March 2026 arXiv papers — page 2

Angel Garcia de la Garza, Britton Sauerbrei, Jeff Goldsmith

Neuron-level firing data is believed to be governed by latent activation patterns during task completion. Analysing repeated trials of a task allows us to study these patterns, typically by averaging in-vivo neural spikes across trials. However, estimates of underlying latent activation patterns show trial-to-trial variability. Our aim is to determine whethe

Reilly Browne, Hsien-Chih Chang

Given an unweighted graph $G$, the *minimum $r$-dominating set problem* asks for the smallest-cardinality subset $S$ such that every vertex in $G$ is within radius $r$ of some vertex in $S$. While the $r$-dominating set problem on planar graphs admits a PTAS from Baker's shifting/layering technique when $r$ is constant, it becomes significantly harder when $

Ksenia Lysikova, Kirill Borodin, Grach Mkrtchian

RuASD (Russian AntiSpoofing Dataset) is a dedicated, reproducible benchmark for Russian-language speech anti-spoofing designed to evaluate both in-domain discrimination and robustness to deployment-style distribution shifts. It combines a large spoof subset synthesized using 37 modern Russian-capable TTS and voice-cloning systems with a bona fide subset cura

Ha Na Cho, Daniel Eisenberg, Cheryl King, Kai Zheng

Mental health challenges among young adults, are on the rise, necessitating effective solutions such as digital mental health interventions (DMHIs). Despite their promise, DMHIs face significant adoption barriers, including low initial uptake and high dropout rates. This study leverages machine learning (ML) to analyze behavioral patterns of users of a DMHI,

Gaston Besanson

When organizations decentralize data product ownership, as in the data mesh paradigm, each domain team optimizes for its immediate analytical needs, underinvesting in the cross-domain generality that enables organization-wide reuse. We formalize this as a simultaneous-move game in which N domains choose quality (q) and generality (g). Generality creates posi

Hai I. Wang, Xiaoyu Jia, Anand Nivedan, Mischa Bonn

Understanding the ultrafast dynamics of photoexcited charges in graphene is essential, as the microscopic mechanisms underlying these dynamics determine many of graphene's optical, optothermal, and optoelectronic properties. These are crucial properties for many functionalities and devices enabled by graphene, such as high-speed photodectors. Therefore, beyo

Ravish Gupta, Saket Kumar, Maulik Dang

Outpatient departments (OPDs) in Indian public hospitals face severe overcrowding, with daily volumes reaching 200--8,000 patients~\cite{aiims2020annual}. The prevailing First-Come-First-Served (FCFS) token system treats all patients equally regardless of clinical urgency, leading to dangerous delays for critical cases. We present an agentic AI framework int

Meng-Lin Tsai, Parth Brahmbhatt, Styliani Avraamidou

Bilevel optimization is a mathematical modeling formulation for hierarchical systems and two-player interactions, with wide-ranging applications in environmental, energy, and control engineering. Despite its utility, the mixed-integer bilevel optimization (MIBO) problem is exceptionally challenging to solve. While numerous exact and metaheuristic methods exi

Anika Goel, Samir Salim, Sara L. Ellison, Shobita Satyapal

In this paper, we investigate the robustness of WISE mid-IR color selection (W1-W2) for identifying obscured (Type 2) active galactic nuclei (AGNs) at low redshift (z<0.3), using a sample of ~360,000 SDSS galaxies classified via emission lines into Seyfert 2 (Sy2), LINER, and star-forming (BPT-SF) galaxies. We find that the K-correction is essential to remov

Bruno A. Veloso, Ciro M. Diniz, Luiz O. R. Solak, Antonio S. M. de Castro

Continuous variable (CV) quantum computation offers an alternative to qubit-based computing by exploiting the infinite-dimensional Hilbert space of bosonic modes. Despite recent progress, superconducting platforms have yet to demonstrate a scalable architecture capable of universal computation. Here, we design and numerically simulate a two-layer superconduc

Esteban Henríquez, Manuel Solano

We analyze a high order unfitted hybridizable discontinuous Galerkin (HDG) method for an optimal control problem governed by a convection-diffusion equation posed in a domain with piecewise-wise $\mathcal{C}^2$ boundary $\partial \Omega$. The computational domain $\Omega_h$ does not necessarily fit $\Omega$ and the Transfer Path Method (TPM) is used to trans

Nicolás Bernal, Sagnik Mukherjee, James Unwin

If the dark matter mass exceeds the highest temperature of the thermal bath, then dark matter production is Boltzmann suppressed. This opens new possibilities for dark matter model building. In particular, WIMP models that are experimentally excluded can be revived in this setting; conversely, freeze-in models, which would typically be beyond experimental re

Thomas Buckley, Leslie Schumm, Manor Askenazi, Edward Rietman

In this paper we extend our earlier work of (Rietman et al. 2022) presenting an application of physical Reservoir Computing (RC) to the classification of handwritten and spoken digits. We utilize an unpoled cube of Lead Zirconate Titanate (PZT) as a computational substrate to process these datasets. Our results demonstrate that the PZT reservoir achieves 89.

Joseph Murtagh, Ian Chow

We present predictions for solar system objects the Vera C.\ Rubin Observatory Legacy Survey of Space and Time (LSST) will not detect over its ten-year baseline survey. Employing state-of-the-art synthetic population models and the \texttt{Sorcha} survey simulator, we identify non-yield populations spanning geometric, photometric, kinematic, temporal, and co

Javier Bisbal, Julio Sotelo, Hernán Mella, Oliver Welin Odeback

This work introduces an unsupervised Divergence and Aliasing-Free neural network (DAF-FlowNet) for 4D Flow Magnetic Resonance Imaging (4D Flow MRI) that jointly enhances noisy velocity fields and corrects phase wrapping artifacts. DAF-FlowNet parameterizes velocities as the curl of a vector potential, enforcing mass conservation by construction and avoiding

Zahra Honjani, Mohsen Heidari

We study the problem of learning nearly $(s,\epsilon)$-sparse unitaries, meaning that the Pauli spectrum is concentrated on at most $s$ components with at most $\epsilon$ residual mass in Pauli $\ell_1$-norm. This class generalizes well-studied families, including sparse unitaries, quantum $k$-juntas, $2^k$-Pauli dimensional channels, and compositions of dep

Sudarshan Harithas, Sangkyung Kwak, Pushkal Katara, Srujan Deolasee

Developing robust autonomous loco-manipulation skills for humanoids remains an open problem in robotics. While RL has been applied successfully to legged locomotion, applying it to complex, interaction-rich manipulation tasks is harder given long-horizon planning challenges for manipulation. A recent approach along these lines is DreamControl, which addresse

Xuanyu Liang, Ahmed Al-Tahmeesschi, Swarna Chetty, Cicek Cavdar

Densely deployed base stations are responsible for the majority of the energy consumed in Radio access network (RAN). While these deployments are crucial to deliver the required data rate in busy hours of the day, the network can save energy by switching some of them to sleep mode and maintain the coverage and quality of service with the other ones. Benefiti

Brenden Latham, Mehrdad Moharrami

We study offline constrained reinforcement learning from human feedback with multiple preference oracles. Motivated by applications that trade off performance with safety or fairness, we aim to maximize target population utility subject to a minimum protected group welfare constraint. From pairwise comparisons collected under a reference policy, we estimate

Hariprasath Govindarajan, Per Sidén, Jacob Roll, Fredrik Lindsten

The Transformer model architecture has become one of the most widely used in deep learning and the attention mechanism is at its core. The standard attention formulation uses a softmax operation applied to a scaled dot product between query and key vectors. We explore the role played by norms of the queries and keys, which can cause training instabilities wh

Abril Azocar Guzman, Sarath Menon, Tilmann Hickel, Stefan Sandfeld

The reuse of atomistic simulation data is often limited by heterogeneous formats, incomplete metadata, and a lack of standardized representations of workflows and provenance. Here we present an ontology-based infrastructure for representing and integrating atomistic simulation data as a knowledge graph. The approach combines domain ontologies with a software

Yang Liu, Patrick Lopatto, Ivana Malenica

We consider Targeted Maximum Likelihood Estimation (TMLE) of weighted average treatment effects (WATEs), a class of causal estimands that reweight the covariate distribution using a specified function of the propensity score. This class includes the average treatment effect and average treatment effect on the treated, as well as various overlap-based targets

Gabriele Montefusco, Marco Antonelli, Francesca Gulminelli

Nuclear metamodels - phenomenological parametrizations of the energy of nuclear matter - are convenient tools to explore the space of realistic neutron star configurations constrained by astrophysical and nuclear data. While much recent work has focused on composition-agnostic barotropic models, the metamodel approach is designed to describe the composition

Rachid Drissi

We introduce L\'evy-Flows, a class of normalizing flow models that replace the standard Gaussian base distribution with L\'evy process-based distributions, specifically Variance Gamma (VG) and Normal-Inverse Gaussian (NIG). These distributions naturally capture heavy-tailed behavior while preserving exact likelihood evaluation and efficient reparameterized s

Korin Aldam-Tajima, Vatche Sahakian

We study Matrix theory at strong coupling in a setting describing two static objects a fixed distance apart, using numerical techniques. We reproduce the exact general relativistic force law between the two objects as an entropic force in Matrix theory. This involves employing an operator algebra that represents an external observer measuring the relative po

Alessandro Bravetti, Miguel Ángel García Ariza, José Roberto Romero-Arias

In dually flat manifolds, there is a deep connection between gradient flows and pregeodesics. This was one of the many important contributions of Amari to information geometry. In this paper, we extend the study of this relationship to general Riemannian manifolds. Our result does not impose conditions of flatness on the connection or symmetry on its non-met

Ruoyu Su, Matteo Esposito, Roberta Capuano, Rafiullah Omar

To support practitioners in understanding how agentic systems are designed in real-world industrial practice, we present a review of practitioner conference talks on AI agents. We analyzed 138 recorded talks to examine how companies adopt agent-based architectures (Objective 1), identify recurring architectural strategies and patterns (Objective 2), and anal

Jingxin Qiao, Myrto Arapinis, Thomas Zacharias

Coercion-resistance (CR) is a crucial security property in e-voting systems. It ensures that an attacker cannot compel a voter to vote in a specific way by using threats or rewards. The Loki e-voting protocol, proposed by Giustolisi \emph{et al.} at IEEE S\&P (2024), introduces a novel design that mitigates last-minute coercion through a re-voting mechanism.

Abu Noman Md Sakib, Protik Dey, Zijie Zhang, Taslima Akter

Explainable Artificial Intelligence (XAI) is critical for ensuring trust and accountability, yet its development remains predominantly visual. For blind and low-vision (BLV) users, the lack of accessible explanations creates a fundamental barrier to the independent use of AI-driven assistive technologies. This problem intensifies as AI systems shift from sin

Jinkai Qiu, Alessandro Saviolo, Chaojie Wang, Mingke Wang

Realistic highway simulation is critical for scalable safety evaluation of autonomous vehicles, particularly for interactions that are too rare to study from logged data alone. Yet highway traffic generation remains challenging because it requires broad coverage across speeds and maneuvers, controllable generation of rare safety-critical scenarios, and behav

Ravish Gupta, Saket Kumar

This paper extends the Acemoglu-Restrepo task exposure framework to address the labor market effects of agentic artificial intelligence systems: autonomous AI agents capable of completing entire occupational workflows rather than discrete tasks. Unlike prior automation technologies that substitute for individual subtasks, agentic AI systems execute end-to-en

Isabel Hubard, Egon Schulte

Abstract polytopes are combinatorial structures with distinctive geometric, algebraic, or topological characteristics, that generalize (the face lattice of) traditional polyhedra, polytopes or tessellations. Most research has focused on abstract polytopes with the highest possible symmetry, in particular those that are regular or chiral. In this paper we stu

Leonardo Colò, David Kohel

We study supersingular isogeny graphs with level structure and their associated Galois representations.

Chiara Damiolini

These notes survey the theory of (twisted) conformal blocks from an algebro-geometric perspective and have two main goals. The first one is to summarize the construction of conformal blocks from vertex operator algebras, and to describe their fundamental properties -- such as factorization and sewing -- which imply that conformal blocks define vector bundles

Leron Borsten, Hyungrok Kim

A computer, in order to perform a given computation, requires a certain amount of space (memory) and a certain amount of time (runtime). This leaves certain computations beyond reach due to technological limits on processing speed and memory density. Some computations, such as the halting problem, are not possible even in principle. However, curved spacetime

Razi Iqbal, Awais Ahmad, Asfandyar Gillani

This paper brings up this idea of using Near Field Communication (NFC) for inventory control system instead of using traditional barcodes. NFC because of its high security, ease of use and efficiency can be very suitable for systems like inventory control. In traditional inventory control systems, each product has a barcode pasted on it, which is vulnerable

Suhan Zhong, Jinling Zhou, Jiawang Nie, Xindong Tang

This paper studies the copositive optimization problem whose objective is a sparse polynomial, with linear constraints over the nonnegative orthant. We propose sparse Moment-SOS relaxations to solve it. Necessary and sufficient conditions are shown for these relaxations to be tight. In particular, we prove they are tight under the cop-SOS convexity assumptio

Yitao Bai, Thinh T. Doan, Justin Romberg

We study the finite-time convergence of projected linear two-time-scale stochastic approximation with constant step sizes and Polyak--Ruppert averaging. We establish an explicit mean-square error bound, decomposing it into two interpretable components, an approximation error determined by the constrained subspace and a statistical error decaying at a subline

Giovanni Amici, Sara Shashaani, Pranav Jain

There is emerging evidence that trust-region (TR) algorithms are very effective at solving derivative-free nonconvex stochastic optimization problems in which the objective function is a Monte Carlo (MC) estimate. A recent strand of methodologies adaptively adjusts the sample size of the MC estimates by keeping the estimation error below a measure of station

Matthew DosSantos DiSorbo, Harang Ju

Effective automation hinges on deciding when to act and when to escalate. We model this as a decision under uncertainty: an LLM forms a prediction, estimates its probability of being correct, and compares the expected costs of acting and escalating. Using this framework across five domains of recorded human decisions-demand forecasting, content recommendatio

Lianrui Zuo, Yihao Liu, Gaurav Rudravaram, Karthik Ramadass

Medical imaging research is increasingly shifting from controlled benchmark evaluation toward real-world clinical deployment. In such settings, applying analytical methods extends beyond model design to require dataset-aware workflow configuration and provenance tracking. Two requirements therefore become central: \textbf{adaptability}, the ability to config

Md Rafi Islam, Md Rejwanul Haque, Elizabeth Choma, Shannon Hayes

Postural stability during movement is fundamental to independent living, fall prevention, and overall health, particularly among older adults who experience age-related declines in balance, muscle strength, and mobility. Among daily functional activities, the Sit-to-Stand (SiSt) transition is a critical indicator of lower-limb strength, musculoskeletal healt

Ljubisa Bojic, Alexander Felfernig, Bojana Dinic, Velibor Ilic

Social media platforms mediate how billions form opinions and engage with public discourse. As autonomous AI agents increasingly participate in these spaces, understanding their behavioral fidelity becomes critical for platform governance and democratic resilience. Previous work demonstrates that LLM-powered agents can replicate aggregate survey responses, y

Paula Orzechowska, R. Harald Baayen

This study investigates the relationship between the phonological and morphological structure of Polish words and their meanings using Distributional Semantics. In the present analysis, we ask whether there is a relationship between the form properties of words containing consonant clusters and their meanings. Is the phonological and morphonological structur

Ethan Cantor, Yinyin Ge, Hongxing Ye, Jie Li

The electric power sector has seen an increased penetration of renewable energy sources (RESs) that could strain the system reliability due to their inherent uncertainties in availability and controllability. Effective load carrying capability (ELCC) is widely used to quantify the reliability contributions of these RESs. However, existing ELCC methods can ov

Martine Hjelkrem-Tan, Marius Aasan, Rwiddhi Chakraborty, Gabriel Y. Arteaga

Masked Image Modeling (MIM) has become a ubiquitous self-supervised vision paradigm. In this work, we show that MIM objectives cause the learned representations to retain non-semantic information, which ultimately hurts performance during inference. We introduce a model-agnostic score for semantic invariance using Principal Component Analysis (PCA) on real a

Oleg Grynets, Vasyl Lyashkevych

The rapid development of AI and LLMs has driven new methods of SDLC, in which a large portion of code, technical, and business documentation is generated automatically. However, since there is no single architectural framework that can provide consistent, repeatable transformations across different representation layers of information systems, such systems r

Pengzhi Huang, Kiwan Maeng, G. Edward Suh

Privacy protection has become an increasing concern in modern machine learning applications. Privacy-preserving machine learning (PPML) has attracted growing research attention, with approaches such as secure multiparty computation (MPC) and fully homomorphic encryption (FHE) being actively explored. However, existing evaluations of these approaches have fre

Zeev Yampolsky, Felipe O. Silva, Adriano Frutuoso, Itzik Klein

Autonomous platforms operating in the oceans require accurate navigation to successfully complete their mission. In this regard, the initial heading estimation accuracy and the time required to achieve it play a critical role. The initial heading is traditionally estimated by model-based approaches employing orientation decomposition. However, methods such a

Joseph Townsend, Chandresh Pravin, Kwun Ho Ngan, Matthieu Parizy

Automatic program repair can be a challenging task, especially when resolving complex issues at a repository-level, which often involves issue reproduction, fault localization, code repair, testing and validation. Issues of this scale can be commonly found in popular GitHub repositories or datasets that are derived from them. Some repository-level approaches

Clara Murgui

We present a UV completion of the Standard Model in which quarks and leptons are unified under color SU(4). A single fermionic representation, the real antisymmetric, provides the building blocks to address the strong CP problem via the Nelson-Barr mechanism, while simultaneously correcting the charged-lepton and down-quark mass relations predicted by Pati-S

E. Chan-López, A. Martín-Ruiz

A comparative algebraic framework for elementary cellular automata is developed, centered on the role of spatial symmetry. The primary object of study is Rule~22, the elementary cellular automaton with algebraic normal form $g(a,b,c)=a\oplus b\oplus c\oplus abc$ over $\mathbb{F}_2$, the simplest rule combining full $S_3$ symmetry with genuine nonlinearity. T

Sudip Chakrabarty, Saheli Mukherjee, Ananda G. Maity, Bivas Mallick

Complex numbers, intrinsic to the formulation of quantum theory, play a pivotal role in enabling advantages across a broad range of quantum information-processing tasks. Despite their fundamental importance, practical and scalable criteria for detecting quantum imaginarity remain relatively underexplored, particularly methods that enable its identification w

Yi-Hsuan Chen, Salman Ghori, Ania Adil, Eric Feron

Autonomous navigation in complex, non-convex environments remains challenging when robot dynamics, control limits, and exact robot geometry must all be taken into account. In this paper, we propose a hierarchical planning and control framework that bridges long-horizon guidance and geometry-aware safety guarantees for a polytopic robot navigating among polyt

Longwei Xu, Feng Feng, Shaojie Zhang, Xin Chen

Optical Character Recognition (OCR) is increasingly regarded as a foundational capability for modern vision-language models (VLMs), enabling them not only to read text in images but also to support downstream reasoning in real-world visual question answering (VQA). However, practical applications further require reliable text anchors, i.e., accurately ground

E. T. Akhmedov, D. V. Diakonov

We find infinitely many soliton-like solutions in a deformation of the sine-Gordon theory in $(d+1)$-dimensional $AdS_{d+1}$ (anti-de Sitter) spacetime for $d \geq 2$, as well as single solitonic solutions in $dS_{d+1}$ (de Sitter) and $\mathrm{H}{d+1}$ (Lobachevsky) spaces for $d \geq 1$ and in $AdS_2$. We also find a deformation of the kink solution in sca

Manuel Barros, Alcino Cunha, Jose Pereira, Eunsuk Kang

Most databases can be configured to operate under isolation levels weaker than serializability. These enforce fewer restrictions on the concurrent access to data and consequently allow for more performant implementations. While formal frameworks for rigorously specifying isolation levels exist, reasoning about the semantic differences between specifications

Jing Lu, Wolfgang E. Kerzendorf, John T. O'Brien, Maryam Modjaz

The absence of helium features in optical spectra is one of the classification criteria for Type Ic supernovae (SNe Ic). However, it is highly debated whether helium is truly absent in ejecta or spectroscopically undetectable in the optical region. The near-infrared (NIR) region contains cleaner He lines that are less blended with other common ions in SNe Ic

Nicholas Wu

This paper studies how uncertainty about problem difficulty shapes problem-solving strategies. I develop a dynamic model where an agent solves a problem by brainstorming approaches of unknown quality and allocating a fixed effort budget among them. Success arrives from spending effort pursuing good approaches, at a rate determined by the unknown problem diff

Jaime Mora-Paz, Stefan Henneking, Leszek Demkowicz, Jacob Grosek

With the goal of accurately extracting the optical field losses in a three-dimensional (3D), circularly coiled waveguide (e.g., bent optical fiber), this effort presents the numerical methodologies that are implemented for an envelope Maxwell model that propagates electromagnetic fields as an entirely boundary value problem. Our unique modeling approach incl

Elias Paakkunainen, Louis Denis, Benoît Vanderheyden, Christophe Geuzaine

Efficient numerical models are required for the design of systems with high temperature superconductor (HTS) coils, as fully resolved finite element simulations of individual coated conductors become computationally prohibitive. This work applies the foil conductor model (FCM) to insulated HTS coils using magnetic field conforming h-(full), h-$\phi$, and t-$

Jose de Jesus Bernal-Alvarado, David Delepine

We present a unified theoretical model relating stochastic microscopic epidemic dynamics with macroscopic non-linear population behavior. Utilizing the Doi-Peliti formalism, we model the pathogen as a gauge mediator field coupled to susceptible and infected host populations, and introduce a Reactive Immunity Field capable of spontaneous symmetry breaking. We

C. Dominik

Interstellar dust forms during stellar mass-loss events, occurring either during a star's giant phase or during supernova explosions. This PhD thesis provides an in-depth investigation into the theory of dust condensation and growth, specifically applied to the winds of cool giants such as Asymptotic Giant Branch (AGB) stars. The thesis begins with a theoret

Duran Serkan Kılıç

Distributed applications need identifiers that satisfy storage efficiency, chronological sortability, origin metadata embedding, zero-lookup verifiability, confidentiality for external consumers, and multi-century addressability. Based on our literature survey, no existing scheme provides all six of these identifier properties within a unified system. This p

Alireza Naderi, Ahmad Hafez, Abdulla Fawzy, Amr Alanwar

Data-driven safety verification of robotic systems often relies on zonotopic reachability analysis due to its scalability and computational efficiency. However, for nonlinear systems, these methods can become overly conservative, especially over long prediction horizons and under measurement noise. We propose a data-driven reachability framework based on the

Ken Deng, Xiangfei Wang, Guijing Duan, Chen Mo

While large language models (LLMs) promise to revolutionize automated scientific discovery, their application in rigorous real-world physical research is stalled by two critical barriers: a lack of realistic evaluation benchmarks and systemic LLM hallucinations. Here, we address both problems. We introduce QMP-Bench, a pioneering end-to-end research-level be

Will Pazner

In this work, we construct high-order finite element spaces for the $L^2$ de Rham complex on triangular meshes amenable to low-order-refined preconditioning. The spaces are constructed using the Duffy transformation, by pulling back appropriately chosen polynomial spaces defined on the unit square; in addition to piecewise polynomials, these spaces also cont

Anoop Mutneja, Kenneth S. Schweizer

The recent introduction of recovery rheology has provided qualitatively new physical insights into the yielding and flow of soft matter systems across diverse mechanically driven nonequilibrium protocols by separating the deformation strain into recoverable and unrecoverable components. A striking finding is that the fluid-like response associated with the g

Chitrabhanu Chaudhuri, Saswati Mukherjee

We explicitly describe unitary representations of mixed braid groups on the cohomology of Abelian branched covers of $\mathbf{CP}^1$ . We show that the image of the representation is generated by complex reflections and relate it to the multivariate Burau representation.

Pranav Nagarajan

Despite their ubiquity in the astronomical literature, there is no consensus tier list of the genitive forms of the 88 constellations officially recognized by the International Astronomical Union. To address this pressing open question, I conduct an anonymous pair comparison survey of 74 professional astronomers to rank these constellation genitives on their

Chen Huang, Carlos R. Mafra, Yi-Xiao Tao

Using BRST cohomology properties in pure spinor superspace and identities for OPE brackets of non-free fields, we obtain a new compact nested-bracket representation of massive tree-level three-point open-string amplitudes in which Moebius invariance is manifest. Explicit superspace calculations for amplitudes with level-one massive states confirm this findin

Yuming Zeng, Wei Xie, Keqi Wang

Stochastic reaction networks governed by Chemical Langevin Equations (CLE) exhibit pronounced multiscale dynamics spanning fast molecular reactions, intermediate transport, and slow cellular regulation, posing significant challenges for efficient and accurate simulation. Although operator splitting naturally decouples fast and slow subsystems, a rigorous err

Sean McBride

Recent advances in semiclassical gravity, both in our understanding of the gravitational path integral and the algebraic structure of a gravitating subregion, rely on the presence of an observer to obtain a nontrivial Hilbert space for closed universe backgrounds. Here I examine this proposal from a postmodern lens, identifying attempts to define ``observer

Stephan Rinner, Jonas Schmitt, Kilian Sandholzer, Andreas Reiserer

Integrated photonic circuits offer great promise for quantum technologies. However, due to the rapid propagation of light, many envisioned applications require efficient on-chip quantum memories with a programmable delay, compact footprint, and high fidelity. Implementing this based on standard semiconductor processing technology is an outstanding challenge.

Annette Taberner-Miller

Multi-model LLM serving operates in a non-stationary, noisy environment: providers revise pricing, model quality can shift or regress without notice, and new models arrive regularly. More than a dozen recent methods have proposed learned routers to navigate the resulting quality--cost tradeoff across portfolios spanning a $\sim$530$\times$ cost range. Despit

Daniela Pérez, Gustavo E. Romero, Santiago E. Perez Bergliaffa

We investigate whether a dynamical wormhole could survive in a universe that undergoes a cosmological bounce. First, the conditions under which a wormhole could persist from a contracting to an expanding phase of the cosmos are presented. Then, the only two known cosmological solutions of Einstein's equations representing wormholes are analyzed, and it is sh

Allison Codi, Elizabeth Rogawski McQuade, Razieh Nabi, Mats Stensrud

Understanding vaccine effects on post-infection outcomes is critical for evaluating the full value proposition of a vaccine. However, defining appropriate causal effects on such outcomes is challenging because infection is affected by vaccination. Existing principal stratification approaches focus on the \emph{Doomed} stratum, individuals who would be infect

Zhe Bai, Hans Johansen

We develop a machine learning (ML) surrogate model to approximate solutions to Maxwell's equations in one dimension, focusing on scenarios involving a material interface that reflects and transmits electro-magnetic waves. Derived from high-fidelity Finite Volume (FV) simulations, our training data includes variations of the initial conditions, as well as var

Ashish Rana, Chia-Chien Hung, Qumeng Sun, Julian Martin Kunkel

Human memory adapts through selective forgetting: experiences become less accessible over time but can be reactivated by reinforcement or contextual cues. In contrast, memory-augmented LLM agents rely on "always-on" retrieval and "flat" memory storage, causing high interference and latency as histories grow. We introduce Oblivion, a memory control framework

Moshe Babaioff, Aviad Rubinstein, Xizhi Tan, Kangning Wang

A central challenge in mechanism design is to develop truthful trade mechanisms that maximize the expected gains-from-trade (GFT) in two-sided markets with strategic agents. As achieving the full GFT is generally impossible, much of the literature has focused on constant-factor approximations. Existing results, however, are limited to the highly structured s

Alison Etheridge, Raphaël Forien, Thomas Hughes, Sarah Penington

We study the asymptotic behaviour, in the small noise limit, of stochastic travelling wave solutions to reaction-diffusion equations perturbed by Wright-Fisher noise. Such equations are predicted to display three distinct responses to noise in three parametric regimes: fully pushed, semi-pushed, and pulled. We prove, for the entire fully pushed regime, that

S. Jiménez, D. Kománek, R. Wünsch, J. Palouš

Context. Stellar feedback regulates star formation and shapes the interstellar medium, yet its role during the collapse of molecular clouds remains uncertain over a wide range of initial conditions. Aims. We explore how stellar winds and supernovae influence star formation in collapsing gas clouds that span a broad parameter space in mass, size, and metallic

Alessandro Lella, Jamie McDonald

This document is based on lectures delivered at a recent COSMIC WISPers COST Action training school in Annecy in September 2025. They examine detection of weakly interacting slim particles (WISPs), specifically axions and high-frequency gravitational waves, with compact objects. These slightly expanded notes focus on searches for axion dark matter and axion-

Bryan González Leandro

In this paper, we prove weak elimination of imaginaries for perfect bounded pseudo-algebraically closed fields equipped with finitely many independent valuations. Our approach combines an extension result for types to invariant types with an amalgamation theorem. As a special case, we obtain full elimination of imaginaries when the field is equipped with a s

Harper Wells

In this paper we study definable families of functions from an ordered abelian group into various naturally arising definable quotients. We show that for an ordered abelian group $G$ and definable family of convex subgroups $\{D\}_{D\in\mathcal{D}}$, any definable family of functions $\{f_D\} _{D\in\mathcal{D}}$ with $f_D:G^d\rightarrow\frac{G}{D}$ is unifor

Rafal Wlodarski

Software engineering courses often require rapid upskilling in supporting knowledge areas such as domain understanding and modeling methods. We report an experience from a two-week milestone in a master's course where 29 students used a customized ChatGPT (GPT-3.5) tutor grounded in a curated course knowledge base to learn cryptocurrency-finance basics and D

Anand Gokhale, Anton V. Proskurnikov, Yu Kawano, Francesco Bullo

This paper studies contractivity of firing-rate and Hopfield recurrent neural networks. We derive sharp LMI conditions on the synaptic matrices that characterize contractivity of both architectures, for activation functions that are either non-expansive or monotone non-expansive, in both continuous and discrete time. We establish structural relationships amo

Caio B. Naves, Thomas Klein Kvorning, Jonas Larson

For Hamiltonian systems, level statistics provide a faithful diagnostic of quantum chaos. By analogy, the statistics of the Lindbladian spectrum are often used in open quantum systems, and the Grobe-Haake-Sommers conjecture proposes that systems with chaotic classical counterparts should exhibit level repulsion in the Lindbladian spectrum. Here we point out

Alberto Castellano, Matteo Zatti

We relate the structure of non-perturbative corrections to BPS black hole observables in flat-spacetime theories with certain properties of probe charged particles in the near-horizon geometry. Concretely, we consider 4d $\mathcal{N} = 2$ supergravity with an infinite tower of F-terms and probe branes in $\text{AdS}_2\times \mathbf{S}^2$ backgrounds threaded

Sergey Syzranov, Arthur P. Ramirez

Identifying extensively degenerate zero-temperature states is key in characterizing spin-liquid-candidate materials and spin ices. In experiments, finding zero-point entropy (ZPE) is often attempted by measuring the entropy released by a material when cooled down from very high to very low temperatures. Such investigations are often unreliable and lead to co

Junkai Dong, Tomohiro Soejima, Daniel E. Parker, Ashvin Vishwanath

Nearly a century after Wigner's initial proposal, electron crystals are now a topic of intense experimental and theoretical interest. However, most proposed crystalline phases are commensurate and therefore become insulating in the presence of even weak pinning. In this work we discuss when a commensurate Wigner crystal will spontaneously self dope and devel

Tonghang Han, Jackson P. Butler, Shenyong Ye, Zhenqi Hua

When the Coulomb interaction dominates over kinetic energy, electrons can crystallize into a Wigner crystal (WC). This paradigmatic correlated electronic phase has been realized in two-dimensional electron gases with parabolic band dispersion and completely flat Landau levels under high magnetic fields. Beyond these conventional contexts of electron crystall

Sameer Shaik, Zhen Huang, Daniela Stan Raicu, Jacob Furst

Detecting software vulnerabilities is critical to ensuring the security and reliability of modern computer systems. Deep neural networks have shown promising results on vulnerability detection, but they lack the capability to capture global contextual information on vulnerable code. To address this limitation, we explore the application of transformers for C

Przemek Mróz, Andrzej Udalski

A recent preprint by Sugiyama et al. reported the discovery of twelve candidates for short-timescale (less than one day) gravitational microlensing events based on high-cadence photometric observations of the Andromeda Galaxy (M31) using the Subaru Hyper Suprime-Cam. These detections were attributed to a large population of planetary-mass primordial black ho

Julianne Goddard, Isaac Shlosman, Emilio Romano-Diaz

We analyze a suite of high-resolution cosmological zoom-in simulations of jetted Seyfert galaxies over $z\leq10$ projected on the major scaling relations, comparing trajectories of `normal' versus jet-hosting galaxies. Models include thermal and mechanical jet feedback launched from supermassive black holes (SMBHs) seeded at $z\sim9.1$ and $z\sim3.7$ with $M

Jiacheng Xu, Yu-Zhe Liu, Xin Ma, Guiqi Shi

We construct two recollements of module categories for the Cohen--Macaulay Auslander algebra $A^{\mathrm{CMA}}$ of a gentle algebra $A$. In this paper, we establish three equivalent characterizations for the quotient algebra $A^{\mathrm{CMA}}/A^{\mathrm{CMA}}(1-\epsilon_{\star}) A^{\mathrm{CMA}}$ of the CM--Auslander algebra of $A$ to be quasi-tilted, precis

K. Narayan

We study no-boundary de Sitter extremal surfaces and their pseudo-entropy areas for generic subregions at the future boundary, building on previous work. For large subregions, timelike+Euclidean extremal surfaces exist with transparent geometric interpretations, as do complex ones. The situation for small subregions is analogous to Poincare $dS$ and only com

Fu-Ming Chang, Zhuo-Yan Chen, Shuang-Yong Zhou

Electroweak boson scattering at the LHC provides a crucial avenue for probing physics beyond the Standard Model, particularly regarding deviations in quartic gauge couplings. We derive the complete set of positivity bounds for the $22$ dimension-$8$ anomalous quartic gauge coupling (aQGC) coefficients within the Standard Model Effective Field Theory (SMEFT).

Franco Cabral, Stuart Williamson, David Curtin, Christopher D. Matzner

Mirror Stars are a generic prediction of dissipative dark matter models, including minimal atomic dark matter and twin baryons in the Mirror Twin Higgs. Mirror Stars capture regular atoms from the interstellar medium through highly suppressed kinetic mixing interactions between the regular and the dark photon. This results in the accumulation of a "nugget",

Adarsh Kumar Dash, Dominic Anstey, Harry T. J. Bevins, Eloy de Lera Acedo

The spin-flip 21-cm signal from the Cosmic Dawn and the Epoch of Reionization is an essential probe of the conditions that led to the formation of the first luminous objects in the early Universe. However, its detection remains a major challenge owing to its low strength compared to the bright foregrounds and the requirement of precise calibration of the ins