March 2025 arXiv papers — page 90

Élie Gouzien, Nicolas Sangouard

We propose a method for exact circuit synthesis using a discrete gate set, as required for fault-tolerant quantum computing. Our approach translates the problem of synthesizing a gate specified by its unitary matrix into a boolean satisfiability (SAT) instance. It leverages the algebraic properties of the coefficients of the matrices that constitute the gate

Lixing Xiao, Shunlin Lu, Huaijin Pi, Ke Fan

This paper addresses the challenge of text-conditioned streaming motion generation, which requires us to predict the next-step human pose based on variable-length historical motions and incoming texts. Existing methods struggle to achieve streaming motion generation, e.g., diffusion models are constrained by pre-defined motion lengths, while GPT-based method

Tongyao Zhu, Qian Liu, Haonan Wang, Shiqi Chen

Recent advancements in LLM pretraining have featured ever-expanding context windows to process longer sequences. However, our pilot study reveals that models pretrained with shorter context windows consistently outperform their long-context counterparts under a fixed token budget. This finding motivates us to explore an optimal context window scheduling stra

Daniel Alan Goldston, Junghun Lee, Jordan Schettler, Ade Irma Suriajaya

Montgomery in 1973 introduced the Pair Correlation Conjecture (PCC) for zeros of the Riemann zeta-function. He also conjectured that asymptotically 100% of the zeros are simple. His reasoning to support these two conjectures used the Riemann Hypothesis (RH). Building on Montgomery's approach, Gallagher and Mueller proved in 1978 that PCC under RH implies tha

William Marfo, Deepak Tosh, Shirley Moore, Joshua Suetterlein

Communication overhead in federated learning (FL) poses a significant challenge for network anomaly detection systems, where diverse client configurations and network conditions impact efficiency and detection accuracy. Existing approaches attempt optimization individually but struggle to balance reduced overhead with performance. This paper presents an adap

Naqash Afzal, Basma Hasanen, Lakmal Seneviratne, Oussama Khatib

The integration of extra-robotic limbs/fingers to enhance and expand motor skills, particularly for grasping and manipulation, possesses significant challenges. The grasping performance of existing limbs/fingers is far inferior to that of human hands. Human hands can detect onset of slip through tactile feedback originating from tactile receptors during the

Yutaka Yoshida

We study BPS loop operators in a 4d $\mathcal{N}=2$ $Sp(N)$ gauge theory with four hypermultiplets in the fundamental representation and one hypermultiplet in the anti-symmetric representation. The algebra of BPS loop operators in the $\Omega$-background provides a deformation quantization of the Coulomb branch, which is expected to coincide with the quantiz

Bo Wu

In order to explore whether environmental liability insurance has an important impact on industrial emission reduction, this paper selects provincial (city) level panel data from 2010 to 2020 and constructs a two-way fixed effect model to analyze the impact of environmental liability insurance on carbon emissions from both direct and indirect levels. The emp

Pierluigi Colli, Jürgen Sprekels

In this paper, we study an optimal control problem for a viscous Cahn--Hilliard system with zero Neumann boundary conditions in which a hyperbolic relaxation term involving the second time derivative of the chemical potential has been added to the first equation of the system. For the initial-boundary value problem of this system, results concerning well-pos

Md Tanzeem Rahat, Md. Manzurul Hasan, Debajyoti Mondal

Let $A$ and $B$ be two number sequences of length $n$ and $m$, respectively, where $m\le n$. Given a positive number $\delta$, a common almost increasing sequence $s_1\ldots s_k$ is a common subsequence for both $A$ and $B$ such that for all $2\le i\le k$, $s_i+\delta > \max_{1\le j < i} s_j$. The LCaIS problem seeks to find the longest common almost increas

Wei-Fan Hu, Te-Sheng Lin, Yu-Hau Tseng, Ming-Chih Lai

In this paper, we propose a categorical embedding discontinuity-capturing shallow neural network for anisotropic elliptic interface problems. The architecture comprises three hidden layers: a discontinuity-capturing layer, which maps domain segments to disconnected sets in a higher-dimensional space; a categorical embedding layer, which reduces the high-dime

Mohammad Bardestani, Keivan Mallahi-Karai, Samrith Ram, Hadi Salmasian

Let $\mathfrak b_n(\mathbb F_q)$ denote the Lie algebra of upper triangular $n\times n$ matrices over the finite field $\mathbb F_q$, and let $\mathfrak u_n(\mathbb F_q)$ be the nilradical of $\mathfrak b_n$. For every $\mathfrak b_n(\mathbb F_q)$-stable ideal $\mathfrak a$ of $\mathfrak u_n(\mathbb F_q)$, and every partition $\mu$ of $n$, we prove two formu

Chao Lu, Muralikrishnan Gopalakrishanan Meena, Kalyana Chakravarthi Gottiparthi

Quantum Phase Estimation (QPE) is a cardinal algorithm in quantum computing that plays a crucial role in various applications, including cryptography, molecular simulation, and solving systems of linear equations. However, the standard implementation of QPE faces challenges related to time complexity and circuit depth, which limit its practicality for large-

Yang Tan, Chen Liu, Jingyuan Gao, Banghao Wu

Natural language processing (NLP) has significantly influenced scientific domains beyond human language, including protein engineering, where pre-trained protein language models (PLMs) have demonstrated remarkable success. However, interdisciplinary adoption remains limited due to challenges in data collection, task benchmarking, and application. This work p

Thorsten Wißmann, Bálint Kocsis, Jurriaan Rot, Ruben Turkenburg

An automaton is called reachable if every state is reachable from the initial state. This notion has been generalized coalgebraically in two ways: first, via a universal property on pointed coalgebras, namely, that a reachable coalgebra has no proper subcoalgebras; and second, a coalgebra is reachable if it arises as the union of an iterative computation of

Felipe I. Flores

Let $G$ be a group of subexponential growth and $\mathscr C\overset{q}{\to}G$ a Fell bundle. We show that any Banach $^*$-algebra that sits between the associated $\ell^1$-algebra $\ell^1( G\,\vert\,\mathscr C)$ and its $C^*$-envelope has the same topological stable rank and real rank as $\ell^1( G\,\vert\,\mathscr C)$. We apply this result to compute the to

Ritwick Banerjee, Bryan Andrews, Erich Kummerfeld

Despite the accelerating presence of exploratory causal analysis in modern science and medicine, the available non-experimental methods for validating causal models are not well characterized. One of the most popular methods is to evaluate the stability of model features after resampling the data, similar to resampling methods for estimating confidence inter

Baolu Li, Zongzhe Xu, Jinlong Li, Xinyu Liu

LiDAR-based Vehicle-to-Everything (V2X) cooperative perception has demonstrated its impact on the safety and effectiveness of autonomous driving. Since current cooperative perception algorithms are trained and tested on the same dataset, the generalization ability of cooperative perception systems remains underexplored. This paper is the first work to study

Yuta Matsumoto, Maxim De Smet, Larysa Tryputen, Sander L. de Snoo

The scalability and power of quantum computing architectures depend critically on high-fidelity operations and robust and flexible qubit connectivity. In this respect, mobile qubits are particularly attractive as they enable dynamic and reconfigurable qubit arrays. This approach allows quantum processors to adapt their connectivity patterns during operation,

Alexandra B. Artusio-Glimpse, Adil Meraki, Hunter Shillingburg, Guy Lavallee

Rydberg-atom electrometry enables highly sensitive electric-field measurements by exploiting the extreme polarizability of Rydberg states in alkali atoms. Millimeter-scale atomic vapor cells can be accurately and economically batch-fabricated by anodically bonding silicon and glass wafers, enabling the large-volume manufacturing of miniature atomic clocks an

Johnathan D. Georgaras, Akash Ramdas, Chung Hsuan Shan, Elena Halsted

Twisted layered van-der-Waals materials often exhibit unique electronic and optical properties absent in their non-twisted counterparts. Unfortunately, predicting such properties is hindered by the difficulty in determining the atomic structure in materials displaying large moir\'e domains. Here, we introduce a split machine-learned interatomic potential and

Daniël Otten, Matteo Spadetto

The semantics of extensional type theory has an elegant categorical description: models of extensional =-types, 1-types, and Sigma-types are biequivalent to finitely complete categories, while adding Pi-types yields locally Cartesian closed categories. We establish parallel results for axiomatic type theory, which includes systems like cubical type theory, w

Deep Ghuge, Debesh Bhattacharjee, Prasad Subramanian

Solar coronal mass ejections (CMEs) directed at the Earth often drive large geomagnetic storms. Here we use velocity, magnetic field and proton density data from 152 CMEs that were sampled in-situ at 1 AU by the WIND spacecraft. We Fourier analyze fluctuations of these quantities in the quiescent pre-CME solar wind, sheath and magnetic cloud. We quantify the

Iulisloi Zacarias, Francisco Carpio, André Costa Drummond, Admela Jukan

Within 3GPP, the campus network architecture has evolved as a deployment option for industries and can be provisioned using network slicing over already installed 5G public network infrastructure. In campus networks, the ultra-reliable low latency communication (URLLC) service category is of major interest for applications with strict latency and high-reliab

Katherine E. Stange

Following work of Mazur-Tate and Satoh, we extend the definition of division polynomials to arbitrary isogenies of elliptic curves, including those whose kernels do not sum to the identity. In analogy to the classical case of division polynomials for multiplication-by-n, we demonstrate recurrence relations, identities relating to classical elliptic functions

Junpeng Hou, Amin Barzegar, Helmut G. Katzgraber

Combinatorial optimization problems are ubiquitous in industrial applications. However, finding optimal or close-to-optimal solutions can often be extremely hard. Because some of these problems can be mapped to the ground-state search of the Ising model, tremendous effort has been devoted to developing solvers for Ising-type problems over the past decades. R

Tuhin G M Al Mamun

The COVID-19 pandemic significantly disrupted household consumption, savings, and income across Europe, particularly affecting countries like Hungary, Slovenia, and the Czech Republic. This study investigates the effectiveness of fiscal policies in mitigating these impacts, focusing on government interventions such as spending, subsidies, revenue, and debt.

Wei Tang, Yanpeng Sun, Qinying Gu, Zechao Li

Although Multimodal Large Language Models (MLLMs) excel at various image-related tasks, they encounter challenges in precisely aligning coordinates with spatial information within images, particularly in position-aware tasks such as visual grounding. This limitation arises from two key factors. First, MLLMs lack explicit spatial references, making it difficu

Piero Giacomelli

In this paper, we investigate the properties of sequences and series under the action of the log-concave operator \(\mathcal{L}\). We explore the relationship between the convergence of a sequence \((a_k)\) and the convergence of sequences and series derived by applying \(\mathcal{L}\) iteratively. These results demonstrate the strong regularity properties o

Alain Govaert, André Teixeira, Emma Tegling

Real-world growth processes and scalings have been broadly categorized into three growth regimes with distinctly different properties and driving forces. The first two are characterized by a positive and constant feedback between growth and growth rates which in the context of networks lead to scale-free or single-scale networks. The third, sublinear, regime

Nelson Caldwell, John C. Raymond, Knox S. Long, Myung Gyoon Lee

With a star formation rate of order 0.4 M$_\odot $ yr$^{-1}$, M31 should have significant population of supernova remnants (SNRs), and, in fact, 156 SNR and SNR candidates have been suggested by Lee et al. (2014) by searching for nebulae with elevated [SII]/H${\alpha}$ ratios in narrow band images. Here we use a combination of low and high resolution optical

M. Pillas, S. Antier, K. Ackley, T. Ahumada

Neutron star-black hole (NSBH) mergers, detectable via their gravitational-wave (GW) emission, are expected to produce kilonovae (KNe). Four NSBH candidates have been identified and followed-up by more than fifty instruments since the start of the fourth GW Observing Run (O4), in May 2023, up to July 2024; however, no confirmed associated KN has been detecte

Michael Robinson, Sourya Dey, Taisa Kushner

This article presents a general and flexible method for prompting a large language model (LLM) to reveal its (hidden) token input embedding up to homeomorphism. Moreover, this article provides strong theoretical justification -- a mathematical proof for generic LLMs -- for why this method should be expected to work. With this method in hand, we demonstrate i

Amirhossein Kazerouni, Soroush Mehraban, Michael Brudno, Babak Taati

Implicit Neural Representations (INRs) are proving to be a powerful paradigm in unifying task modeling across diverse data domains, offering key advantages such as memory efficiency and resolution independence. Conventional deep learning models are typically modality-dependent, often requiring custom architectures and objectives for different types of signal

Sam Oaks-Leaf, David T. Limmer

We present a dynamical model of crystal growth, in which it is possible to reliably achieve asymmetric products, beginning from symmetric initial conditions and growing within an isotropic environment. The asymmetric growth is the result of a positive feedback mechanism that amplifies the effect of thermal fluctuations in the coverage of surfactants on the g

Minghua Shan

Tumor response, a binary variable, has historically been the main measure of antitumor activity for many cancer phase II single-arm trials. Simon two-stage designs are often used. Sargent et al. proposed a three-outcome trial design in this setting which requires smaller sample sizes. For many new, molecularly targeted therapies, however, tumor response may

Harold Haodong Chen, Haojian Huang, Xianfeng Wu, Yexin Liu

Temporal quality is a critical aspect of video generation, as it ensures consistent motion and realistic dynamics across frames. However, achieving high temporal coherence and diversity remains challenging. In this work, we explore temporal augmentation in video generation for the first time, and introduce FluxFlow for initial investigation, a strategy desig

Max Langtry, Ruchi Choudhary

Energy storage is needed to match renewable generation to industrial loads in energy parks. However, the future performance of bulk storage technologies is currently highly uncertain. Due to the urgency of decarbonization targets, energy park projects must be designed and begun now. But, as uncertainty in storage performance reduces, a different technology t

Giovanni Floreale, Piero Baraldi, Enrico Zio, Olga Fink

Deep Learning (DL) models processing images to recognize the health state of large infrastructure components can exhibit biases and rely on non-causal shortcuts. eXplainable Artificial Intelligence (XAI) can address these issues but manually analyzing explanations generated by XAI techniques is time-consuming and prone to errors. This work proposes a novel f

Torbjörn Lundberg, Leif Lönnblad

We present the development of a new colour reconnection model in PYTHIA where the full spacetime separation between partons constrains the reconnection probability throughout the final-state radiative shower. Building upon previous ideas of a perturbative dipole-based model, our objective is to introduce realistic spatially-based colour reconnections within

Fereshteh Forghani, Jason J. Yu, Tristan Aumentado-Armstrong, Konstantinos G. Derpanis

Conventional depth-free multi-view datasets are captured using a moving monocular camera without metric calibration. The scales of camera positions in this monocular setting are ambiguous. Previous methods have acknowledged scale ambiguity in multi-view data via various ad-hoc normalization pre-processing steps, but have not directly analyzed the effect of i

Thota Srinivas, Gaurav Tomar

We investigate the effect of inertial particles on Rayleigh-B\'enard convection using weakly nonlinear stability analysis. In the presence of nonlinear effects, we study the limiting value of growth of instabilities by deriving a cubic Landau equation. An Euler-Euler/two-fluid formulation is being used to describe the flow instabilities in particle-laden Ray

Konrad Schlichtholz, Marcin Markiewicz

Recent work by Vaidman [Phys. Rev. A 86,040101 (2012)] showed that Aharonov-Bohm effect can be explained in terms of local fields, thus effectively restating an old problem of physicality of potentials. In this work, we propose an argument demonstrating the physicality of electromagnetic potential (upon the assumption of locality) based on the causal structu

Mirko Daumann, Thomas Dahm

The imbalanced Hubbard model features a transition between dynamic regimes depending on the mass ratio and coupling strength between two different particle species. A slowdown of the lighter particle transport can be attributed to an emergent effective disorder induced by the heavy particles for high mass ratio and strong coupling. This subdiffusive regime h

Akinari Hoshi, Aiichi Yamasaki

Let $k$ be a global field and $p$ be an odd prime number. We give a necessary and sufficient condition for the Hasse norm principle for separable field extensions $K/k$, i.e. the determination of the Shafarevich-Tate group $Sha(T)$ of the norm one tori $T=R^{(1)}_{K/k}(G_m)$ of $K/k$, with $[K:k]=p^3$ or $p^2$ when the Galois group of the Galois closure of $

Lukas Theiner, Sebastian Hirt, Alexander Steinke, Rolf Findeisen

Trajectory planning for automated vehicles commonly employs optimization over a moving horizon - Model Predictive Control - where the cost function critically influences the resulting driving style. However, finding a suitable cost function that results in a driving style preferred by passengers remains an ongoing challenge. We employ preferential Bayesian o

Pier Luca Lanzi

We present an approach to identify and track the evolution of niches in XCS that can be applied to any XCS model and any problem. It exploits the underlying principles of the evolutionary component of XCS, and therefore, it is independent of the representation used. It also employs information already available in XCS and thus requires minimal modifications

Fabian Denoodt, José Oramas

Since state-of-the-art uncertainty estimation methods are often computationally demanding, we investigate whether incorporating prior information can improve uncertainty estimates in conventional deep neural networks. Our focus is on machine learning tasks where meaningful predictions can be made from sub-parts of the input. For example, in speaker classific

Jisu Nam, Soowon Son, Zhan Xu, Jing Shi

We introduce Visual Persona, a foundation model for text-to-image full-body human customization that, given a single in-the-wild human image, generates diverse images of the individual guided by text descriptions. Unlike prior methods that focus solely on preserving facial identity, our approach captures detailed full-body appearance, aligning with text desc

Foster Sabatino, Matthew Brooks, Charles Tahan, Silas Hoffman

We simulate the non-Abelian exchange of Majorana zero modes (MZMs) on a quantum computer. Rather than utilizing MZMs at the boundaries of quantum Ising chains, which are typically represented as nonlocal operators on a quantum computer, using a Kitaev lattice allows us to exploit a local representation of MZMs. We detail the protocol for braiding two and fou

Yuchen Ren, Zhengyu Zhao, Chenhao Lin, Bo Yang

Vision Transformers (ViTs) have been widely applied in various computer vision and vision-language tasks. To gain insights into their robustness in practical scenarios, transferable adversarial examples on ViTs have been extensively studied. A typical approach to improving adversarial transferability is by refining the surrogate model. However, existing work

Prashant Kumar Choudhary, Nouhaila Innan, Muhammad Shafique, Rajeev Singh

Financial time-series forecasting remains a challenging task due to complex temporal dependencies and market fluctuations. This study explores the potential of hybrid quantum-classical approaches to assist in financial trend prediction by leveraging quantum resources for improved feature representation and learning. A custom Quantum Neural Network (QNN) regr

Alejandro Pequeño-Zurro, Lyes Khacef, Stefano Panzeri, Elisabetta Chicca

Keyword spotting in edge devices is becoming increasingly important as voice-activated assistants are widely used. However, its deployment is often limited by the extreme low-power constraints of the target embedded systems. Here, we explore the Temporal Difference Encoder (TDE) performance in keyword spotting. This recent neuron model encodes the time diffe

Trishul Dhalia, Rohit Juneja, Amita Das

An efficient mechanism of laser pulse focusing with the help of shaped underdense plasma target immersed in inhomogeneous magnetic field has been demonstrated. These studies have been carried out with the help of 2-D Particle-In-Cell (PIC) simulation employing the OSIRIS 4.0 platform. It is shown that the divergent magnetic field profile compresses the EM wa

Jiakun Yan, Marc Snir

Asynchronous Many-Task Systems (AMTs) exhibit different communication patterns from traditional High-Performance Computing (HPC) applications, characterized by asynchrony, concurrency, and multithreading. Existing communication libraries usually do not support AMTs' communication requirements in the most direct and efficient ways. The Lightweight Communicati

Pan Xu

We consider the (offline) vertex-weighted Online Matching problem under Known Identical and Independent Distributions (KIID) with integral arrival rates. We propose a meta-algorithm, denoted as $\mathsf{RTB}$, featuring Real-Time Boosting, where the core idea is as follows. Consider a bipartite graph $G=(I,J,E)$, where $I$ and $J$ represent the sets of offli

Fedor Levkovich-Maslyuk

Separation of variables (SoV) is a powerful method expected to be applicable for a wide range of quantum integrable systems, from models in condensed matter physics to gauge and string theories. Yet its full implementation for many higher rank examples, such as SU(N) spin chains with N>2, has remained elusive for a long time. In this pedagogical review we di

Seth Gerberding

In this paper, we introduce a high order space-time approximation of generalized Korteweg de-Vries equations. More specifically, the method uses continuous $H^1$-conforming finite elements for the spatial approximation and implicit-explicit methods for the temporal approximation. The method is high order in both space, provably stable, and mass-conservative.

Filippo Pantellini

Incompressible vortex flow are observed in a large variety of astrophysical plasmas such as the convection zone and the atmosphere of stars, in astrophysical jets in stellar winds and in planetary magnetospheres. More specifically, magnetohydrodynamic (MHD) simulations have shown that two large scale interlaced Alfv\'enic vortices structure the magnetic tail

Alberto Arletti, Maria Letizia Tanturri, Omar Paccagnella

Online data has the potential to transform how researchers and companies produce election forecasts. Social media surveys, online panels and even comments scraped from the internet can offer valuable insights into political preferences. However, such data is often affected by significant selection bias, as online respondents may not be representative of the

Pablo Cortés, Alejandra Tabares, Fredy Franco

Real-world three-phase microgrids face two interconnected challenges: 1. time-varying uncertainty from renewable generation and demand, and 2. persistent phase imbalances caused by uneven distributed energy resources DERs, load asymmetries, and grid faults. Conventional energy management systems fail to address these challenges holistically and static optimi

Gonzalo Morras, Geraint Pratten, Patricia Schmidt

The observation of gravitational waves from merging black holes and neutron stars provides a unique opportunity to discern information about their astrophysical environment. Two signatures that are considered powerful tracers to distinguish between different binary formation channels are general-relativistic spin-induced orbital precession and orbital eccent

Matthew Brooks, Foster Sabatino, Charles Tahan, Silas Hoffman

While the adiabatic exchange of Majorana zero modes (MZMs) enables a non-universal set of geometrically protected gates, realising an experimental implementation of MZM braiding remains challenging. In an alternative proposal, charge-parity measurement of two neighboring MZMs supports braiding by teleportation. Moreover, owing to the lack of definitive evide

Ziduo Yang, Xiaoqing Liu, Xiuying Zhang, Pengru Huang

Most AI-for-Materials research to date has focused on ideal crystals, whereas real-world materials inevitably contain defects that play a critical role in modern functional technologies. The defects break geometric symmetry and increase interaction complexity, posing particular challenges for traditional ML models. Here, we introduce Defect-Informed Equivari

Yumin Zhang, Yan Gao, Haoran Duan, Hanqing Guo

Transformer-based foundation models (FMs) have recently demonstrated remarkable performance in medical image segmentation. However, scaling these models is challenging due to the limited size of medical image datasets within isolated hospitals, where data centralization is restricted due to privacy concerns. These constraints, combined with the data-intensiv

Menghang Wang, Jingxuan Ding, Grace Xiong, Ni Zhan

In solid acid solid electrolytes CsH$_2$PO$_4$ and CsHSO$_4$, mechanisms of fast proton conduction have long been debated and attributed to either local proton hopping or polyanion rotation. However, the precise role of polyanion rotation and its interplay with proton hopping remained unclear. Nanosecond-scale molecular dynamics simulations, driven by equiva

Natalia Boscolo Meneguolo, Daria Gusakova, Jean-Christophe Toussaint, Mouad Fattouhi

The Perpendicular Shape Anisotropy Spin Transfer Torque Magnetic Random Access Memory (PSA-STT-MRAM) is a recent concept proposed to maintain the thermal stability of standard MRAM at small diameters, considering thick vertical pillars as the free layer. In order to explore the specific physics of PSA-STT-MRAMs expected in relation with their three-dimension

R. Vilela Mendes

Confined to small regions, quantum systems exhibit electronic and structural properties different from their free space behavior. In Coulomb 3-body problems, configurations of close proximity of identically charged particles are classically unstable. They however exist as excited quantum states in confined systems. Quantum control of such states might be use

Amirreza Razmjoo, Sylvain Calinon, Michael Gienger, Fan Zhang

Imitation Learning offers a promising approach to learn directly from data without requiring explicit models, simulations, or detailed task definitions. During inference, actions are sampled from the learned distribution and executed on the robot. However, sampled actions may fail for various reasons, and simply repeating the sampling step until a successful

Dorin Bucur, Richard S. Laugesen, Eloi Martinet, Mickaël Nahon

We prove the existence of an open set $\Omega\subset\mathbb{S}^2$ for which the first positive eigenvalue of the Laplacian with Neumann boundary condition exceeds that of the geodesic disk having the same area. This example holds for large areas and contrasts with results by Bandle and later authors proving maximality of the disk under additional topological

Ivan Villani, Matteo Carrega, Alessandro Crippa, Elia Strambini

The combination of superconductivity and quantum Hall (QH) effect is regarded as a key milestone in advancing topological quantum computation in solid-state systems. Recent quantum interference studies suggest that QH edge states can effectively mediate a supercurrent across high-quality graphene weak links. In this work we report the observation of a superc

Corentin Vazia, Thore Dassow, Alexandre Bousse, Jacques Froment

Photon-counting computed tomography (PCCT) has emerged as a promising imaging technique, enabling spectral imaging and material decomposition (MD). However, images typically suffer from a low signal-to-noise ratio (SNR) due to constraints such as low photon counts and sparse-view settings which provoke artifacts. To prevent this, variational methods minimize

Samuel J. Weisenthal, Amit K. Chowdhry

We live in unprecedented times in terms of our ability to use evidence to inform medical care. For example, we can perform data-driven post-test probability calculations. However, there is work to do. As has been previously noted, sensitivity and specificity, which play a key role in post-test probability calculations, are defined as unadjusted for patient c

Andrés Eduardo Caicedo

We find all linear orders $L,L_2$ such that $L\to(\mathbb Z,L_2)^2$. The key is the identification of the orders $L$ such that $L\to(\mathbb Z,\mathbb Z)^1$.

Bruno França, Denis Kolegov, Igor Konnov, Grzegorz Prusak

We present ChonkyBFT, a partially-synchronous Byzantine fault-tolerant (BFT) consensus protocol used in the ZKsync system. The proposed protocol is a hybrid protocol inspired by FAB Paxos, Fast-HotStuff, and HotStuff-2. It is a committee-based protocol with only one round of voting, single slot finality, quadratic communication, and n >= 5f + 1 fault toleran

Shreshta Rajakumar Deshpande, Mrdjan Jankovic

Highway merges present difficulties for human drivers and automated vehicles due to incomplete situational awareness and a need for a structured (precedence, order) environment, respectively. In this paper, an unstructured merge algorithm is presented for connected and automated vehicles. There is neither precedence nor established passing order through the

Matthieu Jacobs, Mario Paolone

This paper presents a grid-aware probabilistic approach to compute the aggregated flexibility at the grid connection point (GCP) of active distribution networks (ADNs) to allow the participation of DERs in ancillary services (AS) markets. Specifically an optimal power flow (OPF) method using a linear network model is used to compute the aggregated capability

Atanu Paul, Ilya Grinberg

In this work, we develop a framework for atomistic modeling of electronic polarizability to predict the Raman spectra of hydrogen-bonded clusters and liquids from molecular dynamics (MD) simulations. The total polarizability of the system is assumed to arise from contributions of both the monomer unit and intermolecular interactions. The generalized bond-pol

Junseok Park, Eduardo A. Maury, Changhoon Oh, Donghoon Shin

Advances in genome sequencing technologies generate massive amounts of sequence data that are increasingly analyzed and shared through public repositories. On-demand infrastructure services on cloud computing platforms enable the processing of such large-scale genomic sequence data in distributed processing environments with a significant reduction in analys

Tetsuo Hyodo

Plenty of hadrons have been established experimentally, yet the nonperturbative nature of the strong interaction complicates a comprehensive understanding of their internal structure, particularly for exotic hadrons that extend beyond conventional mesons and baryons. One prominent candidate for the internal structure of exotic hadrons is the hadronic molecul

Zijie Deng, Wenjian Peng, Tian-Yi Wang, Haoran Zhang

This paper investigates the well-posedness of contact discontinuity solutions and the vanishing pressure limit for the Aw-Rascle traffic flow model with general pressure functions. The well-posedness problem is formulated as a free boundary problem, where initial discontinuities propagate along linearly degenerate characteristics. To address vacuum degenerac

Anatole Callies, Quentin Bodinier, Philippe Ravaud, Kourosh Davarpanah

Background: Patient recruitment in clinical trials is hindered by complex eligibility criteria and labor-intensive chart reviews. Prior research using text-only models have struggled to address this problem in a reliable and scalable way due to (1) limited reasoning capabilities, (2) information loss from converting visual records to text, and (3) lack of a

Ying Shuai Quan, Mohammad Jeddi, Francesco Prignoli, Paolo Falcone

This paper presents a safe model predictive control (SMPC) framework designed to ensure the satisfaction of hard constraints for systems perturbed by an external disturbance. Such safety guarantees are ensured, despite the disturbance, by online softening a subset of adjustable constraints defined by the designer. The selection of the constraints to be softe

Pieter Pas, Panagiotis Patrinos

Newton systems in quadratic programming (QP) methods are often solved using direct Cholesky or LDL factorizations. When the linear systems in successive iterations differ by a low-rank modification (as is common in active set and augmented Lagrangian methods), updating the existing factorization can offer significant performance improvements over recomputing

Steve Benford, Rachael Garrett, Christine Li, Paul Tennent

We reappraise the idea of colliding with robots, moving from a position that tries to avoid or mitigate collisions to one that considers them an important facet of human interaction. We report on a soma design workshop that explored how our bodies could collide with telepresence robots, mobility aids, and a quadruped robot. Based on our findings, we employed

Yinan Liang, Ziwei Wang, Xiuwei Xu, Jie Zhou

While multimodal large language models demonstrate strong performance in complex reasoning tasks, they pose significant challenges related to model complexity during deployment, especially for resource-limited devices. In this paper, we propose an automatic pruning method for large vision-language models to enhance the efficiency of multimodal reasoning. Con

Cheng Pan, Hung Hon Cheng, Josie Hughes

Teleoperated robotic manipulators enable the collection of demonstration data, which can be used to train control policies through imitation learning. However, such methods can require significant amounts of training data to develop robust policies or adapt them to new and unseen tasks. While expert feedback can significantly enhance policy performance, prov

Jacopo Talpini, Marco Savi, Giovanni Neglia

One-Shot Federated Learning (FL) is a recent paradigm that enables multiple clients to cooperatively learn a global model in a single round of communication with a central server. In this paper, we analyze the One-Shot FL problem through the lens of Bayesian inference and propose FedBEns, an algorithm that leverages the inherent multimodality of local loss f

Seongyu Park, Xavier Durang, Ralf Metzler, Jae-Hyung Jeon

Fickian yet non-Gaussian diffusion is a ubiquitous phenomenon observed in various biological and soft matter systems. This anomalous dynamics is typically attributed to heterogeneous environments inducing spatiotemporal variations in the diffusivity of tracer particles. While previous studies have predominantly focused on systems exhibiting either spatial or

Alessandro D'Andrea, Enrico Fatighenti, Claudio Onorati

We prove some closed formulas for the logarithmic Chern character of a locally free sheaf. The argument used is representation-theoretic and we connect these formulas with the actions of some Casimir elements of $\mathfrak{sl}_r$. As an application, we give a recipe to construct slope polystable modular bundles on hyper-K\"ahler manifolds from old ones.

James Brusseau

Three directions for the AI avant-garde are sketched against the background of time. Posthumanism changes what we are, and belongs to the radical future. Transhumanism changes how we are, and corresponds with the radical past. Genhumanism changes who we are, and exists in the radical present. While developing the concepts, this essay intersects in two ways w

Stefan Haller, Cornelia Vizman

Decorated and augmented nonlinear Grassmannians can be used to parametrize coadjoint orbits of classical diffeomorphism groups. We provide a general framework for decoration and augmentation functors that facilitates the construction of a smooth structure on decorated or augmented nonlinear Grassmannians. This permits to equip the corresponding coadjoint orb

Fangmin Lu, Zheng Chen, Kun Wang

An optimal guidance law for impact time control with field-of-view constraint is presented. The guidance law is derived by first converting the inequality-constrained nonlinear optimal control problem into an equality-constrained one through a saturation function. Based on Pontryagin's maximum principle, a parameterized system satisfying the necessary optima

Tao Hu, Longyao Wu, Wei Dong, Peng Wu

Recovering High Dynamic Range (HDR) images from multiple Standard Dynamic Range (SDR) images become challenging when the SDR images exhibit noticeable degradation and missing content. Leveraging scene-specific semantic priors offers a promising solution for restoring heavily degraded regions. However, these priors are typically extracted from sRGB SDR images

Brandon C. Fallin, Cristian F. Nino, Omkar Sudhir Patil, Zachary I. Bell

Graph neural networks (GNNs) have a message-passing framework in which vector messages are exchanged between graph nodes and updated using feedforward layers. The inclusion of distributed message-passing in the GNN architecture makes them ideally suited for distributed control and coordination tasks. Existing results develop GNN-based controllers to address

Matheus Grossklags, Daniel Lima, Vinicius Zampronio, Fabio Cinti

We investigate the necessary features of the pair interaction for the stabilization of self-assembled quantum quasicrystals in two-dimensional bosonic systems. Unlike the classical scenario, our results show that two-dimensional octagonal, decagonal, and dodecagonal aperiodic phases require a distinct number of properly tuned characteristic length scales for

Thomas Pickard, Aline Villavicencio, Maggie Mi, Wei He

Idiomatic expressions present a unique challenge in NLP, as their meanings are often not directly inferable from their constituent words. Despite recent advancements in Large Language Models (LLMs), idiomaticity remains a significant obstacle to robust semantic representation. We present datasets and tasks for SemEval-2025 Task 1: AdMiRe (Advancing Multimoda

Xuan Ruan, Miguel X. Diaz-Lopez, Matthew T. Gorman, Rui Ni

From particle lifting in atmospheric boundary layers to dust ingestion in jet engines, the transport and deposition of inertial particles in wall-bounded turbulent flows are prevalent in both nature and industry. Due to triboelectrification during collisions, solid particles often acquire significant charges. However, the impacts of the resulting electrostat

Matthieu Jacobs, Hanmin Cai, Mario Paolone

This paper presents the experimental validation of a framework for the coordinated dispatch and control of multiple active distribution networks (ADNs) hosting distributed energy resource (DER). We show that the presented method, which builds further on work done in [1], effectively allows to control multiple ADNs in a distributed way to ensure they achieve

Simon Buchholz, Bernhard Schölkopf

We study the problem of unsupervised representation learning in slightly misspecified settings, and thus formalize the study of robustness of nonlinear representation learning. We focus on the case where the mixing is close to a local isometry in a suitable distance and show based on existing rigidity results that the mixing can be identified up to linear tr