March 2025 arXiv papers — page 92

Shubham Kala, Anik Rudra, Hemwati Nandan

We investigate the quasinormal modes of the Reissner$-$Nordstr\"om anti$-$de Sitter black hole using the Penrose limit, motivated by the geometrical optics approximation. This approach offers a novel framework for approximating quasinormal modes with large real frequencies by associating a plane wave to spacetime regions near null geodesics, providing a geom

Matías Montesinos, Juan Garrido-Deutelmoser, Jorge Cuadra, Mario Sucerquia

Planetary growth within protoplanetary disks involves accreting material from their surroundings, yet the underlying mechanisms and physical conditions of the accreting gas remain debated. This study aims to investigate the dynamics and thermodynamic properties of accreting gas giants, and to characterize the envelope that forms near the planet during accret

Jonathan House, Rashad Bakhshizada, Skirmantas Janušonis, Ralf Metzler

Fractional Brownian motion is a Gaussian stochastic process with long-range correlations in time; it has been shown to be a useful model of anomalous diffusion. Here, we investigate the effects of mutual interactions in an ensemble of particles undergoing fractional Brownian motion. Specifically, we introduce a mean-density interaction in which each particle

Evan P. G. Gale

The localization problem in relativistic quantum theory has persisted for more than seven decades, yet it is largely unknown and continues to perplex even those well-versed in the subject. At the heart of this problem lies a fundamental conflict between localizability and relativistic causality, which can also be construed as part of the broader dichotomy be

Shane Kelly

We show that the category of log homotopy types is a full subcategory of a category of homotopy types with modulus.

Enrique Alvarado, Daniela Beckelhymer, Joshua Dorrington, Tung Lam

A monsoon is a wind system that seasonally reverses its direction, accompanied by corresponding changes in precipitation. The Indian monsoon is the most prominent monsoon system, primarily affecting India's rainy season and its surrounding lands and water bodies. Every year, the onset and withdrawal of this monsoon happens sometime in May-June and September-

Marcin Lawenda, Krzesimir Samborski, Kyrylo Khloponin, Łukasz Szustak

This work is concerned with the evaluation of the performance of parallelization of learning and tuning processes for image classification and large language models. For machine learning model in image recognition, various parallelization methods are developed based on different hardware and software scenarios: simple data parallelism, distributed data paral

Federica Devoto, Kirill Melnikov, Raoul Röntsch, Chiara Signorile-Signorile

We describe the calculation of integrated subtraction terms in the nested soft-collinear subtraction scheme for hadron collider processes with quarks and gluons, thereby extending the results presented in Ref.$~$[1]. Although this extension eventually proves to be straightforward, it requires a more careful treatment of certain collinear limits to achieve a

Quentin Nater, Mourad Khayati

With the prevalence of sensor failures, imputation, the process of estimating missing values, has emerged as the cornerstone of time series data pre-processing. While numerous imputation algorithms have been developed to repair these data gaps, existing time series libraries provide limited imputation support. Furthermore, they often lack the ability to simu

Roland Schmid, Tibor Schneider, Georgia Fragkouli, Laurent Vanbever

Analyzing violations of forwarding properties is a classic networking problem. However, existing work is either tailored to the steady state -- and not to transient states during iBGP convergence -- or does analyze transient violations but with inaccurate proxies, like control-plane convergence, or without precise control over the different impact factors. W

Jomar Thomas Almonte, Santhosh Anitha Boominathan, Nathalia Nascimento

Neglecting non-functional requirements (NFRs) early in software development can lead to critical challenges. Despite their importance, NFRs are often overlooked or difficult to identify, impacting software quality. To support requirements engineers in eliciting NFRs, we developed a framework that leverages Large Language Models (LLMs) to derive quality-drive

J. Aguilar, M. Anastasopoulos, D. Barčot, E. Baussan

In the effort to obtain a precise measurement of leptonic CP-violation with the ESS$\nu$SB experiment, accurate and fast reconstruction of detector events plays a pivotal role. In this work, we examine the possibility of replacing the currently proposed likelihood-based reconstruction method with an approach based on Graph Neural Networks (GNNs). As the like

Anders Malthe Westerkam, Jakob Möderl, Erik Leitinger, Troels Pedersen

In this paper, we propose a direct multiobject tracking (MOT) approach for MIMO-radar signals that operates on raw sensor data via variational message passing (VMP). Unlike classical track-before-detect (TBD) methods, which often rely on simplified likelihood models and exclude nuisance parameters (e.g., object amplitudes, noise variance), our method adopts

Paola Ragonese, Chiara Maurizio, Boris Kalinic, Thomas Kirchartz

This work develops an analytical model to consistently interpret the steady-state and small-perturbation response (both in the time and frequency domain) of photoanodes for solar water-splitting. In addition to accounting for the fundamental mechanisms of charge-carrier generation, recombination and slow hole transfer at the photoanode/electrolyte interface,

Tomohiro Hattori, Shu Tanaka

Quantum annealing is a promising algorithm for solving combinatorial optimization problems. It searches for the ground state of the Ising model, which corresponds to the optimal solution of a given combinatorial optimization problem. The guiding principle of quantum annealing is the adiabatic theorem in quantum mechanics, which guarantees that a system remai

Nanchi Su, Fan Liu, Jiaqi Zou, Christos Masouros

Integrated Sensing and Communication (ISAC) is emerging as a cornerstone technology for forthcoming 6G systems, significantly improving spectrum and energy efficiency. However, the commercial viability of ISAC hinges on addressing critical challenges surrounding security, privacy, and trustworthiness. These challenges necessitate an end-to-end framework to s

Pierre Chambon, Baptiste Roziere, Benoit Sagot, Gabriel Synnaeve

We introduce BigO(Bench), a novel coding benchmark designed to evaluate the capabilities of generative language models in understanding and generating code with specified time and space complexities. This benchmark addresses the gap in current evaluations that often overlook the ability of models to comprehend and produce code constrained by computational co

Chengming Bai, Dongfang Gao

We investigate the compatible root graded anti-pre-Lie algebraic structures on any finite-dimensional complex simple Lie algebra by the representation theory of ${\rm sl_2(\C)}$. We show that there does not exist a compatible root graded anti-pre-Lie algebraic structure on a finite-dimensional complex simple Lie algebra except ${\rm sl_2(\C)}$, whereas there

Sathasivam Kalithasan, Tony N. Mavely, Viji Z. Thomas

One of the aims of this paper is to obtain structural results showing that powerful subgroups are abundant in pro-$p$ groups admitting certain powerful quotients. In particular, we obtain an analogue of Baer's theorem for powerful pro-$p$ groups, namely that the powerfulness of $H/Z_{n-1}(H)$ implies that the $n$th terms of both the lower $p$-series and

Songqiao Hu, Zidong Wang, Zeyi Liu, Zhen Shen

Control barrier functions (CBFs) provide a principled framework for safety-critical control, but their construction typically requires an explicit and differentiable description of the safe or unsafe region. It becomes challenging for data-defined unsafe regions that may evolve over time. This paper proposes SafeLink, a data-driven CBF construction and adapt

Julian Auler, Utkarsh Bajpai, Martin Engler, Viktoria Ermuth

The precise determination of the free neutron lifetime is of great significance in modern precision physics. This key observable is linked to the mixing of up and down quarks via the Cabibbo-Kobayashi-Maskawa matrix element $V_{ud}$, and the abundance of primordial elements after the Big-Bang Nucleosynthesis. However, the two leading measurement techniques f

Aniketh Girish, Joel Reardon, Juan Tapiador, Srdjan Matic

Mobile apps frequently use Bluetooth Low Energy (BLE) and WiFi scanning permissions to discover nearby devices like peripherals and connect to WiFi Access Points (APs). However, wireless interfaces also serve as a covert proxy for geolocation data, enabling continuous user tracking and profiling. This includes technologies like BLE beacons, which are BLE dev

Liyun Zhang, Zheng Lian, Hong Liu, Takanori Takebe

Different annotators often assign different labels to the same sample due to backgrounds or preferences, and such labeling patterns are referred to as tendency. In multi-annotator scenarios, we introduce a novel task called Multi-annotator Tendency Learning (MATL), which aims to capture each annotator tendency. Unlike traditional tasks that prioritize consen

Shouhei Honda, Alexandru Kristály, Alexandru Pîrvuceanu

The main goal of the present paper is to provide sharp hypercontractivity bounds of the heat flow $({\sf H}_t)_{t\geq 0}$ on ${\sf RCD}(0,N)$ metric measure spaces. The best constant in this estimate involves the asymptotic volume ratio, and its optimality is obtained by means of the sharp $L^2$-logarithmic Sobolev inequality on ${\sf RCD}(0,N)$ spaces and a

Chentian Wei, Jiewei Chen, Jinzhu Xu

Word games hold significant research value for natural language processing (NLP), game theory, and related fields due to their rule-based and situational nature. This study explores how large language models (LLMs) can be effectively involved in word games and proposes a training-free framework. "Shei Shi Wo Di" or "Who is the Spy" in English, is a classic w

Wenlong Yu, Qilong Wang, Chuang Liu, Dong Li

Explainability is a critical factor influencing the wide deployment of deep vision models (DVMs). Concept-based post-hoc explanation methods can provide both global and local insights into model decisions. However, current methods in this field face challenges in that they are inflexible to automatically construct accurate and sufficient linguistic explanati

Jun-Cong Zheng, Xiao-Wei Zheng, Xin-Lei Hei, Yi-Fan Qiao

We investigate single photon transmission and the statistical properties of photon correlations in $\chi^{(2)}$ microring optomechanical systems, where optical nonreciprocity is induced by directional quantum squeezing. Due to the presence of thermal phonons in the mechanical resonator, the system is highly sensitive to temperature changes. Our numerical sim

Ashley P. Willis, Michael J. Burin

Applying a sufficiently rapid start-stop to the outer cylinder of the Couette-Taylor system, structures approximately aligned with the axis were recorded in the classic work of Coles (1965). These short-lived rolls are oriented perpendicular to the classic Taylor-vortex rolls. In this work we report numerical observation of this instability, guided by a more

Jingyi Chen, Songqiang Chen, Jialun Cao, Jiasi Shen

Retrieval-augmented generation (RAG) has increasingly shown its power in extending large language models' (LLMs') capability beyond their pre-trained knowledge. Existing works have shown that RAG can help with software development tasks such as code generation, code update, and test generation. Yet, the effectiveness of adapting LLMs to fast-evolving or less

Nathaniel J. Fuller, Nicholas Palermo

The canonical range resolution limit in radar, sonar, and lidar systems is found to be a special case of a more general resolution limit. The general limit indicates that it is possible to surpass the canonical limit in moderate (of order unity) signal-to-noise ratio (SNR) environments by using the signal amplitude and phase information. The canonical limit

Hranislav Stanković

In this paper, we provide several characterizations of a spherically quasinormal tuple $\mathbf{T}$ in terms of its normal extension, as well as in terms of powers of the associated elementary operator $\Theta_{\mathbf{T}}(I)$. Utilizing these results, we establish that the powers of spherically quasinormal tuples remain spherically quasinormal. Additionally

Alessandro Traspadini, Anay Ajit Deshpande, Marco Giordani, Chinmay Mahabal

In 3GPP New Radio (NR) Vehicle-to-Everything (V2X), the new standard for next-generation vehicular networks, vehicles can autonomously select sidelink resources for data transmission, which permits network operations without cellular coverage. However, standalone resource allocation is uncoordinated, and is complicated by the high mobility of the nodes that

D. Miguélez-Caballero, S. Navarro-Obregón, A. Wereszczynski

We show that the moduli space metric of a single vortex gets corrections because of the excitation of the radially symmetric shape mode. It leads to a non-zero amount of the shape mode carried by the vortex when moving with a constant velocity. However, due to the radial symmetry, this effect does not reproduce the Lorentz contraction of the moving vortex. W

Narek Bojikian, Alexander Firbas, Robert Ganian, Hung P. Hoang

We investigate the computation of minimum-cost spanning trees satisfying prescribed vertex degree constraints: Given a graph $G$ and a constraint function $D$, we ask for a (minimum-cost) spanning tree $T$ such that for each vertex $v$, $T$ achieves a degree specified by $D(v)$. Specifically, we consider three kinds of constraint functions ordered by their g

C. -J. Yang, V. Horny, D. Doria, K. Spohr

Despite numerous achievements and recent progress, nuclear physics is often (wrongly) considered an old field of research nowadays. However, developments in theoretical frameworks and reliable experimental techniques have made the field mature enough to explore many new frontiers. In this regard, extending existing knowledge to an emerging field of physics -

You Wang, Michael Pradel, Zhongxin Liu

Automated issue solving aims to resolve real-world issues in software repositories. The most popular benchmarks for automated issue solving are SWE-bench and its human-filtered subset SWE-bench Verified. These benchmarks leverage testing to validate generated patches. However, because testing is rarely exhaustive, a patch may pass the tests but nevertheless

Pritam Kadasi, Sriman Reddy Kondam, Srivathsa Vamsi Chaturvedula, Rudranshu Sen

With the massive surge in ML models on platforms like Hugging Face, users often lose track and struggle to choose the best model for their downstream tasks, frequently relying on model popularity indicated by download counts, likes, or recency. We investigate whether this popularity aligns with actual model performance and how the comprehensiveness of model

Rodrigo Oliver, Josué Pérez-Sabater, Leire Paz-Arbaizar, Diego Herrero-Quevedo

Foundation models have achieved remarkable success across various domains, yet their adoption in healthcare remains limited. While significant advances have been made in medical imaging, genetic biomarkers, and time series from electronic health records, the potential of foundation models for patient behavior monitoring through personal digital devices remai

Rrubaa Panchendrarajan, Arkaitz Zubiaga

Identifying claims requiring verification is a critical task in automated fact-checking, especially given the proliferation of misinformation on social media platforms. Despite notable progress, challenges remain-particularly in handling multilingual data prevalent in online discourse. Recent efforts have focused on fine-tuning pre-trained multilingual langu

Amruta Mishra

The in-medium masses of the pseudoscalar open charm ($D$, $\bar D$, $D_s$ and $\bar {D_s}$) and open bottom ($B$, $\bar B$, $B_s$ and $\bar {B_s}$) mesons in hot asymmetric strange hadronic matter are studied within a QCD sum rule approach. These are computed using the medium modifications of the light quark condensates ($\langle{\bar{q_i}}{q_i}\rangle$, wit

Qiang Li, Ting Xu, Vince D. Calhoun

The world of beauty is deeply connected to the visual cortex, as perception often begins with vision in both humans and marmosets. In this study, to investigate their functional correspondences, we used 13 healthy human volunteers (9 males and 4 females, aged 22-56 years) and 8 common marmosets (6 males and 2 females, aged 20-42 months). We then measured pai

Paolo Tortora, Riccardo Lasagni Manghi, Edoardo Gramigna, Marco Zannoni

This work presents the simulation results of the radio science experiment onboard the proposed Heavy Metal mission to the M-type asteroid (216) Kleopatra. Earth-based radiometric measurements (range and range-rate), complemented by images from the onboard optical camera and by measurements from the inter-satellite link between the maincraft and a secondary s

Jun-Cong Zheng, Xiao-Wei Zheng, Xin-Lei Hei, Yi-Fan Qiao

In this work, we investigate the non-Markovian dynamical evolution of a ${\Lambda}$-type atom interacting with a semi-infinite one-dimensional photonic waveguide via two atomic transitions. The waveguide terminates at a perfect mirror, which reflects the light and introduces boundary effects. We derive exact analytical expressions and show that, under suitab

Longju Yu, Hong Jian Zhao, Laurent Bellaiche, Yanming Ma

Magnetic or electrical manipulation of electronic spin is elementary for spin-based logic, computing, and memory, where the latter is a low-power manipulation scheme. Rashba-like spin splittings stemming from spin-orbit interaction (SOI) enable electric-field manipulation of spin, but the relativistic SOI causes spin relaxations and yields dissipative transp

D. Nash, D. A. Gates, W. S. Walsh, M. Slepchenkov

Thea Energy, Inc. is currently developing the "Eos" planar coil stellarator, the Company's first integrated fusion system capable of forming optimized stellarator magnetic fields without complex and costly modular coils. To demonstrate the field shaping capability required to enable Eos, Thea Energy designed, constructed, and tested the "Canis" 3x3 array of

Jun-Cong Zheng, Xiao-Wei Zheng, Xin-Lei Hei, Yi-Fan Qiao

In this work, we utilize a two-level atom and a ${\Lambda}$-type atom to link two identical waveguides, subsequently extending the model to a giant-atom configuration. Our analytical solutions and numerical simulations demonstrate that this setup can achieve single-photon isolation and nonreciprocal frequency conversion by tuning the atom-waveguide coupling

Hancong Feng KaiLI Jiang Bin tang

Automatic non-cooperative analysis of intercepted radar signals is essential for intelligent equipment in both military and civilian domains. Accurate modulation identification and parameter estimation enable effective signal classification, threat assessment, and the development of countermeasures. In this paper, we propose a symbolic approach for radar sig

Lucie Berger, Mathieu Lamard, Philippe Zhang, Laurent Borderie

Foundation models are large-scale versatile systems trained on vast quantities of diverse data to learn generalizable representations. Their adaptability with minimal fine-tuning makes them particularly promising for medical imaging, where data variability and domain shifts are major challenges. Currently, two types of foundation models dominate the literatu

Zechuan Li, Hongshan Yu, Yihao Ding, Jinhao Qiao

We propose GO-N3RDet, a scene-geometry optimized multi-view 3D object detector enhanced by neural radiance fields. The key to accurate 3D object detection is in effective voxel representation. However, due to occlusion and lack of 3D information, constructing 3D features from multi-view 2D images is challenging. Addressing that, we introduce a unique 3D posi

Wenxing Guo, Jinhan Xie, Jianya Lu, Bei jiang

In this paper, we develop a novel online federated learning framework for classification, designed to handle streaming data from multiple clients while ensuring data privacy and computational efficiency. Our method leverages the generalized distance-weighted discriminant technique, making it robust to both homogeneous and heterogeneous data distributions acr

Rodion Novkin, Hussam Amrouch

Neural network (NN)-based transistor compact modeling has recently emerged as a transformative solution for accelerating device modeling and SPICE circuit simulations. However, conventional NN architectures, despite their widespread adoption in state-of-the-art methods, primarily function as black-box problem solvers. This lack of interpretability significan

Jiazhe Guo, Yikang Ding, Xiwu Chen, Shuo Chen

Current generative models struggle to synthesize dynamic 4D driving scenes that simultaneously support temporal extrapolation and spatial novel view synthesis (NVS) without per-scene optimization. A key challenge lies in finding an efficient and generalizable geometric representation that seamlessly connects temporal and spatial synthesis. To address this, w

Kazu Akiba, Jerome Alozy, David Bacher, Rafael Ballabriga Sune

The spatial and temporal performance of a telescope system comprising planar silicon sensors bump-bonded to Timepix4-v2 ASICs are assessed at the CERN SPS using a $180$~GeV/$c$ mixed hadron beam. The pointing resolution at the centre of the telescope is $2.3 \pm 0.1\;\mathrm{\mu m}$ and $2.4 \pm 0.1\mathrm{\mu m}$ in x and y directions, respectively. The tem

Jie Li, Jing Li, Lu Lv, Peixin Zhang

We propose an algorithm based on Zadoff-Chu (ZC) sequences and time-frequency images (TFI) to achieve drone remote identification (RID). Specifically, by analyzing the modulation parameters and frame structures of drone ratio-frequency (RF) signals in the DroneRFa dataset, we extract prior information about ZC sequences with surprising correlation properties

Kalin V. Staykov, Daniela D. Doneva, Pedro G. S. Fernandes, Stoytcho S. Yazadjiev

We perform an in-depth analysis of rotating scalarized black holes in scalar-Gauss-Bonnet gravity, where scalarization is induced by the spacetime curvature. Our results show that even for very large spins, the scalar charge can reach values comparable to those in the static limit, meaning it is not significantly suppressed. Consequently, curvature-induced s

Tittaya Mairittha, Tanakon Sawanglok, Panuwit Raden, Sorrawit Treesuk

Swine disease surveillance is critical to the sustainability of global agriculture, yet its effectiveness is frequently undermined by limited veterinary resources, delayed identification of cases, and variability in diagnostic accuracy. To overcome these barriers, we introduce a novel AI-powered, multi-agent diagnostic system that leverages Retrieval-Augment

J. M. Carmona, J. L. Cortés, F. Rescic, M. A. Reyes

The lack of a dynamical framework within doubly special relativity theories has impeded the development of a corresponding phenomenology of modified interactions. In this work we show that in a model based on the classical basis of $\kappa$-Poincar\'e and total momentum conservation, one has a well-defined cross section of the photon-photon annihilation proc

Faseeh Ahmad, Hashim Ismail, Jonathan Styrud, Maj Stenmark

Robotic systems often face execution failures due to unexpected obstacles, sensor errors, or environmental changes. Traditional failure recovery methods rely on predefined strategies or human intervention, making them less adaptable. This paper presents a unified failure recovery framework that combines Vision-Language Models (VLMs), a reactive planner, and

Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue

Large language models (LLMs) like GPT-4 and LLaMA-3 utilize the powerful in-context learning (ICL) capability of Transformer architecture to learn on the fly from limited examples. While ICL underpins many LLM applications, its full potential remains hindered by a limited understanding of its generalization boundaries and vulnerabilities. We present a system

Svitlana Pastukh, Pawel T. Jochym, Jan Lazewski, Dominik Legut

In this research, we examine the electronic, magnetic, and lattice properties of the Fe$_4$(P$_2$O$_7$)$_3$ compound using the first principles calculations based on the density functional theory. The crystal lattice has a monoclinic structure, belonging to the P$2_1/n$ space group. The optimized lattice parameters are a=7.406 \AA, b=21.425 \AA, c=9.529 \AA,

Onno Eberhard, Michael Muehlebach, Claire Vernade

Partially observable environments present a considerable computational challenge in reinforcement learning due to the need to consider long histories. Learning with a finite window of observations quickly becomes intractable as the window length grows. In this work, we introduce memory traces. Inspired by eligibility traces, these are compact representations

Luca De Martini, Dario d'Abate, Alessandro Margara, Gianpaolo Cugola

Emerging compute continuum environments pose new challenges that traditional cloud-centric architectures struggle to address. Latency, bandwidth constraints, and the heterogeneity of edge environments hinder the efficiency of centralized cloud solutions. While major cloud providers extend their platforms to the edge, these approaches often overlook its uniqu

Benjamin Hennion, Julian Holstein, Marco Robalo

This paper is a follow-up to arXiv:2407.08471. Let $X$ be a a $(-1)$-shifted symplectic derived Deligne--Mumford stack. Thanks to the Darboux lemma of Brav--Bussi--Joyce, $X$ is locally modeled by derived critical loci of a function $f$ on a smooth scheme $U$. In this paper we study the gluing of the locally defined $2$-periodic (big) dg-categories of matrix

Feifei Li, Mi Zhang, Yiming Sun, Min Yang

Text-to-image diffusion models have achieved state-of-the-art results in synthesis tasks; however, there is a growing concern about their potential misuse in creating harmful content. To mitigate these risks, post-hoc model intervention techniques, such as concept unlearning and safety guidance, have been developed. However, fine-tuning model weights or adap

Spandan Dash, Matteo Brogi, Fabian Lukas Seidler, Paolo A. Sossi

Ultra-short Period exoplanets (USPs) like 55 Cnc e, hosting dayside magma oceans, present unique opportunities to study surface-atmosphere interactions. The composition of a vaporised mineral atmosphere enveloping the dayside is dictated by that of the surface magma ocean, which in turn is sensitive to its oxygen fugacity ($f$O$_2$). Observability estimation

Giorgia Crosilla, Lukas Klic, Giovanni Colavizza

Traditional machine learning models for Handwritten Text Recognition (HTR) rely on supervised training, requiring extensive manual annotations, and often produce errors due to the separation between layout and text processing. In contrast, Multimodal Large Language Models (MLLMs) offer a general approach to recognizing diverse handwriting styles without the

Andrea Costantini, Laura Iacconi, David J. Mulryne

A key step in the comparison between inflationary predictions and cosmological observations is the computation of primordial correlators. Numerical methods have been developed that overcome some of the difficulties arising in analytical calculations when the models considered are complex. The PyTransport package, which implements the transport formalism, all

Martin Azon

We follow the ideas of Darmon's program for solving infinite families of generalised Fermat equations of signatures $(p,p,r)$ and $(r,r,p)$, where, $r$ is a fixed prime and $p$ is varying. We do so by introducing a common framework for both signatures, allowing for a uniform treatment for the two families of equations. We analyse in detail the geometry of Fr

Kritika Babbar, Amit Maji

In this paper we obtain a complete characterization of reducing, invariant, and hyperinvariant subspaces for the completely non-unitary component of a power partial isometry. In particular, precise characterization of reducing, invariant, and hyperinvariant subspaces of a truncated shift operator has been achieved.

Hranislav Stanković

In this paper, we present an elementary proof of the Bhatia-\v{S}emrl Theorem, utilizing the Minimax Theorem for bounded linear operators by Asplund and Ptak [1]. Some related results are also discussed.

Boyang Song

This paper investigates the parallelization of Dijkstra's algorithm for computing the shortest paths in large-scale graphs using MPI and CUDA. The primary hypothesis is that by leveraging parallel computing, the computation time can be significantly reduced compared to a serial implementation. To validate this, I implemented three versions of the algorithm:

Jiexia Ye, Weiqi Zhang, Ziyue Li, Jia Li

Accurate medical time series (MedTS) classification is essential for effective clinical diagnosis, yet remains challenging due to complex multi-channel temporal dependencies, information redundancy, and label scarcity. While transformer-based models have shown promise in time series analysis, most are designed for forecasting tasks and fail to fully exploit

George K. Eleftherakis, Evgenios T. A. Kakariadis, Ivan G. Todorov

Let $A$ be a unital C*-algebra, $S$ be an operator $A$-system and $E$ be an operator space that is a left operator $A$-module. We introduce the symmetrisation of the pair $(E,S)$ as the Hausdorff completion of the balanced tensor product $E^* \odot^{A} S \odot^{A} E$ with respect to a seminorm arising from the family of completely contractive completely posi

Sejong Kim, Hyunseo Song, Hyunwoo Seo, Hyunjun Kim

Retrieval-Augmented Generation (RAG) has emerged as a promising framework to mitigate hallucinations in Large Language Models (LLMs), yet its overall performance is dependent on the underlying retrieval system. In the finance domain, documents such as 10-K reports pose distinct challenges due to domain-specific vocabulary and multi-hierarchical tabular data.

Mohamed Hassouna, Clara Holzhüter, Malte Lehna, Matthijs de Jong

The rising proportion of renewable energy in the electricity mix introduces significant operational challenges for power grid operators. Effective power grid management demands adaptive decision-making strategies capable of handling dynamic conditions. With the increase in complexity, more and more Deep Learning (DL) approaches have been proposed to find sui

Jasper Stone, Raj Patel, Farbod Ghiasi, Sudip Mittal

The adoption of Machine Learning Operations (MLOps) enables automation and reliable model deployments across industries. However, differing MLOps lifecycle frameworks and maturity models proposed by industry, academia, and organizations have led to confusion regarding standard adoption practices. This paper introduces a unified MLOps lifecycle framework, fur

Ian A. Bonnell

The baryonic fraction of galaxies is observed to vary with the mass of its dark matter (DM) halo. Low-mass galaxies have low baryonic fractions which increase to a maximum for masses near $10^{12}\ M_{\odot}$, and decreases thereafter with increasing galaxy mass. This trend is generally attributed to the action of feedback from star formation at the low end

Alba Márquez-Rodríguez, Miguel Ángel Mohedano-Munoz, Manuel J. Marín-Jiménez, Eduardo Santamaría-García

Passive Acoustic Monitoring is a key tool for biodiversity conservation, but the large volumes of unsupervised audio it generates present major challenges for extracting meaningful information. Deep Learning offers promising solutions. BirdNET, a widely used bird identification model, has shown success in many study systems but is limited at local scale due

Zhonghua Qiao, Yifan Wei

The numerical accuracy of particle-based approximations in Smoothed Particle Hydrodynamics (SPH) is significantly affected by the spatial uniformity of particle distributions, especially for second-order derivatives. This study aims to enhance the accuracy of SPH method and analyze its convergence with irregular particle distributions. By establishing regula

Sergiu Busuioc, Victor Sofonea

An Enskog-Vlasov finite-difference Lattice Boltzmann (EV-FDLB) for liquid-vapor systems with variable temperature is introduced. The model involves both the simplified Enskog collision operator and the self-consistent force field which accounts for the long-range interaction between the fluid particles. Full-range Gauss-Hermite quadratures were used for the

Lamia Lamrani, Christian Bongiorno, Marc Potters

Cross-validation is a statistical tool that can be used to improve large covariance matrix estimation. Although its efficiency is observed in practical applications and a convergence result towards the error of the non linear shrinkage is available in the high-dimensional regime, formal proofs that take into account the finite sample size effects are current

Gyeongrok Oh, Sungjune Kim, Heeju Ko, Hyung-gun Chi

The resolution of voxel queries significantly influences the quality of view transformation in camera-based 3D occupancy prediction. However, computational constraints and the practical necessity for real-time deployment require smaller query resolutions, which inevitably leads to an information loss. Therefore, it is essential to encode and preserve rich vi

Yanzhen Li, Zining Wang

To address the risks of validator centralization, Proposer-Builder Separation (PBS) was introduced in Ethereum to divide the roles of block building and block proposing, fostering a more equitable and decentralized block production environment. PBS creates a two-sided market in which searchers submit valuable bundles to builders for inclusion in blocks, whil

Anatolii I. Visser-Zadvornyi, Mary E. Carstairs, Kyle A. Oman, Marc A. W. Verheijen

Observational measurements hint at a peak in the quenching timescale of satellite galaxies in groups and clusters as a function of their stellar masses at $M_{\star} \approx 10^{9.5} \mathrm{M}_{\odot}$; less and more massive satellite galaxies quench faster. We investigate the origin of these trends using the EAGLE simulation in which they are qualitatively

NuPECC

The Nuclear Physics European Collaboration Committee ( NuPECC, http://nupecc.org/ ) hosted by the European Science Foundation represents today a large nuclear physics community from 23 countries, 3 ESFRI (European Strategy Forum for Research Infrastructures) nuclear physics infrastructures and ECT* (European Centre for Theoretical Studies in Nuclear Physics

Kevin M Esvelt

The extent to which foundation models can disclose novel chemical, biological, radiation, and nuclear (CBRN) threats to expert users is unclear due to a lack of test cases. I leveraged the unique opportunity presented by an upcoming publication describing a novel catastrophic biothreat - "Technical Report on Mirror Bacteria: Feasibility and Risks" - to condu

Nikola Herceg, Tajron Jurić, A. Naveena Kumara, Andjelo Samsarov

We explore quasinormal modes (QNMs) of the Schwarzschild black hole under a noncommutative (NC) deformation of spacetime, constructed via a Drinfeld twist formalism. In this approach, the usual Regge--Wheeler (axial) and Zerilli (polar) equations acquire additional contributions that depend on the NC parameter. Employing semi-analytical approximations (high-

Wenjie Huang, Yang Li, Shijie Yuan, Jingjia Teng

The driving risk field is applicable to more complex driving scenarios, providing new approaches for safety decision-making and active vehicle control in intricate environments. However, existing research often overlooks the driving risk field and fails to consider the impact of risk distribution within drivable areas on trajectory planning, which poses chal

Simon B. Jäger

We study the dynamics of polarizable particles coupled to a lossy cavity mode that are transversally driven by a laser. Our analysis is performed in the regime where the cavity linewidth exceeds the recoil frequency by several orders of magnitude. Using a two-stage cooling protocol we show that the particles' kinetic energy can be reduced down to the recoil

Florian De Leger

We introduce a notion of an operad of complexity $m$, for $m \geq 1$. Operads of complexity $1$ are monoids in the category of $\mathbb{N}$-indexed collections, with monoidal product given by the Day convolution, and operads of complexity $2$ are non-symmetric operads. In general, we prove that the operad for operads of complexity $m$ is a suboperad of the $

Alireza Akbari, Peter Thalmeier

The surface tunneling microscope (STM) method probes the itinerant conduction electron spectrum which is influenced by the presence of collective order parameters. It may in fact be used as a tool to obtain important information about their microscopic nature, for example the gap symmetry in unconventional superconductors. Surprisingly it has been found that

Mario Lino, Tobias Pfaff, Nils Thuerey

Physical systems with complex unsteady dynamics, such as fluid flows, are often poorly represented by a single mean solution. For many practical applications, it is crucial to access the full distribution of possible states, from which relevant statistics (e.g., RMS and two-point correlations) can be derived. Here, we propose a graph-based latent diffusion (

Ananya Garg, Mohmmad Ayaan, Swara Parekh, Vikranth Udandarao

Accurate prediction of food delivery times significantly impacts customer satisfaction, operational efficiency, and profitability in food delivery services. However, existing studies primarily utilize static historical data and often overlook dynamic, real-time contextual factors crucial for precise prediction, particularly in densely populated Indian cities

Navya Sonal Agarwal, Sanjay Kumar Sonbhadra

This paper provides a comprehensive review of the integration of Large Language Models (LLMs) with visual analytics, addressing their foundational concepts, capabilities, and wide-ranging applications. It begins by outlining the theoretical underpinnings of visual analytics and the transformative potential of LLMs, specifically focusing on their roles in nat

Nikos Frantzikinakis

Motivated by partition regularity problems of homogeneous quadratic equations, we prove multiple recurrence and convergence results for multiplicative measure preserving actions with iterates given by rational sequences involving polynomials that factor into products of linear forms in two variables. We focus mainly on actions that are finitely generated, an

Minjia Wang, Wei Fan

We study celestial amplitudes for the S-matrix of the 2d integrable Bullough-Dodd model. This model has bound states that appear as poles in the physics strip of its 2d S-matrix, which complicates the computation of celestial amplitudes. However, it turns out that the celestial amplitudes are, in fact, well-structured. The celestial bootstrap (arising from t

Niclas Führling, Ivan Alexander Morales Sandoval, Giuseppe Thadeu Freitas de Abreu

We consider a novel routing protocol suitable for ad-hoc networks with dynamically changing topologies, such as DECT 2020 NR (NR+) systems, which often lead to missing links between the nodes and thus, incomplete or inefficient routes. A key point of the proposed protocol is the combination of network discovery and matrix completion techniques, which allow t

George Stamatelis, Angelos-Nikolaos Kanatas, George C. Alexandropoulos

Multi-Agent Deep Reinforcement Learning (MADRL) has emerged as a powerful tool for optimizing decentralized decision-making systems in complex settings, such as Dynamic Spectrum Access (DSA). However, deploying deep learning models on resource-constrained edge devices remains challenging due to their high computational cost. To address this challenge, in thi

David Fertig, Mathijs Janssen

Electric double layer (EDL) formation underlies the functioning of supercapacitors and several other electrochemical technologies. Here, we study how the EDL formation near two flat blocking electrodes separated by $2L$ is affected by beyond-mean-field Coulombic interactions, which can be substantial for electrolytes of high salt concentration or with multiv

Gaya Cocca, Paolo Frasca, Chiara Ravazzi

Popularity dynamics in social media depend on a complex interplay of social influence between users and popularity-based recommendations that are provided by the platforms. In this work, we introduce a discrete-time dynamical system to model the evolution of popularity on social media. Our model generalizes the well-known Friedkin-Johnsen model to a set of i