April 2026 arXiv papers — page 128

Felicia Bader, Philipp Seeböck, Anastasia Bartashova, Ulrike Attenberger

In diagnostic reports, experts encode complex imaging data into clinically actionable information. They describe subtle pathological findings that are meaningful in their anatomical context. Reports follow relatively consistent structures, expressing diagnostic information with few words that are often associated with tiny but consequential image observation

Subhradip Chakraborty, Ankur Singh, Akhilesh R. Jaiswal

With the rapid growth of deep neural networks (DNNs), compute-in-memory (CIM) has emerged as a promising energy-efficient paradigm for accelerating multiply-and-accumulate (MAC) operations. Yet, current CIM architectures are largely limited to dot-product computations and struggle to efficiently support general-purpose matrix operations, such as transpose, e

Ahmed Bou-Rabee, Yuval Peres, Ecaterina Sava-Huss

We analyze an optimal stopping problem for random walk in random scenery on general graphs, and determine when it has a finite optimum. We use this to extend a theorem of Levine, Murugan, Peres, and Ugurcan [2016]. They proved that on a vertex-transitive graph, the divisible sandpile with i.i.d. initial masses of mean $\mu$ stabilizes almost surely if $\mu <

Haode Yan, Kangquan Li

Niho exponents have found important applications in sequence design, coding theory, and cryptography. Determining the differential spectrum of a power function with Niho exponent is a topic of considerable interest. In this paper, we investigate the power function $F(x) = x^{3q - 2}$ over $\mathbb{F}_{q^2}$, where $q = 2^m$ and $m\geq 4$ is an even integer.

Shangzhe Li, Weitong Zhang

We study value adaptation in offline-to-online reinforcement learning under general function approximation. Starting from an imperfect offline pretrained $Q$-function, the learner aims to adapt it to the target environment using only a limited amount of online interaction. We first characterize the difficulty of this setting by establishing a minimax lower b

Jianzhong Du, L. Jeff Hong

This paper studies the variance dichotomy in continuous simulation optimization (CSO). Existing literature shows a sharp contrast between deterministic CSO and stochastic CSO, with convergence rates in stochastic settings appearing insensitive to the magnitude of the noise variance. However, this asymptotic view does not fully explain the behavior of CSO und

Lorenzo Valentini, Diego Forlivesi, Andrea Talarico, Marco Chiani

The quantum Internet envisions a network where information is transmitted through entanglement, with Einstein-Podolsky-Rosen (EPR) pairs serving as one of the fundamental carriers. In this work, we propose a framework for dimensioning quantum memories capable of storing distilled EPR pairs useful to transmitting and manage quantum error correcting codes. Usi

Jaime Iranzo, Pedro Jódar, Eugene V. Koonin, Susanna Manrubia

Gene-sharing networks provide a powerful framework to study the evolution of viruses and mobile genetic elements. These bipartite networks, which link genes to the genomes that contain them, exhibit characteristic degree distributions: a scale-free distribution for genes and an exponential-like decay for genomes. Here, we propose a mechanistic model that exp

A. Kouloumvakos, D. Lario, G. M. Mason, A. Vourlidas

We present a detailed investigation of the shock properties associated with solar energetic particle (SEP) events that exhibit a concave (``nose-like'') shape in their energy spectrogram, characterized by inverse velocity arrival (IVA) of the particles, where high-energy particles arrive later than mid-energy ones. Using measurements from Solar Orbiter and P

Luca Sartori Boni, Mohamed Moursi, Norbert Wehn, Bilal Hammoud

Oil spills represent a severe threat, making early-stage thickness estimation crucial for guiding remediation efforts. Unmanned Aerial Vehicles (UAVs) are an attractive platform for environmental monitoring. However, due to their limited computation and power budgets, real-time onboard processing requires optimized algorithms or lightweight machine learning

Jiwan Jiang, Soyoung Ahn

This study develops a dynamic fundamental diagram (FD) framework tailored to mixed traffic environments comprising automated vehicles (AVs) and human-driven vehicles (HDVs). Describing function analysis is employed to derive approximate linear transfer functions for nonlinear HDV car-following models. A sequence-based stochastic dynamic FD is then formulated

Umberto Pelliccia, Alberto M. Ruiz, Diego López-Alcalá, Gonzalo Abellán

Twist-engineering of topological phases in two-dimensional materials offers a powerful route to modulate electronic structure beyond conventional strain or chemical control. In particular, group 15 (pnictogens) monolayers such as bismuthene provide an ideal platform due to their strong intrinsic spin-orbit coupling (SOC) and robust topological character. Her

You Rim Choi, Subeom Park, Hyung-Sin Kim

As AI moves from data centers to robots and wearables, scaling ever-larger models becomes insufficient. Physical AI operates under tight latency, energy, privacy, and reliability constraints, and its performance depends not only on model capacity but also on how signals are acquired through controllable sensors in dynamic environments. We present Artificial

Mohammed M. Al Ezzi, Na Xin, Yanmeng Shi, Shuigang Xu

Many-body effects in condensed matter yield novel quantum states when the electronic density of states is enhanced. A vivid example is flat bands, which suppress kinetic energy and let interactions dominate, when they are filled with an integer number of electrons in moire systems. Yet flat bands and commensurate fillings are not the only conditions for corr

Luca-Stefan Pirvu, Bogdan-Alexandru Maciuca, Andrei-Ciprian Rabu, Adrian-Marius Dumitran

Graph theory is a cornerstone of Computer Science education, yet entry-level students often struggle to map abstract node-edge relationships to practical applications. This paper presents the design and architecture of a Minecraft-based educational tool specifically built to visualize graph traversal and shortest-path algorithms. We propose a three-layer sys

Zoe De Simone, Angie Boggust, Fredo Durand, Ashia Wilson

Text-to-image (T2I) systems enable rapid generation of high-fidelity imagery but are misaligned with how visual ideas develop. T2I systems generate outputs that make implicit visual decisions on behalf of the user, often introduce fine-grained details that can anchor users prematurely and limit their ability to keep options open early on, and cause unintende

Matthew Frazier, Kostadin Damevski

According to constructivist theory, students learn software security more effectively when examples are grounded in their own code. Generic examples often fail to connect with students' prior work, limiting engagement and understanding. Advances in LLMs are now making it possible to automatically generate personalized examples by embedding security vulnerabi

Jiacheng Wang, Jinchang Hou, Fabian Wang, Ping Jian

Existing agent-safety evaluation has focused mainly on externally induced risks. Yet agents may still enter unsafe trajectories under benign conditions. We study this complementary but underexplored setting through the lens of \emph{intrinsic} risk, where intrinsic failures remain latent, propagate across long-horizon execution, and eventually lead to high-c

Michael Levet

In this paper, we exhibit $\textsf{AC}^{3}$ isomorphism tests for coprime extensions $H \ltimes N$ where $H$ is elementary Abelian and $N$ is Abelian; and groups where $\text{Rad}(G) = Z(G)$ is elementary Abelian and $G = \text{Soc}^{*}(G)$. The fact that isomorphism testing for these families is in $\textsf{P}$ was established respectively by Qiao, Sarma, a

João Paulo S. H. Lima, Marcin L. Filo, Chathura Jayawardena, Konstantinos Nikitopoulos

The rise of Artificial Intelligence (AI)-driven services, machine-type communications, and massive Internet of Things (IoT) deployments is reshaping wireless traffic toward dense, uplink-oriented, bursty, and latency-critical patterns. In these regimes, Multi-User Multiple-Input Multiple-Output (MU-MIMO) is essential to support massive concurrent connectivit

Vojtěch Novák, Ivan Zelinka, Lenka Přibylová, Lubomír Martínek

This study evaluates colorectal risk factors and compares classical models against Quantum Neural Networks (QNNs) for anastomotic leak prediction. Analyzing clinical data with 14\% leak prevalence, we tested ZZFeatureMap encodings with RealAmplitudes and EfficientSU2 ansatze under simulated noise. $F_\beta$-optimized quantum configurations yielded significan

Sasha Boguraev, Kyle Mahowald

We show how causal interventions in Transformer models provide insights into English syntax by focusing on a long-standing challenge for syntactic theory: syntactic islands. Extraction from coordinated verb phrases is often degraded, yet acceptability varies gradiently with lexical content (e.g., "I know what he hates art and loves" vs. "I know what he looke

Xiao-Jing Gao, Yanfeng Ge, Yan Gao

The coexistence of topological states with different dimensionalities in a single crystalline system offers a unique platform to study the interplay of distinct fermionic excitations. Here, integrating first-principles calculations with symmetry analysis, we propose the three-dimensional boron allotrope $P6_3$-$\text{B}_{30}$ as an ideal, structurally stable

To Eun Kim, Alireza Salemi, Hamed Zamani, Fernando Diaz

Modern information access ecosystems consist of mixtures of systems, such as retrieval systems and large language models, and increasingly rely on marketplaces to mediate access to models, tools, and data, making competition between systems inherent to deployment. In such settings, outcomes are shaped not only by benchmark quality but also by competitive pre

Hamed Ouattara, Pierre Duthon, Pascal Houssam Salmane, Frédéric Bernardin

We present lightweight and efficient architectures to detect weather conditions from RGB images, predicting the weather type (sunny, rain, snow, fog) and 11 complementary attributes such as intensity, visibility, and ground condition, for a total of 53 classes across the tasks. This work examines to what extent weather conditions manifest as variations in vi

Duy Tung Doan, Quang Huy Phung, Dzung Nguyen, Khac-Hoai Nam Bui

Automated code generation remains a persistent challenge in software engineering, as conventional multi-agent frameworks are often constrained by static planning, isolated execution, high computational overhead, and limited adaptability to complex tasks. This paper introduces CollabCoder, a novel Plan-Code Co-Evolution framework that improves code generation

Long Feng

High-dimensional data arise routinely in modern statistics, econometrics, finance, genomics, and machine learning. While a large body of existing methodology is developed under Gaussian or light-tailed assumptions, many real data sets exhibit heavy tails, heterogeneity, and departures from classical covariance-based models. This book provides a systematic tr

Lei-Han Yao, Shang-Wei Lin, Yu-Chung Chen, Yean-Ru Chen

The Quantum Leading-Zero/One Counter (QLZOC) is a fundamental component in quantum arithmetic, playing a critical role in normalization, floating-point units, dynamic range scaling, and logarithmic approximations. Conventional designs primarily rely on direct Boolean-to-quantum mapping, which results in inefficient resource utilization such as irregular gate

Zhen Liu, Xinyu Ning, Zhe Hu, Xinxin Xie

Recent vision-language-action (VLA) systems have demonstrated strong capabilities in embodied manipulation. However, most existing VLA policies rely on limited observation windows and end-to-end action prediction, which makes them brittle in long-horizon, memory-dependent tasks with partial observability, occlusions, and multi-stage dependencies. Such tasks

Songlin Du, Xiaoyong Lu, Yaping Yan, Guobao Xiao

Local feature matching plays a critical role in understanding the correspondence between cross-view images. However, traditional methods are constrained by the inherent local nature of feature descriptors, limiting their ability to capture non-local scene information that is essential for accurate cross-view correspondence. In this paper, we introduce SceneG

Joydeep Biswas, Sheila Schoepp, Gautham Vasan, Anthony Opipari

Scientific peer review faces mounting strain as submission volumes surge, making it increasingly difficult to sustain review quality, consistency, and timeliness. Recent advances in AI have led the community to consider its use in peer review, yet a key unresolved question is whether AI can generate technically sound reviews at real-world conference scale. H

Martin Amster, Camila María Polotto

Computer vision techniques have advanced significantly in recent years, finding diverse and impactful applications within the medical field. In this paper, we introduce a new framework for the detection of Bethesda cells in Pap smear images, developed for Track B of the Riva Cytology Challenge held in association with the International Symposium on Biomedica

Tianze Xia, Zijian Ning, Zonglin Zhao, Mingjia Wang

Subject-driven image generation has shown great success in creating personalized content, but its capabilities are largely confined to single subjects in common poses. Current approaches face a fundamental conflict when handling multiple subjects with complex, distinct actions: preserving individual identities while enforcing precise pose structures. This ch

Enrico Sartor

We formulate and analyse an optimal control problem for the coagulation-fragmentation equation, where a scalar, time-dependent control modulates the coagulation rate by multiplying the coagulation kernel. The objective functional consists of a quadratic penalisation of the control and a terminal cost depending on the final size distribution. In a weighted $L

Anna Ritz-Zwilling, Olesia Dmytruk

We study a Su-Schrieffer-Heeger chain coupled to a single mode photonic cavity. Considering an off-resonant regime we use the high-frequency expansion in order to obtain an effective fermionic Hamiltonian with cavity-mediated interactions. We characterize the effects of the cavity on topology in a finite size chain by studying three different markers adapted

STAR Collaboration

The STAR experiment at the Relativistic Heavy Ion Collider presents measurements of correlations between charged hadron triggers of high transverse momenta ($7 < p_{\rm T} < 30$ GeV/$c$) with recoiling charged hadrons ($3 < p_{\rm T} < 7$ GeV/$c$) or charged--particle jets ($p_{\rm T, jet} > 8$ GeV/$c$) in event--activity selected O+O collisions at $\sqrt{s_

Landy Jimenez, Mariah Weatherspoon, Bingyu Shen, Yi Sheng

Proof-of-Work (PoW) blockchain consensus consumes vast computational resources without producing useful output, while the rapid growth of large language model (LLM) agents has created unprecedented demand for GPU computation. We present HadAgent, a decentralized agentic AI serving system that replaces hash-based mining with Proof-of-Inference (PoI), a consen

Daniel Rodriguez-Cardenas, David Nader Palacio, Denys Poshyvanyk

Software engineering research has focused on automating maintenance and evolution processes to reduce costs and improve reliability. The emergence of foundation models (FMs) with strong code understanding and reasoning abilities offers new opportunities for autonomous software behavior. Inspired by Artificial Life (ALife), we propose a fundamental shift in t

Matthias Tschope, Mohamed Moursi, Vladimir Rybalkin, Bo Zhou

Crack segmentation on edge devices can support continuous infrastructure monitoring and maintenance and thereby help to preserve public safety. Furthermore, autonomous infrastructure monitoring by using Unmanned Aerial Vehicles (UAVs) can reduce inspection risks, as human operators no longer need to enter hazardous areas. Edge processing reduces the cost of

Korinna Zapp

Colour coherence affects the radiation pattern of hard partons both in vacuum and in a dense coloured background formed in heavy ion collisions. In vacuum evolution it leads to the well-known phenomenon of angular ordering, and in heavy ion collisions the appearance of a medium resolution scale strongly affects the way in which a fragmenting hard parton inte

Buddhika Hondamuni, Théo Balland, Fabian Kammerbauer, Ashish Moharana

Topologically nontrivial magnetic textures such as skyrmions offer promising opportunities for spintronic applications. In recent years, it has been shown that the magnetic properties of layered materials can be affected by depositing chiral molecules on the surface, while the influence of chiral overlayers on skyrmion properties such as their stability and

Yan Sun, Yong Yuan, Minghui Du, Wen-Fan Feng

Gravitational waves (GWs) from the galactic double white dwarf (DWD) systems are one of the primary targets for upcoming space-based detectors. Due to their vast abundance and widespread distribution throughout the Galactic disk and bulge, these systems may provide a high-statistical population for probing GW microlensing effects induced by Galactic compact

Renaud A. L. Vallée

Anatase TiO2 dispersed in a silica aerogel matrix forms porous monolithic photocatalysts promising for indoor air purification and VOC photo-degradation. Their bicontinuous spinodal architecture provides high surface area, structural integrity, and intense UV multiple scattering. Extracting kinetic descriptors from apparent rate constants requires an optical

Sergej Krasnikov, Lukas Meitz, Samineh Bagheri, Michael Heider

Industrial time-series data from real production environments exhibits substantially higher complexity than commonly used benchmark datasets, primarily due to heterogeneous, multi-stage operational processes. As a result, anomaly detection methods validated under simplified conditions often fail to generalize to industrial settings. This work presents an emp

Akash Deo, Simone Campanoni, Tommy McMichen

Modern AI agents optimize programs by refactoring source code to trigger trusted compiler transformations. This preserves program semantics and reduces source code pollution, making the program easier to maintain and portable across architectures. However, this collaborative workflow is limited by legacy compiler interfaces, which obscure analysis behind uns

David Gonzalez

We count the number of countable homogeneous colored linear orderings in $k$ colors. Relatedly, we count the number of countable $C_{n,m}$-homogeneous linear orderings. $C_{n,m}$-homogeneity is a strong homogeneity notion that approximates $sp-$homogeneity, a notion recently uncovered in [2] to have important computability theoretic properties. Explicit form

Alexandre M. V. Gouveia, Md. Umar Hashmi, Reinhilde D'hulst, Dirk Van Hertem

The increasing penetration of Distributed Energy Resources (DERs), particularly electric vehicles, heat pumps, and photovoltaic systems, is fundamentally changing power flows in Low-Voltage (LV) distribution networks. Despite this transition, Distribution System Operators (DSOs) often lack reliable and up-to-date knowledge of the DER capacity connected downs

Yuqi Chen, Wenfeng Zhou, Min Sun, Xun Zhang

Recent advances in integrated photonics have enabled on-chip signal modulation and processing through localized photon-phonon interactions. For acousto-optic devices, compact footprint and high efficiency are essential for dense integration, while strong power handling is critical for stable operation in demanding applications. However, it remains challengin

Rahul Gupta, Florian Mintert, Himadri Shekhar Dhar

We present a Krylov space based theoretical framework for modeling inhomogeneous spin ensembles with arbitrary distributions of spin frequencies and couplings. The framework is then used to asymptotically large spin ensemble. In the single-excitation subspace, the Krylov construction allows for to derive exact expressions for the Lieb-Robinson velocity and q

Lorenzo Codecasa, Bernard Kapidani, Joachim Schöberl, Markus Wess

We present a higher-order extension of the dual cell method for the time-domain Maxwell equations in three spatial dimensions. The approach builds upon a variational reinterpretation of the Finite Integration Technique on dual meshes and generalises a previously developed two-dimensional high-order formulation. The electric and magnetic fields are discretise

Taylor Olson

The field of machine ethics aims to build Artificial Moral Agents (AMAs) to better understand morality and make AI agents safer. To do so, many approaches encode human moral intuition as a set of axioms on actions e.g., do not harm, you must help others. However, this introduces (at least) two limitations for future AMAs. First, it does not consider the agen

Chris F. D. Wattjes, Zichao Li, Minxing Xu, Richard A. Norte

Nonlinear modal interactions in resonant systems govern a wide range of phenomena, with broad relevance across modern physics and engineering. Yet, experimentally determining the strength of nonlinear coupling in multimode resonators remains highly challenging. Here, we introduce a multi-tone spectroscopy method for identifying nonlinear coupling coefficient

Anran Jiao, Wengyao Jiang, Xiaoyi Lu, Yi Wang

Computational fluid dynamics (CFD) has become an essential tool for predicting fire behavior, yet maintaining both efficiency and accuracy remains challenging. A major source of computational cost in fire simulations is the modeling of radiation transfer, which is usually the dominant heat transfer mechanism in fires. Solving the high-dimensional radiative t

Xianggang Yu, Lingteng Qiu, Xiaohang Ren, Guanying Chen

We present PartNerFace, a part-based neural radiance fields approach, for reconstructing animatable facial avatar from monocular RGB videos. Existing solutions either simply condition the implicit network with the morphable model parameters or learn an imaginary canonical radiance field, making them fail to generalize to unseen facial expressions and capture

Florian Gast, Meik Dörpinghaus, Gerhard Fettweis

Future mobile networks must achieve substantial improvements in energy efficiency to offset the anticipated traffic growth. Despite this requirement, many discussions regarding physical layer design remain primarily focused on peak data rates and spectral efficiency, even though typical network operation is dominated by low-data-rate regimes. To address this

Jakob Jurij Snoj

We show that the centralizer of a nonscalar element in the coproduct $k\langle X\rangle *k[Y]$ of a free associative algebra and a polynomial algebra over a given field is commutative. For $k\langle X \rangle$ this is part of Bergman's centralizer theorem. Our proof relies on a reduction given in Bergman's proof and is of combinatorial nature, employing a st

Ziyue Zhao, Huikang Liu, Man-Chung Yue

A rigid motion in $\mathbb{R}^d$ consists of a proper rotation and a translation, and it can be represented as a matrix in $\mathbb{R}^{(d+1)\times (d+1)}$. The problem of rigid motion synchronization aims to estimate a collection of rigid motions $G^*_1, \dots, G^*_n$ from noisy observations of their comparisons ${G^*_i}^{-1} G^*_j$. Such problems naturally

Reyhan Aydoğan, Tim Baarslag, Tamara C. P. Florijn, Katsuhide Fujita

This paper presents the primary research challenges and key findings from the 15th International Automated Negotiating Agents Competition (ANAC 2025), one of the official competitions of IJCAI 2025. We focus on two critical domains: multi-deal negotiations and the development of agents capable of concurrent negotiation within complex supply chain management

Jan Burczak, László Székelyhidi,, Bian Wu

For any $\beta_0<1/3$ we construct divergence free vector fields in $ C_{x,t}^{\beta_0}$ and a sequence of diffusivities $\kappa_q \searrow 0$ such that, for an arbitrary initial datum from a low regularity class, the classical solution $\rho_q$ to the advection-diffusion equation exhibits anomalous dissipation along the sequence $\kappa_q$. At the same time

Darij Grinberg

Let $A$ be a commutative ring with unity, and $M$ a finitely generated $A$-module. In 1971, Morris Orzech showed that any surjective $A$-module homomorphism from a submodule of $M$ to $M$ must be an isomorphism. We give a constructive proof of this fact using the Cayley--Hamilton theorem.

Linlin Ye, Zhaoqi Wu, Shao-Ming Fei

Quantum coherence plays a central role in Grover's search algorithm. We study the Tsallis relative $\alpha$ entropy of coherence dynamics of the evolved state in Grover's search algorithm. We prove that the Tsallis relative $\alpha$ entropy of coherence decreases with the increase of the success probability, and derive the complementarity relations between t

Kenny Campbell

Distributed quantum computing (DQC) is a promising proposal for overcoming the scalability challenges of quantum computing. However, the evaluation of DQC hardware and software is difficult due to the relative dearth of classical simulation tools available for DQC devices. In this work, we introduce dqc_simulator, a novel simulation toolkit, written in Pytho

Christian Lanza, José Álvarez-Cuervo, Kirill V. Voronin, Gonzalo Álvarez-Pérez

Twistoptics has recently emerged as a branch of nano-optics that explores light propagation in stacks of thin anisotropic layers rotated relative to one another. The concept is particularly relevant for polaritons -- hybrid light-matter quasiparticles -- in van der Waals (vdW) materials, where strong in-plane anisotropy and deep subwavelength confinement mak

Shuyun Wang, Hu Zhang, Xin Shen, Dadong Wang

Bitstream-corrupted video recovery aims to restore realistic content degraded during video storage or transmission. Existing methods typically assume that predefined masks of corrupted regions are available, but manually annotating these masks is labor-intensive and impractical in real-world scenarios. To address this limitation, we introduce a new blind vid

Zhiyuan Xu, Jiuming Liu, Yuxin Chen, Masayoshi Tomizuka

We present SparseGen, a novel framework for efficient image-to-3D generation, which exhibits low input-view bias while being significantly faster. Unlike traditional approaches that rely on dense volumetric grids, triplanes, or pixel-aligned primitives, we model scenes with a compact sparse set of learned 3D anchor queries and a learned expansion operator th

Rahul Gupta, Florian Mintert, Himadri Shekhar Dhar

The storage of quantum information in spin-ensembles is limited by practically unavoidable inhomogeneous broadening, and the macroscopic number of spins in such an ensemble makes the design of control solutions to increase the coherence time a challenging task. Together with a concurrently developed Krylov theory that allows us to treat the control problem e

Chuanxiang Yang, Junhui Hou, Yuan Liu, Siyu Ren

Implicit neural representations are powerful for geometric modeling, but their practical use is often limited by the high computational cost of network evaluations. We observe that implicit representations require progressively lower accuracy as query points move farther from the target surface, and that even within the same iso-surface, representation diffi

Liam Connor, Vikram Ravi, Pranav Sanghavi, Vishnu Balakrishan

Radio astronomy is uniquely coupled to exponential trends in computation because the optics (cross-correlation, beamforming, and imaging) and spectrometry (i.e. channelization) can now be done digitally. Inexpensive analog-to-digital converters (ADCs) can sample signals from large numbers of antennas and graphics processing units (GPUs) allow us to coherentl

Xiaofan Li, Ming Yang, Zhiyuan Ma, Shichao Ma

Reinforcement Learning with Verifiable Rewards (RLVR) has catalyzed significant advances in the reasoning capabilities of Large Language Models (LLMs). However, effectively managing the exploration and exploitation trade-off remains a critical challenge. In this paper, we fully analyze the exploration and exploitation dilemma of extremely hard and easy sampl

Aday Cárdenas, Rui E. F. Silva, Álvaro Jiménez-Galán

We study strong-field driven ultrafast dynamics and high-harmonic generation (HHG) in monolayer 2H-NbSe$_2$ and compare them with those of monolayer 2H-MoS$_2$ by solving the multiband reduced-density-matrix equations including time-dependent electron-electron interaction effects within the time-dependent Hartree + screened exchange (TD-HSEX). In MoS$_2$, th

Ilse Maillette de Buy Wenniger, Paul Burdekin, Shicheng Zhang, Mikhael J. Rasiah

The Off-Resonant Cascaded Absorption (ORCA) protocol in warm atomic vapors offers a scalable platform for high-bandwidth, low noise quantum memories, but its coherence time is fundamentally limited by Doppler-induced dephasing. We introduce and experimentally demonstrate a dynamic rephasing protocol that counteracts Doppler dephasing in a telecom-band ORCA q

Daniel Groves, Emily Stark, Genevieve S. Walsh, Kevin Whyte

We prove that if a proper metric space is quasi-isometric to a finitely generated group and to a space with a horoball over a finitely generated group, then that space is quasi-isometric to a rank-one symmetric space or the real line.

C. Monfardini, E. Pisanelli

Why do large gender inequalities in everyday life persist even as women strengthen their attachment to paid work? Existing evidence shows that women continue to do more unpaid work than men, but much of that evidence is based on individual diaries, says little about how inequality is jointly organized within couples, and rarely links daily time allocation to

Dario Mazzoleni, Riccardo Moraschi, Berardo Ruffini

We consider a shape optimization problem for a hybrid energy combining local confinement and nonlocal Coulomb repulsion. Specifically, for any open set $\Omega \subseteq \mathbb{R}^3$ of prescribed volume, we consider the ground state energy of an $L^2$-normalized function supported in $\Omega$, defined as a linear combination of its homogeneous $\dot{H}^1$

Daniel Burgarth, Paolo Facchi, Marilena Ligabò, Vito Viesti

This paper introduces the concept of the wandering range of a robust symmetry $S$ of a Hamiltonian $H$. This quantity measures how the perturbed time evolution $\mathrm{e}^{\mathrm{i}t(H+\varepsilon V)} S \mathrm{e}^{-\mathrm{i} t(H+\varepsilon V)}$ deviates from its unperturbed counterpart $\mathrm{e}^{\mathrm{i} tH} S\mathrm{e}^{-\mathrm{i} tH} = S$. Altho

Philipp Schwendke, Julia Stähler, Samuel Palato

Time-resolved scanning near-field optical microscopy (tr-SNOM) enables the measurement of the dynamic optical response of functional surfaces beyond the diffraction limit. Experimental challenges are imposed both by the use of a pulsed light source, and by the need for interferometric signal modulation to isolate the near-field contribution. We present a nov

Saeed Rahmani, Gözde Körpe, Zhenlin, Xu

Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need to balance safety and efficiency. Model Predictive Control (MPC) offers structured constraint handling through optimization but relies on hand-crafted rules that often produce overly conservative behavior. Deep Reinforcement Learning (RL) lea

Fabrizio Napolitano, Luca Della Penna, Tommaso Tedeschi, Livio Fanò

The application of quantum algorithms to jet substructure analysis is of growing interest as NISQ hardware continues to mature in qubit count and gate depth. Jet substructure remains essential for addressing demanding and complementary challenges at the LHC and beyond, notably object classification and polarization tagging. However, existing quantum machine

Diego Vallarino

Why do capitalist economies recurrently generate crises whose severity is disproportionate to the size of the triggering shock? This paper proposes a structural answer grounded in the evolutionary geometry of production networks. As economies evolve through specialization, integration, and competitive selection, their inter-sectoral linkages drift toward con

Qigang Liang, Xuejun Xu

In this paper, we propose an efficient two-level additive Schwarz method for solving large-scale eigenvalue problems arising from the finite element discretization of symmetric elliptic operators, which may compute efficiently more interior multiple and clustered eigenvalues other than only the first several smallest eigenvalues. The proposed method is paral

Bo Yu, Cheng Yang, Dongyang Hou, Chengfu Liu

The integration of Large Language Models (LLMs) into Geographic Information Systems (GIS) marks a paradigm shift toward autonomous spatial analysis. However, evaluating these LLM-based agents remains challenging due to the complex, multi-step nature of geospatial workflows. Existing benchmarks primarily rely on static text or code matching, neglecting dynami

Alice Drera, Pablo Spiga

The orbit dimension $\sigma(G)$ (also called the separation number or rigidity index) of a permutation group $G$ with domain $\Omega$ is the minimum cardinality of a subset $S \subseteq \Omega$ such that, for any two distinct elements $\omega,\omega'\in \Omega$, there exists $\alpha\in S$ for which $\omega$ and $\omega'$ lie in distinct orbits of the stabili

William J. Crilly

Synchronized radio telescope-based experiments conducted since 2017, together with subsequent interferometer experiments, provide evidence of an anomalous source of 3.7 Hz bandwidth pulses, sourced from near the direction of the star Rigel. The current experiment, reported here, uses a two-element phase-measuring interferometer to monitor the hypothetical pu

Anders Malthe Westerkam, Jakob Möderl, Erik Leitinger, Troels Pedersen

The growing proliferation of unmanned aerial vehicles (UAVs) poses major challenges for reliable airspace surveillance, as drones are typically small, have low radar cross-sections, and often move slowly in cluttered environments. These characteristics make the joint tasks of detecting, localizing, and tracking multiple objects difficult for conventional det

Mamuka Meskhishvili

Given a regular $n$-gon on the plane, it is evident that from any point on the plane, taken as a center, one can draw $n$ concentric circles such that each circle passes through one of the vertices of the polygon. Naturally, this raises the problem of whether such a construction is possible for any two given regular $n$-gons on the plane. In this paper, we e

Frieda Born, Tom Neuhäuser, Lukas Muttenthaler, Brett D. Roads

Modern machine learning models typically represent inputs as fixed points in a high-dimensional embedding space. While this approach has been proven powerful for a wide range of downstream tasks, it fundamentally differs from the way humans process information. Because humans are constantly adapting to their environment, they represent objects and their rela

Debjyoti Mondal, Rituraj Singh, Subhadarshi Panda

Large vision-language models (VLMs) achieve strong performance on multimodal tasks but often suffer from hallucination and poor grounding in knowledge-intensive reasoning. We propose SmoGVLM, a small, graph-enhanced VLM that integrates structured knowledge with visual and textual modalities, using Graph Neural Networks. We investigate the effects of our meth

Xuanyan Liu, Ignacio Cabrera Martin, Marcello Trovati, Xiaolong Xu

The evaluation of supervised machine learning models is a critical stage in the development of reliable predictive systems. Despite the widespread availability of machine learning libraries and automated workflows, model assessment is often reduced to the reporting of a small set of aggregate metrics, which can lead to misleading conclusions about real-world

Shingo Kono, Jesper Ilves, Arjan F. van Loo, Yoshiki Sunada

Quantum-limited parametric amplifiers are essential components for many quantum technologies operating in the microwave domain. Achieving both high gain and broad bandwidth, however, remains challenging due to trade-offs between gain and bandwidth, pump efficiency, and dynamic range. Moreover, high-gain broadband amplifiers become increasingly sensitive to t

Vladimir Molchanov, Hennes Rave, Lars Linsen

Cartograms are a technique for visually representing geographically distributed statistical data, where values of a numerical attribute are mapped to the size of geographic regions. Contiguous cartograms preserve the adjacencies of the original regions during the mapping. To be useful, contiguous cartograms also require approximate preservation of shapes and

Hossem Eddine Hafidi, Elisabetta De Giovanni, Teodoro Montanaro, Ilaria Sergi

Driver drowsiness significantly impairs the ability to accurately judge safe braking distances and is estimated to contribute to 10%-20% of road accidents in Europe. Traditional driver-assistance systems lack adaptability to real-time physiological states such as drowsiness. This paper proposes a deep reinforcement learning-based autonomous braking system th

Yu-Cheng Xiao, Jen-Yu Chang, Tzu-Ling Kuo, Aninda Astuti

We propose Scalable Quantum Molecular Generation (SQMG), a variational quantum-circuit for sampling molecular graphs using chemical priors on atoms and bonds. SQMG assigns a fixed 3-qubit register to each heavy atom and reuses a single 2-qubit bond register to generate bonds sequentially, yielding an ''atom no-reuse, bond reuse'' architecture with linear qub

Yan Xi Foo, Kian Hwee Lim, Jia-Bin You, Leong Chuan Kwek

We study transient entanglement generation between two quantum nodes coupled through a chiral one-dimensional channel. In an emitter-only Born-Markov description, we show that continuous driving and an initial ground state can raise the maximum transient concurrence above the undriven $2/e$ benchmark associated with the effectively single-excitation model. W

M. Kriener, C. Terakura, A. Kikkawa, Z. Liu

The new family of superconducting nickelates centered around La$_{3}$Ni$_{2}$O$_{7}$ possesses attractive features, such as the high transition temperature and the presence of an antiferromagnetic ground state at ambient pressure, suggesting an unconventional pairing mechanism. In the nonsuperconducting state, the possibility of different density-wave orders

Thomas Huettemann, Dan Kucerovsky

We propose a definition of an Euler characteristic for unbounded chain complexes by taking the (usual) Euler characteristics of successively longer parts of the complex, weighted inversely proportional to the length, and passing to the limit. This amounts to taking the limit of the sequence of ranks of homology modules with alternating signs in the sense of

Eymen Ipek

Odrzywolek (2026) recently introduced the Exp-Minus-Log (EML) operator eml (x, y) = exp(x) - ln(y) and proved constructively that, paired with the constant 1, it generates the entire scientific-calculator basis of elementary functions; in this sense EML is to continuous mathematics what NAND is to Boolean logic. We investigate whether such a uniform single-o

Julian Y. Z. Jee, Nihar Makadia, Joseph H. Pham, Gustavo Café de Miranda

Quantum simulation with controllable many-body platforms offers a powerful route to exploring complex phases and dynamics that are difficult to access in natural materials. Among these, topological spin textures such as skyrmions are central to modern condensed-matter physics and play a key role in chiral quantum many-body systems. Their controlled realisati

Eymen Ipek

Deep neural networks (DNNs) deliver state-of-the-art accuracy on regression and classification tasks, yet two structural deficits persistently obstruct their deployment in safety-critical, resource-constrained settings: (i) opacity of the learned function, which precludes formal verification, and (ii) reliance on heterogeneous, library-bound activation funct

Guy Kornowski, Ohad Shamir

We consider the well-studied setting of minimizing a convex Lipschitz function using either gradient descent (GD) or its stochastic variant (SGD), and examine the last iterate convergence. By now, it is known that standard stepsize choices lead to a last iterate convergence rate of $\log T/\sqrt{T}$ after $T$ steps. A breakthrough result of Jain et al. [2019

Santeri Salomaa, Esko Keski-Vakkuri, Sergi Nadal-Gisbert

We study bipartite entanglement harvesting from the quantum vacuum of a massless scalar field between two subsystems, each composed of a finite number of Unruh-DeWitt detectors. Using perturbation theory, we show that the leading-order negativity is fully determined by a submatrix of the reduced density matrix, with the submatrix dimension scaling only linea