March 2026 arXiv papers — page 43

Chengkun Li, Cheryl Wang, Bianca Ziliotto, Merkourios Simos

Learning motor control for muscle-driven musculoskeletal models is hindered by the computational cost of biomechanically accurate simulation and the scarcity of validated, open full-body models. Here we present MuscleMimic, an open-source framework for scalable motion imitation learning with physiologically realistic, muscle-actuated humanoids. MuscleMimic p

Fangzhou Xie

Florida has experienced significant population increase in recent years, driven in part by domestic migration from other states. This study analyzes the migration patterns of voters in Florida between 2017 and 2022 using voter registration data. By examining demographic characteristics such as race/ethnicity, gender, age, and party affiliation, I identify tr

Daniele Fasano, Myriam Benisty, Jochen Stadler, Francesco Zagaria

ALMA observations have shown that substructures are ubiquitous in protoplanetary discs. A sub-group, the transition discs, shows large cavities and rings in dust continuum. Among these, some present very high contrast asymmetries possibly due to the presence of vortices. HD 34700A is a binary system featuring a cavity, a ring, and multiple spiral arms detect

Yihao Wang, Yang Miao, Wenshuai Zhao, Wenyan Yang

Articulation perception aims to recover the motion and structure of articulated objects (e.g., drawers and cupboards), and is fundamental to 3D scene understanding in robotics, simulation, and animation. Existing learning-based methods rely heavily on supervised training with high-quality 3D data and manual annotations, limiting scalability and diversity. To

Nikolai Ilinykh, Hyewon Jang, Shalom Lappin, Asad Sayeed

We study narrative coherence in visually grounded stories by comparing human-written narratives with those generated by vision-language models (VLMs) on the Visual Writing Prompts corpus. Using a set of metrics that capture different aspects of narrative coherence, including coreference, discourse relation types, topic continuity, character persistence, and

Yichao Huang, Xiaolin Zeng

We use supersymmetric localization and integration by parts to derive variational and convex correlation inequalities in statistical physics. As a primary application, we give an alternative proof of the monotonicity theorem for the $H^{2|2}$ supersymmetric hyperbolic sigma model. This recovers a result of Poudevigne without relying on probabilistic coupling

David Brunner, Marie Bordes, Elisabeth Mayrhuber, Stephan M. Winkler

To date, there is little research on how to design back marks to best support individual-level monitoring of uniform looking species like pigs. With the recent surge of machine learning-based monitoring solutions, there is a particular need for guidelines on the design of marks that can be effectively recognised by such algorithms. This study provides valuab

Pin-Tian Lyu, Yifan Zhu, Qing Xia, Guangrui Ding

Current single molecule methods either rely on fluorescence or lack chemical information. Here we report stimulated Raman photothermal encoded scattering (SRPSCAT) microscopy for quantitative bond-selective imaging of single-biomolecule structures and interactions in native environments. In this approach, scattering of the target molecule is modulated by the

Ning Ding, Keisuke Fujii, Toru Tamaki

Understanding tactical dynamics in badminton requires analyzing entire matches rather than isolated clips. However, existing badminton datasets mainly focus on short clips or task-specific annotations and rarely provide full-match data with dense multimodal annotations. This limitation makes it difficult to generate accurate shot captions and perform match-l

Joshua Krook

In this paper, I evaluate the risks of an AI criminal mastermind, an AI agent capable of planning, coordinating, and committing a crime through the onboarding of human collaborators ('taskers'). In heist films, a criminal mastermind is a character who plans a criminal act, coordinating a team of specialists to rob a bank, casino or city mint. I argue that AI

A. A. Rispo Constantinou, B. Magyari, G. Ianniruberto, E. van Ruymbeke

Traditional plastics demand a choice between durability (thermosets) and reprocessability (thermoplastics). Vitrimers are a recent class of polymer network combining both these qualities. Their increased cost of production can be offset by mixing them with a traditional thermoplastic; however, phase separation in such blends can lead to inhomogenous material

Partha Roop, Sobhan Chatterjee, Avinash Malik, Nathan Allen

Many Cyber Physical System (CPS) work in a safety-critical environment, where correct execution, reliability and trustworthiness are essential. Signal Temporal Logic (STL) provides a formal framework for checking safety-critical CPS. However, static verification of STL is undecidable in general, except when we want to verify using run-time-based methods, whi

Noah Steidle, Joppe De Jonghe, Mariya Ishteva

Tensors provide a structured representation for multidimensional data, yet discretization can obscure important information when such data originates from continuous processes. We address this limitation by introducing a functional Tucker decomposition (FTD) that embeds mode-wise continuity constraints directly into the decomposition. The FTD employs reprodu

Pedro Picchetti

In this paper I develop a breakdown frontier approach to assess the sensitivity of Local Average Treatment Effects (LATE) estimates to violations of monotonicity and independence of the instrument. I parametrize violations of independence using the concept of $c$-dependence from Masten & Poirier (2018) and allow for the share of defiers to be greater than ze

Xiangyang Luo, Qingyu Li, Yuming Li, Guanbo Huang

Recent advances in video generation models have achieved impressive results. However, these models heavily rely on the use of high-quality data that combines both high visual quality and high motion quality. In this paper, we identify a key challenge in video data curation: the Motion-Vision Quality Dilemma. We discovered that visual quality and motion inten

Marcus Armstrong, ZiWei Qiu, Huy Q. Vo, Arjun Mukherjee

Large Language Models (LLMs) possess a theoretical capability to model information density far beyond the limits of classical statistical methods (e.g., Lempel-Ziv). However, utilizing this capability for lossless compression involves navigating severe system constraints, including non-deterministic hardware and prohibitive computational costs. In this work,

Sooraj KC, Vivek Mishra

Structured reinforcement learning and stochastic optimization often involve parameters evolving on matrix Lie groups such as rotations and rigid-body transformations. We establish a representation-optimization dichotomy for Lie-algebra-parameterized Gaussian policy objectives in the Lie Group MDP class: the gradient Lipschitz constant L(R), governing step si

Alex Hoi Hang Chan, Neha Singhal, Onur Kocahan, Andrea Meltzer

Long-term behavioral monitoring of individual animals is crucial for studying behavioral changes that occur over different time scales, especially for conservation and evolutionary biology. Computer vision methods have proven to benefit biodiversity monitoring, but automated behavior monitoring in wild populations remains challenging. This stems from the lac

Quang-Tuan Dang

We study the stability and H\"older continuity of solutions to degenerate complex Monge--Amp\`ere equations associated with a (non-closed) big form on compact Hermitian manifolds. We also show that the solution is globally continuous when the reference form is the pullback of a Hermitian metric. As a consequence, we establish a uniform diameter bound for the

Pierre-Luc Dallaire-Demers, BTQ Technologies Team

Bitcoin already faces a quantum threat through Shor attacks on elliptic-curve signatures. This paper isolates the other component that public discussion often conflates with it: mining. Grover's algorithm halves the exponent of brute-force search, promising a quadratic edge to any quantum miner of Bitcoin. Exactly how large that edge grows depends on fault-t

Xuesong Bai, Jonathan Touboul, Thomas G. Fai

Robust oscillations play crucial roles in a wide variety of biological processes and are often generated by deterministic mechanisms. However, stochastic fluctuations often generate complex perturbations of these deterministic oscillations, potentially strengthening or weakening their robustness. In this paper, we study bistable phosphorylation as a mechanis

Inês Valentim, Nuno Antunes, Nuno Lourenço

Neuroevolution automates the complex task of neural network design but often ignores the inherent adversarial fragility of evolved models which is a barrier to adoption in safety-critical scenarios. While robust training methods have received significant attention, the design of architectures exhibiting intrinsic robustness remains largely unexplored. In thi

Giuseppe Cuono, Srdjan Stavric, Javier Sivianes Castano, Julen Ibanez-Azpiroz

NiI2 is an exotic van der Waals material in which a noncollinear spin spiral breaks spatial inversion symmetry without sizeable structural distortion, generating improper ferroelectric polarization, and stabilizing p-wave magnetic states with electron-volt-scale odd-parity spin splitting. Using first-principles calculations, here we establish that nonlinear

R. Z. Jiang, Z. L. Li, Y. J. Li

We propose a method to accurately calculate the momentum distributions and the phase distributions of the probability amplitude for both boson and fermion pair production in a spatially homogeneous and time-dependent electric field. Applying this method to multiphoton pair production in a circularly polarized electric field rotating around the $z$-axis, we c

Arun Kumar Jaiswal, Di Wang, Ji Soo Lim, Shruti Roy

Interfacial charge transfer (ICT) provides a powerful route to engineer electronic phases in correlated oxide heterostructures, yet predictive design principles remain elusive. Here, we systematically investigate superlattices composed of the 5d spin-orbit coupled semimetal SrIrO3 and a series of correlated 3d perovskites (LaMnO3, LaFeO3, LaCoO3, and NdNiO3)

Jerzy Wojciechowski

The longstanding conjecture of Halin characterizing the existence of normal spanning trees in infinite graphs has been recently proved by Max Pitz [3]. A critical step in the proof involves the construction of dominated torsos, whose properties are essential to the overall proof. In this note, we provide a correction to the proof of a key property of this co

Jie Deng, Haibin Wang, Bin Zhou

In this paper, we prove a Brezis-Merle type inequality for $k$-convex functions vanishing on the boundary. As an application, we establish an Alexandrov-Bakelman-Pucci type estimate for the intermediate Hessian equation. Furthermore, we establish a concentration-compactness principle for the blow-up behavior of solutions to the mean field type $k$-Hessian eq

Koldo Basterretxea, Jon Gutiérrez-Zaballa, Javier Echanobe

The use of hyperspectral imaging (HSI) in autonomous driving (AD), while promising, faces many challenges related to the specifics and requirements of this application domain. On the one hand, non-controlled and variable lighting conditions, the wide depth-of-field ranges, and dynamic scenes with fast-moving objects. On the other hand, the requirements for r

Masahiro Kato

We propose a method for constructing distribution-free prediction intervals in nonparametric instrumental variable regression (NPIV), with finite-sample coverage guarantees. Building on the conditional guarantee framework in conformal inference, we reformulate conditional coverage as marginal coverage over a class of IV shifts $\mathcal{F}$. Our method can b

Yuji Tachikawa, Keita Tsuji, Masataka Watanabe

We study wavepackets of exotic excitations after two-dimensional fermions are scattered by the boundary condition constructed by Maldacena and Ludwig, which turns elementary excitations into exotic fractionally-charged objects. They are of interest in the s-wave approximation of the fermion-monopole scattering in four-dimensional QED and of the multi-channel

Giampaolo Bovenzi, Domenico Ciuonzo, Jonatan Krolikowski, Antonio Montieri

Network Traffic Classification (NTC) increasingly relies on data-driven models, yet its practical deployment is often constrained by limited labeled data, strict privacy requirements, and the cost of collecting representative traffic traces. While Network Traffic Generation (NTG) provides an effective means to mitigate data scarcity, conventional generative

Florian Fürnsinn, Danylo Radchenko, Wadim Zudilin

We prove a general statement about the integrality of the sequences generated by a recursion of the following form: $nu_n$ equals a linear combination of $u_{n-1},u_{n-2},\dots,u_0$ with polynomial coefficients in $n$ of special form. This includes a conjectural integrality of the sequence related to the H\"ormander-Bernhardsson extremal function, for which

Shobha Singh, Shivam Rathod, Rong chen, Lipika

In recent years, layered kagome magnets have emerged as promising platforms for Berry-curvature engineering and unconventional transport phenomena. Here, we present the single-crystal growth, magnetization, and electrical transport characterizations of the van der Waals-like layered antiferromagnet GdTi3Bi4. The system exhibits pronounced field-induced first

Ritesh Srivastava, Sumati Surya

We explore different implementations of the quantum Bell causality (QBC) condition in the quantum sequential growth (QSG) dynamics of causal set quantum gravity, for non-commuting transition operators. Assuming a non-singular dynamics we show that for the two most natural choices of operator orderings for the QBC, the transition operator algebra reduces to a

Yufeng Yang, Xianfang Zeng, Zhangqi Jiang, Fukun Yin

Image restoration under real-world degradations is critical for downstream tasks such as autonomous driving and object detection. However, existing restoration models are often limited by the scale and distribution of their training data, resulting in poor generalization to real-world scenarios. Recently, large-scale image editing models have shown strong ge

Pietro Dell'Oglio, Alessandro Bondielli, Francesco Marcelloni, Lucia C. Passaro

In recent years, fake news detection has received increasing attention in public debate and scientific research. Despite advances in detection techniques, the production and spread of false information have become more sophisticated, driven by Large Language Models (LLMs) and the amplification power of social media. We present a critical assessment of 12 rep

Pei Chen, Geng Hong, Xinyi Wu, Mengying Wu

The emergence of Large Language Model-enhanced Search Engines (LLMSEs) has revolutionized information retrieval by integrating web-scale search capabilities with AI-powered summarization. While these systems demonstrate improved efficiency over traditional search engines, their security implications against well-established black-hat Search Engine Optimizati

Jakob Paul Zimmermann, Gerrit Holzbach, David Lerch

Object detectors deployed in safety-critical environments can fail silently, e.g. missing pedestrians, workers, or other safety-critical objects without emitting any warning. Traditional Out Of Distribution (OOD) detection methods focus on identifying unfamiliar inputs, but do not directly predict functional failures of the detector itself. We introduce Know

Linxiao Li, Zhixiang Lu

As the Web transitions from static retrieval to generative interaction, the escalating environmental footprint of Large Language Models (LLMs) presents a critical sustainability challenge. Current paradigms indiscriminately apply computation-intensive strategies like Chain-of-Thought (CoT) to billions of daily queries, causing LLM overthinking, a redundancy

Zebedeus F. Osseweijer, Lumen Eek, Harold J. W. Zandvliet, Pantelis Bampoulis

We present an in-depth study of end states in honeycomb nanoribbons, focusing on the interplay between nanoribbon termination, chiral symmetry, and complex next-nearest-neighbor hopping in the framework of the Haldane model. Although previous work has identified zero-dimensional end states in such systems, this analysis is incomplete. Here, we systematically

Claudia De Lazzari, Francesco Stocco, Edoardo Signorini, Giacomo Fregona

Quantum Key Distribution (QKD) protocols require Information-Theoretically Secure (ITS) authentication of the classical channel to preserve the unconditional security of the distilled key. Standard ITS schemes are based on one-time keys: once a key is used to authenticate a message, it must be discarded. Since QKD requires mutual authentication, two independ

Moazzam Umer Gondal, Hamad ul Qudous, Asma Ahmad Farhan, Sultan Alamri

Accurate short-term air-quality forecasting is essential for public health protection and urban management, yet many recent forecasting frameworks rely on complex, data-intensive, and computationally demanding models. This study investigates whether lightweight and interpretable forecasting approaches can provide competitive performance for hourly PM2.5 pred

Xuzhi Wang, Xinran Wu, Song Wang, Lingdong Kong

Indoor monocular semantic scene completion (MSSC) is notably more challenging than its outdoor counterpart due to complex spatial layouts and severe occlusions. While transformers are well suited for modeling global dependencies, their high memory cost and difficulty in reconstructing fine-grained details have limited their use in indoor MSSC. To address the

Benjamin Hollering, Elia Mazzucchelli, Matteo Parisi, Bernd Sturmfels

Landau analysis in momentum twistor space can be formulated as the study of varieties of lines in three-dimensional projective space, together with their projections and discriminants. Within this framework, we define enumerative invariants (LS degrees) that count leading singularities. Leading Landau singularities (LS discriminants) arise as discriminants d

Gaia Nicosia, Andrea Pacifici, Ulrich Pferschy

A new class of multi agent single machine scheduling problems is introduced, where each job is associated with a self interested agent with a utility function decreasing in completion time. We aim to achieve a fair solution by maximizing the minimum utility across all agents. We study the problem's complexity and propose solution methods for several variants

Qi Zhang, Denis Rozumny, Francesco Girlanda, Sezer Karaoglu

We propose Unblur-SLAM, a novel RGB SLAM pipeline for sharp 3D reconstruction from blurred image inputs. In contrast to previous work, our approach is able to handle different types of blur and demonstrates state-of-the-art performance in the presence of both motion blur and defocus blur. Moreover, we adjust the computation effort with the amount of blur in

Olavi Kiuru, Joonas Nättilä, Risto Paatelainen, Aleksi Vuorinen

The magnetospheres of magnetars, a class of highly magnetized neutron stars, host magnetic fields exceeding the Schwinger limit, where Quantum Electrodynamics (QED) becomes nonlinear. In such environments, QED scattering processes are strongly modified, which may affect plasma dynamics. In this work, we apply a formalism originally developed for the study of

Zhen Wang, Mohammad Reza Hesamzadeh, Shudian Zhao, Jan Kronqvist

The presence of integer variables in the European day-ahead electricity market renders the social welfare maximization problem non-convex and non-differentiable, making classical marginal pricing theoretically inconsistent. Existing pricing mechanisms often struggle to balance revenue adequacy with incentive compatibility, typically relying on discriminatory

Jannis Vamvas, Ignacio Pérez Prat, Angela Heldstab, Dominic P. Fischer

Recent strategies for low-resource machine translation rely on LLMs to generate synthetic data based on text in higher-resource languages. We revisit this idea for Romansh, a language with 6 distinct varieties. LLMs tend to confuse these varieties when translating into Romansh, but they are quite good at translating out of Romansh into a high-resource langua

Fedor B. Lyudogovskiy

We develop a directional formalism for the partition graph G_n based on several canonical reference sets: the main chain, the self-conjugate axis, the spine, and the boundary framework. For each such set S, the graph distance d_S induces a shell structure and a local trichotomy of edges into inward, outward, and level classes. Passing from edges to paths, we

Jingwei Chen, Jun Ye, Feng Chen

This paper establishes a stochastic maximum principle for optimal control problems governed by time-changed forward-backward stochastic differential equations with L\'evy noise. The system incorporates a random, non-decreasing operational time (the inverse of an $\alpha$-stable subordinator) to model phenomena like trapping events and subdiffusion. Using a d

Daniel Collins, Carolina Moreira Ferrera, Ismael L. Paiva, Sandu Popescu

We show that networks of quantum frames of reference, in which one frame may be used to produce multiple other frames that in their turn prepare systems which may interact with one another, have counterintuitive properties that make following the exchange of conserved quantities very subtle, and raise questions about the very nature of conserved quantities.

Padma Priyanka, Avhishek Chatterjee, Sheetal Kalyani

Quantum communication networks require transmission of high-fidelity, uncoded qubits for applications such as entanglement distribution and quantum key distribution. However, current implementations are constrained by limited buffer capacity and qubit decoherence, which degrades qubit quality while waiting in the buffer. A key challenge arises from the stoch

Ling Zhang, Boxiang Yun, Ting Jin, Qingli Li

Prediction of genetic biomarkers, e.g., microsatellite instability in colorectal cancer is crucial for clinical decision making. But, two primary challenges hamper accurate prediction: (1) It is difficult to construct a pathology-aware representation involving the complex interconnections among pathological components. (2) WSIs contain a large proportion of

Motonari Kambara, Koki Seno, Tomoya Kaichi, Yanan Wang

We address language-conditioned robotic manipulation using flow-based trajectory generation, which enables training on human and web videos of object manipulation and requires only minimal embodiment-specific data. This task is challenging, as object trajectory generation from pre-manipulation images and natural language instructions requires appropriate ins

Harrison Katz

Model retraining is usually treated as an ongoing maintenance task. But as Harrison Katz now argues, retraining can be better understood as approximate Bayesian inference under computational constraints. The gap between a continuously updated belief state and your frozen deployed model is "learning debt," and the retraining decision is a cost minimization pr

Yannic Steenbeck

We prove that there is only one translation-invariant Gibbsian point process w.r.t. to a chosen interaction if any of them satisfies a certain bound related to concentration-of-measure. This concentration-of-measure bound is e.g. fulfilled if a corresponding modified logarithmic Sobolev inequality holds. In particular, for natural examples with non-uniquenes

Esteban Currás-Rivera, Guido Haefeli, Federico Ronchetti

In the context of the Scintillating Fibre (SciFi) Tracker for the LHCb Upgrade 2, radiation-induced damage in silicon photomultipliers (SiPMs) has been studied over a wide temperature range, from room temperature down to 100 K. With the LHCb detector Upgrade 1, installed during the LHC's Long Shutdown 2 (LS2) (2019-2021), the first large-scale SciFi tracker

Lucia Caporaso, Amos Turchet

We study the algebraic exceptional set for surfaces (S,B) of log general type, when B has at least three irreducible components; we prove that in most cases it is finite or empty.

Peter Schneider

In all forms of the local Langlands program the abelian category of smooth representations of p-adic groups G in vector spaces over a field k plays a central role. Of particular interest are its finiteness properties. If the field k has characteristic zero then, by work of Bernstein, this category is most of the time locally noetherian. But if the field has

Benjamin Redden, Hui Wang, Shuyan Li

Understanding directed temporal interactions in multivariate time series is essential for interpreting complex dynamical systems and the predictive models trained on them. We present Causal-INSIGHT, a model-agnostic, post-hoc interpretation framework for extracting model-implied (predictor-dependent), directed, time-lagged influence structure from trained te

Yihe Wang, Yu Yu

We present HEALFormer, a transformer-based neural network architecture for weak gravitational lensing mass mapping that reconstructs convergence maps from incomplete and noisy shear observations on the celestial sphere. The model operates directly on the Hierarchical Equal Area isoLatitude Pixelization and employs learnable mask tokens to handle arbitrary su

Fangli Quan, Zhong-Wu Xia, Rui Ding, Qiyuan Pan

We obtain exact expressions for the quasinormal modes (QNMs) of the massive scalar, fermionic and vector perturbations around a rotating BTZ-like black hole in the Einstein-bumblebee gravity. We find that the Lorentz symmetry breaking (LSB) parameter $\ell$ leaves its imprint only on the imaginary parts of the quasinormal frequencies and the corresponding pe

Mohamed Eltahir, Ahmed O. Ibrahim, Obada Siralkhatim, Tabarak Abdallah

Vision-Language Models (VLMs) are powerful open-set reasoners, yet their direct use as anomaly detectors in video surveillance is fragile: without calibrated anomaly priors, they alternate between missed detections and hallucinated false alarms. We argue the problem is not the VLM itself but how it is used. VLMs should function as anomaly proposers, generati

Kakei Yamamoto, Martin J. Wainwright

We study statistical estimation in a student--teacher setting, where predictions from a pre-trained teacher are used to guide a student model. A standard approach is to train the student to directly match the teacher's outputs, which we refer to as student soft matching (SM). This approach directly propagates any systematic bias or mis-specification present

Vittorio Barlucchi, Alex Gnech, Scilla Degl'Innocenti, Laura Elisa Marcucci

The astrophysical $S$-factor for the proton-proton fusion is calculated in the low-energy regime for a variety of nuclear interactions and consistent nuclear currents, derived within chiral effective field theory. We estimate, for the first time, the theoretical uncertainty on the $S$-factor due to the truncation of the chiral expansion of the currents using

Yuan Zhang, Sihao Dou, Kai Hu, Shuhua Deng

Endoscopic video analysis is essential for early gastrointestinal screening but remains hindered by limited high-quality annotations. While self-supervised video pre-training shows promise, existing methods developed for natural videos prioritize dense spatio-temporal modeling and exhibit motion bias, overlooking the static, structured semantics critical to

Keming Ye, Zhou Zhao, Fan Wu, Shengyu Zhang

Auto-regressive (AR) models have recently made notable progress in image generation, achieving performance comparable to diffusion-based approaches. However, their computational intensity and sequential nature impede on-device deployment, causing disruptive latency. We address this via a cloud-device collaboration framework \textbf{CIAR}, which utilizes on-d

Xiang Li, Bikun Wang, John Zhang, Jianjun Wang

Motion planning in dynamic urban environments requires balancing immediate safety with long-term goals. While diffusion models effectively capture multi-modal decision-making, existing approaches treat trajectories as monolithic entities, overlooking heterogeneous temporal dependencies where near-term plans are constrained by instantaneous dynamics and far-t

Elhabib Jaloum, Omar Bachain, Mohamed Amazioug, Nazek Alessa

In this work, we derive the bipartite density matrix for the $e^{+}e^{-} \rightarrow J/\psi \rightarrow \Lambda(p\pi^{-}) \bar{\Lambda}(\bar{p}\pi^{+})$ process at BESIII. We evaluate the impact of mass corrections and memory effects (within Markovian and non-Markovian regimes) on quantum correlations even beyond entanglement. The dependence of these quantum

Shangkun Huang, Huan Shen, Wei Zou, Yunzhang Chen

Speech LLM-based ASR often struggles with named entities and long-tail words due to strong internal language-model priors. Retrieval-augmented biasing can help, but its effectiveness depends on accurate hotword localization in full-utterance speech under weak supervision. We propose CLAR, a dual-encoder speech-text retriever that uses Continuous Integrate-an

Songhao Liu, Qiman Shao, Jingyu Xu

We establish a Cram\'er-type moderate deviation theorem for double-index permutation statistics (DIPS). To the best of our knowledge, previous results only provided Berry-Esseen type bounds for DIPS, which cannot yield moderate deviation results and are insufficient to capture the optimal convergence rates for some relatively sparse DIPS. Our result overcome

CMS Collaboration

A measurement is presented of dijet angular distributions in proton-proton collisions at $\sqrt{s}$ = 13 TeV, using data collected with the CMS detector at the CERN LHC and corresponding to an integrated luminosity of 138 fb$^{-1}$. For the first time, the dijet angular distributions, corrected for detector effects, are compared with the predictions of pertu

Marco De Paoli, Xiaojue Zhu

Buoyancy-driven convection in porous media governs heat and mass transport in a wide range of natural and engineered systems, from groundwater aquifers and geothermal reservoirs to carbon storage in geological formations and flows through planetary interiors. Yet the transient regime, in which fingering flows emerge and transport is strongly enhanced, is sti

Yuxiang Liu, Artan Sheshmani, Shing-Tung Yau

In this paper, we study the homogeneous components of the Chern--Schwartz--MacPherson (CSM) classes of Schubert cells. We prove that, under suitable conditions, each such component is represented by an irreducible subvariety. In particular, our result extends Huh's result \cite{Huh} by relaxing the regularity assumption on log resolutions. As a consequence,

Tommy Walker Mackay, Mingtong Xu, Shahrokh F. Shariat, Roger Sewell

In a dataset of 423 patients who had had radical prostatectomy for localised prostate cancer we estimated the apparent Shannon information (ASI) about time to biochemical recurrence in various subsets of the available pre-op variables using a Bayesian Gamma-power-mixture survival regression model. In all the subsets examined the ASI was positive with posteri

Benjamin Hollering, Elia Mazzucchelli, Matteo Parisi, Bernd Sturmfels

Momentum twistors for scattering amplitudes in particle physics are lines in three-space. We develop Landau analysis for Feynman integrals in this setting. The resulting discriminants and resultants are identified with Hurwitz and Chow forms of incidence varieties in products of Grassmannians. We study their degrees and factorizations, and the kinematic regi

Eng Keat Hng, Meng Ji, Ander Lamaison

More than thirty years ago, Erd\H{o}s, Faudree, Rousseau, and Schelp posed a fundamental question in extremal graph theory: What is the optimal constant $c_k$ such that $r(C_{2k+1}, G) \le c_k m$ for any graph $G$ with $m$ edges and no isolated vertices? In this paper, we make a significant step towards answering this question by proving that $r(C_{2k+1}, G)

Roméo Kouassi Konan, Auguste Aman

We address the optimal control of stochastic Volterra integral equations with delay through the lens of Hida-Malliavin calculus. We show that the corresponding adjoint processes satisfy an anticipated backward stochastic Volterra integral equation (ABSVIE), and, exploiting this structure, we establish both necessary and sufficient stochastic maximum principl

Geri Gokaj, Marvin Künnemann, Sabine Storandt, Carina Truschel

The Pareto sum of two-dimensional point sets $P$ and $Q$ in $\mathbb{R}^2$ is defined as the skyline of the points in their Minkowski sum. The problem of efficiently computing the Pareto sum arises frequently in bi-criteria optimization algorithms. Prior work establishes that computing the Pareto sum of sets $P$ and $Q$ of size $n$ suffers from conditional l

Sagar Basak, Gloria Paoli, Rossano Sannipoli, Sheela Verma

In this article, we study the mixed Steklov--Neumann eigenvalue problem on doubly connected domains. First, we show that among all doubly connected domains in $\mathbb{R}^n$ of the form $B_{R_2}\setminus \overline{B_{R_1}}$, where $B_{R_1}$ and $B_{R_2}$ are open balls of fixed radii satisfying $\overline{B_{R_1}} \subset B_{R_2}$, the first non-zero Steklov

Oihan Joyot, Zoé Ferrand, Fernando Muzzopappa, Pierre Weiss

Biomolecular condensates organize biochemical processes by spatially concentrating molecules while allowing for dynamic exchange with their surroundings. However, transport across their interface can be strongly attenuated, leading to enhanced retention and preferential internal mixing. Two key mechanisms have been proposed to describe this behavior: biased

Peijin Zhang, Anastasia Kuske, Bin Chen, Mengjia Xu

Strong solar activity is often accompanied by a variety of radio bursts. These bursts are valuable diagnostics of coronal and heliospheric processes and also have potential applications in space weather monitoring and forecasting. However, space weather applications require low-latency, high-sensitivity radio burst recording and reporting capabilities, which

Nurjahan Khatun, Joe F. Khoury, Agnes C. Nkele, Lingyu Wang

Phase transitions between crystalline solids occur either through the nucleation and growth mechanism, a process that is slow and destructive or through the diffusion-less and order preserving Martensitic route. In both organic and inorganic materials, Martensitic transformations are known to occur only between phases with crystalline symmetry. We demonstrat

Rubén Moreno-Bote

If the universe follows a specific design, then a central question is which cost function is optimized by the observed forces. This is the problem of inverse optimal control, or inverse reinforcement learning, in which a reward function is inferred from the dynamics of the observed system. We first establish the {\em least cost principle}, whereby the laws o

Matilde Coello-Guzmán, Víctor A. Pinto, Roberto E. Navarro, Pablo S. Moya

Using Parker Solar Probe measurements of the solar wind, we demonstrate that $β_{\parallel}$ is the main driver that determines which instabilities limit proton temperature anisotropy. At radial distances from 10 to 30 solar radii, $β_{\parallel}<1$ drives electromagnetic ion-cyclotron and parallel firehose instabilities, in contrast to the situation at 1 as

Wei Lian, Fei Ma, Hang Pan, Zhesen Cui

Achieving globally optimal point cloud registration under partial overlaps and large misalignments remains a fundamental challenge. While simultaneous transformation ($\boldsymbol{\theta}$) and correspondence ($\mathbf{P}$) estimation has the advantage of being robust to nonrigid deformation, its non-convex coupled objective often leads to local minima for h

Omar Elezabi, Eduard Zamfir, Zongwei Wu, Radu Timofte

Text-guided diffusion models have advanced image editing by enabling intuitive control through language. However, despite their strong capabilities, we surprisingly find that SOTA methods struggle with simple, everyday transformations such as rain or blur. We attribute this limitation to weak and inconsistent textual supervision during training, which leads

Giovanni Catania, Aurélien Decelle, Suhanee Korpe

We introduce and solve a teacher-student formulation of the symmetric binary Perceptron, turning a traditionally storage-oriented model into a planted inference problem with a guaranteed solution at any sample density. We adapt the formulation of the symmetric Perceptron which traditionally considers either the u-shaped potential or the rectangular one, by i

Victor Laliena

It is shown that the nonselfadjoint (and non-normal) linear ordinary differential operators of a certain class are spectral operators of scalar type in the sense of Dunford and Bade. Operators of this kind appear in physical problems such as the scattering of spin waves by magnetic solitons.

Omer Offen

In this short note we observe that the gamma factor defined by Gelfand and Kazhdan coincides with the Rankin-Selberg root number defined by Jacquet, Piatetskii-Shapiro and Shalika.

L. Lastrucci, M. Grassi, A. Triossi, J. Hu

In particle physics, experiments generate substantial amounts of data that can be difficult to process without preliminary scaling. To avoid losing potentially crucial data, experimental collaborations are studying novel techniques for real-time data processing to extract features for further physics analysis. A common approach, especially in neutrino physic

Shakya Jayakody, Youpeng Zhao, Chinmay Dhanraj Nehate, Jun Wang

The rise of million-token, agent-based applications has placed unprecedented demands on large language model (LLM) inference services. The long-running nature of these tasks increases their susceptibility to hardware and software faults, leading to costly job failures, wasted resources, and degraded user experience. The stateful key-value (KV) cache, which g

Adrian Kirkeby, Trygve Halsne

Starting from the free surface Euler equations, we derive a leading-order system in terms of surface variables, depending on the surface current and on the bathymetry through the depth-dependent Dirichlet-to-Neumann (DN) operator. The resulting system is shown to be well-posed using the theory of hyperbolic systems of pseudo-differential operators. We then c

Huan Shen, Yingao Wang, Shangkun Huang, Wei Zou

Turn-taking modeling is fundamental to spoken dialogue systems, yet its evaluation remains fragmented and often limited to binary boundary detection under narrow interaction settings. Such protocols hinder systematic comparison and obscure model weaknesses across conversational conditions. We present CoDeTT, a context-aware decision benchmark for turn-taking

E. E. Perepelkin, B. I. Sadovnikov, N. G. Inozemtseva, A. S. Medvedev

By applying the nonlinear Legendre transform to the continuity equation, this paper derives exact solutions to the Schr\"odinger equation and the equations of continuum mechanics. A generalized Maxwell distribution has been used as the momentum density function. Explicit expressions for the vector fields of time independent flows, density distributions, quan

J. Daisie Rock

Motivated by the desire for a new kind of approximation, we define a type of localization called pixelation. We present how pixelation manifests in representation theory and in the study of sites and sheaves. A path category is constructed from a set, a collection of "paths" into the set, and an equivalence relation on the paths. A screen is a partition of t

Arkady Pikovsky

The interaction between phase oscillators is conservative if the phase volume is conserved throughout the dynamics. We derive a general condition, based on the notion of a pair-Hamiltonian, for the pairwise couplings to be conservative. The conservative networks with Winfree-type and Kuramoto-Daido-type couplings are also discussed. It is demonstrated that a

Jinshui Zhang, Zane Mannings, Chris Dittmer, Angel V Peterchev

Static synchronous compensators (STATCOMs) manage reactive power compensation in modern power grids and have become essential for the integration of renewable energy sources such as wind farms. Cascaded H bridges have become the preferred topology for high-power STATCOMs, but balancing module capacitor voltages remains a persistent challenge. Conventional so

Daniela O. Bastos, André M. R. Soares, Leonor Andrade, Randy K. Dumas

Accurately measuring the magnetocaloric effect is necessary to foster the development of magnetic refrigeration devices. However, current methods are inconvenient, requiring different instruments to measure each individual property or a custom-made setup. By measuring the time-varying magnetization in a commercially available VersaLab\textsuperscript{\textre