March 2025 arXiv papers — page 186

A. Dutta, P. C. C. Freire, T. Gautam, N. Wex

PSR J0514$-$4002A is a binary millisecond pulsar located in the globular cluster NGC 1851. The pulsar has a spin period of 4.99 ms, an orbital period of 18.8 days, and is in a very eccentric ($e = 0.89$) orbit around a massive companion. In this work, we present the updated timing analysis of this system, obtained with an additional 1 yr of monthly observati

Chenyu Shi, Gabriele Leoni, Mauro Petrillo, Antonio Puertas Gallardo

Computing the similarity between two DNA sequences is of vital importance in bioscience, yet it can be computationally expensive on classical hardware. For example, the edit distance with move operations (EDM), a DNA similarity measure of interest in biology, is proven to be NP-Complete to compute exactly on classical hardware. Recently, applied quantum algo

Ruslan Gokhman, Jialu Li, Youshan Zhang

Automating teaching presents unique challenges, as replicating human interaction and adaptability is complex. Automated systems cannot often provide nuanced, real-time feedback that aligns with students' individual learning paces or comprehension levels, which can hinder effective support for diverse needs. This is especially challenging in fields where abst

Davide Maestrini, Daniele Noto, Giovanni Dematteis, Miguel Onorato

The wave kinetic equation has become an important tool in different fields of physics. In particular, for surface gravity waves, it is the backbone of wave forecasting models. Its derivation is based on the Hamiltonian dynamics of surface gravity waves. Only at the end of the derivation are the non-conservative effects, such as forcing and dissipation, inclu

M. Stein, J. Kleimann, B. Adebahr, R. -J. Dettmar

Understanding galactic magnetic fields is essential for interpreting feedback processes in galaxies. Despite their importance, the exact structure of these fields, particularly in galactic halos, remains unclear. Accurate descriptions are crucial for understanding the interaction between star formation and halo magnetisation. By systematically analysing the

T. J. Duckenfield, D. B. Jess, R. J. Morton, S. Jafarzadeh

Coronal oscillations offer insight into energy transport and driving in the solar atmosphere. Knowing its polarisation state helps constrain a wave's displacement and velocity amplitude, improving estimates of wave energy flux and deposition rate. We demonstrate a method to combine imaging and spectral data to infer the polarisation of a coronal loop's stand

Gaia Da Prato, Yong Yu, Ronald Bode, Simon Gröblacher

A tunable magnetic field at low temperatures is essential for numerous applications, including spintronics, magnetic resonance imaging, and condensed matter physics. While commercial superconducting vector magnets are available, they are complex, expensive, and often not adaptable to specific experimental needs. As a result, simple in-house designs are often

Lars Meuser, Alexandros Patsilinakos, Pietro Faccioli

In silico de novo design can drastically cut the costs and time of drug development. In particular, a key advantage of bottom-up physics-based approaches is their independence from training datasets, unlike generative models. However, they require the simultaneous exploration of chemical and conformational space. In this study, we address this formidable cha

Keri D'Angelo, Sophie Libkind

Directed wiring diagrams can be used as a composition pattern for composing input/output systems such as Moore machines. In a Moore machine, the input parametrizes an internal state and the internal state defines the output. Because the value of the output is shielded from the input by the internal state, Moore machines can compose by connecting the output o

Jinwook Kim, Sangmin Park, Qiushi Zhou, Mar Gonzalez-Franco

This paper investigates multi-selection in XR interfaces based on eye and hand interaction. We propose enabling multi-selection using different variations of techniques that combine gaze with a semi-pinch gesture, allowing users to select multiple objects, while on the way to a full-pinch. While our exploration is based on the semi-pinch mode for activating

Chase McDonald, Cleotilde Gonzalez

Research on human-AI collaboration often prioritizes objective performance. However, understanding human subjective preferences is essential to improving human-AI complementarity and human experiences. We investigate human preferences for controllability in a shared workspace task with AI partners using Behavior Shaping (BS), a reinforcement learning algorit

Alexander Guthmann, Felix Lang, Louisa Marie Kienesberger, Sian Barbosa

Scattering resonances are fundamental in science, spanning energy scales from stellar nuclear fusion to ultracold collisions. In ultracold quantum gases, magnetic Feshbach resonances have transformed quantum many-body research by enabling precise interaction control between atoms. Here, we demonstrate unprecedented control to engineer new Feshbach resonances

Taco Cohen, David W. Zhang, Kunhao Zheng, Yunhao Tang

RL-based post-training of language models is almost exclusively done using on-policy methods such as PPO. These methods cannot learn from arbitrary sequences such as those produced earlier in training, in earlier runs, by human experts or other policies, or by decoding and exploration methods. This results in severe sample inefficiency and exploration diffic

Greta Segantini, Ludovica Tovaglieri, Chang Jae Roh, Chih-Ying Hsu

In this study, we explore the ferroelectric domain structure and mechanical properties of PbTiO$_3$-based membranes, which develops a well-ordered and crystallographic-oriented ripple pattern upon release from their growth substrate. The ferrolectric domain structure of the PbTiO$_3$ layer was examined at various length scales using optical second harmonic g

Margarita Capretto, Martín Ceresa, Antonio Fernández Anta, Pedro Moreno-Sánchez

Blockchains face a scalability challenge due to the intrinsic throughput limitations of consensus protocols and the limitation in block sizes due to decentralization. An alternative to improve the number of transactions per second is to use Layer 2 (L2) rollups. L2s perform most computations offchain using blockchains (L1) minimally under-the-hood to guarant

Aramis Raiola, Fabio Acerbi, Cyril Alispach, Hossein Arabi

Position-sensitive SiPMs are useful in all light detection applications requiring a small number of readout channels while preserving the information about the incoming light's interaction position. Focusing on a 2x2 array of LG-SiPMs covering an area of $\sim 15.5 \times 15.5~\rm{mm}$ with just 6 readout channels, we proposed a quantitative method to evalua

Nenad Petrovic, Fengjunjie Pan, Vahid Zolfaghari, Alois Knoll

In this paper, we introduce an automated approach to domain-specific metamodel construction relying on Large Language Model (LLM). The main focus is adoption in automotive domain. As outcome, a prototype was implemented as web service using Python programming language, while OpenAI's GPT-4o was used as the underlying LLM. Based on the initial experiments, th

Duong H. T. Vo, Nelofer Syed, Thomas Thorne

Graphical modeling is a widely used tool for analyzing conditional dependencies between variables and traditional methods may struggle to capture shared and distinct structures in multi-group or multi-condition settings. Joint graphical modeling (JGM) extends this framework by simultaneously estimating network structures across multiple related datasets, all

Weigao Sun, Disen Lan, Tong Zhu, Xiaoye Qu

Linear Sequence Modeling (LSM) like linear attention, state space models and linear RNNs, and Mixture-of-Experts (MoE) have recently emerged as significant architectural improvements. In this paper, we introduce Linear-MoE, a production-level system for modeling and training large-scale models that integrate LSM with MoE. Linear-MoE leverages the advantages

Youwei Zhang, Shenchao Jin, Junlei Duan, Klaus Mølmer

Creating highly spin-squeezed states for quantum metrology surpassing the standard quantum limit is a topic of great interest. Spin squeezing has been achieved by either entangling different atoms in an ensemble, or by controlling the multilevel internal spin state of an atom. Here, we experimentally demonstrate combined internal and collective spin squeezin

Meiyu Lin, Haichuan Zhang, Jiale Lao, Renyuan Li

Large language models (LLMs) have shown state-of-the-art results in translating natural language questions into SQL queries (Text-to-SQL), a long-standing challenge within the database community. However, security concerns remain largely unexplored, particularly the threat of backdoor attacks, which can introduce malicious behaviors into models through fine-

Rahul Sharma, Chetana Jain, Biswajit Paul, Aru Beri

We report results from an $AstroSat$ Target-of-Opportunity (ToO) observation of 4U 1626$-$67, performed on 2023 May 18, soon after the discovery of torque reversal to spin-down in the source. The X-ray emission exhibited significant dependence on both energy and torque state. This work highlights the comparison of timing features of 4U 1626$-$67 with a previ

Sam Bennett, Amihay Hanany

D3-/D5-/NS5-brane systems with $O3$ orientifold planes realise 3d $\mathcal{N}=4$ gauge theories with orthogonal and symplectic gauge groups on the D3-brane worldvolume. Such setups have long contained an ambiguity regarding the global form of $D$-type gauge groups. This note offers a partial prescription for reading $\mathrm{O}(2k)$ and $\mathrm{SO}(2k)$ ga

Yi-Lu Luo, Yun-Ping Deng, Yuan Sun

Let $G$ be a simple connected graph with vertex set $V(G)$ and edge set $E(G)$. Let $T$ be a subset of $ V(G)$ with cardinality $|T|\geq2$. A path connecting all vertices of $T$ is called a $T$-path of $G$. Two $T$-paths $P_i$ and $P_j$ are said to be internally disjoint if $V(P_i)\cap V(P_j)=T$ and $E(P_i)\cap E(P_j)=\emptyset$. Denote by $\pi_G(T)$ the max

Qian Wan, Da-Xin Zhang

In this paper, we present a discussion for cosmological inflation based on a general renormalizable supersymmetric model which can be naturally embedded into grand unified models. Successful hybrid inflation has been realized with an effective Mexican-hat potential, while avoiding the generation of extra massless multiplets so that gauge coupling unification

Xiao-Juan An, Jian-Rong Li, Yan-Feng Luo, Wen-Ting Zhang

Fix $\varepsilon^{2\ell}=1$ with $\ell \geq 2$. In this paper, we show that all finite-dimensional simple modules of any restricted quantum loop algebra $U_{\varepsilon}^{\rm res}({L\mathfrak{sl}_{n+1}})$ in a certain category can be transformed into snake modules. We obtain an effective and concrete path description for $\varepsilon$-characters of any simpl

Navdeep Kaur, Lachlan McPheat, Alessandra Russo, Anthony G Cohn

In this paper, we examine the use of Conformal Language Modelling (CLM) alongside Answer Set Programming (ASP) to enhance the performance of standard open-weight LLMs on complex multi-step reasoning tasks. Using the StepGame dataset, which requires spatial reasoning, we apply CLM to generate sets of ASP programs from an LLM, providing statistical guarantees

Frederik Austrup, Wolfgang Häusler, Michael Lau, Michael Thorwart

When magnetic skyrmions decay, their size in real space decreases in a finite time before they eventually collapse. We construct an effective continuum model and use its dynamics to describe the shrinking behavior of skyrmions before they collapse. Using the Landau-Lifshitz-Gilbert equation and the time derivative of the vector field, we find a set of couple

Thomas Apel, Katharina Lorenz, Serge Nicaise

To verify theoretical results it is sometimes important to use a numerical example where the solution has a particular regularity. The paper describes one approach to construct such examples. It is based on the regularity theory for elliptic boundary value problems.

C. Buzzi, J. Llibre, P. Santana

In this paper we study the phase portraits and bifurcation diagram of the symmetric singularities of codimensions zero, one and two of planar reversible vector fields having a line of reversibility.

Norbert Hungerbühler, Clemens Pohle, Yun Zhang

We show that the centers of the excircles of a bicentric polygon $B$ are concyclic on a circle $E$. The center of the circumscribed circle $K$ of $B$ is the midpoint of the center of $E$ and the center of the inscribed circle $C$ of $B$. The radius of $E$ is given by a simple formula in terms of the radii of $C$ and $K$ and the distance between their centers

Cristiano Germani, Mohammad Ali Gorji, Michiru Uwabo-Niibo, Masahide Yamaguchi

We formulate the statistics of peaks of non-Gaussian random fields and implement it to study the sphericity of peaks. For non-Gaussianity of the local type, we present a general formalism valid regardless of how large the deviation from Gaussian statistics is. For general types of non-Gaussianity, we provide a framework that applies to any system with a give

Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith

The IRAC camera on the Spitzer Space Telescope observed 2175 Near Earth Objects (NEOs) during its Warm Mission phase, primarily in three large surveys, and also in a small number of a dedicated projects. In this paper we present the final reprocessing of the NEO data and determine fluxes at 3.6 microns (where available) and 4.5 microns. The observing windows

Patrick Serwene, Constantin-Cosmin Todea

In this short research note we obtain a reduction theorem for the non-vanishing of the first Hochschild cohomology of block algebras of finite groups with non-trivial defect groups. Along the way we investigate this problem for the blocks of some simple finite group algebras. Mimicking the case of blocks of finite group algebras we find some examples of cate

Toshiaki Koike-Akino, Francesco Tonin, Yongtao Wu, Frank Zhengqing Wu

This paper introduces Quantum-PEFT that leverages quantum computations for parameter-efficient fine-tuning (PEFT). Unlike other additive PEFT methods, such as low-rank adaptation (LoRA), Quantum-PEFT exploits an underlying full-rank yet surprisingly parameter efficient quantum unitary parameterization. With the use of Pauli parameterization, the number of tr

Jacob Camilleri, Ashley Sheil, Michelle O'Keeffe, Moya Cronin

Digital inequality remains a significant barrier for many older adults, limiting their ability to navigate online spaces securely and confidently while increasing their susceptibility to cyber threats. In response, we propose a novel shedding-type card game for older adults to conceptually learn and reinforce cyber hygiene practices in educational settings.

Thijs Havinga, Xianjun Jiao, Wei Liu, Baiheng Chen

Cross-Technology Interference (CTI) poses challenges for the performance and robustness of wireless networks. There are opportunities for better cooperation if the spectral occupation and technology of the interference can be detected. Namely, this information can help the Orthogonal Frequency Division Multiple Access (OFDMA) scheduler in IEEE 802.11ax (Wi-F

Maarten V. de Hoop, Sean Holman, Alexei Iantchenko

We study the essential spectrum, which corresponds to inertia-gravity modes, of the system of equations governing a rotating and self-gravitating gas planet. With certain boundary conditions, we rigorously and precisely characterize the essential spectrum and show how it splits from the portion of the spectrum corresponding to the acoustic modes. The fundame

Simon Malacek, José Portela, Yannick Marcus Werner, Sonja Wogrin

Despite various efforts, decarbonizing the heating sector remains a significant challenge. To tackle it by smart planning, the availability of highly resolved heating demand data is key. Several existing models provide heating demand only for specific applications. Typically, they either offer time series for a larger area or annual demand data on a building

Egemen Gover, Doga Veske, M. Bilge Demirkoz

For studies where a reliable neutron source/beam is required and a nuclear reactor is not a viable option (considering their high neutron flux supply, which may not be suitable for research concerning low flux operations), alternative approaches may be sought. We present a comprehensive simulation analysis of 30 MeV proton induced ${}^9\mathrm{Be}\text{(p,n)

Jian Shen, Huai Yu, Ji Wu, Wen Yang

This paper introduces LiGSM, a novel LiDAR-enhanced 3D Gaussian Splatting (3DGS) mapping framework that improves the accuracy and robustness of 3D scene mapping by integrating LiDAR data. LiGSM constructs joint loss from images and LiDAR point clouds to estimate the poses and optimize their extrinsic parameters, enabling dynamic adaptation to variations in s

Niklas Penzel, Joachim Denzler

Deep learning models achieve high predictive performance but lack intrinsic interpretability, hindering our understanding of the learned prediction behavior. Existing local explainability methods focus on associations, neglecting the causal drivers of model predictions. Other approaches adopt a causal perspective but primarily provide global, model-level exp

Run He, Di Fang, Yicheng Xu, Yawen Cui

Exemplar-Free Class-Incremental Learning (EFCIL) aims to sequentially learn from distinct categories without retaining exemplars but easily suffers from catastrophic forgetting of learned knowledge. While existing EFCIL methods leverage knowledge distillation to alleviate forgetting, they still face two critical challenges: semantic shift and decision bias.

Peter James Nee, Aldo Gamboa, Harald P. Pfeiffer, Lorenzo Pompili

Accurate modelling of black hole binaries is critical to achieve the science goals of gravitational-wave detectors. Modelling such configurations relies strongly on calibration to numerical-relativity (NR) simulations. Binaries on quasi-circular orbits have been widely explored in NR, however, coverage of the broader 9-dimensional parameter space, including

Timo Zwettler, Filip Marijanović, Tabea Bühler, Sambuddha Chattopadhyay

Coherent light-matter interactions between a quantum gas and light in a high-finesse cavity can drive self-ordering phase transitions. To date, such phenomena have involved exclusively single-atom coupling to light, resulting in coupled charge-density or spin-density wave and superradiant order. In this work, we engineer simultaneous coupling of cavity photo

Abedulgader Baktheer, Fadi Aldakheel

Accurate lifetime prediction of structures subjected to cyclic loading is vital, especially in scenarios involving non-uniform loading histories where load sequencing critically influences structural durability. Addressing this complexity requires advanced modeling approaches capable of capturing the intricate relationship between loading sequences and fatig

Ahmed Magbool, Vaibhav Kumar, Marco Di Renzo, Mark F. Flanagan

Integrated sensing and communication (ISAC) has been identified as a promising technology for the sixth generation (6G) of communication networks. Target privacy in ISAC is essential to ensure that only legitimate sensors can detect the target while keeping it hidden from malicious ones. In this paper, we consider a downlink reconfigurable intelligent surfac

Vinit Vijay Deshpande, Romana Piat

The work proposes an image segmentation algorithm that isolates slender regions in three-dimensional microstructures. Characterizing slender regions in material microstructures is an extremely important aspect in material science because these regions govern the macroscopic behavior of materials for many applications like energy absorption, activation of met

Colva M. Roney-Dougal, Gareth Tracey

In this paper, we prove that the symmetric group $\mathrm{S}_n$ has $2^{n^2/16+o(n^2)}$ subgroups, settling a conjecture of Pyber from 1993. We also derive asymptotically sharp upper and lower bounds on the number of subgroups of $\mathrm{S}_n$ of various kinds, including the number of $p$-subgroups. In addition, we prove a range of theorems about random sub

Hancen Lu, Tianyuan Zhang, Chang Xu, Shuqi Li

The Circular Electron-Positron Collider (CEPC), as the next-generation electron-positron collider, is tasked with advancing not only Higgs physics but also the discovery of new physics. Achieving these goals requires high-precision measurements of particles. Taichu seires, Monolithic Active Pixel Sensor (MAPS), a key component of the vertex detector for CEPC

KeeTaek Kim, Taketo Sano

We introduce a diagrammatic approach to Rasmussen's $s$-invariant, based on Bar-Natan's reformulation of Khovanov homology for tangles and cobordisms. This method enables a local computation of $s$ from a tangle decomposition of a knot diagram. As an application, we compute the $s$-invariants of all 3-strand pretzel knots.

Aviran Gal, Igal Bilik

Automotive radar is a key component of sensing suites in autonomous driving (AD) and advanced driver-assist systems (ADAS). However, limited line-of-sight (LOS) significantly reduces radar efficiency in dense urban environments. Therefore, automotive radars need to extend their capabilities beyond LOS by localizing occluding and reflective surfaces and non-l

Colazo Milagros, Dagmara Oszkiewicz, Alvaro Alvarez-Candal, Patrycja Pożniak

We determined phase curves for 301,272 asteroids in the orange filter and 280,953 in the cyan filter from the latest ATLAS Solar System Catalog V2 (SSCAT-2). Among them, 3,345 and 492 asteroids in the orange and cyan filters, respectively, have uncertainties below 15%. Our simple model, which considers only the apparition effect, showed good consistency with

Jia-Ying Cao, Jin-Yuan Liao, Shuang-Nan Zhang, Hua Feng

The new black hole transient Swift J1727.8--1613 exhibited a series of X-ray flares during its 2023 outburst extensively observed with Insight-HXMT. We analyze the spectra of the flaring period using a series of models consisting of a multi-color disk and several different non-thermal components, and several consistent conclusions are obtained among these mo

Sebastian Herr, Christopher Maulén, Claudio Muñoz

We study the long-time behavior of small and large solutions to a broad class of nonlinear Dirac-type equations. Our results are classified in 1D massless and massive cases, 3D general and $n$ dimensional in generality. In the 1D massless case we prove that any globally defined solution converges to zero as time tends to infinity, within a spatial region exp

Sunit Ghosh, Younis Ahmad Bhat, Jitendriya Swain

The aim of the paper is two-fold. First, we provide an explicit form of the functions for which equality holds for the uncertainty inequalities studied in \cite{Fei}. Second, we establish an $L^p$-type Heisenberg-Pauli-Weyl uncertainty principle for the fractional Dunkl transform, with $1 \leq p \leq 2$. For the case $p = 2$, we further derive a sharper unce

Toni Böhnlein, Pál András Papp, Raphael S. Steiner, Christos K. Matzoros

We develop and analyze new scheduling algorithms for solving sparse triangular linear systems (SpTRSV) in parallel. Our approach produces highly efficient synchronous schedules for the forward- and backward-substitution algorithm. Compared to state-of-the-art baselines HDagg and SpMP, we achieve a $3.32 \times$ and $1.42 \times$ geometric-mean speed-up, resp

Jennifer Müller, Markus Reineke

We consider representation spaces of quivers, together with their base change action, and classify the spherical varieties among them.

Kaede Shintani, Hamada Rizk, Hirozumi Yamaguchi

The field of energy-free sensing and context recognition has recently gained significant attention as it allows operating systems without external power sources. Photovoltaic cells can convert light energy into electrical energy to power sensing devices, but their power may not be sufficient to ensure energy-free sensing due to the varying power needs of sen

Yi-Chi Liao, Paul Streli, Zhipeng Li, Christoph Gebhardt

Optimal input settings vary across users due to differences in motor abilities and personal preferences, which are typically addressed by manual tuning or calibration. Although human-in-the-loop optimization has the potential to identify optimal settings during use, it is rarely applied due to its long optimization process. A more efficient approach would co

Huijin Park, Mykyta Onizhuk, Eunsang Lee, Harim Lim

The negatively charged nitrogen-vacancy (NV) center in diamond has emerged as a leading qubit platform for quantum technology applications. One of the key challenges for NV-based quantum applications is building an accurate model to predict its decoherence properties and their quantum nature. In this study, we combine theory and experiment to investigate NV

Maria Bergemann, Katharina Lodders, Herbert Palme

This chapter provides a brief introduction to the chemical composition of the Sun. The focus of the chapter is on results obtained from the physical analysis of the solar photosphere. Data obtained from meteorites, solar wind and corona measurements, as well as helioseismology, and solar neutrinos are briefly reviewed. The elemental and isotopic composition

Nguyen Van Phu

We first study subextensions of m-subharmonic functions in weighted energy classes with given boundary values. The results are used to approximate an m-subharmonic function in weighted energy classes with given boundary values by an increasing sequence of m-subharmonic functions defined on larger domains.

Dmitrii Pantiukhin, Boris Shapkin, Ivan Kuznetsov, Antonia Anna Jost

This Perspective explores the transformative potential of Multi-Agent Systems (MAS) powered by Large Language Models (LLMs) in the geosciences. Users of geoscientific data repositories face challenges due to the complexity and diversity of data formats, inconsistent metadata practices, and a considerable number of unprocessed datasets. MAS possesses transfor

Yanis Baouche, Magali Le Goff, Christina Kurzthaler, Thomas Franosch

We study the first-passage-time (FPT) properties of active Brownian particles to reach an absorbing wall in two dimensions. Employing a perturbation approach we obtain exact analytical predictions for the survival and FPT distributions for small P\'eclet numbers, measuring the importance of self-propulsion relative to diffusion. While randomly oriented activ

R. A. Barcan, I. Samaras, K. Barr, G. Juska

We investigate site-controlled In$_{0.25}$Ga$_{0.75}$As quantum dots in (111)B GaAs pyramidal recesses as spin qubits. Combining scanning confocal cryomicroscopy, magneto-photoluminescence studies and resonant excitation, we identify and isolate a positively charged exciton with a hole-spin in its ground state. Application of a strong 5 T magnetic field para

Vedansh Arya, Daniele De Gennaro, Anna Kubin

We study the asymptotic behavior of flat flow solutions to the periodic and planar two-phase Mullins-Sekerka flow and area-preserving curvature flow. We show that flat flows converge to either a finite union of equally sized disjoint disks or to a finite union of disjoint strips or to the complement of these configurations exponentially fast. A key ingredien

Kejun Hu, Peng Yu, Ning Tan

Self-modeling enables robots to build task-agnostic models of their morphology and kinematics based on data that can be automatically collected, with minimal human intervention and prior information, thereby enhancing machine intelligence. Recent research has highlighted the potential of data-driven technology in modeling the morphology and kinematics of rob

Sakharam Gawade, Shivam Akhouri, Chinmay Kulkarni, Jagdish Samant

Large Action Models (LAMs) have revolutionized intelligent automation, but their application in healthcare faces challenges due to privacy concerns, latency, and dependency on internet access. This report introduces an ondevice, multi-agent healthcare assistant that overcomes these limitations. The system utilizes smaller, task-specific agents to optimize re

Jori Merikoski

Let $a,b>0$ be coprime integers. Assuming a conjecture on Hecke eigenvalues along binary cubic forms, we prove an asymptotic formula for the number of primes of the form $ax^2+by^3$ with $x \leq X^{1/2}$ and $y \leq X^{1/3}$. The proof combines sieve methods with the theory of real quadratic fields/indefinite binary quadratic forms, the Weil bound for expone

Hannes Holey, Peter Gumbsch, Lars Pastewka

Lubricated friction is a multiscale problem where molecular processes dictate the macroscopic response of the system. Traditional lubrication models rely on semi-empirical constitutive relations, which become unreliable under extreme conditions. Here, we present a simulation framework that seamlessly couples molecular and continuum models for boundary lubric

Sujoy Roychowdhury, Giriprasad Sridhara, A K Raghavan, Joy Bose

We describe a novel approach to automating unit test generation for Java methods using large language models (LLMs). Existing LLM-based approaches rely on sample usage(s) of the method to test (focal method) and/or provide the entire class of the focal method as input prompt and context. The former approach is often not viable due to the lack of sample usage

R. Au-Yeung, V. M. Kendon, S. J. Lind

Recent years have seen great progress in quantum computing, providing opportunities to overcome computational bottlenecks in many scientific applications. In particular, the intersection of computational fluid dynamics (CFD) and quantum computing has become an active area of research with exponential computational speedup as an ultimate goal. In this work, w

Steven Hoehner, Sudan Xing

Three new combinations of convex bodies are introduced and studied: the $L_p$ fiber, $L_p$ chord and graph combinations. These combinations are defined in terms of the fibers and graphs of pairs of convex bodies, and each operation generalizes the classical Steiner symmetral, albeit in different ways. For the $L_p$ fiber and $L_p$ chord combinations, we deri

Mohammad Haidar

In this study, we investigate the synchronization of propagating spin waves in a novel spin torque oscillator device layout using micromagnetic simulations. This design enables individual probing of the dc current in each oscillator, allowing precise control over the synchronization state and providing direct phase measurement. Our findings reveal that two a

Aapo Laukkarinen, Jaakko Sinko

We study the two-weighted off-diagonal compactness of commutators of rough singular integral operators $T_\Omega$ that are associated with a kernel $\Omega\in L^q(\mathbb{S}^{d-1})$. We establish a characterisation of compactness of the commutator $[b,T_\Omega]$ in terms of the function $b$ belonging to a suitable space of functions with vanishing mean oscil

Miao-Ling Lin, Jiang-Bin Wu, Xue-Lu Liu, Tao Liu

We report Raman forbidden layer-breathing modes (LBMs) in layered semiconductor materials (LSMs). The intensity distribution of all observed LBMs depends on layer number, incident light wavelength and refractive index mismatch between LSM and underlying substrate. These results are understood by a Raman scattering theory via the proposed spatial interference

Anna Sofia Lippolis, Mohammad Javad Saeedizade, Robin Keskisärkkä, Sara Zuppiroli

The ontology engineering process is complex, time-consuming, and error-prone, even for experienced ontology engineers. In this work, we investigate the potential of Large Language Models (LLMs) to provide effective OWL ontology drafts directly from ontological requirements described using user stories and competency questions. Our main contribution is the pr

Rasul Abdusalamov, Mikhail Itskov

The accurate modeling of the mechanical behavior of rubber-like materials under multi-axial loading constitutes a long-standing challenge in hyperelastic material modeling. This work employs deep symbolic regression as an interpretable machine learning approach to discover novel strain energy functions directly from experimental results, with a specific focu

Francesca Rossi, Sergi Costa Dilme, Josep Arevalo-Soler, Eduardo Prieto-Araujo

Hybrid AC/DC transmission grids incorporate Modular Multilevel Converters functioning as Interconnecting Power Converters (IPCs). The control role assigned to each converter significantly influences grid dynamics. Traditionally, these converters operate with static control roles, but recent studies have proposed scheduling their roles based on day-ahead fore

Suyoung Choi, Younghan Yoon, Seonghyeon Yu

Full subcomplexes of a simplicial complex encode essential structure for understanding the complex itself. For a simplicial complex $K$, possibly with a ghost vertex, the Bier sphere of $K$ is a simplicial sphere obtained as the deleted join of $K$ and its combinatorial Alexander dual. In this paper, we determine the homotopy types of all full subcomplexes o

Hanjiang Hong, Kai-Kit Wong, Haoyang Li, Hao Xu

Fluid antenna system (FAS) is an emerging technology that uses the new form of shape- and position-reconfigurable antennas to empower the physical layer for wireless communications. Prior studies on FAS were however limited to narrowband channels. Motivated by this, this paper addresses the integration of FAS in the fifth generation (5G) orthogonal frequency

Weiyu Ma, Yuqian Fu, Zecheng Zhang, Bernard Ghanem

We introduce AVACraft, a multimodal StarCraft II benchmark supporting both Multi-Agent Reinforcement Learning (MARL) and Vision-Language Model (VLM) paradigms. Unlike SMAC-family environments that rely on abstract state representations and exclude VLMs, AVACraft provides RGB visuals, natural language observations, and structured state information, enabling s

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $20.3~\mathrm{fb}^{-1}$ of $e^+e^-$ collision data collected at a center-of-mass energy of 3.773 GeV with the BESIII detector operating at the BEPCII collider, the branching fractions of three hadronic charm meson decays, $D^+\to \phi\pi^+\pi^+\pi^-$, $D^+\to K^0_SK^+\pi^+\pi^-\pi^0$, and $D^+\to K^0_SK^+\omega$, are measured for the first time to be $

Bálint Hartmann, Géza Ódor, Kristóf Benedek, István Papp

This paper presents a quantitative comparison of power grid reinforcement strategies. We evaluate three approaches: (1) doubling transmission links (bridges) between different communities, (2) adding bypasses around weakly synchronized nodes, and (3) reinforcing edges that trigger the largest cascade failures. We use two different models of the Hungarian hig

Jiaxing Zhao, Xihan Wei, Liefeng Bo

In this work, we present the first application of Reinforcement Learning with Verifiable Reward (RLVR) to an Omni-multimodal large language model in the context of emotion recognition, a task where both visual and audio modalities play crucial roles. We leverage RLVR to optimize the Omni model, significantly enhancing its performance in three key aspects: re

Iva Kertusha, Gebremariem Assress, Onur Duman, Andrea Arcuri

Web application testing is an essential practice to ensure the reliability, security, and performance of web systems in an increasingly digital world. This paper presents a systematic literature survey focusing on web testing methodologies, tools, and trends from 2014 to 2025. By analyzing 259 research papers, the survey identifies key trends, demographics,

Andreas Ruschhaupt, Juan Gonzalo Muga

Recent implementations of Maxwell demons and other devices exhibiting asymmetric response to particles incident from opposite directions have raised conceptual and practical interest. According to quantum-scattering-theory selection rules, demons necessitate, among other conditions, non-local and non-Hermitian potentials. These potentials arise as effective

Jiaoyi Zhang, Liqiang Peng, Mo Sha, Weiran Liu

With increasing demands for privacy, it becomes necessary to protect sensitive user query data when accessing public key-value databases. Existing Private Information Retrieval (PIR) schemes provide full security but suffer from poor scalability, limiting their applicability in large-scale deployment. We argue that in many real-world scenarios, a more practi

Guillaume Krieger, Chia-Ping Su, Hoshang Sahib, Raymond Fan

In transition metal oxides electron-electron interaction and lattice degree of freedom are basic ingredients of emergent phenomena, such as metal-to-insulator transition (MIT) and superconductivity. Perovskite rare-earth nickelates are largely studied for their temperature-driven MIT which is accompanied by a breathing mode distortion, and associated to a bo

Yu-Tao Hu, Meng-Yuan Li, Peng Ye

Demonstrating how long-range entangled states are born from product states has gained much attention, which is not only important for quantum technology but also provides an unconventional tool in characterizing and classifying exotic phases of matter. In this paper, we introduce a unified and efficient framework of quantum circuits (i.e., a series of local

Linh Le, Guido Zuccon, Gianluca Demartini, Genghong Zhao

Previous work on clinical relation extraction from free-text sentences leveraged information about semantic types from clinical knowledge bases as a part of entity representations. In this paper, we exploit additional evidence by also making use of domain-specific semantic type dependencies. We encode the relation between a span of tokens matching a Unified

Feng-Kun Guo, Christoph Hanhart

We argue that the hypothesis that positive-parity charm meson resonances exhibit a compact tetraquark structure has some clear tension with recent lattice results for the $S$-wave $\pi D$ system for an SU(3) flavor symmetric setting. In particular, we show that such a diquark--anti-diquark tetraquark scenario would call for the presence of a state in the fla

Zara Siddique, Irtaza Khalid, Liam D. Turner, Luis Espinosa-Anke

We present a novel approach to bias mitigation in large language models (LLMs) by applying steering vectors to modify model activations in forward passes. We compute 8 steering vectors, each corresponding to a different social bias axis, such as age, gender, or race, on a training subset of the BBQ dataset and compare the effectiveness of these to 3 addition

Alea Miako Tokita, Timothée Devergne, A. Marco Saitta, Jörg Behler

Machine learning potentials (MLPs) have become a popular tool in chemistry and materials science as they combine the accuracy of electronic structure calculations with the high computational efficiency of analytic potentials. MLPs are particularly useful for computationally demanding simulations such as the determination of free energy profiles governing che

Roya Aliakbarisani, Marián Boguñá, M. Ángeles Serrano

The latent space approach to complex networks has revealed fundamental principles and symmetries, enabling geometric methods. However, the conditions under which network topology implies geometricity remain unclear. We provide a mathematical proof and empirical evidence showing that the multiscale self-similarity of complex networks is a crucial factor in im

Sagy Ephrati, Erik Jansson, Klas Modin

Spectral analysis for a class of Lagrangian-averaged Navier--Stokes (LANS) equations on the sphere is carried out. The equations arise from the Navier--Stokes equations by applying a Helmholtz filter of width $\alpha$ to the advecting velocity $\beta$ times. Power laws for the energy spectrum are derived and indicate a $\beta$-dependent scaling at wave numbe

Jing Zhang, Alexandre Bousse, Chi-Hieu Pham, Kuangyu Shi

Targeted Radionuclide Therapy (TRT) is a modern strategy in radiation oncology that aims to administer a potent radiation dose specifically to cancer cells using cancer-targeting radiopharmaceuticals. Accurate radiation dose estimation tailored to individual patients is crucial. Deep learning, particularly with pre-therapy imaging, holds promise for personal

Jaehyun Yoo, Jip Kim

This paper presents a risk-aware bi-level bidding strategy for Virtual Power Plant (VPP) that integrates Power-to-Hydrogen (P2H) system, addressing the challenges posed by renewable energy variability and market volatility. By incorporating Conditional Value at Risk (CVaR) within the bi-level optimization framework, the proposed strategy enables VPPs to miti

Zhigang Wang, Shaojing Fan, Zhenguang Liu, Zheqi Wu

Human pose estimation, with its broad applications in action recognition and motion capture, has experienced significant advancements. However, current Transformer-based methods for video pose estimation often face challenges in managing redundant temporal information and achieving fine-grained perception because they only focus on processing low-resolution