarse-grained velocity fields arising solely from collision-induced momentum exchange. Closed-form expressions for the growth of velocity variance as functions of coarse-graining scale and time are derived and shown to imply a power-law decay of variance

K. A. Forsberg, A. R. Massih

Migration of hydrogen and hydride formation under thermal gradient leads to hydrogen redistribution in certain metals. These metals include zirconium, titanium, hafnium and their alloys with tendency to form hydrides. A computational method for hydrogen localization in such metals is presented. The method utilizes the heat flux in a steady state to compute t

Carlos Henrique Trigo Nasser Felix, Nancy Lopes Garcia, Alex Rodrigo dos Santos Sousa

We propose randomized confidence intervals based on the Neyman-Pearson lemma, in order to make them more broadly applicable to distributions that do not satisfy regularity conditions. This is achieved by using the definition of fuzzy confidence intervals. These intervals are compared with methods described in the literature for well-known distributions such

Nana Oye Akrofi Quarcoo, Milena Radenkovic

This paper investigates the latter scenario of individual emergency alerts in airports by applying two existing benchmark delay tolerant network protocols and evaluating their performance of delivery ratio and latency. First, the paper provides a background on Mobile Ad Hoc Networks (MANETs) and Delay Tolerant Networks (DTNs), as well as Vehicular Ad Hoc Net

A. Andrade, I. Saviane, L. Monaco, M. Gullieuszik

Study the ionized gas in metal-poor environments is key to understanding the mechanisms regulating galaxy evolution. However, most of the previous studies of extragalactic HII regions rely on unresolved observations of gaseous structures. We study the south-western, spatially resolved, HII region of Leo A, one of the most studied isolated dwarf galaxies in t

Ruizhe Huang, Kexuan Zhang, Yihao Fang, Baifeng Yu

This study investigates small-scale pretraining for Small Language Models (SLMs) to enable efficient use of limited data and compute, improve accessibility in low-resource settings and reduce costs. To enhance long-context extrapolation in compact models, we focus on Infini-attention, which builds a compressed memory from past segments while preserving local

Sayeh Rezaee, Cesar Nieto, Abhyudai Singh

Measurements of cell size dynamics have established the adder principle as a robust mechanism of cell size homeostasis. In this framework, cells add a nearly constant amount of size during each cell cycle, independent of their size at birth. Theoretical studies have shown that the adder principle can be achieved when cell-cycle progression is coupled to cell

Qucheng Peng, Hongfei Xue, Pu Wang, Chen Chen

3D Human Pose Estimation (3D HPE) is vital in various applications, from person re-identification and action recognition to virtual reality. However, the reliance on annotated 3D data collected in controlled environments poses challenges for generalization to diverse in-the-wild scenarios. Existing domain adaptation (DA) paradigms like general DA and source-

Leah Hope Ajmani, Arka Ghosh, Benjamin Kaveladze, Eugenia Kim

Online, people often recount their experiences turning to conversational AI agents (e.g., ChatGPT, Claude, Copilot) for mental health support -- going so far as to replace their therapists. These anecdotes suggest that AI agents have great potential to offer accessible mental health support. However, it's unclear how to meet this potential in extreme mental

Yue Guan, Changming Yu, Shihan Fang, Weiming Hu

Speculative decoding improves LLM inference by generating and verifying multiple tokens in parallel, but existing systems suffer from suboptimal performance due to a mismatch between dynamic speculation and static runtime assumptions. We present Yggdrasil, a co-designed system that enables latency-optimal speculative decoding through context-aware tree draft

Jiawei Chen, Yifei Yu, Chaoqun Liu

A relative Liutex vortex identification method is proposed in this study, together with its explicit mathematical formulation. The method is designed to identify vortical structures based solely on local flow-field information and is inherently Galilean invariant, ensuring robustness under different reference frames. To validate the proposed approach, a thre

Mark Van der Merwe, Kei Ota, Dmitry Berenson, Nima Fazeli

Prehensile autonomous manipulation, such as peg insertion, tool use, or assembly, require precise in-hand understanding of the object pose and the extrinsic contacts made during interactions. Providing accurate estimation of pose and contacts is challenging. Tactile sensors can provide local geometry at the sensor and force information about the grasp, but t

Pablo Thomassin, Guillaume Guerard, Sonia Djebali, Vincent Marc Lambert

Effectively encoding inequality constraints is a primary obstacle in applying quantum algorithms to financial optimization. A quantum model for Markowitz portfolio optimization is presented that resolves this by embedding slack variables directly into the problem Hamiltonian. The method maps each slack variable to a dedicated ancilla qubit, transforming the

Muyang Ren

To evaluate the effectiveness of a counterfactual policy, it is often necessary to extrapolate treatment effects on compliers to broader populations. This extrapolation relies on exogenous variation in instruments, which is often weak in practice. This limited variation leads to invalid confidence intervals that are typically too short and cannot be accurate

Hussen Abu Hamad, Dan Rosenbaum

Neural processes (NPs) are a class of models that learn stochastic processes directly from data and can be used for inference, sampling and conditional sampling. We introduce a new NP model based on flow matching, a generative modeling paradigm that has demonstrated strong performance on various data modalities. Following the NP training framework, the model

Mahdi Karami, Ali Behrouz, Praneeth Kacham, Vahab Mirrokni

Transformers, while powerful, suffer from quadratic computational complexity and the ever-growing Key-Value (KV) cache of the attention mechanism. This paper introduces Trellis, a novel Transformer architecture with bounded memory that learns how to compress its key-value memory dynamically at test time. Trellis replaces the standard KV cache with a fixed-si

Rahul Baxi

Current language model evaluations measure what models know under ideal conditions but not how robustly they know it under realistic stress. Static benchmarks like MMLU and TruthfulQA cannot distinguish a model that lacks knowledge from one whose verification mechanisms collapse when information degrades or adversaries probe for weaknesses. We introduce the

Igor Lodin, Sergii Filatov, Vira Filatova, Dmytro Filatov

We propose Motion-Compensated Latent Semantic Canvases (MCLSC) for visual situational awareness on resource-constrained edge devices. The core idea is to maintain persistent semantic metadata in two latent canvases - a slowly accumulating static layer and a rapidly updating dynamic layer - defined in a baseline coordinate frame stabilized from the video stre

Yukun Zhang, Stefan Elbl Droguett, Samyak Jain

This research project addresses the errors of financial numerical reasoning Question Answering (QA) tasks due to the lack of domain knowledge in finance. Despite recent advances in Large Language Models (LLMs), financial numerical questions remain challenging because they require specific domain knowledge in finance and complex multi-step numeric reasoning.

N. Cristi-Cambiaso, C. Navarrete, M. Catelan, M. Zoccali

Although many globular clusters (GCs) have been identified in the Galaxy, their population is estimated to be incomplete, especially in regions with strong crowding and interstellar extinction such as the Galactic bulge and plane.RR Lyrae stars, as bright standard candles and tracers of old stellar populations, are powerful tools for finding GCs in these reg

Sergio Cacciatori, Batu Güneysu, Sebastian Wündsch

Given a m-dimensional Gaussian process and polynomial m variables with real coefficients, we calculate the induced path odered exponenial in two different ways: one is purely algebraic in spirit and the other one is diagrammatic in spirit and uses multigraph labelings (and is inspired by the use of Feynman diagrams in quantum field theory).

Tao Dong, Harini Sampath, Ja Young Lee, Sherry Y. Shi

As Large Language Models (LLMs) evolve from code generators into collaborative partners for software engineers, our methods for evaluation are lagging. Current benchmarks, focused on code correctness, fail to capture the nuanced, interactive behaviors essential for successful human-AI partnership. To bridge this evaluation gap, this paper makes two core cont

Manish Krishan Lal

We study the Reflect-Reflect-Relax (RRR) algorithm in its small-step (flow-limit) regime. In the smooth transversal setting, we show that the transverse dynamics form a hyperbolic sink, yielding exponential decay of a natural gap measure. Under uniform geometric assumptions, we construct a tubular neighborhood of the feasible manifold on which the squared ga

Daniel J. Aronoff, Robert M. Townsend, Madars Virza

A repo trade involves the sale of a security coupled with a contract to repurchase at a later time. Following the 2008 financial crisis, accounting standards were updated to require repo intermediaries, who are mostly banks, to increase recorded assets at the time of the first transaction. Concurrently, US bank regulators implemented a supplementary leverage

A. F. Cabrera, C. E. Rodríguez Torres, P. de la Presa, S. J. Stewart

Monophasic MgFe$_2$O$_4$ nanoparticles synthesized by a simple autocombustion method were assessed as magnetically recoverable catalysts for the degradation of methylene blue (MB) in water. The NPs exhibit a crystallite size of $\sim$ 9 nm, a band gap of $\sim$ 2.11 eV, and soft ferrimagnetic behavior, enabling efficient photocatalytic and Fenton-like activi

Edoardo Monti, Peter Yatsyshin, Konstantinos Gkagkas, Andrew B. Duncan

Predicting interfacial thermodynamics across molecular and continuum scales remains a central challenge in computational science. Classical density functional theory (cDFT) provides a first-principles route to connect microscopic interactions with macroscopic observables, but its predictive accuracy depends on approximate free-energy functionals that are dif