December 2025 arXiv papers — page 122

Sergey Pankratov, Dan Alistarh

Speculative generation has emerged as a promising technique to accelerate inference in large language models (LLMs) by leveraging parallelism to verify multiple draft tokens simultaneously. However, the fundamental limits on the achievable speedup remain poorly understood. In this work, we establish the first ``tight'' lower bounds on the runtime of any dete

Yaling Ke

In this work, we present a proof-of-concept investigation of non-equilibrium chemical reaction dynamics at a molecule-electrode interface, driven out of equilibrium by an applied votage bias and mediated by a confined, enhanced vacuum electromagnetic field inside an optical cavity. The coupled electron-vibration-photon system, together with the electrodes an

Wei Chow, Linfeng Li, Lingdong Kong, Zefeng Li

Recent advances in diffusion models (DMs) have achieved exceptional visual quality in image editing tasks. However, the global denoising dynamics of DMs inherently conflate local editing targets with the full-image context, leading to unintended modifications in non-target regions. In this paper, we shift our attention beyond DMs and turn to Masked Generativ

Ondrej Klicnik, Alessandro Zannotti, Yannick Folwill, Oliver de Vries

Polarization instability is a critical challenge for polarization-entangled satellite quantum key distribution (QKD), where atmospheric effects and platform motion continuously distort photon polarization. To maintain entanglement fidelity, these transformations must be accurately identified and compensated prior to detection. In this work, a compact and fas

Amirreza Akbari, Johan Thunberg

For multi-vehicle complex traffic scenarios in shared spaces such as intelligent intersections, safe coordination and trajectory planning is challenging due to computational complexity. To meet this challenge, we introduce a computationally efficient method for generating collision-free trajectories along predefined vehicle paths. We reformulate a constraine

Luca Marchetti, Tom R. Ladstätter, Daniele Oriti

We present a mechanism for the emergence of cosmic acceleration within the mean-field approximation of Group Field Theory models of quantum gravity. Depending on the interaction type, the resulting cosmological dynamics can either feature a late-time attractor corresponding to a dynamical dark energy phase, often with characteristic phantom behavior, includi

An-Dong Fan, Yong-Kun Wang, Jin-Yang Li, Si Li

Altermagnets represent a newly identified third class of collinear magnets and have recently emerged as a focal point in condensed matter physics. In this work, through first-principles calculations and theoretical analysis, we identify monolayer Fe$_2$MoX$_4$ (X = S, Se, Te) and Fe$_2$WTe$_4$, a class of iron-based transition metal chalcogenides, as promisi

Goran Doll, Chiara Buttitta, Enrichetta Iodice, Anna Ferré-Mateu

Context: This paper presents new results from the ESO Large Programme Looking into the faintEst WIth MUSE (LEWIS). The sample consists of low-surface brightness (LSB) and ultra-diffuse galaxies (UDGs) located inside 0.4 R$_{vir}$ of the Hydra I cluster. Integral field spectroscopy is acquired for 24 galaxies with the MUSE spectrograph mounted on the Very Lar

Shun Li, Jing-Yang Xiao Feng, Xiu-Qing Yang, Xiaodong Zeng

We propose an interaction-free ghost imaging scheme based on a thermal light source. By utilizing the quantum Zeno-like effect, our approach significantly reduces the light dose absorbed by the sample, thereby effectively preventing sample damage induced by light-matter interactions. Combined with the elimination of entangled photon sources and single-photon

John Mahlon Scott, Hsin-Hsiung Huang

The Automatic Identification System (AIS) provides time stamped vessel positions and kinematic reports that enable maritime authorities to monitor traffic. We consider the problem of relabeling AIS trajectories when vessel identifiers are missing, focusing on a challenging nationwide setting in which tracks are heavily downsampled and span diverse operating

Liam Doyle, Fargol Seifollahi, Chandralekha Singh

The rapid growth of quantum information science and technology (QIST) presents unique educational challenges as it brings together students and researchers from many disciplines. This work presents findings from in-depth interviews with leading quantum researchers who are also educators, whose perspectives provide guidance for developing a framework for inte

Sebastian Hirt, Valentinus Suwanto, Hendrik Alsmeier, Maik Pfefferkorn

Learning controller parameters from closed-loop data has been shown to improve closed-loop performance. Bayesian optimization, a widely used black-box and sample-efficient learning method, constructs a probabilistic surrogate of the closed-loop performance from few experiments and uses it to select informative controller parameters. However, it typically str

Thomas Nicosanti, Pavel Putrov, Johann Quenta-Raygada

Motivated by some previously known facts from mathematical and physics literature, we explore certain relations between 3-dimensional topological gauge theories with continuous and finite gauge groups, commonly known as Chern-Simons (CS) and Dijkgraaf-Witten (DW) theories, respectively. Specifically, we consider the continuous and finite gauge groups to be t

Murray R. Bremner

Veronese powers of operads were introduced in 2020 By Dotsenko, Markl, and Remm \cite{DMR}. The $m$-th Veronese power of a weight-graded operad $\mathcal{V}$ is the suboperad $\mathcal{V}^{[m]}$ generated by the operations of weight $m$. If $\mathcal{V}$ is generated by binary operations and governs the variety $\mathbf{V}$ of algebras, this gives a natural

Jonathan Elmer, Anja Meyer

Let $M$ denote the vector space of $2 \times 2$ matrices with coefficients in $\mathbb{F}_3$ and trace zero. Let $G = SL_2(\mathbb{F}_3)$. Then $G$ acts on $M$ via conjugation. Let $R =(S(M^*) \otimes \Lambda(M^*))$ be the algebra of differential forms on $M$. We compute a minimal generating set for $R^G$ as a commutative-graded algebra. In doing so we utili

Binwu Gao, Junxuan Liu, Ekaterina Borisova, Hao Tan

In the transmitter of a quantum key distribution (QKD) system, a wavelength-division multiplexer (WDM) is typically used to combine quantum and synchronization signals and is directly connected to the quantum channel. As a result, it becomes the first optical component exposed to laser-injection attacks. Therefore, understanding the behavior of WDMs under su

M. Treyer, R. Ait-Ouahmed, S. Arnouts, J. Pasquet

The multi-band HSC-CLAUDS survey comprises several sky regions with varying observing conditions, only one of which, the COSMOS Ultra Deep Field (UDF), offers extensive redshift coverage. We aim to exploit a complete sample of labeled galaxies from the COSMOS UDF at i<25 (z<~5) to train a convolutional neural network (CNN) and infer more accurate photometric

Roberta De Viti, Vaastav Anand, Pierfrancesco Ingo, Deepak Garg

This paper systematizes knowledge on the performance of Multi-Party Computation (MPC) protocols. Despite strong privacy and correctness guarantees, MPC adoption in real-world applications remains limited by high costs (especially in the malicious setting) and lack of guidance on choosing suitable protocols for concrete workloads. We identify the theoretical

Tanuj Gupta, Emil J. Straube

Let $\Omega\subset \mathbb{C}^{n}$, with $n \geq 3$, be a smooth bounded pseudoconvex domain satisfying the symmetric eigenvalue comparability condition $D(q_0)$ for some $1\le q_0\le n-2$. We show that if the Diederich-Fornaess-index of $\Omega$ is one, then the complex Green operator $G_q$, associated with $\Omega$, is globally regular for $q$ in the range

G. Chachamis, A. Sabio Vera, D. Vaccaro

We show that rank-ordered jet rapidity distributions - a direct application of order statistics - provide a simple yet powerful probe of high-energy (small-x) QCD dynamics at the LHC. In inclusive dijet topologies at s^(1/2) = 8 and 13 TeV, with realistic jet selections, we compare a BFKL-based Monte Carlo (BFKLex) to two general-purpose event generators bas

Gaoxiang Jin, Guinevere Kauffmann, Y. Sophia Dai, Martin J. Hardcastle

We study the spatially resolved star formation, gas ionisation, and outflow properties of 1813 active galactic nuclei (AGNs) from the MaNGA survey, which we classify into infrared (IR), broad-line (BL), narrow-line (NL), and radio (RD) AGNs based on their mid-infrared colours, optical spectra, and/or radio photometry. We also provide estimations of AGN power

Yongkang Li, Kevin J. Wiehe, Scott C. Schmidler

We introduce a method for approximating posterior probabilities of phylogenetic trees and reconstructing ancestral sequences under models of sequence evolution with site-dependence, where standard phylogenetic likelihood computations (pruning) fail. Our approach uses a combined data-augmentation and importance sampling scheme. A key advantage of our approach

Benno van den Berg, John Bourke, Paul Seip

Bourke and Garner described how to cofibrantly generate algebraic weak factorisation systems by a small double category of morphisms. However they did not give an explicit construction of the resulting factorisations as in the classical small object argument. In this paper we give such an explicit construction, as the colimit of a chain, which makes the resu

Aya Kaysan Bahjat

This is to present a text image classifier device that identifies textual content in images and then categorizes each image into one of four predefined categories, including Invoice, Form, Letter, or Report. The device supports a gallery mode, in which users browse files on flash disks, hard disk drives, or microSD cards, and a live mode which renders feeds

Timothy Friesen, Philomène Labilloy, Deven Parekh, Maia List

Background: Stress and negative affect play significant roles in developing psychosis. Bayesian analyses applied to the conditioned hallucinations (CH) task suggest that hallucinations arise when maladaptive prior beliefs outweigh sensory evidence. Prior weighting is linked to hallucination severity, yet the nature of these priors remains unclear. Negative a

Grant Bosworth, Keewoo Lee, Sunwoong Kim

While end-to-end encryption protects the content of messages, it does not secure metadata, which exposes sender and receiver information through traffic analysis. A plausible approach to protecting this metadata is to have senders post encrypted messages on a public bulletin board and receivers scan it for relevant messages. Oblivious message retrieval (OMR)

Manuela Chacon-Chamorro, Juan Sebastián Pinzón, Rubén Manrique, Luis Felipe Giraldo

This paper presents a comparative analysis of cooperative resilience in multi-agent systems, defined as the ability to anticipate, resist, recover from, and transform to disruptive events that affect collective well-being. We focus on mixed-motive social dilemmas instantiated as a \textit{Tragedy of the Commons} environment from the Melting Pot suite, where

Ruslan Nauryzbaev, Ivan Shestakov, Ualbai Umirbaev

We describe all automorphisms of a free metabelian anticommutative algebra of rank $n\geq 3$ over a field $K$ that move only one variable while fixing the others. Such automorphisms are called Chein automorphisms in the cases of free metabelian groups and free metabelian Lie algebras. We show that all automorphisms of a free metabelian anticommutative algebr

Nolan Smyth, Laurence Perreault-Levasseur, Yashar Hezaveh

The search for free-floating planets (FFPs) is a key science driver for upcoming microlensing surveys like the Nancy Grace Roman Galactic Exoplanet Survey. These rogue worlds are typically detected via short-duration microlensing events, the characterization of which often requires analyzing noisy, irregularly-sampled observations. We present a pipeline for

Rui Zhang, Han Wan, Yang Liu, Hao Sun

Accurate modeling of spatiotemporal dynamics is crucial to understanding complex phenomena across science and engineering. However, this task faces a fundamental challenge when the governing equations are unknown and observational data are sparse. System stiffness, the coupling of multiple time-scales, further exacerbates this problem and hinders long-term p

N. Maffezzoli, E. Rignot, C. Barbante, M. Morlighem

We present a global dataset of glacier ice thickness modeled with IceBoost v2.0, a machine learning model trained on 7 million ice thickness measurements and informed by physical and geometrical predictors. We model the distributed ice thickness for every glacier in the two latest Randolph Glacier Inventory releases (v6.0 and v7.0), totaling 215,547 and 274,

Péter Csikvári, Ivan Damnjanović, Marko Milošević, Ivan Stanković

The energy $E(G)$ of a simple graph $G$ is the sum of absolute values of the eigenvalues of its adjacency matrix. A borderenergetic graph of order $n \in \mathbb{N}$ is any noncomplete graph~$G$ such that $E(G) = E(K_n) = 2n - 2$. Here we combine two-phase computer-assisted search with theoretical arguments to show that there are only three borderenergetic c

Christopher Aykroyd, Adrien Bourgoin, Christophe Le Poncin-Lafitte

We present a fully analytical solution to the dynamics of the non-spinning 2.5 post-Newtonian binary problem, accounting for both the long-term (secular) and short-term (oscillatory) temporal behavior, with no restriction on eccentricity. The radiative degrees of freedom are handled within the nonconservative Hamiltonian framework introduced in a companion p

John Homer

We develop Spectral-Operator Calculus (SOC), an axiomatic calculus for scalar evaluation of operator-generated spectral observables. This paper (SOC-I) treats the self-adjoint setting, where observables are bounded Borel transforms and locality is enforced via additivity across spectral partitions. Under unitary invariance, extensivity on orthogonal sums, pr

Qiushi Guo

Data augmentation is crucial for improving the robustness of face detection systems, especially under challenging conditions such as occlusion, illumination variation, and complex environments. Traditional copy paste augmentation often produces unrealistic composites due to inaccurate foreground extraction, inconsistent scene geometry, and mismatched backgro

Hai-Peng Li, Wei-Hong Liang, Chu-Wen Xiao, Eulogio Oset

We study the $J/\psi\to\phi\eta\pi^{0}$ reaction measured recently by the BESIII collaboration with high precision, paying attention to three important aspects: 1) The production of the $a_0(980)$ in the $\pi^0\eta$ mass distributions, with the typical narrow width observed in isospin violating processes; 2) The origin of two peaks in the $\phi\pi^{0}$ mass

Xu Zhang, Jiabin Fang, Zhuoming Ding, Jin Yuan

Recent advances in image understanding have enabled methods that leverage large language models for multimodal reasoning in remote sensing. However, existing approaches still struggle to steer models to the user-relevant regions when only simple, generic text prompts are available. Moreover, in large-scale aerial imagery many objects exhibit highly similar v

Ning Wu, Kaiyu Cui, Ziming Chen, Chenxuan Wang

Higher-order exceptional points (EPs) govern non-Hermitian system dynamics through their enriched and sharpened spectral topology, yet the intrinsic topological fragility hinders robust experimental realization. Here, we present a scalable architecture that implements arbitrary-order EPs via a recurrent network comprising a single nanomechanical resonator an

Emanuelly Silva, Gabriel Hartmann, Rafael C. Nunes

Interacting Dark Energy (IDE) models offer a promising avenue to explore possible exchanges of energy and momentum between dark matter and dark energy, providing a dynamical extension of the standard $\Lambda$CDM paradigm. Such interactions modify the growth of cosmic structures, imprinting distinctive signatures on the matter power spectrum that can be test

Stefan Sommer, Gefan Yang, Elizabeth Louise Baker

Stochastic processes of evolving shapes are used in applications including evolutionary biology, where morphology changes stochastically as a function of evolutionary processes. Due to the non-linear and often infinite-dimensional nature of shape spaces, the mathematical construction of suitable stochastic shape processes is far from immediate. We define and

Reza Shahriari, Eric D. Ragan, Jaime Ruiz

Knowledge graphs are often visualized using node-link diagrams that reveal relationships and structure. In many applications using graphs, it is desirable to allow users to edit graphs to ensure data accuracy or provides updates. Commonly in graph visualization, users can interact directly with the visual elements by clicking and typing updates to specific i

Ayumi Kanamoto, Takuya Isogawa, Shunsuke Nishimura, Haidong Yuan

Designing optimal control for multiparameter quantum sensing is essential for approaching the ultimate precision limits. However, analytical solutions are generally available only for simple systems, while realistic scenarios often involve coupled qubits and time-dependent Hamiltonians. Here we numerically investigate optimal control of a two-qubit sensor-an

Collin C. D. Frink, Chaoyang Ti, Stephen K. Gray, Xu Han

The kernel trick is a widely applicable technique in machine learning domains that maps datasets that are difficult to classify into a computationally friendly feature space. As the dimension of the dataset scales, these kernel calculations can quickly become computationally intractable or data inefficient. In this work, we extend prior efforts in quantum ke

Miriam Resch, Dennis Herb, Mirko Rossini, Joachim Ankerhold

Quantum sensing is an emerging field with the potential to outperform classical methods in both precision and spatial resolution. However, the sensitivity of the underlying quantum platform also makes the sensors highly susceptible to their environmental noise. To address this issue, techniques from the field of quantum error mitigation use information about

Tanja Đurić, Pinaki Sengupta

Kagome lattice antiferromagnets exhibit plethora of intriguing phases of matter. Particularly interesting state appears at the magnetic field-induced $1/9$ magnetization plateau observed in several recent experimental studies. The nature and exotic physical properties of the plateau however remain controversial due to an exceptional complexity of the state g

Lázaro Martínez-Ortíz, Youri H. Lemm, Herman J. H. Clercx, Rudie P. J. Kunnen

The large-scale circulation (LSC) of turbulent convection is a prominent feature of its dynamics and forms the basis for descriptive theories. We show, using experimental and numerical results from thermal convection in a cylindrical cell, that the LSC possesses a persistent internal `clock': its pulsating velocity as a function of time is described by a con

Afonso Lourenço, João Gama, Eric P. Xing, Goreti Marreiros

In streaming scenarios, models must learn continuously, adapting to concept drifts without erasing previously acquired knowledge. However, existing research communities address these challenges in isolation. Continual Learning (CL) focuses on long-term retention and mitigating catastrophic forgetting, often without strict real-time constraints. Stream Learni

Gabriel Almeida, João Paulo Esper, Cleverson Nahum, Aldebaro Klautau

Virtual Reality Cloud Gaming (VR-CG) represents a demanding class of immersive applications, requiring high bandwidth, ultra-low latency, and intelligent resource management to ensure optimal user experience. In this paper, we propose a scalable and QoE-aware multi-stage optimization framework for resource allocation in VR-CG over 6G networks. Our solution d

Graham L Giller

An analytical solution to single-horizon asset allocation for an investor with a piecewise-linear utility function, called herein the "budget threshold utility," and exogenous position limits is presented. The resulting functional form has a surprisingly simple structure and can be readily interpreted as representing the addition of a simple "risk cost" to o

Ruiwen Xie, Hamza Zerdoumi, Hongbin Zhang

Hematite $\alpha$-Fe$_2$O$_3$ is a $g$-wave altermagnetic material, which has an easy-axis phase and easy-plane weak ferromagnetic phase below and above Morin transition temperature, respectively. The presence of these phases renders it a good candidate to study the characteristic spin splitting in altermagnets under the impacts of relativistic effect and fi

Gianluca Gubbiotti, Olha Bezsmertna, Oleksandr V. Pylypovskyi, Rui Xu

Curvilinear magnetic nanostructures enable control of magnetization dynamics through geometry-induced anisotropy and chiral interactions as well as magnetic field modulation. In this work, we report a curvilinear magnonic crystal based on large-area square arrays of truncated nanospikes fabricated by conformal coating of 3D hierarchical templates with permal

Thiago H Silva, Daniel Silver, Gustavo Santos, Myriam Delgado

Why are some neighborhoods strongly connected while others remain isolated? Although standard explanations focus on demographics, economics, and geography, movement across the city may also depend on cultural styles and amenity mix. This study proposes a relational, cross-national model in which local culture and amenity mix alignment creates a "soft infrast

Brenda Nogueira, Werner Geyer, Andrew Anderson, Toby Jia-Jun Li

Large Language Models (LLMs) are increasingly embedded in academic writing practices. Although numerous studies have explored how researchers employ these tools for scientific writing, their concrete implementation, limitations, and design challenges within the literature review process remain underexplored. In this paper, we report a user study with researc

Sami Fersi

We generalize the Cartier transform of Ogus and Vologodsky to log smooth schemes. More precisely, we generalize a local version of this transform, due to Shiho, and a topos-theoretic version, due to Oyama. Let $k$ be a perfect field of positive characteristic $p$ and equip $S=\operatorname{Spec}k$ with the trivial log structure. For a log smooth scheme $X$ o

Raphael Appenzeller, Auguste Hébert, Alexander Lytchak

We prove that any convex flat subset in a complete Euclidean building is contained in an apartment of the maximal system of apartments.

Alessandro D'Andrea, Enrico Fatighenti, Claudio Onorati

Given a vector bundle $E$, we give an explicit formula to compute Chern classes of Schur bundles $\operatorname{S}^\alpha E$ in terms of those of $E$.

Chenguang Liu, Hao Tian, Jinlong Shao

In this paper, we introduce a novel bond-based peridynamic model that utilizes a Gaussian kernel function. Previous peridynamic models, when directly discretized, have exhibited a lack of asymptotically compatibility with their corresponding local elastic solutions. Additionally, these models have faced challenges in accurately computing the volume of inters

Chutian Ma, Grigorii Pomazkin, Giacinto Paolo Saggese, Paul Smith

Energy demand prediction is critical for grid operators, industrial energy consumers, and service providers. Energy demand is influenced by multiple factors, including weather conditions (e.g. temperature, humidity, wind speed, solar radiation), and calendar information (e.g. hour of day and month of year), which further affect daily work and life schedules.

Hester G. Vennema, Cristina Mier, Evert W. Stolte, Leonard Edens

The nuclear spin is a prime candidate for quantum information applications due to its weak coupling to the environment and inherently long coherence times. However, this weak coupling also challenges the addressability of the nuclear spin. Here we demonstrate nuclear magnetic resonance (NMR) on a single on-surface atom using a local scanning probe. We employ

Connie M. Wang, Roberta M. Sabino, Aditya Garg, Ahmed E. Salih

Innovation in biomaterials has brought both breakthroughs and new challenges in medicine, as implant materials have become increasingly multifunctional and complex. One of the greatest issues is the difficulty in assessing the temporal and multidimensional dynamics of tissue-implant interactions. Implant biology remains hard to decipher without a noninvasive

Pramudita Satria Palar, Paul Saves, Rommel G. Regis, Koji Shimoyama

Explainable machine learning techniques have gained increasing attention in engineering applications, especially in aerospace design and analysis, where understanding how input variables influence data-driven models is essential. Partial Dependence Plots (PDPs) are widely used for interpreting black-box models by showing the average effect of an input variab

Zicun Li, Huanjing Gong, Ruijuan Xiao, Xinguo Ren

With the rapid advancement of machine learning techniques for materials simulations, machine-learned force fields (MLFFs) have become a powerful tool that complements first-principles calculations by enabling high-accuracy molecular dynamics simulations over extended timescales. Typically, MLFFs are trained on data generated from density functional theory (D

Jean-Patrick Mascomère, Jérémie Messud, Yagnik Chatterjee, Isabel Barros Garcia

This article proposes a unified framework for portfolio optimization (PO), recognizing an object called the `gain probability density function (PDF)' as the fundamental object of the problem from which any objective function could be derived. The gain PDF has the advantage of being 1-dimensional for any given portfolio and thus is easy to visualize and inter

Henri Ver Hulst, Carles Blanch Mercader, Frank Jülicher, Pascal Martin

The cochlea's capacity to process a broad range of sound intensities has been linked to nonlinear amplification by critical oscillators. However, while the increasing sensitivity of a critical oscillator upon decreasing the stimulus magnitude comes with proportionally sharper frequency tuning and slower responsiveness -- critical slowing down, the observed b

Jiapeng Tang, Kai Li, Chengxiang Yin, Liuhao Ge

We introduce FactorPortrait, a video diffusion method for controllable portrait animation that enables lifelike synthesis from disentangled control signals of facial expressions, head movement, and camera viewpoints. Given a single portrait image, a driving video, and camera trajectories, our method animates the portrait by transferring facial expressions an

Georgia Samara, Christoforos Theodorou, Alexandros Mavropoulis, Nikolaos Vasileiadis

High performance devices consisting of interdigitated electrodes (IDEs) on top of single-layer graphene (SLG) are candidates with favorable prospects for sensing applications. Graphene micro ribbons (GMRs) of various widths and IDE design geometries were fabricated and experimentally examined regarding their low-frequency noise (LFN) behavior. Measurements r

Manideep Reddy Chinthareddy

Snowflake-style distributed ID generators are the industry standard for producing k-ordered, unique identifiers at scale. However, the traditional requirement for manually assigned or centrally coordinated worker IDs introduces significant friction in modern container-orchestrated environments (e.g., Kubernetes), where workloads are ephemeral and autoscaled.

Timm Gilles

We study the recovery of low-rank Hermitian matrices from rank-one measurements obtained by uniform sampling from complex projective 3-designs, using nuclear-norm minimization. This framework includes phase retrieval as a special case via the PhaseLift method. In general, complex projective $t$-designs provide a practical means of partially derandomizing Gau

Bruno Rodrigues, Inês Ochoa, Agostinho Gomes

Calorimeters are a crucial component in modern particle detectors. They are responsible for providing accurate energy measurements of particles produced in high-energy collisions. The demanding requirements set for next-generation collider experiments impose new challenges on the design of new detectors, and a systematic approach to their optimization is inc

Daniel Carando, Verónica Dimant, Jorge Tomás Rodríguez

We study the structure of the spectrum of the algebra of uniformly continuous holomorphic functions on the unit ball of $\ell_p$. Our main focus is the relationship between \emph{Gleason parts} and \emph{fibers}. For every $z \in B_{\ell_p}$ with $1 < p < \infty$, we prove that the fiber over $z$ contains $2^{\mathfrak{c}}$ distinct Gleason parts. We also in

Juan Andrés Urrea-Niño, Ryan Bignell, Ruaidhrí Campion, Sinéad M. Ryan

Drawing upon well established zero-temperature techniques, we present, for the first time in a lattice calculation, insight into the fate of the $1^{-+}$ exotic charmonium state at finite temperature. Specifically, using anisotropic FASTSUM ensembles we employ distillation with a wide operator basis which has been extensively used at zero-temperature by the

Nicolas Guès

We show that the moduli space of $n$ suitably embedded copies of a closed smooth manifold $P$ inside a closed smooth manifold $M$ satisfies cohomological periodicity over $\mathbb F_\ell$ when $n$ grows, with an explicit linear bound on the period and the periodicity range. This generalizes a known result about configuration spaces. We also show integral sta

Keerthana Murugaraj, Salima Lamsiyah, Marten During, Martin Theobald

Extracting coherent and human-understandable themes from large collections of unstructured historical newspaper archives presents significant challenges due to topic evolution, Optical Character Recognition (OCR) noise, and the sheer volume of text. Traditional topic-modeling methods, such as Latent Dirichlet Allocation (LDA), often fall short in capturing t

Elia Palme, Juan Pablo Dorsch, Ali Khosravi, Giovanni Pizzi

Introducing FirecREST v2, the next generation of our open-source RESTful API for programmatic access to HPC resources. FirecREST v2 delivers a 100x performance improvement over its predecessor. This paper explores the lessons learned from redesigning FirecREST from the ground up, with a focus on integrating enhanced security and high throughput as core requi

Tan Le, Van Le, Sachin Shetty

Open Radio Access Networks (O-RAN) enhance modularity and telemetry granularity but also widen the cybersecurity attack surface across disaggregated control, user and management planes. We propose a hierarchical defense framework with three coordinated layers-anomaly detection, intrusion confirmation, and multiattack classification-each aligned with O-RAN's

Giuseppe Paolo Seta, Louisiane Devaud, Lorenzo Dania, Lukas Novotny

Optically levitated nanoparticles are promising candidates for the generation of macroscopic quantum states of mechanical motion. Protocols to generate such states expose the particle to a succession of different potentials. Limited reproducibility of the alignment of these potentials across experimental realizations introduces additional noise. Here, we exp

Ronald Santiago Cortes, Aravindh S. Shankar, Marcello Dalmonte, Roberto Verdel

Neural Quantum States (NQS) are powerful tools used to represent complex quantum many-body states in an increasingly wide range of applications. However, despite their popularity, at present only a rudimentary understanding of their limitations exists. In this work, we investigate the dependence of NQS on the choice of the computational basis, focusing on re

Alexander J. B. Russell, James A. McLaughlin, Philippa Browning, Jennifer Carter

Magnetic reconnection powers explosive releases of magnetic energy, heating and particle acceleration throughout the plasma universe. Knowledge of this universal process is vital to understanding the Heliosphere, as it plays a key role in solar flares, coronal mass ejections, coronal heating, solar wind acceleration, geomagnetic storms, and interactions betw

Vasile-Laurentiu Dosan, Alek Lagarrigue, Alessandro Zannotti, Tushar Parab

Entangled photon sources (EPSs) are essential building blocks for scalable quantum communication and quantum key distribution (QKD). We present a stable, highly nondegenerate EPS based on type-0 spontaneous parametric down-conversion (SPDC) in a crossed-crystal configuration, generating photon pairs at 680~nm and 1550~nm when pumped by a 473~nm laser. This w

Anish Nair, Austin O' Connell, Shalomi Arulpragasam, Noah Kim

This work investigates the feasibility and design trade-offs for a companion spacecraft, or PaddleSat, to charge a host spacecraft by wirelessly transmitting power using a directional laser system. The primary goal of the PaddleSat is to supplement power on a host spacecraft to reduce the requirements for onboard power systems of the host spacecraft or exten

Yichi Zang

We study irregular representations of Virasoro algebra associated with half-integer order singularities, which arise naturally in the 2d CFT description of Argyres-Douglas theories of type $(A_1, A_{\text{even}})$ and $(A_1, D_{\text{odd}})$. While integer-rank irregular states admit a well-established free-field construction, the half-integer case is more s

Bastian Rubrecht, Ellen Häußler, Mirtha Pillaca, Pritam Bhattacharyya

Delafossite compounds containing rare-earth ions have been proven to be an ideal platform to investigate frustrated magnetic ground states. Here, we discuss two triangular-lattice antiferromagnets, TlErSe$_2$ and TlTmSe$_2$, as potential candidates for hosting exotic quantum states. Powder X-ray diffraction data analysis of the black-color polycrystalline Tl

Chang-Wei Lin, Yi-Ting Ma, Jiun-Shiuan Shiu, Yong-Fan Chen

We demonstrate polarization-entangled biphotons in a cold-atom double-$\Lambda$ system, overcoming atomic selection rules that suppress polarization correlations and favor orbital angular momentum (OAM) entanglement. Using spatial light modulators, we coherently map a selected two-dimensional OAM subspace onto the polarization basis and thereby open an other

Maik Dannecker, Steven Jia, Nil Stolt-Ansó, Nadine Girard

Recovering high-fidelity 3D images from sparse or degraded 2D images is a fundamental challenge in medical imaging, with broad applications ranging from 3D ultrasound reconstruction to MRI super-resolution. In the context of fetal MRI, high-resolution 3D reconstruction of the brain from motion-corrupted low-resolution 2D acquisitions is a prerequisite for ac

Jay Pandey, Kedar Damle

We argue that the low-temperature physics of $S=1$ pyrochlore magnets with a predominantly Ising-like easy-axis exchange coupling $J$ that favors the local tetrahedral body diagonals, and a comparably large easy-plane single-ion anisotropy $\Delta =J + \mu$ ($|\mu| \ll J$) that favors the plane perpendicular to these local axes will exhibit interesting new p

Jiri Mazurek, Luis Ángel Calvo

The analytic hierarchy process (AHP) is one of the most widely used multicriteria decision-making methods, with applications from agriculture to space engineering. Despite its popularity, AHP has been repeatedly criticised for rank reversal, a phenomenon in which the ranking of alternatives changes after the addition or removal of an irrelevant or duplicate

Pablo Roig-Madrid, Miguel Carmona-Cabello, Alberto-Jesus Perea-Moreno, M. P. Dorado

This study investigates the energy valorization potential of 16 aromatic seed residues (ASW), a by-product generated after essential oil extraction from Mediterranean aromatic and medicinal plants. Driven by the increasing demand for natural bioactive ingredients and the expansion of aromatic crop production, large amounts of residual biomass remain underuti

Kanisorn Sangchai, Methasit Boonpun, Withawin Kraipetchara, Paulo Garcia

The realization of intelligent robots, operating autonomously and interacting with other intelligent agents, human or artificial, requires the integration of environment perception, reasoning, and action. Classic Artificial Intelligence techniques for this purpose, focusing on symbolic approaches, have long-ago hit the scalability wall on compute and memory

Xi Wang, Jing Liu, Siqian Li, Hengtai Dai

Thin dielectric elastomer actuator (DEA) features a unique in-plane configuration, enabling low-profile designs capable of accessing millimetre-scale narrow spaces. However, most existing DEA-powered soft robots require high voltages and wired power connections, limiting their ability to operate in confined environments. This study presents an untethered thi

Diogo Pinheiro, M. Rosário Oliveira, Igor Kravchenko, Lina Oliveira

In Data Science, entities are typically represented by single valued measurements. Symbolic Data Analysis extends this framework to more complex structures, such as intervals and histograms, that express internal variability. We propose an extension of multiclass Fisher's Discriminant Analysis to interval-valued data, using Moore's interval arithmetic and th

Lorenzo Carfagna, Carlo Tosoni

Entropy quantifies the number of bits required to store objects under certain given assumptions. While this is a well established concept for strings, in the context of tries the state-of-the-art regarding entropies is less developed. The standard trie worst-case entropy considers the set of tries with a fixed number of nodes and alphabet size. However, this

Sasha Glendinning, Susana N. Gomes, Marie-Therese Wolfram

We establish an approach for consensus control of opinion dynamics by introducing a liar to the classical system. The liar's aim is to steer the population towards consensus at their goal opinion by showing 'apparent opinions', or 'lies', to members of the population. We analyse this as an optimal control problem for how best to lie to a population in order

Javier Fumanal-Idocin, Raquel Fernandez-Peralta, Javier Andreu-Perez

Fuzzy rule-based systems have been mostly used in interpretable decision-making because of their interpretable linguistic rules. However, interpretability requires both sensible linguistic partitions and small rule-base sizes, which are not guaranteed by many existing fuzzy rule-mining algorithms. Evolutionary approaches can produce high-quality models but s

S. Frenkel, V. Zakharov, E. A. Katz

Predicting degradation rates is an important task in the development of new perovskite solar cells (PSCs). In this paper, we explore the feasibility of solving this problem using Machine Learning models supported by LLM tools. We consider both the "lifetime" prediction of the device and the prediction of degree of its degradation at specific time intervals.

Björn Deiseroth, Max Henning Höth, Kristian Kersting, Letitia Parcalabescu

Retrieval-augmented generation (RAG) relies on retrieved context to guide large language models (LLM), yet treats the retrieval as a heuristic rather than verifiable evidence -- leading to unsupported answers, hallucinations, and reliance on spurious context. We introduce a novel evaluation, data augmentation, and training framework that treats the RAG pipel

Stefano Giordano, Giuseppe Florio, Giuseppe Puglisi, Fabrizio Cleri

Open quantum systems play a central role in contemporary nanoscale technologies, including molecular electronics, quantum heat engines, quantum computation and information processing. A major theoretical challenge is to construct dynamical models that are simultaneously consistent with classical thermodynamics and complete positivity. In this work, we develo

Chunyi Li, Rui Qing, Jianbo Zhang, Yuan Tian

Image Compression for Machines (ICM) has emerged as a pivotal research direction in the field of visual data compression. However, with the rapid evolution of machine intelligence, the target of compression has shifted from task-specific virtual models to Embodied agents operating in real-world environments. To address the communication constraints of Embodi

Chunyi Li, Longfei Li, Zicheng Zhang, Xiaohong Liu

Graphical User Interface (GUI) agents adopt an end-to-end paradigm that maps a screenshot to an action sequence, thereby automating repetitive tasks in virtual environments. However, existing GUI agents are evaluated almost exclusively on commodity software such as Microsoft Word and Excel. Professional Computer-Aided Design (CAD) suites promise an order-of-

Tingyu Yuan, Biaoliang Guan, Wen Ye, Ziyan Tian

In embodied intelligence, the embodiment gap between robotic and human hands brings significant challenges for learning from human demonstrations. Although some studies have attempted to bridge this gap using reinforcement learning, they remain confined to merely reproducing human manipulation, resulting in limited task performance. Moreover, current methods

A. Raymond, P. Cathala, M. Morassi, A. Lemaître

Unlike discrete photonic circuits, which manipulate photons step-by-step using a series of optical elements, arrays of coupled waveguides enable photons to interfere continuously across the entire structure. When composed of a nonlinear material, such arrays can also directly generate quantum states of light within the circuit. To clarify the similarities an