March 2026 arXiv papers — page 108

Leo Margolis, Taro Sakurai

We introduce a procedure based on computational algebraic geometry to determine whether two algebras are isomorphic. We then apply it to show that if $R$ is a commutative unital ring in which $2$ is not invertible, $G$ is a group of order dividing $64$ and $H$ some group, then an isomorphism of unital algebras $RG \cong RH$ implies an isomorphism of groups $

Hassan Abdelraouf, Vijay Gupta, Jeff S. Shamma

We study the convergence properties of a payoff-based higher-order version of replicator dynamics, a widely studied model in evolutionary dynamics and game-theoretic learning, in contractive games. Recent work has introduced a control-theoretic perspective for analyzing the convergence of learning dynamics through passivity theory, leading to a classificatio

Guillem Casadesus Vila, Adam Dai, Grace Gao

Navigation and mapping on the lunar surface require robust perception under challenging conditions, including poorly textured environments, high-contrast lighting, and limited computational resources. This paper presents a real-time mapping framework that integrates dense perception models with a 3D Gaussian Splatting (3DGS) representation. We first benchmar

Unnati Akhouri, Pei-Jun Huang, Elliott Rose, Sarah Shandera

We demonstrate that $k$-Markov sequences of unitary gates provide low-cost handles to manipulate the rate and structure of information spreading compared to traditional random, 0-Markov, circuits. For SWAP gates and brickwork circuits, we use graph cover time to demonstrate how $k$-Markov processes can be used to control operator transport. With SWAP gates a

Diego Cifuentes, Zhuorui Li

Sparsity is a fundamental modeling principle in statistics, signal processing, and data science. However, optimization with sparsity constraints is notoriously difficult. We introduce a new convex relaxation framework for {sparse quadratically constrained quadratic programs} (QCQPs), a class that subsumes sparse regression, sparse principal component analysi

Federico Testagrossa, Damiano F. G. Fiorillo, Luca Comisso, Enrico Peretti

The TeV neutrino signal observed by IceCube from the active galactic nucleus (AGN) NGC 1068 can probe its innermost coronal regions. If these neutrinos originate from hadrons accelerated within a magnetized turbulent corona, their intensity and spectrum depend on the turbulent magnetic field strength and turbulence coherence scale. The gamma rays accompanyin

Gabriele Staffieri, Giuseppe D'Ambruoso, Giovanni Scala, Cosmo Lupo

It is known that preprocessing noise may boost quantum key distribution by expanding the range of values of tolerated noise. For BB84, adding trusted noise may allow the generation of secret keys even for qubit error rate (QBER) beyond the 11% threshold in the asymptotic regime. Here we study the effect of preprocessing noise in the finite-size regime where

Aaqib Ali, Giovanni Scala, Cosmo Lupo, Antonio Mandarino

Quantum kernels offer a valid procedure for learning quantum phase transitions on quantum processing devices, yet issues on the scalability of the learning strategy in connection with the symmetry of the critical model have not been clarified. We derive a link between model symmetry and fidelity-kernel resource scaling. We quantify the measurement resources

MoniJesu James, Amir Atef Habel, Aleksey Fedoseev, Dzmitry Tsetserokou

Object-goal navigation has traditionally been limited to ground robots with closed-set object vocabularies. Existing multi-agent approaches depend on precomputed probabilistic graphs tied to fixed category sets, precluding generalization to novel goals at test time. We present GoalVLM, a cooperative multi-agent framework for zero-shot, open-vocabulary object

Changyan Shi, Bao-Feng Feng

We consider the soliton solutions of a recently proposed coupled Sasa-Satsuma-mKdV equation using the Kadomtsev-Petviashvili reduction method. The system consists of a complex-valued component coupled with a real-valued one. Under zero or nonzero boundary conditions, we derive four distinct classes of soliton solutions: bright-bright, dark-dark, bright-dark,

Kensei Kobayashi, Vladimir S. Airapetian, Takumi Udo, Shunsuke Mouri

The emergence of habitable conditions on the early Earth and on rocky exoplanets requires persistent energy sources that can drive both prebiotic chemistry and climate warming under magnetically active young G to M stars. To quantify the contribution of stellar energetic particle (StEP) events associated with superflares to the atmospheric chemistry of young

Dominic Schuh, Lena Funcke, Janik Kreit, Thomas Luu

The Hubbard model at finite chemical potential is a cornerstone for understanding doped correlated systems, but simulations are severely limited by the sign problem. In the auxiliary-field formulation, the spin basis mitigates the sign problem, yet severe ergodicity issues have limited its use. We extend recent advances with normalizing flows at half-filling

Carlos García Meixide, Mingxun Wang, Alejandro Schuler, Mark J. van der Laan

The Highly Adaptive Lasso (HAL) delivers unprecedented guarantees in nonparametric minimum loss estimation under minimal smoothness assumptions, such as dimension-free minimax optimal rates. However, the practical use of HAL has been severely limited by its exponentially growing computationally prohibitive indicator basis expansion in moderate to high dimens

Alex Anvi Eponon, Ildar Batyrshin, Christian E. Maldonado-Sifuentes, Grigori Sidorov

Current artificial intelligence systems struggle with systematic compositional reasoning: the capacity to recombine known components in novel configurations. This paper argues that the failure is architectural, not merely a matter of scale or training data, and that its origins lie in the psychological learning theories from which AI paradigms were derived.

Naoki Morihira, Amal Nahar, Kartik Bharadwaj, Yasuhiro Kato

A central challenge in image-based Model-Based Reinforcement Learning (MBRL) is to learn representations that distill essential information from irrelevant visual details. While promising, reconstruction-based methods often waste capacity on large task-irrelevant regions. Decoder-free methods instead learn robust representations by leveraging Data Augmentati

Fenglian Pan, Yinwei Zhang, Yili Hong, Larry Head

Artificial Intelligence (AI) systems are increasingly prominent in emerging smart cities, yet their reliability remains a critical concern. These systems typically operate through a sequence of interconnected functional stages, where upstream errors may propagate to downstream stages, ultimately affecting overall system reliability. Quantifying such error pr

Steven Li, Luis Rodrigues

Electrified propulsion is expected to play an important role in the sustainable development of Advanced Air Mobility (AAM). However, the limited energy density of batteries motivates the need to minimize energy consumption during flight. This paper studies the minimum total energy problem for an all-electric aircraft in steady cruise flight. The problem is f

Alejandro Simon, James Shi, Dominik Spath, Eva Kogler

Experimentally relevant signatures of superconductivity require access to real-frequency quantities, such as the spectral functions, optical response, and transport properties, yet Migdal-Eliashberg calculations are commonly performed on the imaginary axis and then analytically continued, a step that is numerically delicate and can obscure physically relevan

Jay Lawrence

We present a local unitary theory of a Bell-EPR measurement, starting with the premeasurement filtering of the individual photon polarizations and extending through the detection process involving four photodetectors, two at each receiving station. The essential feature is that decoherence occurs locally and independently with each detector upon its absorpti

Sunyoung Kim, Hokeun Kim

Recent studies reveal gaps in delegating critical tasks to agentic AI that accesses websites on the user's behalf, primarily due to limited access control mechanisms on websites designed for agentic AI. In response, we propose a design of website-based interaction for AI agents with fine-grained access control for delegated critical tasks. Our approach encom

Xavier Cadet, Aditya Vikram Singh, Harsh Mamania, Edward Koh

Investigating cybersecurity incidents requires collecting and analyzing evidence from multiple log sources, including intrusion detection alerts, network traffic records, and authentication events. This process is labor-intensive: analysts must sift through large volumes of data to identify relevant indicators and piece together what happened. We present a R

Lidia Ceriani, Paolo Verme

This paper pays tribute to Professor Giovanni Andrea Cornia's lifelong contributions to the measurement of global inequality. We review twelve world and regional databases of the Gini coefficient, illustrate their coverage, overlapping, and data gaps, and analyse the major sources of discrepancy among published Ginis. Merging all databases into a unified col

Todor D. Todorov

We show that the field of complex numbers $\mathbb C$ contains non-zero infinitesimals by observing that $\mathbb C$ contains non-Archimedean subfields. Our observation is based on an old theorem in algebra due to E. Steinitz, discussed in the article in detail. The presence of infinitesimals in $\mathbb C$ was surprise to the author and might be surprise to

Zenan Li, Ziran Yang, Deyuan He, Haoyu Zhao

Large language models (LLMs) can generate plausible code but offer limited guarantees of correctness. Formally verifying that implementations satisfy specifications requires constructing machine-checkable proofs, a task that remains beyond current automation. We propose a hierarchical proof search framework for automated code verification in Lean~4 that deco

Jakub Wójcik, Owidiusz Makuta, Wojciech Bruzda, Remigiusz Augusiak

We demonstrate that absolutely maximally entangled (AME) states consisting of $N=4n$ qudits with $n\in\{1,2,3,...\}$, each of even local dimension, cannot be realized as graph states. This result imposes strong constraints on AME states in composite local dimensions and characterizes the limitations of graph-state constructions for highly entangled multipart

Alexander Rasch, Rahul Rajendra Pai

Micromobility is a growing mode of transportation, raising new challenges for traffic safety and planning due to increased interactions in areas where vulnerable road users (VRUs) share the infrastructure with micromobility, including parked micromobility vehicles (MMVs). Approaches to support traffic safety and planning increasingly rely on detecting road u

Jiayi Guo, Panyi Dong, Zhiyu Quan

When working with real-world insurance data, practitioners often encounter challenges during the data preparation stage that can undermine the statistical validity and reliability of downstream modeling. This study illustrates that conventional data preparation procedures such as random train-test partitioning, often yield unreliable and unstable results whe

Isabel Molnar, Peiyu Li, Si Chen, Sugana Chawla

Higher education instructors often lack timely and pedagogically grounded support, as scalable instructional guidance remains limited and existing tools rely on generic chatbot advice or non-scalable teaching center human-human consultations. We present TeachingCoach, a pedagogically grounded chatbot designed to support instructor professional development th

Mingjian Zhu, Han Pu

We investigate dissipative phase transitions (DPTs) in a parametrically amplified open quantum Rabi model (QRM) with both single- and two-photon decay. In the classical oscillator limit, four composite phases emerge, arising from the possible normal or superradiant regimes across the upper and lower spin branches. A mean-field analysis reveals an ``inverted"

Elvira Bilokon, Valeriia Bilokon, Stanislava Litvinova, Denys I. Bondar

Spin transport typically relies on direct manipulation of the spin degree of freedom via magnetic fields, spin-orbit coupling, or engineered spin-dependent potentials. We show theoretically that directional spin currents can arise in a relatively simple setting - a one-dimensional interacting fermionic ring with static, spin-independent asymmetric barriers.

Jakob Ulmer

The overarching goal of this thesis was to develop categorical methods that connect enumerative geometry, as studied in mirror symmetry, with large $N$ gauge theories. In the first part, we established a relation between graph complexes, Calabi-Yau $A_\infty$-categories, and Kontsevich's cocycle construction. The next main result is the construction of a for

Benedetta Bertoli, Benjamin D. Goddard, Grigorios A. Pavliotis

We study a Kuramoto-Vicsek model of self-propelled particles with periodic boundary conditions subject to a constant angular tilt and a confining potential, and its mean-field (Fokker-Planck) behaviour. In the absence of confinement, the uniform density is stationary and we compute the critical coupling for four normalisation variants of the interaction kern

Morris Alper, Enora Rice, Bhargav Shandilya, Alexis Palmer

Interlinear glossed text (IGT) is a standard notation for language documentation which is linguistically rich but laborious to produce manually. Recent automated IGT methods treat glosses as character sequences, neglecting their compositional structure. We propose CWoMP (Contrastive Word-Morpheme Pretraining), which instead treats morphemes as atomic form-me

Xuan Kien Phung

Gottschalk's surjunctivity conjecture states that for all group universes and finite alphabets, every equivariant and continuous selfmap of the full shift, known as cellular automaton, cannot be a strict embedding. Not all surjective cellular automata are injective. However, if the surjectivity condition is replaced by a certain strengthened property called

Alejandro Simon, James Shi, Eva Kogler, Reed Foster

Experiments on superconducting materials have unveiled unique emergent properties when they are driven far from equilibrium. However, a quantitative first-principles treatment that describes experimental observations is lacking. In this work, we develop an ab-initio model for the nonequilibrium response of optically irradiated superconducting films within th

Yohan Vianna, Marcelo F. Santos

In this paper we discuss a protocol for charging a two-level quantum battery using a bipartite charger composed of two quantum harmonic oscillators. As one of its features, it allows us to fully charge the battery and is universally optimal in the regime of a single excitation added as energy input. We also make use of a selective interaction to extend the p

Yide Cai, Sabarenath Jayaprakash, James T. Liu, Yi Pang

We consider four-derivative superinvariants of five-dimensional $\mathcal N=2$ supergravity coupled to $n_v\le 2$ vector multiplets, which we obtain from both the superconformal tensor calculus approach and dimensional reduction. For the minimal case, with no vector multiplets, it is known that there is a unique four-derivative superinvariant. However, for t

Tom Sanders

We show that for non-zero integers $a$ and $b$ there is a natural number $N < \exp(r^{2+o_{a,b;r\rightarrow \infty}(1)})$ such that in any $r$-colouring of $\{1,\dots,N\}$ there are $x,y,z$, all in the same colour class, such that $ax-ay=bz$.

Rosemary Barrass, Harsha Nagarajan, Mathieu Tanneau, Russell Bent

The U.S. power grid is undergoing a paradigm shift as energy demand grows in scale and volatility. In response to this growing need, the U.S. has increased adoption of combined-cycle generators (CCs). CCs are fast-ramping generators that utilize variable configurations of combustion turbines (CTs) and steam turbines (STs) to achieve higher efficiency than tr

Hossein Hosseinabadi, Pavel E. Dolgirev, Sarang Gopalakrishnan, Amir Yacoby

Multi-qubit quantum sensors are rapidly emerging as platforms that extend the capabilities of conventional single-qubit sensing. In this work we show how suitable pulse sequences applied to a two-qubit sensor enable separate extraction of the response and noise of a probed environment within a $T_2$ spectroscopy framework. By resorting to representative exam

Xunzhuo Liu, Hao Wu, Huamin Chen, Bowei He

Conflict detection in policy languages is a solved problem -- as long as every rule condition is a crisp Boolean predicate. BDDs, SMT solvers, and NetKAT all exploit that assumption. But a growing class of routing and access-control systems base their decisions on probabilistic ML signals: embedding similarities, domain classifiers, complexity estimators. Tw

Ja Young Lee, Mírian Silva, Mohamed Nasr, Shonda Witherspoon

Large language models (LLMs) are largely motivated by their performance on popular topics and benchmarks at the time of their release. However, over time, contamination occurs due to significant exposure of benchmark data during training. This poses a risk of model performance inflation if testing is not carefully executed. To address this challenge, we pres

Wael Hafez, Amir Nazeri

Large language models, LLMs, are increasingly deployed in multiturn settings where earlier responses shape later ones, making reliability dependent on whether a conversation remains consistent over time. When this consistency degrades undetected, downstream decisions lose their grounding in the exchange that produced them. Yet current evaluation methods asse

Maria Andueza Rodriguez, Marie Candito, Richard Huyghe

Large language models (LLMs) achieve impressive results in terms of fluency in text generation, yet the nature of their linguistic knowledge - in particular the human-likeness of their internal lexicon - remains uncertain. This study compares human and LLM-generated word associations to evaluate how accurately models capture human lexical patterns. Using Eng

M. Ángeles Serrano

The intricate relations between elements in natural and human-made systems sustain the complex processes that shape our world, forming multiscale networks of interactions. These networks can be represented as graphs composed of nodes connected by links and, regardless of their domain, they share a set of fundamental structural properties. The family of netwo

Bernard Teles de Menezes, José Abdalla Helayël-Neto

In this paper, we pursue an investigation of the consequences of a mixing between supersymmetric partners - the photon and photino - analogous to the so-called Primakoff effect, but induced by a Lorentz-symmetry violating (LSV) fermionic-condensate background. In our framework, the LSV parameters are introduced as members of a non-dynamical superfield. As a

Louis-Pierre Chaintron, Lénaïc Chizat, Javier Maass

We establish convergence of the training dynamics of residual neural networks (ResNets) to their joint infinite depth L, hidden width M, and embedding dimension D limit. Specifically, we consider ResNets with two-layer perceptron blocks in the maximal local feature update (MLU) regime and prove that, after a bounded number of training steps, the error betwee

Antonius Bima Murti Wijaya, Paul Henderson, Marwa Mahmoud

Crowd trajectory prediction plays a crucial role in public safety and management, where it can help prevent disasters such as stampedes. Recent works address the problem by predicting individual trajectories and considering surrounding objects based on manually annotated data. However, these approaches tend to overlook dense crowd scenarios, where the challe

Yuqi Kang, Hu Bin, Dongxing Li, Jan Hamann

In this work, we introduce TUNeS (Temporal UNet emulator for Structure formation), a neural network framework for accelerating N-body simulations by predicting the nonlinear evolution of the matter density field from an initial particle distribution. TUNeS employs a two-stage modeling strategy, combining particle-based inference with a density-field refineme

Ionel-Dumitrel Ghiba, Trung Hieu Giang, Catalina Ureche

Starting from a three-dimensional model based on the Ciarlet-Geymonat energy, we derive nonlinear shell models within the classical elasticity theory of compressible isotropic materials. The Neo-Hookean term involving the norm of the deformation gradient leads to an energy depending on the first, the second, and the third fundamental forms of the deformed mi

Jennifer B. Bergner, Nicole Arulanantham, Emmanuel Dartois, Maria N. Drozdovskaya

The icy material within protoplanetary disks plays a central role in planet formation, yet remains poorly characterized by observations. We present 1.6-28$\mu$m spectra of five disks obtained as part of the JWST Edge-on Disk Ice (JEDIce) program, representing the largest survey of disk ices to date. The major ice species H$_2$O, CO$_2$, and CO are detected t

Ignacio García-Marco, Philippe Gimenez, Mario González-Sánchez

We establish upper bounds for the Castelnuovo--Mumford regularity of the coordinate ring of a simplicial projective toric variety with at most one singular point. In the smooth case, our results recover the bound of Herzog and Hibi [Proc. Amer. Math. Soc. 131 (2003), 2641--2647], and therefore the Eisenbud--Goto bound. Furthermore, when the variety has exact

Marwa Abdulhai, Isadora White, Yanming Wan, Ibrahim Qureshi

Large language models (LLMs) are used by over a billion people globally, most often to assist with writing. In this work, we demonstrate that LLMs not only alter the voice and tone of human writing but also consistently alter the intended meaning. First, we conduct a human user study to understand how people actually interact with LLMs when using them for wr

Wasilij Barsukow, Christian Klingenberg, Simon Krotsch

The Active Flux (AF) method employs a globally continuous approximation, like continuous Finite Element methods. This is achieved through the placement of point values at cell interfaces which are shared between adjacent cells. With, on average, K+1 degrees of freedom per cell, Active Flux achieves a polynomial approximation of degree K+1, while the Disconti

Patricio Escalona, Jacinto P. Neto, M. J. Neves, Camila Ramos

We investigate a two-component dark matter scenario in the type-I two-Higgs-doublet model. The dark sector contains a real scalar $s$ and a Dirac fermion $\chi$, whose stability is ensured by a $Z_4$ symmetry together with kinematic conditions. The scalar interacts with the visible sector through Higgs-portal couplings, while the fermion interacts with the s

Anish Hebbar, Rong Ge, Amit Kumar, Debmalya Panigrahi

The field of learning-augmented algorithms seeks to use ML techniques on past instances of a problem to inform an algorithm designed for a future instance. In this paper, we introduce a novel model for learning-augmented algorithms inspired by online learning. In this model, we are given a sequence of instances of a problem and the goal of the learning-augme

S. Peluso, G. Lanzuisi, A. Comastri, M. Brusa

We present the X-ray analysis of coronal properties in a statistically representative sample of 23 mostly radio-quiet AGN from the SUBWAYS campaign (SUpermassive Black holes Winds in XrAYs), focusing on quasars at redshifts $0.1 < z < 0.4 $ and bolometric luminosities $2 \times 10^{44} <L_{bol}(erg/s) < 2 \times 10^{46}$. The main aim of this work is to inve

Henry Maxfield

The Schwarzian theory, which governs the universal low-energy dynamics of near-extremal black holes and the SYK model, can be characterised as an integral over a particular coadjoint orbit of the Virasoro group. We describe and solve a complete classification of all possible generalised Schwarzian theories, defined by integrals over any Virasoro coadjoint or

Katarina Bleau, Joachim Kopp, Jiheon Lee, Jorinde van de Vis

Tentative evidence suggests that the cores of massive neutron stars consist of deconfined quark matter. We argue that the formation of such a quark matter core during a galactic supernova could be accompanied by the emission of gravitational waves in the MHz band. These signals constitute a new target for high-frequency gravitational wave detectors, demonstr

Diego Godoy-Rivera, Desmond H. Grossmann, Tyler Richey-Yowell, Angela R. G. Santos

The ~ 200,000 stars observed by the Kepler mission have provided unprecedented constraints across astrophysics. With the advent of modern spectroscopic and photometric surveys, new limits in stellar characterizations are within reach. In this work, we report a compilation of atmospheric parameters (Teff, logg, and [M/H]) for the Kepler stars by crossmatching

Hongrui Gu, Zhou Fan, Bingqiu Chen, Xiaoying Pang

Halo star clusters serve as vital tracers for the formation and evolution of the Andromeda galaxy. In this work, we present physical parameters for 29 M31 halo star clusters, derived from a combination of spectroscopic and photometric data. Low-resolution spectra were acquired using the BFOSC spectrograph on the NAOC Xinglong 2.16-m telescope. For the photom

Xue Zhang, Yan-Kun Qu, Shuang-Xi Yi, Yu-Peng Yang

In this Letter, we establish a robust, physically motivated classification method using a Support Vector Machine (SVM) trained on a "gold-standard" sample of 24 GRBs with spectroscopically confirmed progenitors (associated SNe or KNe). By isolating the prompt main spike to excise contamination from extended emission, we derive a quantitative classification i

Ryan Campbell, Kristina Grolmusova, Lydia Kakampakou, Jeongjin Lee

Motivated by the EVA 2025 Data Challenge, we address the problem of predicting extreme rainfall in the eastern United States using data from a large ensemble of climate model runs. The challenge focuses on three quantities of interest related to the spatial extent and/or temporal duration of extreme rainfall, each requiring extrapolation. To tackle these que

Zhou-Quan Wan, Roeland Wiersema, Shiwei Zhang

Variational Monte Carlo (VMC) is a powerful and fast-growing method for optimizing and evolving parameterized many-body wave functions, especially with modern neural-network quantum states. In practice, however, the stochastic estimators that form the backbone of the method can become unstable or biased due to the presence of nodes, a ubiquitous feature of q

Anamaria Hell, Tatsuya Daniel

We propose the idea that our Universe is a realization among different possible branches, which can be observationally tested through the modified dispersion relation of the gravitational waves. We achieve this through a framework of spatially constrained vector fields. We show that the simplest realizations of such theories in flat and cosmological spacetim

Massimo Cipressi, Kevin Langhoff, Toby Opferkuch

We explore the potential of future high-energy lepton colliders to probe heavy vector resonances. At wakefield colliders, intense beam-beam interactions produce radiation, called beamstrahlung, which redistributes luminosity from the nominal energy across a broad spectrum of lower collision energies. We show that this effect, conventionally viewed as a drawb

Nico Schuster, Andrés N. Salcedo, Simon Bouchard, Dennis Frei

Scientists across all disciplines share a common challenge: the divide between their theoretical knowledge and the specialized skills and time needed to build interactive tools to communicate this expertise. While large language models (LLMs) offer unparalleled acceleration in code generation, they frequently prioritize functional syntax over scientific accu

Rachael M. Roettenbacher, John D. Monnier, Heidi Korhonen, Gregory W. Henry

The evolution of starspots of the giant primaries of RS CVn systems is typically detected indirectly with photometric and spectroscopic monitoring. These observations suggest slowly-evolving stellar surfaces and can constrain differential rotation as starspots move with respect to one another. However, starspot latitudes are difficult to constrain without re

Colin Littlefield, Krystian Ilkiewicz, Paul A. Mason, Peter Garnavich

A recent development in the study of magnetic cataclysmic variable stars (mCVs) has been the identification of asynchronously spinning mCVs with orbital periods <2 h that have significantly higher white dwarf spin-to-orbital period ratios than their longer-period counterparts. We report the discovery of two additional mCVs in this class. The first, Gaia21akb

Bob Knighton, Nathan McStay, Vit Sriprachyakul

We carefully examine the Polyakov path integral for strings on $\text{AdS}_3$ in superspace, both for type II and heterotic superstrings. We construct a free-field realization of the supersymmetric $\text{SL}(2,\mathbb{R})$ WZW model which manifestly preserves worldsheet supersymmetry and use this free-field realization to construct spectrally-flowed vertex

Andrés Anabalón, Horatiu Nastase, Carlos Nunez, Marcelo Oyarzo

We study ${\cal N}=4$ super Yang-Mills theory compactified on a circle at zero temperature, with VEVs for two scalar bilinears and three independent current sources. We show that type IIB supergravity provides a complete holographic description of this setup, admitting both supersymmetric and non-supersymmetric AdS soliton solutions, which are asymptotically

Li-Yuan Chiang, David Poland, Gordon Rogelberg

We develop a novel numerical bootstrap for unitary, crossing-symmetric conformal field theories, focusing on moment observables defined as weighted averages over conformal data. Providing a global and coarse-grained probe of the operator spectrum, this framework yields numerically rigorous bounds on the operator distribution using standard semidefinite progr

Federica Chiti, Jennifer L. van Saders, Oleg Kochukhov, Travis S. Metcalfe

We present the first spectropolarimetric time-series analysis of the Maunder Minimum analog HD 166620, using 12 nights of data from CFHT/SPIRou and a single epoch from CFHT/ESPaDOnS. While individual Stokes $V$ profiles exhibit no significant polarization signatures, we leverage the rotational coverage of the SPIRou dataset to compute a grand average LSD pro

Senrui Chen, Francesco Anna Mele, Marco Fanizza, Alfred Li

Continuous-variable systems enable key quantum technologies in computation, communication, and sensing. Bosonic Gaussian states emerge naturally in various such applications, including gravitational-wave and dark-matter detection. A fundamental question is how to characterize an unknown bosonic Gaussian state from as few samples as possible. Despite decades-

Robin Eappen, Pavel Kroupa

Mass discrepancies in galaxies are empirically known to appear only below a characteristic acceleration scale a0. Here we show that this behaviour is not limited to galaxies: it extends continuously across the full hierarchy of self-gravitating stellar systems, from gas-rich dwarfs and spirals to massive early-type galaxies, and further down to compact stell

José Calderón-Infante, Gongrui Cheng, Alvaro Herráez, Thomas Van Riet

We revisit codimension-one End-of-the-World curvature singularities that drive scalars to infinite distance in field-space and have appeared in the context of dynamical cobordisms. We confront them with Gubser's horizon and potential criteria and with the Maldacena--Nu\~nez criterion. Moduli-space flows do not admit a near-extremal horizon generalization. St

Brian Batell, Akshay Ghalsasi, Subhajit Ghosh, Mudit Rai

Thermal misalignment provides an alternative to the standard misalignment mechanism for the cosmological production of scalar dark matter. In this framework, feeble couplings to particles in the thermal bath generate a finite-temperature potential that drives the scalar towards large field values early in the radiation era, dynamically inducing the misalignm

Zachary J. Weiner

We present a simplified and general description of the high-redshift information in acoustic scale measurements from the cosmic microwave background and large-scale structure. The transverse distance interval between photon--baryon decoupling and a late epoch in the matter era provides an analytically tractable summary statistic thereof and a general diagnos

Jianrui Zhang, Yue Yang, Rohun Tripathi, Winson Han

Token pruning is essential for enhancing the computational efficiency of vision-language models (VLMs), particularly for video-based tasks where temporal redundancy is prevalent. Prior approaches typically prune tokens either (1) within the vision transformer (ViT) exclusively for unimodal perception tasks such as action recognition and object segmentation,

Kevin Qu, Haozhe Qi, Mihai Dusmanu, Mahdi Rad

Multimodal Large Language Models (MLLMs) have made impressive progress in connecting vision and language, but they still struggle with spatial understanding and viewpoint-aware reasoning. Recent efforts aim to augment the input representations with geometric cues rather than explicitly teaching models to reason in 3D space. We introduce Loc3R-VLM, a framewor

Kai Zou, Hongbo Liu, Dian Zheng, Jianxiong Gao

In this work, we present EchoGen, a unified framework for layout-to-image generation and image grounding, capable of generating images with accurate layouts and high fidelity to text descriptions (e.g., spatial relationships), while grounding the image robustly at the same time. We believe that image grounding possesses strong text and layout understanding a

Zhang Zhang, Shuqi Lu, Hongjin Qian, Di He

Building LLM-based agents has become increasingly important. Recent works on LLM-based agent self-evolution primarily record successful experiences as textual prompts or reflections, which cannot reliably guarantee efficient task re-execution in complex scenarios. We propose AgentFactory, a new self-evolution paradigm that preserves successful task solutions

Yigit Ekin, Yossi Gandelsman

We present a training-free framework for continuous and controllable image editing at test time for text-conditioned generative models. In contrast to prior approaches that rely on additional training or manual user intervention, we find that a simple steering in the text-embedding space is sufficient to produce smooth edit control. Given a target concept (e

Boon Suan Ho

We prove Ehrenborg's conjecture that every connected bipartite graph $G$ with parts of size $m$ and $n$ has at most $\frac{1}{mn}\prod_{v\in V(G)} \operatorname{deg}(v)$ spanning trees, and that equality holds if and only if $G$ is a Ferrers graph. The proof is fully formalized in Lean 4.

Wenlong Wang

Linear limit continuation was recently developed as a systematic and effective method for constructing numerically exact solitary waves from their respective linear limits. In this work, we apply the technique to two typical anisotropic harmonic traps in two-dimensional Bose-Einstein condensates to further establish the method and also to find more solitary

Niladri Shekhar Dutt, Zifan Shi, Paul Guerrero, Chun-Hao Paul Huang

Tokenization is a fundamental technique in the generative modeling of various modalities. In particular, it plays a critical role in autoregressive (AR) models, which have recently emerged as a compelling option for 3D generation. However, optimal tokenization of 3D shapes remains an open question. State-of-the-art (SOTA) methods primarily rely on geometric

D. T. Huong, Phung Van Dong, A. E. Carcamo Hernandez

We revisit the flipped standard model where a $U(1)_N$ gauge group is added, determining a dark charge through the weak isospin such as $D=T_3+N$, analogous to the electric charge and hypercharge relation. We find %discover that neutrino masses are appropriately generated by a radiative inverse seesaw mechanism mediated by dark fields. Dark matter candidate

Huajian Zeng, Abhishek Saroha, Daniel Cremers, Xi Wang

Synthesizing controllable 6-DOF object manipulation trajectories in 3D environments is essential for enabling robots to interact with complex scenes, yet remains challenging due to the need for accurate spatial reasoning, physical feasibility, and multimodal scene understanding. Existing approaches often rely on 2D or partial 3D representations, limiting the

Juan P Wachs

The CARE Workshop on Robotics and AI in Medicine, held on December 1, 2025 in Indianapolis, convened leading researchers, clinicians, industry innovators, and federal stakeholders to shape a national vision for advancing robotics and artificial intelligence in healthcare. The event highlighted the accelerating need for coordinated research efforts that bridg

Taylor Dupuy, David Zureick-Brown

We prove that the Dimension Conjecture implies the Jacobi Bound Conjecture.

Taylor Dupuy, David Zureick-Brown

We prove the Strong Jacobi Bound Conjecture for generically reduced components of differential schemes.

Yash Kulkarni, Mobina Tavangarifard, Daniyal Maroufi, Mohsen Khadem

This paper introduces a novel shape-sensing approach for Concentric Tube Steerable Drilling Robots (CT-SDRs) based on Optical Frequency Domain Reflectometry (OFDR). Unlike traditional FBG-based methods, OFDR enables continuous strain measurement along the entire fiber length with enhanced spatial resolution. In the proposed method, a Shape Sensing Assembly (

Vladimir Kulikov, Roni Paiss, Andrey Voynov, Inbar Mosseri

Controlled video generation has seen drastic improvements in recent years. However, editing actions and dynamic events, or inserting contents that should affect the behaviors of other objects in real-world videos, remains a major challenge. Existing trained models struggle with complex edits, likely due to the difficulty of collecting relevant training data.

Yuanjia Wang, Todd A. Brun

In the presence of qubit losses, the building blocks of fault-tolerant error correction (FTEC) must be revisited. Existing loss-tolerant approaches are mainly architecture-specific, and little attention has been given to optimizing the syndrome measurement sequences under loss. Schemes designed for the standard Pauli error model are not directly applicable b

Azalbek Boltaev, Tursunali Xamidov, Sanjar Shaymatov

In this work, we derive novel exact solutions describing Schwarzschild-like black holes (BHs) embedded in a Dehnen-type dark matter (DM) halo density profile and investigate their geometric, dynamical, and observational signatures arising from such geometries. We begin by analyzing the horizon structure and spacetime curvature invariants, as well as examinin

Alexander Soloviev, Michał Spaliński

We consider the dynamics of an expanding superfluid modeled by Mueller-Israel-Stewart theory coupled to a complex scalar field with a $U(1)$ symmetry that is spontaneously broken. This is a manageable theoretical setting for explorations of the chiral phase transition of expanding quark-gluon plasma. We study the late proper-time behavior of Bjorken flow in

Gao Zijun, Roquain Etienne

In a multiple testing task, finding an appropriate estimator of the proportion $\pi_0$ of non-signal in the data to boost power of false discovery rate (FDR) controlling procedures is a long-standing research theme, sometimes referred to as 'adaptive FDR control'. The interest in this theme has been reinforced in the recent years with conformal novelty detec

Hamza Rehman, Sanjar Shaymatov, Saddam Hussain, Tao Zhu

In this study, the behavior of high-frequency quasi-periodic oscillations (QPOs) is investigated around a Kerr black hole immersed in a uniform Bertotti-Robinson magnetic field. The motion of the test particle is analyzed by determining the geodesic equations and evaluating the corresponding orbital, radial, and vertical epicyclic frequencies. These fundamen

Stefan Kahler, Josef Obermaier

We consider random walk polynomial sequences $(P_n(x))_{n\in\mathbb{N}_0}\subseteq\mathbb{R}[x]$ given by recurrence relations of the form $P_0(x)=1$, $P_1(x)=x$ and $x P_n(x)=a_n P_{n+1}(x)+c_n P_{n-1}(x)\;(n\in\mathbb{N})$, where $a_n$ and $c_n$ are positive and sum up to $1$. $(P_n(x))_{n\in\mathbb{N}_0}$ is said to satisfy nonnegative linearization of pr

Davide Sipione, Giacomo Como, Gustav Nilsson

We consider a multi-commodity Dynamic Traffic Assignment (DTA) problem formulated as a network flow control problem on the Cell Transmission Model (CTM). The objective is to design optimal control policies using variable speed limits, ramp metering, and dynamic routing to regulate traffic evolution over time on a given limited-capacity transportation network