December 2025 arXiv papers — page 36

Manas Mandal, Divya Setia

We obtain a rigidity phenomena of rational cohomology automorphisms of certain homogeneous spaces, in the presence of external cohomology classes arising from spaces with trivial cup product in rational cohomology algebra. We classify graded endomorphisms of the rational cohomology algebra of the product of a sphere and a complex Grassmannian, whose images a

Fabrizio Genovese, Lev Stambler

In this work we present a publicly verifiable quantum money protocol which assumes close to no quantum computational capabilities. We rely on one-time memories which in turn can be built from quantum conjugate coding and hardware-based assumptions. Specifically, our scheme allows for a limited number of verifications and also allows for quantum tokens for di

Erik Aquino-Ortíz, Bernardo Cervantes-Sodi, Karol Chim-Ramirez

We explore how the physical properties of disc galaxies relate to the presence of bars using data from the SDSS-IV MaNGA survey. By combining internal kinematical properties and environmental diagnostics, we find that barred galaxies are more frequently associated with centrally concentrated stellar mass distributions (within 1 and 2 effective radii) and exh

Yue Cao, Yingyao Wang, Pi Bu, Jingxuan Xing

Graphical user interface (GUI) agents can substantially improve productivity by automating frequently executed long-latency tasks on mobile devices. However, existing evaluation benchmarks are still constrained to limited applications, simple tasks, and coarse-grained metrics. To address this, we introduce AndroidLens, a challenging evaluation framework for

Abdullah G. Elafifi, Basma Mamdouh, Mariam Hanafy, Muhammed Alaa Eldin

Acute Myeloid Leukemia (AML) remains a clinical challenge due to its extreme molecular heterogeneity and high relapse rates. While precision medicine has introduced mutation-specific therapies, many patients still lack effective, personalized options. This paper presents a novel, end-to-end computational framework that bridges the gap between patient-specifi

Ben Chugg, Aaditya Ramdas

We derive a new closed-form variance-adaptive confidence sequence (CS) for estimating the average conditional mean of a sequence of bounded random variables. Empirically, it yields the tightest closed-form CS we have found for tracking time-varying means, across sample sizes up to $\approx 10^6$. When the observations happen to have the same conditional mean

Bachir Bekka, Christian Brouder

We investigate the representations of the symmetry groups of infinite crystals. Crystal symmetries are usually described as the finite symmetry group of a finite crystal with periodic boundary conditions, for which the Brillouin zone is a finite set of points. However, to deal with the continuous crystal momentum $\mathbf{k}$ required to discuss the continui

Tzamn Melendez Carmona, Federico Marchesin, Marco P. Abrate, Peter Bienstman

PNNs present promising opportunities for accelerating machine learning by leveraging the unique benefits of photonic circuits. However, current state of the art PNN simulation tools face significant scalability challenges when training large-scale PNNs, due to the computational demands of transfer matrix calculations, resulting in high memory and time consum

Thilo Hartel, Johannes Rauch, Dieter Rautenbach

For a non-negative integer $k$, a vertex cut in a graph is $k$-degenerate if it induces a $k$-degenerate subgraph. We show that a graph of order $n$ at least $2k+2$ without a $k$-degenerate cut has the size at least $\frac{1}{2}\left(k+\Omega\left(\sqrt{k}\right)\right)n$ and that a graph of order $n$ at least $5$ without a $2$-degenerate cut has the size at

Liet Vo

This work investigates a fully discrete mixed finite element method for the stochastic Boussinesq system driven by multiplicative noise. The spatial discretization is performed using a standard mixed finite element method, while the temporal discretization is based on a semi-implicit Euler-Maruyama scheme. By combining a localization technique with high-mome

Mike Goldsmith

The AAVSO-based historical light curve of the oxygen-rich Mira variable R Leonis is used to determine and analyse the properties of the star's maxima and minima. The pulsation period is found to have shortened by about 3 days over the past two centuries. Superimposed on the mean period are clear modulations on timescales of approximately 35 and 98 years. The

Soham Ghosh, Mohammad Ashraf Hossain Sadi

As hyperscale and co-located data centers scale, the electric grid sees an increase in large, voltage-sensitive IT loads with these data center plant size ranging between 500 MW to 2 GW. A sudden loss of these loads as they switch to onsite UPS during grid voltage excursion events causes a grid frequency rise from generation and load imbalance, and a voltage

Massimiliano Alessandro, Davide Frapporti, Christian Gleissner

We study canonical and pluricanonical maps of varieties isogenous to a product of curves, i.e., quotients of the form $X = (C_1 \times \dots \times C_n)/G$ with $g(C_i)\ge 2$ and $G$ acting freely. For this purpose, we provide a technical result which is of general interest: a decomposition theorem for pluricanonical systems of abelian covers. This theorem p

Muhtadin, Vincentius Gusti Putu A. B. M., Ahmad Zaini, Mauridhi Hery Purnomo

Traditional control interfaces for quadruped robots often impose a high barrier to entry, requiring specialized technical knowledge for effective operation. To address this, this paper presents a novel control framework that integrates Large Language Models (LLMs) to enable intuitive, natural language-based navigation. We propose a distributed architecture w

Brian Knaeble, Qinyun Lin, Erich Kummerfeld, Kenneth A. Frank

Sensitivity analysis informs causal inference by assessing the sensitivity of conclusions to departures from assumptions. The consistency assumption states that there are no hidden versions of treatment and that the outcome arising naturally equals the outcome arising from intervention. When reasoning about the possibility of consistency violations, it can b

Joyful E. Mdhluli

The Office of Astronomy for Development (OAD) believes that in order for astronomy-for-development activities to be effective, a scientific approach is required. Evaluation is an essential component in identifying which projects work best, for whom and under what conditions. Evidence-informed project design and selection ensures that projects build on past l

Patricio Gaete, Piero Nicolini

We investigate the interplay between T-duality and (2+1)- dimensional electrodynamics, revealing a relationship between short and large length scales of the gauge potential. Our findings demonstrate that the electrostatic potential energy between static charges is no longer divergent at short distances in the presence of T-duality effects. It remains logarit

N. Holanda, V. Loaiza-Tacuri, A. Sonally, S. Bijavara Seshashayana

We present a chemical abundance study of giant stars in the Galactic open cluster NGC 5822, which hosts two barium stars (#002 and #201) and three lithium-enriched giants (#006, #102, and #240). Using high-resolution optical and near-infrared ($H$ and $K$ band) spectra from FEROS and IGRINS, we determine atmospheric parameters and abundances for 23 elements

Aahan Sachdeva, Dhanvinkumar Ganeshkumar, James E. Gallagher, Tyler Treat

Autonomous robotic platforms are playing a growing role across the emergency services sector, supporting missions such as search and rescue operations in disaster zones and reconnaissance. However, traditional red-green-blue (RGB) detection pipelines struggle in low-light environments, and thermal-based systems lack color and texture information. To overcome

Seyed Arshan Dalili, Mehrdad Mahdavi

Model merging has emerged as a lightweight alternative to joint multi-task learning (MTL), yet the generalization properties of merged models remain largely unexplored. Establishing such theoretical guarantees is non-trivial, as the merging process typically forbids access to the original training data and involves combining fine-tuned models trained on fund

Suren Bandara

Structured data extraction from tables plays a crucial role in document image analysis for scanned documents and digital archives. Although many methods have been proposed to detect table structures and extract cell contents, accurately identifying table segment boundaries (rows and columns) remains challenging, particularly in low-resolution or noisy images

Marco Muraca, Pablo Rodriguez-Fernandez, Joe Hall, Nathaniel T. Howard

In this paper, an overview of the impurity transport for three H-mode plasmas in the upcoming SPARC tokamak has been provided. The simulations have been performed within the ASTRA+STRAHL framework, using FACIT and TGLF-SAT2 to predict, respectively, neoclassical and turbulent core transport, while a neural network trained on EPED simulations has been employe

Alex Krasnok

Resonant phase shifters inevitably mix phase and amplitude. We present a topological synthesis that guarantees a full $2\pi$ phase swing at a prescribed constant scattering magnitude $|S_{ij}|=C$ by winding a scattering zero around the operating point in the complex-frequency plane while avoiding pole windings. We realize this either by complex-frequency wav

Shihao Zou, Jingjing Li, Wei Ji, Jincai Huang

Modern surgical systems increasingly rely on intelligent scene understanding to improve intra-operative safety and situational awareness, with surgical scene segmentation playing a fundamental role in fine-grained surgical perception. Although recent ANN models, especially large foundation models, have achieved impressive accuracy, their high computational a

Yuyao Wang, Andrew Ying, Ronghui Xu

In prevalent cohort studies with delayed entry, time-to-event outcomes are often subject to left truncation where only subjects that have not experienced the event at study entry are included, leading to selection bias. Existing methods for handling left truncation mostly rely on the (quasi-)independence assumption or the weaker conditional (quasi-)independe

Paulo F. Bedaque, Edison M. Murairi, Gautam Rupak, Valery S. Simonyan

In relativistic field theories, the mass spectrum is given by the difference between the energy of the vacuum and the excited states. Near the continuum limit, the cancellation between these two values leads to loss of precision. We propose a method to extract the mass gap directly using quantum computers and apply it to a particular version of the nonlinear

Amit Acharya

The Hamilton-Jacobi equation of classical mechanics is approached as a model reduction of conservative particle mechanics where the velocity degrees-of-freedom are eliminated. This viewpoint allows an extension of the association of the Hamilton-Jacobi equation from conservative systems to general Newtonian particle systems involving non-conservative forces,

Divij Dudeja, Mayukha Pal

The user of Engineering Manuals (EM) finds it difficult to read EM s because they are long, have a dense format which includes written documents, step by step procedures, and standard parameter lists for engineering equipment. Off the shelf transformers, especially compact ones, treat this material as a flat stream of tokens. This approach leads to confident

Vasiliki E. Alexopoulou

The interaction of an intense laser pulse with a solid target produces energetic proton and ion beams through the Target Normal Sheath Acceleration (TNSA) mechanism. Such beams are under active investigation for applications in proton beam therapy, materials modification, and nuclear and high-energy-density physics. Despite extensive experimental and theoret

Ingrid Torres, Alex Krasnok

Twist-angle control offers a bias-free route to reconfigurable metasurfaces, yet its extension to deeply subwavelength resonant platforms at VHF/UHF remains limited. We demonstrate a sub-GHz double-layer wire metasurface formed by two identical wire grids separated by a gap G, with in-plane rotation angle as the sole tuning parameter. One-port, loop-coupled

Snehal Singh Tomar, Alexandros Graikos, Arjun Krishna, Dimitris Samaras

Modern deep learning methods typically treat image sequences as large tensors of sequentially stacked frames. However, is this straightforward representation ideal given the current state-of-the-art (SoTA)? In this work, we address this question in the context of generative models and aim to devise a more effective way of modeling image sequence data. Observ

Irene Benedetti, Paola Rubbioni

We study a class of semilinear impulsive differential inclusions with infinite delay in Banach spaces. The model incorporates multivalued nonlinearities, impulsive effects, and infinite memory, allowing for the description of systems influenced by long-lasting past states and sudden changes. We prove the existence of mild solutions and the compactness of the

Lydia Bieri, David Garfinkle, James Isenberg, David Maxwell

We demonstrate that in constructing asymptotically flat vacuum initial data sets in General Relativity via the conformal method, certain asymptotic structures may be prescribed a priori through the specified seed data, including the ADM momentum components, the leading- and next-to-leading-order decay rates, and the anisotropy in the metric's mass term, yiel

Imtiaz Waheed, Erkinjon Karimov, Mujeeb ur Rehman

This study investigates the nth-level Prabhakar fractional derivative, a generalization encompassing some well-known fractional derivatives. We establish its fundamental properties, particularly its relationship with the corresponding Prabhakar fractional integral. Furthermore, we develop Mikusinski-type operational calculus for this derivative, providing a

Alex Krasnok

Poorly transparent barriers (e.g., reinforced walls, shielding panels, metallic or high-contrast dielectrics) strongly reflect incident radiation, limiting wireless power transfer (WPT) unless the barrier is structurally modified to support a narrowband transparency window. Here we introduce a barrier-agnostic alternative based on coherent scattering control

Andre M. Sonnet, Epifanio G. Virga

In the direct approach to continua in reduced space dimensions, a thin shell is described as a mathematical surface in three-dimensional space. An exploratory kinematic study of such surfaces could be very valuable, especially if conducted with no use of coordinates. Three energy contents have been identified in a thin shell, which refer to three independent

Emmanuel Gnandi, Fortuné Massamba

In this work, we revisit quasi-Sasakian geometry in dimension three and examine how these structures interact with the foliation generated by the Reeb vector field and its basic cohomology. Through a deformation-based approach, we show that a closed, orientable $3$-manifold admits a quasi-Sasakian structure precisely when it is either Sasakian or arises as a

Kewang Chen, Yongqiu Jiang, Kees Vuik

This paper provides a rigorous derivation and analysis of accelerated optimization algorithms through the lens of High-Resolution Ordinary Differential Equations (ODEs). While classical Nesterov acceleration is well-understood via asymptotic vanishing damping, the dynamics of Anderson Acceleration (AA) remain less transparent. This work makes significant the

Weiqi Li, Zehao Zhang, Liang Lin, Guangrun Wang

Controllability is a fundamental requirement in video synthesis, where accurate alignment with conditioning signals is essential. Existing classifier-free guidance methods typically achieve conditioning indirectly by modeling the joint distribution of data and conditions, which often results in limited controllability over the specified conditions. Classifie

Papri Dey

Lorentzian and completely log-concave polynomials have recently emerged as a unifying framework for negative dependence, log-concavity, and convexity in combinatorics and probability. We extend this theory to variational analysis and cone-constrained dynamics by studying $K$-Lorentzian and $K$-completely log-concave polynomials over a proper convex cone $K\s

Matteo Vezzelli, Carsten Gachot, Maria Clelia Righi

Black phosphorus and its single-layer constituent, phosphorene, have emerged as promising two-dimensional materials with remarkable tribological properties. However, recent experimental investigations revealed that the their lubricating capabilities can change with the substrate. The present computational study employs density functional theory calculations

Changwei Wu, Yifei Chen, Yuxin Du, Mingxuan Liu

Reliable anomaly detection in brain MRI remains challenging due to the scarcity of annotated abnormal cases and the frequent absence of key imaging modalities in real clinical workflows. Existing single-class or multi-class anomaly detection (AD) models typically rely on fixed modality configurations, require repetitive training, or fail to generalize to uns

Georgi Gary Rozenman, Kyle I. McKee, Arnaud Lazarus, Valeri Frumkin

We report the results of an experimental study of an analog of the Aharonov-Bohm (AB) effect achieved with the hydrodynamic pilot-wave system. A walking droplet is confined to an annular cavity that encircles a shielded vortex, but lies outside its range of direct influence. While there is no vortex-induced flow in the immediate vicinity of the droplets, the

Isaac Pesenson

This paper is essentially a survey on several classical results of harmonic analysis and their recent extensions to Banach spaces. The first part of the paper is a summary of some important results in such topics as Bernstein spaces, Shannon-type sampling, Riesz and Boas interpolation formulas. The second part contains extensions of these ideas to Banach spa

Camilo Hernández, Ludovic Tangpi

This paper introduces a dynamic formulation of divergence-regularized optimal transport with weak targets on the path space. In our formulation, the classical relative entropy penalty is replaced by a general convex divergence, and terminal constraints are imposed in a weak sense. We establish well-posedness and a convex dual formulation, together with a dua

Diandian Wang

We study the crossing symmetry of the ensemble of large-$c$ 2D CFTs defined through 3D gravity. A central observation is that statistical moments of OPE coefficients are not independent; rather, lower and higher moments are strongly correlated. Using Virasoro TQFT, we clarify how these correlations arise and how they guarantee consistency across OPE channels

Jiakai Tang, Chuan Wang, Gaoming Yang, Han Wu

Industrial recommender systems face two fundamental limitations under the log-driven paradigm: (1) knowledge poverty in ID-based item representations that causes brittle interest modeling under data sparsity, and (2) systemic blindness to beyond-log user interests that constrains model performance within platform boundaries. These limitations stem from an ov

Alaa Alburai, Lluís Galbany, Umut Burgaz, Georgios Dimitriadis

The Zwicky Transient Facility Data Release 2 (ZTF DR2) includes a total of 3,628 Type Ia supernovae (SNe~Ia), providing the largest and most complete sample of spectroscopically confirmed SNe~Ia at low redshift to date. In this paper, we present a photometric and spectroscopic analysis of 124 subluminous SNe~Ia, the largest sample of spectroscopically classi

Nele Callebaut, Blanca Hergueta, Ruben Monten, Matteo Selle

We study deformations of the model by Henneaux, Mart\'inez, Troncoso and Zanelli [arXiv:hep-th/0201170] which features asymptotically AdS$_3$ black hole solutions that incorporate the exact backreaction of a scalar field. The presence of bulk matter causes the $T \overline T$ deformation of the (putative) dual CFT$_2$ to differ from the deformation defined i

F. Thomas Bruss, Davy Paindaveine

We study the win rate $R_{N_d}/N_d$ of a biased simple random walk $S_n$ on $\mathbb{Z}$ at the first-passage time $N_d=\inf\{n\ge 0:S_n=d\}$, with $p=P[X_1=+1]\in[1/2,1)$. Using generating-function techniques and integral representations, we derive explicit formulas for the expectation and variance of $R_{N_d}/N_d$ along with monotonicity properties in the

Xinrui Li, R. Michael Buehrer

Reconfigurable intelligent surfaces (RIS) have recently been proposed as an effective means for spatial interference suppression in large reflector antenna systems. Existing RIS weight optimization algorithms typically rely on accurate theoretical radiation models. However, in practice, distortions on the reflector antenna may cause mismatches between the th

Adwa Alangari, Ohoud Alharbi

This systematic literature review surveys technical defenses against software-based cheating in online multiplayer games. Categorizing existing approach-es into server-side detection, client-side anti-tamper, kernel-level anti-cheat drivers, and hardware-assisted TEEs. Each category is evaluated in terms of detection effectiveness, perfor-mance overhead, pri

Jiawei Liu, Junqiao Li, Jiangfan Deng, Gen Li

The "one-shot" technique represents a distinct and sophisticated aesthetic in filmmaking. However, its practical realization is often hindered by prohibitive costs and complex real-world constraints. Although emerging video generation models offer a virtual alternative, existing approaches typically rely on naive clip concatenation, which frequently fails to

Martijn Dekker

My main worry, and the core of my research, is that our cybersecurity ecosystem is slowly but surely aging and getting old and that aging is becoming an operational risk. This is happening not only because of growing complexity, but more importantly because of accumulation of controls and measures whose effectiveness are uncertain. I introduce a new term for

Haoyang Li, Mingjin Li, Jinxin Zuo, Siqi Li

LLM-based code agents(e.g., ChatGPT Codex) are increasingly deployed as detector for code review and security auditing tasks. Although CoT-enhanced LLM vulnerability detectors are believed to provide improved robustness against obfuscated malicious code, we find that their reasoning chains and semantic abstraction processes exhibit exploitable systematic wea

Xinyao Zhang

In this article, we study the Zariski closure of modular points in the two-dimensional universal deformation space when the residual Galois representation is reducible. Unlike the previous approaches in the residually irreducible case from Gouv\^ea-Mazur, B\"ockle and Allen, our method relies on local-global compatibility results, potential pro-modularity ar

Richard Derbyshire

Lateral movement is a tactic that adversaries employ most frequently in enterprise IT environments to traverse between assets. In operational technology (OT) environments, however, few methods exist for lateral movement between domain-specific devices, particularly programmable logic controllers (PLCs). Existing techniques often rely on complex chains of vul

Pedro Marun, Saharon Shelah, Corey Bacal Switzer

We contribute to the study of $\aleph_1$-dense sets of reals, a mainstay in set theoretic research since Baumgartner's seminal work in the 70s. In particular, we show that it is consistent with $\textsf{MA}$ that there exists an $\aleph_1$-dense set of reals $A$ so that, in any cardinal-preserving generic extension by a forcing of size $\aleph_1$, $A$ and $A

Gaia Ebli, Bianca Raimondi, Maurizio Gabbrielli

The increasing integration of AI tools in education has led prior research to explore their impact on learning processes. Nevertheless, most existing studies focus on higher education and conventional instructional contexts, leaving open questions about how key learning factors are related in AI-mediated learning environments and how these relationships may

Jean Claudio Cardoso Cerbino, Diego Muraca

A novel theoretical expression for the relaxation time of magnetic nanoparticles with dipolar interactions is derived from Kramers' theory, extending the Boltzmann-Gibbs framework to incorporate Tsallis statistics. The model provides a unified description of magnetic relaxation from weakly to strongly interacting regimes. It accounts for both the decrease an

Deuksun Hong, Donghyeon Song, Mingyu Jeong, Junsoo Kim

While computation-enabled cryptosystems applied to control systems have improved security and privacy, a major issue is that the number of recursive operations on encrypted data is limited to a finite number of times in most cases, especially where fast computation is required. To allow for nonlinear dynamic control under this constraint, a method for repres

Anatoly O. Onishchenko, Alexey K. Kovalev, Aleksandr I. Panov

Methods that use Large Language Models (LLM) as planners for embodied instruction following tasks have become widespread. To successfully complete tasks, the LLM must be grounded in the environment in which the robot operates. One solution is to use a scene graph that contains all the necessary information. Modern methods rely on prebuilt scene graphs and as

Alireza Abdollahi, Zeinab Akhlaghi, Majid Arezoomand

A subset \( C \) of the vertex set \( V \) of a graph \( \Gamma = (V,E) \) is termed an $(r,s)$-regular set if each vertex in \( C \) is adjacent to exactly \( r \) other vertices in \( C \), while each vertex not in \( C \) is adjacent to precisely \( s \) vertices in \( C \). A specific case, known as a $(0,1)$-regular set, is referred to as a perfect code

Xinjie Xu, Shuyu Cheng, Dongwei Xu, Qi Xuan

In hard-label black-box adversarial attacks, where only the top-1 predicted label is accessible, the prohibitive query complexity poses a major obstacle to practical deployment. In this paper, we focus on optimizing a representative class of attacks that search for the optimal ray direction yielding the minimum $\ell_2$-norm perturbation required to move a b

Agniva Roychowdhury

High-energy blazar light curves, in X-rays and beyond, have historically preferred a log-normal flux distribution, signifying multiplicative processes either in the jet itself or due to connection(s) with accretion. Here we present 18 year archival Fermi-LAT light curves (0.1-100 GeV) of the flat spectrum radio quasar (FSRQ) CTA 102 from August 2008 to Novem

Adam Bradley, John Hastings, Khandaker Mamun Ahmed

The insurance industry is undergoing a paradigm shift through the adoption of artificial intelligence (AI) technologies, particularly in the realm of intelligent conversational agents. Chatbots have evolved into sophisticated AI-driven systems capable of automating complex workflows, including policy recommendation and claims triage, while simultaneously ena

Mohammed Latif Siddiq, Natalie Sekerak, Antonio Karam, Maria Leal

Large language models (LLMs) are increasingly used in software development, but their level of software security expertise remains unclear. This work systematically evaluates the security comprehension of five leading LLMs: GPT-4o-Mini, GPT-5-Mini, Gemini-2.5-Flash, Llama-3.1, and Qwen-2.5, using Blooms Taxonomy as a framework. We assess six cognitive dimens

Bowen Dang, Lin Wu, Xiaohang Yang, Zheng Yuan

Generating 3D human motions from textual descriptions is an important research problem with broad applications in video games, virtual reality, and augmented reality. Recent methods align the textual description with human motion at the sequence level, neglecting the internal semantic structure of modalities. However, both motion descriptions and motion sequ

Yifan Huang, Xiaojun Jia, Wenbo Guo, Yuqiang Sun

Large language models (LLMs) have revolutionized software development through AI-assisted coding tools, enabling developers with limited programming expertise to create sophisticated applications. However, this accessibility extends to malicious actors who may exploit these powerful tools to generate harmful software. Existing jailbreaking research primarily

Perseas Christodoulidis, Jinn-Ouk Gong

We construct a gravitational open extension of the effective field theory of inflation in the Schwinger-Keldysh framework. While physical symmetries allow many open operators in the Schwinger-Keldysh action, most of them overconstrain the equations of motion, yielding inconsistent dynamics. We identify the minimal open operators compatible with propagating s

Chi Zhang, Penglin Cai, Haoqi Yuan, Chaoyi Xu

Tactile sensing is crucial for robotic hands to achieve human-level dexterous manipulation, especially in scenarios with visual occlusion. However, its application is often hindered by the difficulty of collecting large-scale real-world robotic tactile data. In this study, we propose to collect low-cost human manipulation data using haptic gloves for tactile

Zi-Yao Hu, Yan-Lin Ye, Jian-Ling Lou, Zai-Hong Yang

Experimental and theoretical investigation of the fragmentation reaction in Fermi-energy domain is currently of particular importance for not only the nuclear physics but also some interdisciplinary fields. In the present work, neutron-rich $^{14}$C and $^{16}$C ion beams at 27.5 MeV/nucleon were used to bombard carbon and polyethylene (CD$_{2}$)$_{n}$ targe

Andres M Bran, Tong Xie, Shai Pranesh, Jeffrey Meng

Large Language Models can develop reasoning capabilities through online fine-tuning with rule-based rewards. However, recent studies reveal a critical constraint: reinforcement learning succeeds only when the base model already assigns non-negligible probability to correct answers -- a property we term 'latent solvability'. This work investigates the emergen

Juan Pablo Paz, Corina Révora, Christian Tomás Schmiegelow

We define and study the properties of ``squeezed quantum multiplets''. Ordinary multiplets are sets of $D$-orthonormal quantum states formed by superpositions of states squeezed along $D$ equally spaced directions in quadrature space. More generally, we also discuss superpositions of ``higher-order squeezed states'', including tri-squeezed and quad-squeezed

Shuhan Zhang

This paper presents the design and implementation of a relative localization system for SnailBot, a modular self reconfigurable robot. The system integrates ArUco marker recognition, optical flow analysis, and IMU data processing into a unified fusion framework, enabling robust and accurate relative positioning for collaborative robotic tasks. Experimental v

Stephane Geudens, Florian Schaetz, Alfonso G. Tortorella

Given a compact symplectic manifold $(M,\omega)$ and a compact Lagrangian submanifold $L\subset(M,\omega)$, we describe small deformations of the pair $(\omega,L)$ modulo the action by isotopies. We show that the resulting moduli space can be identified with an open neighborhood of the origin in the second relative de Rham cohomology group $H^2(M,L)$. This i

Haoran Chen, Yue Chen, Yizi Feng, Ruda Guo

High-order anisotropic magnetoresistance (AMR) is observed up to the 18th harmonic in cubic Fe(001) thin films, overturning the long-standing paradigm that only two- and four-fold terms are symmetry-allowed. Using angle-resolved transport and Fourier analysis, we show that six-fold and higher-order terms are intrinsic, tunable by temperature and thickness, a

Peter V. Danchev, Patrick W. Keef

We completely describe in certain important cases the class of commutative co-finitely Hopfian groups as defined by Bridson-Groves-Hillman- Martin in the journal Groups, Geometry, and Dynamics on 2010 (see [3]). We also consider and give a satisfactory description of several related classes of commutative groups. We also discuss in the commutative case a sli

Peter Bradshaw, Abhishek Dhawan, Nhi Dinh, Shlok Mulye

A $k$-uniform hypergraph (or $k$-graph) $H = (V, E)$ is $k$-partite if $V$ can be partitioned into $k$ sets $V_1, \ldots, V_k$ such that each edge in $E$ contains precisely one vertex from each $V_i$. We show that $k$-partite $k$-graphs of maximum degree $\Delta$ are $q$-choosable for $q \geq \left(\frac{4}{5}(k-1 + o(1))\Delta/\log \Delta\right)^{1/(k-1)}$.

Dao Sy Duy Minh, Huynh Trung Kiet, Nguyen Lam Phu Quy, Phu-Hoa Pham

Retrieving images from natural language descriptions is a core task at the intersection of computer vision and natural language processing, with wide-ranging applications in search engines, media archiving, and digital content management. However, real-world image-text retrieval remains challenging due to vague or context-dependent queries, linguistic variab

Le Wang, Zonghao Ying, Xiao Yang, Quanchen Zou

Embodied agents powered by vision-language models (VLMs) are increasingly capable of executing complex real-world tasks, yet they remain vulnerable to hazardous instructions that may trigger unsafe behaviors. Runtime safety guardrails, which intercept hazardous actions during task execution, offer a promising solution due to their flexibility. However, exist

Muhtadin, Faris Rafi Pramana, Dion Hayu Fandiantoro, Moh Ismarintan Zazuli

Maintaining stability during the single-support phase is a fundamental challenge in humanoid robotics, particularly in dance robots that require complex maneuvers and high mechanical freedom. Traditional tethered sensor configurations often restrict joint movement and introduce mechanical noises. This study proposes a wireless embedded balance system designe

Ishika Palit, Miles Angelo Paloma Sodejana, Hsiang-Yi Karen Yang

In this work, we investigate how the choice of initial vector potential and plasma parameters influences the development of accretion columns and jet formation in magnetized accretion flows. Using general relativistic magnetohydrodynamic simulations, we explore two different configurations of the vector potential $A_{\phi}$ and three plasma beta values $\bet

Hongyu Wang, Chenda Li, Xin Zhou, Shuai Wang

Sound separation (SS) and target sound extraction (TSE) are fundamental techniques for addressing complex acoustic scenarios. While existing SS methods struggle with determining the unknown number of sound sources, TSE approaches require precisely specified clues to achieve optimal performance. This paper proposes a unified framework that synergistically com

Nadine Aburumman, Ju-Ling Shih, Cigdem Sengul, Monica Pereira

This paper presents Microtopia, an interdisciplinary programme designed to broaden participation in computer science (CS) among ethnic minority girls. The programme combined coding with design thinking activities, incorporating Artificial Intelligence (AI), the Internet of Things (IoT), and Robotics as key technologies. Learning activities were formulated ar

Kuei-Lin Chiu, Avishma J. Lasrado, Cheng-Han Lo, Yen-Chih Chen

We construct a series of graphene-based superconducting quantum circuits and integrate them into 3D cavities. For a single-qubit device, we demonstrate flux-tunable qubit transition, with a measured $T_1$ $\approx$ 48 ns and a lower bound estimate of $T_2^\ast$ $\approx$ 17.63 ns. By coupling the device to cavities with different resonant frequencies, we acc

Konstantin Popov, Hiroshi Kaji, Tetsuya Kobayashi, Aurelien Martens

A precise synchronization between laser pulse and electron beam arrival time is essential for achieving sub-picosecond stability in modern accelerator facilities. In this work, a Low-Level RF system architecture combined with White Rabbit based timing system has been tested through a collaboration between KEK (Japan) and CNRS/IN2P3, IJClab (France). The setu

Nalin Dhiman

Observed rotation curves of disk galaxies remain a sharp empirical probe of the relationship between baryons and dynamics. We study a minimal, explicitly \emph{phenomenological} alternative to standard halo parameterizations: an additional inward \emph{radial} acceleration proportional to the local \emph{tangential} speed, $a_{\vca}(r)=\gamma(r)\,v(r)$, with

Georgios Filippou, Boi Mai Quach, Diana Lenghel, Arthur White

Attribution modelling lies at the heart of marketing effectiveness, yet most existing approaches depend on user-level path data, which are increasingly inaccessible due to privacy regulations and platform restrictions. This paper introduces a Causal-Driven Attribution (CDA) framework that infers channel influence using only aggregated impression-level data,

Joon-Hwi Kim, Jung-Wook Kim, Jungwon Lim

We propose to call a class of deformed Feynman integrals as twisted Feynman integrals, where the integrand has an additional exponential factor linear in loop momenta. Such integrals appear in various contexts: tensor reduction of Feynman integrals, Fourier transform of Feynman integrals, and spin-resummed dynamics in post-Minkowskian gravity. First, we cons

Siqi Zhu, Yixuan Li, Junfu Li, Qi Wu

While on-body device-based human motion estimation is crucial for applications such as XR interaction, existing methods often suffer from poor wearability, expensive hardware, and cumbersome calibration, which hinder their adoption in daily life. To address these challenges, we present EveryWear, a lightweight and practical human motion capture approach base

A. Andreani, C. Brizzolari, E. J. Cristaldo Morales, M. J. Delgado Gonzalez

The Power over Fiber (PoF) technology delivers electrical power by transmitting laser light through a lightweight, non-conductive fiber optic cable to a remote photovoltaic optical converter, which in turn powers sensors or electrical devices. Among the several advantages offered by this solution are spark-free operation in the presence of electric fields, e

Gargi Mukherjee, Helen W. J. Zhang, Ying Zhong

In this paper, we give explicit error bounds for the asymptotic expansion of the shifted distinct partition function $q(n +s)$ for any nonnegative integer $s$. Then based on this refined asymptotic formula, we give the exact thresholds of $n$ for the inequalities derived from the invariants of the quartic binary form, the double Tur\'{a}n inequalities, the L

Rahul D Ray

Physics-constrained data generation is essential for machine learning in scientific domains where real data are scarce; however, existing approaches often over-constrain models without identifying which physical components are necessary. We present a systematic ablation study of a physics-informed grating coupler spectrum generator that maps five geometric p

Mahi Luthra, Jiayi Shen, Maxime Poli, Angelo Ortiz

Human infants, with only a few hundred hours of speech exposure, acquire basic units of new languages, highlighting a striking efficiency gap compared to the data-hungry self-supervised speech models. To address this gap, this paper introduces SpidR-Adapt for rapid adaptation of speech units to new languages using minimal unlabeled data. We cast such low-res

Ece Bingöl, Eylem Ekici, Mehmet C. Vuran

The large bandwidths available at millimeter wave (mmWave) FR2 bands (24-71 GHz) and the emerging FR3 bands (7-24 GHz) are essential for supporting high data rates. Highly directional beams utilized to overcome the attenuation in these frequencies necessitate robust and efficient beamforming schemes. Nevertheless, antenna and beam management approaches still

Aadarsh Singh, Sudhir K Vempati

We revisit the proposal of Craig and Sutherland that Anderson localization in a disordered fermion theory space can generate small neutrino masses from TeV scale physics \citecraig2018exponential}. Building on this idea, we ask a broader question: can randomness in fermion mass parameters also give rise to nonanarchical neutrino mixing angles, and how does t

Yasaman Hakiminejad, Arash Tavakoli

Pedestrian well-being is a critical yet rarely measured component of sustainable urban mobility and livable city design. Existing approaches to evaluating pedestrian environments often rely on static, infrastructure-based indices or retrospective surveys, which overlook the dynamic, subjective, and psychophysiological dimensions of everyday walking experienc

Xiaoxuan Pan, Chuanlong Ma, Jia-Qi Wang, Zheng-Xu Zhu

Superconducting quantum circuits operate at millikelvin temperatures, typically requiring independent microwave cables for each qubit for connecting room-temperature control and readout electronics. However, scaling to large-scale processors hosting hundreds of qubits faces a severe input/output (I/O) bottleneck, as the dense cable arrays impose prohibitive

Kai Xu, Hang Zhao, Ruizhen Hu, Min Yang

Driven by breakthroughs in next-generation artificial intelligence, embodied intelligence is rapidly advancing into industrial manufacturing. In flexible manufacturing, industrial embodied intelligence faces three core challenges: accurate process modeling and monitoring under limited perception, dynamic balancing between flexible adaptation and high-precisi