April 2026 arXiv papers — page 59

Jiapeng Zhao, Stéphane Vinet, Amir Minoofar, Michael Kilzer

Quantum networks are a keystone of the quantum internet. However, existing implementations remain largely confined to static point-to-point links due to the absence of a switching paradigm capable of dynamically routing fragile quantum entanglement without introducing decoherence. Here, we propose the Universal Quantum Switch, a foundational building block a

Neeraj Gangwar, Rishabh Deshmukh, Michael Shavlovsky, Hancao Li

As model sizes continue to grow, parameter-efficient fine-tuning has emerged as a powerful alternative to full fine-tuning. While LoRA is widely adopted among these methods, recent research has explored vector-based adaptation methods due to their extreme parameter efficiency. However, these methods typically require substantially higher ranks than LoRA to m

Daniel Chan, Adam Nyman

Let $k$ denote an algebraically closed field of characteristic zero and let $X$ denote a smooth elliptic curve over $k$. Given a three-periodic elliptic helix $\underline{\mathcal{E}}$ of vector bundles over $X$ with endomorphism $\mathbb{Z}$-algebra $\operatorname{End} \underline{\mathcal{E}}$ and quadratic cover $\mathbb{S}^{nc}(\underline{\mathcal{E}})$,

Xiaoyang Chen, Wenliang Zhang, Fei Peng, Ting Cui

The recent discovery of Ruddlesden--Popper (RP) nickelate thin-film superconductors has opened a new frontier in unconventional superconductivity. Its realization requires both compressive epitaxial strain and highly oxidative growth conditions, yet the microscopic pathway from the parent phase to the superconducting phase remains elusive. Here, X-ray absorp

Ayush Chaturvedi, Rob Pokorney, Elyn Fritz-Waters, Charlotte Rouse

Research computing centers around the world struggle with onboarding new users. Subject matter experts, researchers, and principal investigators are often overwhelmed by the complex infrastructure and software offerings designed to support diverse research domains at large academic and national institutions. As a result, users frequently fall into confusion

Flávio Soriano, Victoria F. Mello, Pedro B. Rigueira, Gisele L. Pappa

Analyses of legislative behavior often rely on voting records, overlooking the rich semantic and rhetorical content of political speech. In this paper, we ask three complementary questions about parliamentary discourse: how things are said, what is being said, and who is speaking in discursively similar ways. To answer these questions, we introduce a scalabl

Chee Wei Tan, Yuchen Wang, Shangxin Guo

This paper introduces a new paradigm for AI game programming, leveraging large language models (LLMs) to extend and operationalize Claude Shannon's taxonomy of game-playing machines. Central to this paradigm is Nemobot, an interactive agentic engineering environment that enables users to create, customize, and deploy LLM-powered game agents while actively en

Jean F. Du Plessis, Bruno Scheihing-Hitschfeld

We find that heavy quark transport beyond leading logarithm at weak coupling is intrinsically non-Gaussian: the longitudinal momentum transfer distribution has asymmetric exponential tails that are crucial for equilibration dynamics. We show this by computing the leading-order momentum transfer kernel for relativistic heavy quarks in weakly coupled non-Abeli

Stephen Barrett, Francisco Javier Campos Zabala, Sean P. Fillingham, Umair Siddique

Safety cases for frontier AI systems should provide a convincing argument, supported by evidence, that the risk of harm is within an acceptable bound. When developers author their own safety cases, confirmation bias and conflicted incentives can affect the quality of argument. External review can help to address this. In this paper, we apply the Assurance 2.

Maximilian Stralz, Meshal Alharbi, Yujun Huang, Gioele Zardini

Designing multi-agent robotic systems requires reasoning across tightly coupled decisions spanning heterogeneous domains, including robot design, fleet composition, and planning. Much effort has been devoted to isolated improvements in these domains, whereas system-level co-design considering trade-offs and task requirements remains underexplored. In this wo

Sherly Alfonso-Sánchez, Cristián Bravo, Kristina G. Stankova

Geographic context is often consider relevant to motor insurance risk, yet public actuarial datasets provide limited location identifiers, constraining how this information can be incorporated and evaluated in claim-frequency models. This study examines how geographic information from alternative data sources can be incorporated into actuarial models for Mot

Reace H. J. Willis, Thomas H. Speak, Alex N. Byrne, Christopher N. Shingledecker

Hydrogen atom tunneling likely plays a substantial role in the gas-phase chemistry of astrochemical environments. To determine the potential effect that it has on the chemical modeling of aromatic molecules, we screened the kida.uva.2024 network, and our own expanded network to find reactions which could be significantly accelerated by hydrogen atom tunnelin

Muhy Eddin Za'ter, Anna Van Boven, Bri-Mathias Hodge, Kyri Baker

Maintaining instantaneous balance between electricity supply and demand is critical for reliability and grid instability. System operators achieve this through solving the task of Unit Commitment (UC),ca high dimensional large-scale Mixed-integer Linear Programming (MILP) problem that is strictly and heavily governed by the grid physical constraints. As grid

Praval Sharma, Ashok Samal, Leen-Kiat Soh, Deepti Joshi

Event extraction identifies the central aspects of events from text. It supports event understanding and analysis, which is crucial for tasks such as informed decision-making in emergencies. Therefore, it is necessary to develop automated event extraction approaches. However, existing datasets for algorithm development have limitations, including limited cov

Anton Molnar, Cosmin Pohoata, Michael Zheng

For every $n \geq 5$, we show that the Kneser graph of triangulations of a convex $n$-gon contains a Hamiltonian cycle.

Benedikt Gräßle

A Newton--Kantorovich-type argument enables the a posteriori existence verification of a unique regular root near a computed approximation, purely from computable data. This framework allows for non-selfadjoint problems and extends the existing verification theory to nonconforming discretisations. A key ingredient is a guaranteed lower bound on the continuou

Olivia Curtis, Van Hunter Adams, Daniel Angerhausen, Joseph Bates

The Dyson Minds 2025 Workshop, held at the Center for Brains, Minds & Machines at MIT and organized by Penn State, MIT, and The Ultraintelligence Foundation, brought together researchers in astrophysics, engineering, artificial intelligence, computer science, and philosophy to examine "Dyson Minds" -- large-scale post-biological intelligences powered by ener

He Zhang, Bumjin Kim, John M. Carroll, Jie Cai

The integration of AI-driven support systems within online communities has opened new avenues for enhancing user engagement and support efficiency in recent years. This study investigates the differences in user interactions and engagement within two distinct support channels on the VRChat Discord server: "user support," where human users provide assistance

Praval Sharma

Event extraction is essential for event understanding and analysis. It supports tasks such as document summarization and decision-making in emergency scenarios. However, existing event extraction approaches have limitations: (1) closed-domain algorithms are restricted to predefined event types and thus rarely generalize to unseen types and (2) open-domain ev

Xiangyu Wang, Zhenyu Zhang, Hai-Qing Zhang, Minyong Guo

We use GRAVITY near-infrared (NIR) flare astrometry to test whether Sagittarius A* could be a solitonic boson star. We consider five spherically symmetric solitonic boson-star models with different effective radii, together with the Schwarzschild black hole. Treating the flares as hot spots on circular equatorial orbits, we analyze their centroid motions and

Yuto Nishida, Naoki Shikoda, Yosuke Kishinami, Ryo Fujii

Understanding what kinds of factual knowledge large language models (LLMs) memorize is essential for evaluating their reliability and limitations. Entity-based QA is a common framework for analyzing non-verbatim memorization, but typical evaluations query each entity using a single canonical surface form, making it difficult to disentangle fact memorization

Guoyu Li, Yang Cao, Lucas H L Ng, Alexander Charlton

With network requirements diverging across emerging applications, latency-critical services demand minimal logic delay, while hyperscale training and collectives require sustained line-rate throughput for synchronized bulk transfers. This divergence creates an urgent need for custom network switches tailored to specialized protocols and application-specific

Umar Masud, Abhijith Punnappurath, Luxi Zhao, David B. Lindell

The ability of generative AI (GenAI) methods to photorealistically alter camera images has raised awareness about the authenticity of images shared online. Interestingly, images captured directly by our cameras are considered authentic and faithful. However, with the increasing integration of deep-learning modules into cameras' capture-time hardware -- namel

Matilde Barbini, Stefano Sorrentino, Daniel Gatica-Perez

The integration of AI into journalism challenges participatory design (PD), particularly with respect to stakeholder influence, workplace perceptions, and organizational dynamics. Traditional PD assumes that users can shape technologies, yet AI systems resist influence due to opaque data, fixed architectures, and inaccessible objectives. Through interviews w

Noah Weninger

In the knapsack interdiction problem, there are $n$ items, each with a non-negative profit, interdiction cost, and packing weight. There is also an interdiction budget and a capacity. The objective is to select a set of items to interdict (delete) subject to the budget which minimizes the maximum profit attainable by packing the remaining items subject to th

Laura Pecorari, Gavin K. Brennen, Stanimir S. Kondov, Guido Pupillo

We investigate the limits of quantum error correction (QEC) in neutral-atom processors approaching high-fidelity gates and fast cycle times. We show that shorter QEC cycles amplify platform-specific errors, notably Rydberg excitation hopping, and hinder decay of residual Rydberg population, leading to non-Markovian correlated errors that degrade logical perf

Vivek Shrivastav, Mani K Chettri, Hemam D. Singh, Britan Singh

We present 1X2V continuum Vlasov-Maxwell simulations of interpenetrating plasma beams with mobile ions. While the early-time evolution is similar to the stationary-ion case, the late-time dynamics are dominated by the ion-Weibel instability. As ion channels merge, the magnetic energy increases and the magnetic structures extend further along the beam directi

Jonatan A. Posligua, David E. Stewart, Denis R. Candido

Solid-state spin defects hold great promise as building blocks for various quantum technologies. Embedding spin centers in $p$-$n$ diodes under reverse bias has proved to be a powerful strategy to narrow the optical linewidth and increase spin coherence, while also enabling control of the photoluminescence wavelength via Stark shift. Given the multitude of p

Alibay Osmanli, Zixu Cheng, Shaogang Gong

Physical video understanding requires more than naming an event correctly. A model can answer a question about pouring, sliding, or collision from textual regularities while still failing to localize the event in time or space. We introduce a grounded benchmark for physical video understanding that extends the what--when--where evaluation structure of V-STaR

Jiseon Kim, Jea Kwon, Luiz Felipe Vecchietti, Wenchao Dong

Human moral judgment is context-dependent and modulated by interpersonal relationships. As large language models (LLMs) increasingly function as decision-support systems, determining whether they encode these social nuances is critical. We characterize machine behavior using the Whistleblower's Dilemma by varying two experimental dimensions: crime severity a

Kaitlin Gili, Mainak Nistala, Kristen Wendell, Michael C. Hughes

STEM education researchers are often interested in identifying moments of students' mechanistic reasoning for deeper analysis, but have limited capacity to search through many team conversation transcripts to find segments with a high concentration of such reasoning. We offer a solution in the form of an interpretable machine learning model that outputs time

Iain A. Bisset, Bhaskar Dutta, Doojin Kim, Samiran Sinha

Neutrino experiments are often limited by low statistics, sizable systematic uncertainties, and coarse observable binning, which can hinder discrimination among competing beyond-the-Standard-Model (BSM) explanations of anomalous signals. In particular, analyses based primarily on total event-rate differences are vulnerable to source-normalization uncertainti

Igor Vlasenko, Sergiy Maksymenko

Say that a connected non-Hausdorff one-dimensional manifold $M$ is "graph-like", whenever the set $M_{br}$ of its non-Hausdorff (called "branch") points is locally finite and every connected component of its complement has a countable base. We prove that for every graph-like manifold $M$ there exists a one-dimensional CW complex $K$ with the

Don Winter, Thiago L. M. Guedes, Markus Müller

Execution of quantum algorithms on large-scale quantum computers will require extremely low logical error rates, which necessitates the development of scalable decoding architectures. Local decoders are promising candidates for this task, as they avoid the communication and data processing bottlenecks inherent in global decoding strategies. Cellular automato

Zhigen Zhao, Shonosuke Sugaasawa

Empirical Bayes methods are widely used for large-scale inference, yet most classical approaches assume homoscedastic observations and focus primarily on posterior mean estimation. We develop a nonparametric empirical Bayes framework for the heteroscedastic normal means problem with unequal and unknown variances. Our first contribution is a generalized Tweed

Stefano Sorrentino, Matilde Barbini, Daniel Gatica-Perez

Building on recent interpretivist approaches, we conduct a critical narrative review across journalism studies, human-computer interaction, and FAccT scholarship, conceptualizing editorial authority as the conjunction of decision rights, epistemic warrant, and responsibility. We provide a comprehensive theoretical framework for addressing how concerns on fai

Akash Kundu, Sebastian Feld

Deep reinforcement learning (RL) for quantum circuit optimization faces three fundamental bottlenecks: replay buffers that ignore the reliability of temporal-difference (TD) targets, curriculum-based architecture search that triggers a full quantum-classical evaluation at every environment step, and the routine discard of noiseless trajectories when retraini

Subham Naskar, Sujit Manna

Interfacing two-dimensional bismuth with a magnetic layer provides a promising route towards realizing higher-order topological phases. In particular, bismuthene on a ferromagnetic insulator substrate has been theoretically proposed by \citet{Chen2020} as a universal platform for magnetic second-order topological insulators. Here, we report the experimental

Mahadev Sunil Kumar, Adarsh Ganesan

Parametrically driven oscillators provide a natural platform for neuromorphic computation, where nonlinear mode coupling and intrinsic dynamics enable both memory and high-dimensional transformation. Here, we investigate a two-mode system exhibiting 2:1 parametric resonance and demonstrate its operation as a reservoir computer across distinct dynamical regim

Naheed Rayhan, Sohely Jahan

Large language models (LLMs) are increasingly integrated into sensitive workflows, raising the stakes for adversarial robustness and safety. This paper introduces Transient Turn Injection(TTI), a new multi-turn attack technique that systematically exploits stateless moderation by distributing adversarial intent across isolated interactions. TTI leverages aut

N. S. Kavya, Avik De, Tee-How Loo

A comprehensive analysis of cosmological perturbations and structure formation is presented for the Extended Proca-Nuevo (EPN) framework, a vector-tensor extension of General Relativity with a massive spin-1 field. In this scenario, the vector field modifies the background expansion through an algebraic constraint, leading to a characteristic Hubble evolutio

Miha Rot, Gregor Kosec

One of the main challenges in numerically solving partial differential equations is finding a discretisation for the computational domain that balances the accurate representation of the underlying field with computational efficiency. Meshless methods approximate differential operators based on the values of the field in computational nodes, offering a natur

Ziqiang Huang, Qi Meng, Xuan Liu, Wei Ma

While spin polarization from synchrotron radiation is well established, the polarization of orbital angular momentum (OAM) in such radiative processes remains elusive. We study radiation and polarization of relativistic electrons in a uniform magnetic field, focusing on OAM polarization radiation for vortex electrons which carry intrinsic OAM. The results il

Haixiang Zhang, Mengyu Cao, Mei Lu

For $\mathcal H\subseteq\binom{[n]}k$, let $ν(\mathcal H)$ denote its matching number and let $d_{\mathcal H}(E)$ denote the codegree of a $(k-1)$-set $E$. We study the codegree moments $ co_p(\mathcal H)=\sum_{E\in\binom{[n]}{k-1}}d_{\mathcal H}(E)^p $ and the number of copies of the $k$-uniform $l$-petal sunflower $S_{k,l}^{k-1}$ whose core has size $k-1$.

Natan Levy, Gadi Perl

Artificial intelligence now decides who receives a loan, who is flagged for criminal investigation, and whether an autonomous vehicle brakes in time. Governments have responded: the EU AI Act, the NIST Risk Management Framework, and the Council of Europe Convention all demand that high-risk systems demonstrate safety before deployment. Yet beneath this regul

Fabian Baumann, Erol Akçay, Joshua B. Plotkin

Generative artificial intelligence (genAI) is rapidly reshaping how knowledge and culture are produced and consumed. Yet generative models are vulnerable to model collapse: when trained on data generated by earlier versions of themselves, their outputs can lose diversity and accuracy. This creates a social dilemma, because delegating tasks to genAI can be in

Yang Hu, Vladyslav Turlo

The FAIR principles have transformed how computational data and workflows are shared in materials research, yet existing repositories can only serve pre-computed entries -- broad coverage is perpetually incomplete and cannot adapt to new questions on demand. To address these challenges, we present OptiMat Alloys, a large language model-powered conversational

Di Wu, Ling Liang, Haizhao Yang

Bayesian Optimal Experimental Design (BOED) provides a rigorous framework for decision-making tasks in which data acquisition is often the critical bottleneck, especially in resource-constrained settings. Traditionally, BOED typically selects designs by maximizing expected information gain (EIG), commonly defined through the Kullback-Leibler (KL) divergence.

Nicholas F. Wogan, Natasha E. Batalha, Joshua Krissansen-Totton, Kevin Zahnle

The James Webb Space Telescope and the future Habitable Worlds Observatory aim to discover exoplanet atmospheric spectra that detect life. Currently, most existing spectral "retrieval" algorithms focus on inferring the abundances of biogenic gases from these spectra. However, abundances are hard to interpret as signatures of life because they are modified by

Nicholas Kocurek, Shayan Oveis Gharan, Dante Tjowasi

We design an efficient sampling algorithm to generate samples from the hardcore model on random regular bipartite graphs as long as $\lambda \lesssim \frac{1}{\sqrt{\Delta}}$, where $\Delta$ is the degree. Combined with recent work of Jenssen, Keevash and Perkins this implies an FPRAS for the partition function of the hardcore model on random regular biparti

Shinya Yamada, Yuto Ichinohe, Hideyuki Tatsuno, Ryota Hayakawa

We have succeeded in operating a transition-edge sensor (TES) spectrometer and evaluating its performance at the SPring-8 synchrotron X-ray light source. The TES spectrometer consists of a 240 pixel National Institute of Standards and Technology (NIST) TES system, and 220 pixels are operated simultaneously with an energy resolution of $4$~eV at 6~keV at a ra

Matthew Kafker, Aurel Bulgac

We present the first implementation of a novel extension of the Generator Coordinate Method (GCM), dubbed the enhanced GCM (eGCM), which is applied to the grazing Multi-Nucleon Transfer (MNT) reaction $^{48}$Ca+$^{208}$Pb near the Coulomb barrier. eGCM incorporates major qualitative differences with either Time-Dependent Hartree-Fock (TDHF) or GCM frameworks

Tim Kutta, Nina Dörnemann, Piotr Kokoszka

Functional data analysis is concerned with the analysis of infinite-dimensional data functions. Functional principal component analysis (FPCA) is a key method to obtain finite-dimensional summaries. Consistency of FPCA has been theoretically established for sufficiently regular data functions. However, empirical evidence shows that FPCA can become severely i

Li Chen, Xiaotong Shen, Wei Pan

Standard diffusion models are flexible estimators of complex distributions, but they do not encode causal structures and therefore do not by themselves support causal analysis. We propose a causality-encoded diffusion framework that incorporates a known directed acyclic graph by training conditional diffusion models consistent with the graph factorisation. T

Yang Hu, Benoit Sklénard, Wouter Vels, Yaroslav E. Romanyuk

Photothermal (photonic) sintering crystallizes as-deposited amorphous LiCoO2 (LCO) cathodes for solid-state thin-film batteries using millisecond, surface-localized heating. However, process design often relies on 1D models with phase-averaged, temperature-independent properties, which can mispredict peak temperatures and thermal damage margins. Here we deve

Shahriar Rahman Khan, Raiful Hasan

Autonomous Vehicles (AVs) increasingly depend on Multi-Sensor Fusion (MSF) to combine complementary modalities such as cameras and LiDAR for robust perception. While this redundancy is intended to safeguard against single-sensor failures, the fusion process itself introduces a subtle and underexplored vulnerability. In this work, we investigate whether an at

Haolin Zhang, William Reber, Yuxuan Zhang, Guofei Gu

Modern phishing campaigns increasingly evade snapshot-based URL classifiers using interaction gates (e.g., checkbox/slider challenges), delayed content rendering, and logo-less credential harvesters. This shifts URL triage from static classification toward an interactive forensics task: an analyst must actively navigate the page while isolating themselves fr

Hidir Selcuk Nogay

Electric arc welding (EAW) exhibits strongly non stationary and temporally evolving behavior, making reliable assessment of arc stability difficult using conventional frame based approaches. In this study, arc dynamics are modeled as a sequence of latent operational regimes within a probabilistic state-space framework. The welding current signal is transform

Eghbal A. Hosseini, Brian Cheung, Evelina Fedorenko, Alex H. Williams

Neural networks exhibit a remarkable degree of representational convergence across diverse architectures, training objectives, and even data modalities. This convergence is predictive of alignment with brain representation. A recent hypothesis suggests this arises from learning the underlying structure in the environment in similar ways. However, it is uncle

Cheng Chi, Long-tu Yuan

We study edge-colorings of the complete $p$-graph on $n$ vertices that contain no three edges $A,B,C$ of distinct colors such that the symmetric difference of $A$ and $B$ is contained in $C$. For $p\ge3$ and $n\ge p+1$, we show that every such coloring contains at most $1+\floor{n/p}$ colors and characterize the extremal colorings, generalizing a theorem of

Quan Chen

We prove that if a finite group $G$ acts outerly on a McDuff $\rm II_1$ factor $M$, then $\mathsf{Rep}(G/KL)$ is a braided monoidal full subcategory of the categorical Connes' $\tilde{\chi}(M\rtimes G)$ defined in arXiv:2111.06378, where $K$ and $L$ are the centrally trivial and approximately inner parts in $G$ respectively. When $L$ is trivial, we give an e

Gustavo G. Cambrainha, Daniel M. Castro, Leonardo L. Gollo, Pedro V. Carelli

The hierarchical organization of the brain is a fundamental structural principle, while brain criticality is a leading hypothesis for its collective dynamics. However, the connection between structure and signatures of criticality remains an open question. Here, we address this issue by applying phenomenological renormalization group approaches to large-scal

Piotr Kawałek, Jacek Krzaczkowski

Most classical results in circuit complexity theory concern circuits over the Boolean domain. Besides their simplicity and the ease of comparing different languages, the actual architecture of computers is also an important motivating factor. On the other hand, by restricting attention to Boolean circuits, we lose sight of the much richer landscape of circui

Florian Holeczek, Andreas Hinterreiter, Alex Hernandez-Garcia, Marc Streit

We present GFlowState, a visual analytics system designed to illuminate the training process of Generative Flow Networks (GFlowNets or GFNs). GFlowNets are a probabilistic framework for generating samples proportionally to a reward function. While GFlowNets have proved to be powerful tools in applications such as molecule and material discovery, their traini

Zihan Wang, Rui Zhang, Yu Liu, Chi Liu

Large language model (LLM) agents increasingly rely on skills to package reusable capabilities through instructions, tools, and resources. High-quality skills embed expert knowledge, curated workflows, and execution constraints into agents, fueling a growing skill economy through their value and scalability. Yet this ecosystem also creates a new attack surfa

Tieu-Long Phan, Lai Hoang Son Le, Thanh-An Pham, Nhu-Ngoc Nguyen Song

Protein--ligand docking is widely used in structure-based discovery, but routine studies often fail at the workflow level rather than at the scoring level. Receptor cleaning, ligand preparation, file conversion, box definition, run organization, and downstream parsing are frequently handled by fragmented scripts, which reduces reproducibility, obscures prove

Cédric Deffayet, Atabak Fathe Jalali, Aaron Held, Shinji Mukohyama

We quantise integrable point-particle systems with opposite-sign kinetic terms and nontrivial interactions. Using methods from separability theory, we show that previously determined classical stability conditions also imply discrete separated eigenvalue spectra. The resulting energy spectrum is unbounded above and below but not necessarily dense. We establi

Zahra Monfared, Saksham Malhotra, Sekiya Hajime, Ioannis Kevrekidis

For continuous-time dynamical systems with reversible trajectories, the nowhere-vanishing eigenfunctions of the Koopman operator of the system form a multiplicative group. Here, we exploit this property to accelerate the systematic numerical computation of the eigenspaces of the operator. Given a small set of (so-called ``principal'') eigenfunctions that are

Yanis Le Fur, Javier Lalueza-Puértolas, Carlos Sánchez Muñoz, Alberto Muñoz de las Heras

Bosonic quantum error correction enables hardware-efficient protection of quantum information by encoding logical qubits in harmonic oscillators. Bosonic grid states, such as Gottesman-Kitaev-Preskill (GKP) states, are particularly promising due to their potential to correct small displacements and boson loss. However, their generation remains challenging, t

Cédric Deffayet, Atabak Fathe Jalali, Aaron Held, Shinji Mukohyama

We quantize a classically stable system of a harmonic oscillator polynomially coupled to a ghost with negative kinetic energy. We prove that due to an integral of motion with a positive discrete spectrum: i) the Hamiltonian has a pure point spectrum unbounded in both directions, ii) the evolution is manifestly unitary, iii) the vacuum is well-defined, iv) ex

Adam Štefunko, Jan Hajič

A central part of the contemporary Historically Informed Practice movement is basso continuo, an improvised accompaniment genre with its traditions originating in the baroque era and actively practiced by many keyboard players nowadays. Although computational musicology has studied the theoretical foundations of basso continuo expressed by harmonic and voice

Sophie Moufawad, Nabil Nassif, Faouzi Triki

We consider the mathematical model of gas trapping in deep polar ice (firns), which consists of a parabolic partial differential equation, that can degenerate at one boundary extreme. In [1], we considered all the coefficients to be constants, except the diffusion coefficient D(z) that is to be reconstructed. In this paper, we assume both the diffusion coeff

Nikolay Yegovtsev, Sayan Choudhury, W. Vincent Liu

The Dicke model (DM) serves as a paradigm for understanding collective light-matter interactions. We introduce the chiral Dicke model, a generalization where an atomic ensemble couples to a two-mode cavity via chiral interactions. Unlike the standard DM, the chiral DM is endowed with an inherent continuous $U(1)$ symmetry associated with angular momentum con

Gewei Zhang, Deqing Wang, Lizhao You, Xiangming Cai

Physical-layer network coding (PNC) can increase end-to-end throughput in bi-directional multi-hop underwater acoustic (UWA) networks. However, multipath delay spread and Doppler-induced inter-carrier interference (ICI) in UWA channels can degrade the reliability of PNC transmission in a three-node relay configuration. More critically, error accumulation acr

Yue Zhao, Daochang Zhang, Dijana Mosic

This paper establishes exact expressions for the Drazin inverse of the modified tensor $\mathcal A-\mathcal C*_N\mathcal D^D*_N\mathcal B$ via the Einstein product, formulated using the Drazin inverse of $\mathcal A$ and the generalized Schur complement $\mathcal D-\mathcal B*_N\mathcal A^{D}*_N\mathcal C$, providing a comprehensive generalization and unific

Mark J. Henriksen

We have searched for the 3.55 keV line from sterile neutrino decay using 3.1 megaseconds of RXTE cluster data. A 2.5$\sigma$ excess of emission over a thermal model is found over the energy span of the 3.55 keV line in the combined spectra of the eight clusters that individually have an excess. The residuals are added to increase the signal to noise ratio of

Anuj Sadani, Deepak Kumar

The Model Context Protocol (MCP) has become a common interface for connecting large language model (LLM) agents to external tools, but its reliance on stateless, eager schema injection imposes a hidden per-turn overhead the MCP Tax or Tools Tax that practitioner reports place between roughly 10k and 60k tokens in typical multi-server deployments. This payloa

Reinhard Nabben, Ludwig Rooch

Recently a new approach to analyze and create algebraic multigrid methods (AMG) for nonsymmetric and indefinite matrices was established. Convergence is measured in general norms induced by a certain HPD matrix $B$ and $B$-orthogonal projections built by compatible transfer operators are used. Here we continue our theoretical framework, started in Nabben and

Bowen Liu, Li Yang, Shanshan Song, Mingyu Tang

Capsule endoscopy (CE) enables non-invasive gastrointestinal screening, but current CE research remains largely limited to frame-level classification and detection, leaving video-level analysis underexplored. To bridge this gap, we introduce and formally define a new task, diagnosis-driven CE video summarization, which requires extracting key evidence frames

Long Yuan, Wenkun Wen, Junlin Liu, Peiran Wu

Low-power wide-area networks (LPWANs) are crucial for large-scale Internet of Things (IoT) applications, yet they face increasing demands for higher data rates, improved reliability, and enhanced energy efficiency under stringent hardware constraints. To address these challenges, this paper introduces a generalized code-index modulation (CIM) transceiver tha

Carter Blair, Ben Armstrong, Shiri Alouf-Heffetz, Nimrod Talmon

A primary goal of online deliberation platforms is to identify ideas that are broadly agreeable to a community of users through their expressed preferences. Yet, consensus elicitation should ideally extend beyond the specific statements provided by users and should incorporate the relative salience of particular topics. We address this issue by modelling con

Daniel Fu, Gabby Litterio, Pedro Felzenszwalb, Rashid Zia

We address the ambiguities in the super-resolution problem under translation. We demonstrate that combinations of low-resolution images at different scales can be used to make the super-resolution problem well posed. Such differences in scale can be achieved using sensors with different pixel sizes (as demonstrated here) or by varying the effective pixel siz

Yufeng Song, Qin Yue

For a nonnegative integer $r$ and a positive integer $v$ satisfying \[ \frac{r(q-1)}{2}<v<\frac{(r+1)(q-1)}{2}, \] we define the combinatorial numbers \[ A_r(v)= \begin{cases} \displaystyle \sum_{t=r(q-1)-v}^{v}\ \sum_{j=0}^{r}(-1)^j\binom{r}{j}\binom{t-jq+r-1}{r-1}, & r>0,\\[1.2ex] 1, & r=0. \end{cases} \] For the projective Reed-Muller code $\PRM(q,m,v)$,

Li-Cheng Hsiao, Zi-Kui Liu, Wesley Reinhart

Processing treatments of alloys, despite being influential to alloy properties, are often neglected in machine-learning aided alloy designs due to the difficulties in expressing this information. We investigated the expressiveness of transformer embeddings through synthesized annealing processing treatment text and verified that embeddings could be utilized

Yuxin Zhao, Han Huang, Zhifeng Hao

Optimization problems are fundamental in diverse fields, such as engineering, economics, and scientific computing. However, current algorithms are mostly designed for specific problem types and exhibit limited generality in solving multiple types of optimization problems. To enhance generality, we propose an automated reduction method named OP-to-MaxSAT redu

Zixu Li, Yupeng Hu, Zhiheng Fu, Zhiwei Chen

Composed Image Retrieval (CIR) is an important image retrieval paradigm that enables users to retrieve a target image using a multimodal query that consists of a reference image and modification text. Although research on CIR has made significant progress, prevailing setups still rely simple modification texts that typically cover only a limited range of sal

Ovidiu Cristinel Stoica

I show that the clock ambiguity cannot be solved by a purely relational condition like the noninteraction condition, and it is even stronger, extending to evolution laws. The ambiguity is solved by specifying the physical meaning of observables. Page and Wootters (1983) showed how time and dynamics can emerge from entanglement within a stationary quantum sys

Benoît Tabone, Milou Temmink, Laurens B. F. M. Waters, Ewine F. van Dishoeck

(Abridged) We aim to investigate the inner regions of large and massive disks orbiting T Tauri stars, thought to be progenitors of systems with wide-orbit planets and possible cases of halted pebble drift. We analyze the MIRI spectra of three disks from the MINDS program: V1094 Sco, DL Tau, and IM Lup. The spectra reveal a striking diversity. V1094 Sco and D

Safouane El Ghazouali, Nicola Venturi, Michael Rueegsegger, Umberto Michelucci

Recent advances in deep learning for remote sensing rely heavily on large annotated datasets, yet acquiring high-quality ground truth for geometric, radiometric, and multi-domain tasks remains costly and often infeasible. In particular, the lack of accurate depth annotations, controlled illumination variations, and multi-scale paired imagery limits progress

Arunaday Gupta, Baisong Sun, Xi He, Bei Zeng

Exact quantum codes detecting a prescribed set of Pauli errors are approached through algebraic constructions--stabilizer, codeword-stabilized, permutation-invariant, topological, and related families. Geometrically, exact Pauli detection is governed by joint higher-rank numerical ranges of these Pauli operators, whose structure for rank $\geq 2$ is largely

Changwang Xiao, Nan Yang, Qingxin Meng

This paper investigates the $H_{2}/H_{\infty}$ control problem for linear stochastic differential systems under partial observation. Unlike existing studies that assume full state accessibility, we consider the scenario where the controller has access only to an observation process. The objective is to design a controller that balances the $H_2$ performance

François Clément, Stefan Steinerberger

The k-means problem is perhaps the classical clustering problem and often synonymous with Lloyd's algorithm (1957). It has become clear that Hartigan's algorithm (1975) gives better results in almost all cases, Telgarsky-Vattani note a typical improvement of $5\%$ -- $10\%$. We point out that a very minor variation of Hartigan's method leads to another $2\%$

Jens Kanstrup Larsen, Alceste Scalas, Guy Amir, Jules Jacobs

This paper introduces NEST (Network-Enforced Session Types), a runtime verification framework that moves application-level protocol monitoring into the network fabric. Unlike prior work that instruments or wraps application code, we synthesize packet-level monitors that enforce protocols directly in the data plane. We develop algorithms to generate network-l

Ye Yu, Heming Liu, Haibo Jin, Xiaopeng Yuan

Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and orchestration while treating inter-agent communication as a fixed interface. Latent communication through internal representations such as key-value caches offers a promising alternative to text-based protocols

Yvon K. Awuklu, Meghyn Bienvenu, Katsumi Inoue, Vianney Jouhet

In this paper, we develop a novel logic-based approach to detecting high-level temporally extended events from timestamped data and background knowledge. Our framework employs logical rules to capture existence and termination conditions for simple temporal events and to combine these into meta-events. In the medical domain, for example, disease episodes and

KyeongRo Kim

Calegari and Loukidou introduced zippers, consisting of a disjoint pair of invariant real trees in the boundary of a closed hyperbolic 3-manifold group $\pi_1(M)$, which ensure the existence of a universal circle. We study the action of $\pi_1(M)$ on a minimal zipper and prove a fixed point dichotomy: every nontrivial element either fixes a unique point in e

Devashish Tupkary

This thesis is concerned with rigorous security analyses of practical Quantum Key Distribution (QKD) protocols, using a variety of modern proof techniques. The main results are as follows. First, we establish a security proof for variable-length QKD protocols against IID collective attacks, and extend this result to coherent attacks using the postselection t

Anne Moore, Lucia A. Perez, Elisabeth Krause

Constraining primordial non-Gaussianity via its scale-dependent imprint on galaxy clustering requires knowledge of the bias parameter $b_{\phi}$, which is exactly degenerate with $f^{\rm{loc}}_{\rm{NL}}$ at leading order. To break this degeneracy, current analyses adopt the relation $\left(b_{\phi} = 2\delta_c\left(b_1 - 1\right)\right)$ based on the assumpt

Fintan M. Bolton

The partial oracles framework is a quantum search algorithm that has the potential to exceed the quadratic speedup of Grover's algorithm, up to a theoretical maximum of an exponential speedup. Until now, however, the framework has lacked an explicit method for constructing the operator that represents the search iteration. In this paper, we provide the missi

Po-Yen Lai, Xinyu Yang, Derrick Low, Huizhe Liu

In response to the urban heat island effects and building energy demands in Singapore, this study proposes an agentic AI-enabled reasoning framework that integrates large language models (LLMs) with lightweight physics-based models. Through prompt customization, the LLMs interpret urban design tasks, extract relevant policies, and activate appropriate physic