February 2025 arXiv papers — page 6

Tarun Kumar, Barilang Mawlong

The rare $b \to s \ell^+\ell^-$ transition is a well-explored transition, particularly for new physics beyond the standard model. Similar to this transition, another flavor changing neutral current transition $b \to s \nu\bar{\nu}$ involving a dineutrino pair also plays an important role in the search for new physics. The $B \to K \nu\bar{\nu}$ mode is one s

Sabina Jangirova, Branislava Jankovic, Waseem Ullah, Latif U. Khan

Wildfire catastrophes cause significant environmental degradation, human losses, and financial damage. To mitigate these severe impacts, early fire detection and warning systems are crucial. Current systems rely primarily on fixed CCTV cameras with a limited field of view, restricting their effectiveness in large outdoor environments. The fusion of intellige

Richard Gerlach, Antonio Naimoli, Giuseppe Storti

A method for quantile-based, semi-parametric historical simulation estimation of multiple step ahead Value-at-Risk (VaR) and Expected Shortfall (ES) models is developed. It uses the quantile loss function, analogous to how the quasi-likelihood is employed by standard historical simulation methods. The returns data are scaled by the estimated quantile series,

Tommi Heikkilä

MultiResolution Low-Rank decomposition is formulated for regularization of dynamic image sequences. The decomposition applies a local low-rank decomposition on a sequence of discrete wavelet transforms. Its effective formulation as a regularization functional is discussed and numerically tested for dynamic X-ray tomography in comparison to other low-rank met

L. Cadamuro, T. Ingebretsen Carlson, J. Sjölin

Di-Higgs ($hh$) production is crucial for probing the Higgs boson self-interaction and understanding the electroweak phase transition. Deviations from Standard Model predictions in $hh$ gluon-gluon fusion (ggF) can be systematically parameterized using effective field theories (EFT), such as Higgs Effective Field Theory (HEFT) and Standard Model Effective Fi

Naman Bansal, Yash mahajan, Sanjeev Sinha, Santu Karmaker

Sentence encoders play a pivotal role in various NLP tasks; hence, an accurate evaluation of their compositional properties is paramount. However, existing evaluation methods predominantly focus on goal task-specific performance. This leaves a significant gap in understanding how well sentence embeddings demonstrate fundamental compositional properties in a

Yujie Li, Xiangkun Wang, Xin Yang, Marcello Bonsangue

Open-world continual learning (OWCL) adapts to sequential tasks with open samples, learning knowledge incrementally while preventing forgetting. However, existing OWCL still requires a large amount of labeled data for training, which is often impractical in real-world applications. Given that new categories/entities typically come with limited annotations an

Perla Al Almaoui, Pierrette Bouillon, Simon Hengchen

In this era of rapid technological advancements, communication continues to evolve as new linguistic phenomena emerge. Among these is Arabizi, a hybrid form of Arabic that incorporates Latin characters and numbers to represent the spoken dialects of Arab communities. Arabizi is widely used on social media and allows people to communicate in an informal and d

Muhammad Rizwan Ali, Violet Ka I Pun, Guillermo Román-Díez

Cross-organisational workflows involve multiple concurrent, collaborative workflows across different departments or organisations, necessitating effective coordination due to their interdependent nature and shared resource requirements. The complexity of designing and managing these workflows stems from the need for comprehensive domain knowledge and a unifi

James Nevin, Salvatore Flavio Pileggi, Michael Lees, Paul Groth

The large amounts of data continuously generated online offer opportunities to identify and analyse trends in various aspects of society. For instance, data from online social media are frequently used as a means of analysing informal interactions, opinions, and feelings of groups of people. Additionally, bibliometric data can be used to investigate more for

Mateusz Mrukiewicz, Paweł Perkowski, Jakub Karcz, Przemysław Kula

We investigated the electrical properties of the liquid crystal compound, known as an RM734, exhibiting a ferroelectric nematic phase. The influence of alternating (AC) and direct (DC) current electric fields on the switching process of the polarization vector and dielectric constant of planarly aligned ferronematic and nematic phases were examined. The decr

Yunqi Shi, Siyuan Xu, Shixiong Kai, Xi Lin

Timing optimization during the global placement of integrated circuits has been a significant focus for decades, yet it remains a complex, unresolved issue. Recent analytical methods typically use pin-level timing information to adjust net weights, which is fast and simple but neglects the path-based nature of the timing graph. The existing path-based method

Weixiang Zhao, Yulin Hu, Yang Deng, Jiahe Guo

Role-playing enables large language models (LLMs) to engage users in immersive and personalized interactions, but it also introduces significant safety risks. Existing role-play fine-tuning techniques improve role adaptability but may degrade safety performance, particularly for villainous characters. In this work, we conduct the first comprehensive assessme

R. Rodrigues, F. J. Galindo-Rosales, L. Campo-Deaño

Aiming towards the magnetorheological characterisation of whole human blood, we evaluated the suitability of our experimental setup for steady shear measurements with low-viscosity fluids. Previous measurements with a rotational rheometer equipped with a magnetorheological cell returned low and inconsistent apparent-viscosity values. In this work, a parametr

Richard Bergna, Stefan Depeweg, Sergio Calvo Ordonez, Jonathan Plenk

Uncertainty quantification in neural networks through methods such as Dropout, Bayesian neural networks and Laplace approximations is either prone to underfitting or computationally demanding, rendering these approaches impractical for large-scale datasets. In this work, we address these shortcomings by shifting the focus from uncertainty in the weight space

Joaquin Tarraga-Moreno, Jesus Escudero-Sahuquillo, Pedro Javier Garcia, Francisco J. Quiles

In the last decade, specific-purpose computing and storage devices, such as GPUs, TPUs, or high-speed storage, have been incorporated into server nodes of Supercomputers and Data centers. The development of high-bandwidth memory (HBM) enabled a much more compact form factor for these devices, thus allowing the interconnection of several of them within a serv

Zhengxuan Zhang, Yin Wu, Yuyu Luo, Nan Tang

Visual Question Answering (VQA) focuses on providing answers to natural language questions by utilizing information from images. Although cutting-edge multimodal large language models (MLLMs) such as GPT-4o achieve strong performance on VQA tasks, they frequently fall short in accessing domain-specific or the latest knowledge. To mitigate this issue, retriev

Gerion Spielberger, Florian M. Artinger, Jochen Reb, Rudolf Kerschreiter

Analyzing textual data is the cornerstone of qualitative research. While traditional methods such as grounded theory and content analysis are widely used, they are labor-intensive and time-consuming. Topic modeling offers an automated complement. Yet, existing approaches, including LLM-based topic modeling, still struggle with issues such as high data prepro

Anshuman Tripathi, Abhirup Datta, Aishrila Mazumder, Suman Majumdar

The Epoch of Reionization (EoR) and Cosmic Dawn (CD) are pivotal stages during the first billion years of the universe, exerting a significant influence on the development of cosmic structure. The detection of the redshifted 21-cm signal from these epochs is challenging due to the dominance of significantly stronger astrophysical foregrounds and the presence

Gianluca Allinson, Lucy A. Downes, Kevin J. Weatherill, C. Stuart Adams

We present new measurements of quantum defects and core polarizabilities in cesium ($^{133}$Cs), based on transition frequency measurements between Rydberg states ($14 \leq n \leq 38$) obtained through terahertz (THz) and radio-frequency spectroscopy in a thermal atomic vapor. %By detuning resonant fields coupling neighbouring Rydberg states, we observe a de

Florian Herren, Bastian Kubis, Raynette van Tonder

We introduce a novel parameterization of $B\rightarrow\pi\pi\ell\nu$ form factors relying on partial-wave decompositions and series expansions in suitable variables. We bound the expansion coefficients through unitarity and include left-hand cut contributions using established dispersive methods. The two-hadron lineshapes are treated in a model-independent m

Z. Wu, Y. Deng, J. Hu, L. Cui

Serverless computing has emerged as a pivotal paradigm for deploying Deep Learning (DL) models, offering automatic scaling and cost efficiency. However, the inherent cold start problem in serverless ML inference systems, particularly the time-consuming model loading process, remains a significant bottleneck. Utilizing pipelined model loading improves efficie

Run-Qiang Jian, Li Luo, Xianfa Wu

We introduce and study Lyndon bases of split $\imath$quantum groups $\mathbf{U}^\imath(\mathfrak{g})$. A relationship between the Lyndon bases and PBW-type bases was provided. As an application, we establish the existence of canonical bases for the type A split $\imath$quantum groups $\mathbf{U}^\imath(\mathfrak{sl}_n)$.

Giseung Park, Youngchul Sung

In this paper, we introduce a simple yet effective reward dimension reduction method to tackle the scalability challenges of multi-objective reinforcement learning algorithms. While most existing approaches focus on optimizing two to four objectives, their abilities to scale to environments with more objectives remain uncertain. Our method uses a dimension r

Yudan Xiong, Fangjun Xu, Jinjiong Yu

Let $X=\{X_n: n\in\mathbb{N}\}$ be the linear process defined by $X_n=\sum^{\infty}_{j=1} a_j\varepsilon_{n-j}$, where the coefficients $a_j=j^{-\beta}\ell(j)$ are constants with $\beta>0$ and $\ell$ a slowly varying function, and the innovations $\{\varepsilon_n\}_{n\in\mathbb{Z}}$ are i.i.d. random variables belonging to the domain of attraction of an $\al

Ryo Nagai, Takashi Takemoto, Yusuke Wachi, Hiroyuki Mizuno

We propose a digital-controlled conveyor-belt shuttling method for silicon-based quantum processors, addressing the scalability challenges of conventional analog sinusoidal implementations. By placing a switch matrix and low-pass filters in a cryogenic environment, our approach synthesizes near-sinusoidal waveforms from a limited number of DC voltage levels.

Hannes Homburger, Florian Messerer, Moritz Diehl, Johannes Reuter

Model predictive path integral (MPPI) control has recently received a lot of attention, especially in the robotics and reinforcement learning communities. This letter aims to make the MPPI control framework more accessible to the optimal control community. We present three classes of optimal control problems and their solutions by MPPI. Further, we investiga

Hongyuan Shen, Min Zheng, Jincheng Wang, Yang Zhao

With the widespread application of Large Language Models across various domains, their security issues have increasingly garnered significant attention from both academic and industrial communities. This study conducts sampling and normalization of the parameters of the LLM to generate visual representations and heatmaps of parameter distributions, revealing

Kanchan Bala, Rahul Verma, Shovan Dan, Suman Nandi

Understanding the interplay among magnetism, electron correlations, and complex electronic structures in rare-earth materials requires both high-quality single crystals and systematic investigation of their electronic properties. In this study, we have successfully grown a single crystal of SmAg$_2$Ge$_2$ and investigated its anisotropic physical properties

M. Tsantaki, L. Magrini, C. Danielski, D. Bossini

The next mission dedicated to the study of planetary atmospheres is the Ariel space mission, planned for launch in 2029, which will observe a variety of planetary systems belonging to different classes around stars with spectral types from M to A. To optimise the scientific outcome of the mission, such stars need to be homogeneously characterised beforehand.

Luigi Montoro, Luigi Muglia, Berardino Sciunzi

We consider positive solutions to $\displaystyle -\Delta_p u=\frac{1}{u^\gamma}+f(u)$ under zero Dirichlet condition in the half space. Exploiting a prio-ri estimates and the moving plane technique, we prove that any solution is monotone increasing in the direction orthogonal to the boundary.

Petr Sokerin, Dmitry Anikin, Sofia Krehova, Alexey Zaytsev

The emergence of deep learning led to the broad usage of neural networks in the time series domain for various applications, including finance and medicine. While powerful, these models are prone to adversarial attacks: a benign targeted perturbation of input data leads to significant changes in a classifier's output. However, formally small attacks in the t

Maksymilian Graczyk, Stefan Roiser

Given the recent technological trends and novel computing paradigms spanning both software and hardware, physicists and software developers can no longer just rely on computers becoming faster to meet the ever-increasing computing demands of their research. Adapting systems to the new environment may be difficult though, especially in case of large and compl

Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang

Diffusion models have recently driven significant breakthroughs in generative modeling. While state-of-the-art models produce high-quality samples on average, individual samples can still be low quality. Detecting such samples without human inspection remains a challenging task. To address this, we propose a Bayesian framework for estimating generative uncer

Margherita Martorana, Tobias Kuhn, Jacco van Ossenbruggen

Over the past decade, the Table Union Search (TUS) task has aimed to identify unionable tables within data lakes to improve data integration and discovery. While numerous solutions and approaches have been introduced, they primarily rely on open data, making them not applicable to restricted access data, such as medical records or government statistics, due

Julian Rasch, Matthias Wilhalm, Florian Müller, Francesco Chiossi

With the increasing spread of AR head-mounted displays suitable for everyday use, interaction with information becomes ubiquitous, even while walking. However, this requires constant shifts of our attention between walking and interacting with virtual information to fulfill both tasks adequately. Accordingly, we as a community need a thorough understanding o

Xue Yang, Tao Chen, Lei Guo, Wenbo Jiang

Reference-based image super-resolution (RefSR) represents a promising advancement in super-resolution (SR). In contrast to single-image super-resolution (SISR), RefSR leverages an additional reference image to help recover high-frequency details, yet its vulnerability to backdoor attacks has not been explored. To fill this research gap, we propose a novel at

Jingwei Hu, Dave Zachariah, Torbjörn Wigren, Petre Stoica

We consider the joint problem of online experiment design and parameter estimation for identifying nonlinear system models, while adhering to system constraints. We utilize a receding horizon approach and propose a new adaptive input design criterion, which is tailored to continuously updated parameter estimates, along with a new sequential estimator. We dem

B. Vaia, Ž. Bošnjak, A. Bracco, S. Campana

The observation of 21 X-ray dust-scattering rings around the extraordinarily bright gamma-ray burst (GRB) 221009A provides a unique opportunity to study the interstellar medium (ISM) through which the X-ray radiation traveled in our Galaxy and, by difference, in the host galaxy as well. In particular, since the ring intensity and radius at a given time depen

Simon F. Martina-Perez, Luke A. Heirene, Jennifer C. Kasemeier, Paul M. Kulesa

Neuroblastoma is a paediatric extracranial solid cancer that arises from the developing sympathetic nervous system and is characterised by an abnormal distribution of cell types in tumours compared to healthy infant tissues. In this paper, we propose a new mathematical model of cell differentiation during sympathoadrenal development. By performing Bayesian i

Divya Perumal, Swaroop Panda

The growing popularity and widespread adoption of large language models (LLMs) necessitates the development of tools that enhance the effectiveness of user interactions with these models. Understanding the structures and functions of these models poses a significant challenge for users. Visual analytics-driven tools enables users to explore and compare, faci

Andrew Parry, Maik Fröbe, Harrisen Scells, Ferdinand Schlatt

The fundamental property of Cranfield-style evaluations, that system rankings are stable even when assessors disagree on individual relevance decisions, was validated on traditional test collections. However, the paradigm shift towards neural retrieval models affected the characteristics of modern test collections, e.g., documents are short, judged with four

Michael Dinzinger, Laura Caspari, Kanishka Ghosh Dastidar, Jelena Mitrović

We present WebFAQ, a large-scale collection of open-domain question answering datasets derived from FAQ-style schema.org annotations. In total, the data collection consists of 96 million natural question-answer (QA) pairs across 75 languages, including 47 million (49%) non-English samples. WebFAQ further serves as the foundation for 20 monolingual retrieval

Philemon Urbain Mballa

This article proposes a unified analytical approach leading to a partial resolution of the Erdos-Straus, Sierpinski conjectures, and their generalization. We introduce an equivalent reformulation of these conjectures while constructing two new explicit analytical formulas. The first formula, which is a special case of the second, is based on a divisibility c

Utku Ozbulak, Seyed Amir Mousavi, Francesca Tozzi, Niki Rashidian

Real-time video segmentation is a promising opportunity for AI-assisted surgery, offering intraoperative guidance by identifying tools and anatomical structures. Despite growing interest in surgical video segmentation, annotation protocols vary widely across datasets -- some provide dense, frame-by-frame labels, while others rely on sparse annotations sample

Jingru Gan, Peichen Zhong, Yuanqi Du, Yanqiao Zhu

Crystal structure generation is fundamental to materials science, enabling the discovery of novel materials with desired properties. While existing approaches leverage Large Language Models (LLMs) through extensive fine-tuning on materials databases, we show that pre-trained LLMs can inherently generate novel and stable crystal structures without additional

Hyunwoo Jeon, Joonil Kim

Let $\mathbb{H}^n$ denote the Heisenberg group, identified with $\mathbb{R}^d \times \mathbb{R}$, where $d = 2n$ and $n \in \mathbb{N}$. We consider the spherical maximal operator $\mathcal{M}$ associated with the sphere $S^{d-1}$ embedded in the horizontal subspace $\mathbb{R}^d \times \{0\}$ of $\mathbb{H}^n$. It is known that $\mathcal{M}$ is bounded on $

Ilya Koziev

Generative poetry systems require effective tools for data engineering and automatic evaluation, particularly to assess how well a poem adheres to versification rules, such as the correct alternation of stressed and unstressed syllables and the presence of rhymes. In this work, we introduce the Russian Poetry Scansion Tool library designed for stress mark pl

Christoph Aistleitner, Lorenz Frühwirth, Manuel Hauke, Maryna Manskova

In a recent paper, Aistleitner, Gantert, Kabluchko, Prochno and Ramanan studied large deviation principles (LDPs) for lacunary trigonometric sums $\sum_{n=1}^N \cos(2 \pi n_k x)$, where the sequence $(n_k)_{k \geq 1}$ satisfies the Hadamard gap condition $n_{k+1} / n_k \geq q > 1$ for $k \geq 1$. A crucial ingredient in their work were asymptotic estimates f

Pierpaolo Fontana, Andrea Trombettoni

Due to their broad applicability, gauge theories (GTs) play a crucial role in various areas of physics, from high-energy physics to condensed matter. Their formulations on lattices, lattice gauge theories (LGTs), can be studied, among many other methods, with tools coming from statistical mechanics lattice models, such as mean field methods, which are often

Nan Li, Yansha Deng, Dusit Niyato

Efficient video transmission is essential for seamless communication and collaboration within the visually-driven digital landscape. To achieve low latency and high-quality video transmission over a bandwidth-constrained noisy wireless channel, we propose a stable diffusion (SD)-based goal-oriented semantic communication (GSC) framework. In this framework, w

Chunmei Xu, Yi Ma, Rahim Tafazolli

This paper presents a novel framework for importance-aware adaptive data transmission, designed specifically for real-time computer vision (CV) applications where task-specific fidelity is critical. An importance-weighted mean square error (IMSE) metric is introduced, assigning data importance based on bit positions within pixels and semantic relevance withi

Bao Duong, Nu Hoang, Thin Nguyen

Testing for the conditional independence structure in data is a fundamental and critical task in statistics and machine learning, which finds natural applications in causal discovery - a highly relevant problem to many scientific disciplines. Existing methods seek to design explicit test statistics that quantify the degree of conditional dependence, which is

Zuzanna Bączek, Michał Bizoń, Aneta Pawelec, Piotr Sankowski

Algorithmic solutions have significant potential to improve decision-making across various domains, from healthcare to e-commerce. However, the widespread adoption of these solutions is hindered by a critical challenge: the lack of human-interpretable explanations. Current approaches to Explainable AI (XAI) predominantly focus on complex machine learning mod

Haonan An, Guang Hua, Zhengru Fang, Guowen Xu

The intellectual property of deep image-to-image models can be protected by the so-called box-free watermarking. It uses an encoder and a decoder, respectively, to embed into and extract from the model's output images invisible copyright marks. Prior works have improved watermark robustness, focusing on the design of better watermark encoders. In this paper,

Christoph Adam, Jorge Castelo Mourelle, Alberto García Martín-Caro, Andrzej Wereszczynski

Boson stars are hypothetical compact objects derived from solutions of a self-gravitating complex scalar field. In this study, we extend the traditional models by generalizing the kinetic term of the scalar field to that of a nonlinear sigma model. Concretely, we obtain spinning boson star solutions for a family of models parametrized by the curvature of the

F. Fiore, M. Elvis

Will it be possible in the future to realize large, complex space missions dedicated to basic science like HST, Chandra and JWST? Or will their cost be too great? Today's space scene is completely different from that of even five years ago, and certainly from that of the time when HST, Chandra and JWST were conceived and built. Space-related investments have

Malitha Gunawardhana, Mark L Trew, Gregory B Sands, Jichao Zhao

Atrial Fibrillation (AF), the most common sustained cardiac arrhythmia worldwide, increasingly requires accurate bi-atrial structural assessment to guide ablation strategies, particularly in persistent AF. Late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) enables visualisation of atrial fibrosis, but precise manual segmentation remains time-consu

Leo Katayama, Andreas P. Schnyder, Yasuhiro Asano, Satoshi Ikegaya

The definitive detection of Majorana modes in topological superconductors is a key issue in condensed matter physics. Here we propose a smoking-gun experiment for the detection of one-dimensional dispersing Majorana edge modes, based on theoretical results for multi-terminal transport in a setup consisting of two normal metal leads and a topological supercon

Jigyasa Watwani, Sakshi Pahujani, V Jemseena, Vishal Vasan

Mechanochemical patterns arising in the actomyosin cortex drive many cellular processes. Here we consider a hydrodynamic model for the actomyosin cortex of cells and study the sensitivity of the emergent patterns to both physical parameters and the geometry of the confining domain. We first establish a general framework for the Galerkin analysis of such patt

Ramón González Rodríguez, Brais Ramos Pérez

The present article represents a step forward in the study of the following problem: If $\mathbb{A}=(A_{1},A_{2})$ and $\mathbb{H}=(H_{1},H_{2})$ are Hopf braces in a symmetric monoidal category C such that $(A_{1},H_{1})$ and $(A_{2},H_{2})$ are matched pairs of Hopf algebras, then we want to know under what conditions the pair $(A_{1}\bowtie H_{1},A_{2}\bo

Luis Alberto Razo López, Pierre Wulles, Geoffroy J. Aubry, Sergey E. Skipetrov

Topologically nontrivial band structure of a material may give rise to special states that are confined to the material's boundary and protected against disorder and scattering. Quantum spin Hall effect (QSHE) is a paradigmatic example of phenomenon in which such states appear in the presence of time-reversal symmetry in two dimensions. Whereas the spatial s

Andreas Dzemski, Ryo Okui, Wenjie Wang

We examine the location properties of a conditional selective confidence interval constructed via the polyhedral method. The interval is derived from the distribution of a test statistic conditional on the event of statistical significance. For a one-sided test, its behavior depends on whether the parameter is highly or only marginally significant. In the hi

LiquidO Collaboration, S. R. Soleti, J. J. Gómez-Cadenas, J. Apilluelo

COCOA (COmpact COmpton cAmera) is a next-generation gamma-ray telescope designed for astrophysical observations in the MeV energy range. The detector comprises a scatterer volume employing the LiquidO detection technology and an array of scintillating crystals acting as absorber. Surrounding plastic scintillator panels serve as a veto system for charged part

Yu Xu, Xueheng Zhang, Yuhong Yu, Pei Yu

Generating a mono-energetic, high-energy muon beam using accelerator facilities can be very attractive for many purposes, for example, improving muon tomography currently limited by the low flux and wide energy spread of cosmic ray muons, and searching for muon related new physics beyond the Standard Model. One potential accelerator facility is the High Inte

Qifei Ma, Mauro Chinappi, Ali Douaki, Yanqiu Zou

Recent research on silver nanowires prepared on DNA templates has focused on two fundamental applications: nano-scale circuits and sensors. Despite its broad potential, the formation kinetics of DNA-templated silver nanowires remains unclear. Here, we present an experimental demonstration of the formation of silver nanowires with a diameter of 2.2+0.4 nm at

Chandana Sree Mala, Gizem Gezici, Fosca Giannotti

Large Language Models (LLMs) excel in language comprehension and generation but are prone to hallucinations, producing factually incorrect or unsupported outputs. Retrieval Augmented Generation (RAG) systems address this issue by grounding LLM responses with external knowledge. This study evaluates the relationship between retriever effectiveness and halluci

Eva A. Gallardo-Gutiérrez, F. Javier González-Doña

We prove that a large class of trace-class perturbations of diagonalizable normal operators on a separable, infinite dimensional complex Hilbert space have non-trivial closed hyperinvariant subspaces. Moreover, a large subclass consists of decomposable operators in the sense of Colojoar\u{a} and Foia\c{s}.

Eeli O. Lamponen, Sofia K. Pöntys, Päivi Törmä

We consider superconductivity and pair density waves (PDWs) arising from off-site pairing in frustrated lattice geometries. We express the pair susceptibility in a generic form that highlights the importance of both the density of states, and the quantum geometry of the eigenstates and calculate the superfluid weight (stiffness) as well as the Berezinskii-Ko

Jerson Caro, Fabien Pazuki, Riccardo Pengo

We study the Northcott and Bogomolov property for special values of Dedekind $\zeta$-functions at real values $\sigma \in \mathbb{R}$. We prove, in particular, that the Bogomolov property is not satisfied when $\sigma \geq \frac{1}{2}$. If $\sigma > 1$, we produce certain families of number fields having arbitrarily large degrees, whose Dedekind $\zeta$-func

Justin Dallant

Pseudoline arrangements are fundamental objects in discrete and computational geometry, and different works have tackled the problem of improving the known bounds on the number of simple arrangements of $n$ pseudolines over the past decades. The lower bound in particular has seen two successive improvements in recent years (Dumitrescu and Mandal in 2020 and

Leigh Lapworth, Christoph Sünderhauf

Quantum linear system solvers like the Quantum Singular Value Transformation (QSVT) require a block encoding of the system matrix $A$ within a unitary operator $U_A$. Unfortunately, block encoding often results in significant subnormalisation and increase in the matrix's effective condition number $\kappa$, affecting the efficiency of solvers. Matrix precond

Matti Ettel, Philipp Patrick Vieweg, Jörg Schumacher

The constant temperature and constant heat flux thermal boundary conditions, both developing distinct flow patterns, represent limiting cases of ideally conducting and insulating plates in Rayleigh-B\'enard convection (RBC) flows, respectively. This study bridges the gap in between, using a conjugate heat transfer (CHT) set-up and studying finite thermal dif

Tingting Wang, Bilel Selmi, Zhiming Li

In this paper, we consider definitions including $(q, \vartheta)$-Bowen topological entropy and $(q, \vartheta)$-packing topological entropy. We systematically explore their properties and measurability and analyze the relationship between $(q, \vartheta)$-packing topological entropy and topological entropy on level sets. Furthermore, the study demonstrates

Johannes Rauch, Leo Zanotti

We provide an improved implementation of Schmitzer's sparse multi-scale algorithm for discrete optimal transport on grids. We report roughly 2-4 times faster runtimes on the DOTmark benchmark. The source code is open source and publicly available.

Jiaming Chu, Lei Jin, Tao Wang, Junliang Xing

The rapid development of image generation and editing algorithms in recent years has enabled ordinary user to produce realistic images. However, the current AI painting ecosystem predominantly relies on text-driven diffusion models (T2I), which pose challenges in accurately capturing user requirements. Furthermore, achieving compatibility with other modaliti

Lev O. Luchnikov, Ekaterina A. Ilicheva, Victor A. Voronov, Prokhor A. Alekseev

The use of mixed cation absorber composition was considered as an efficient strategy to mitigate the degradation effects in halide perovskite solar cells. Despite the reports about partial stabilization at elevated temperatures, unfavorable phase transition after thermocycling and electric field-driven corrosion remains critical bottlenecks of perovskite thi

Manjula Rajaa, Anirban Ghoshb, Chukkapalli Praveen Kumarc, Suleiman Samba

Source location privacy (SLP) has been of great concern in WSNs when deployed for habitat monitoring applications. The issue is taken care of by employing privacy-preserving routing schemes. In the existing works, the attacker is assumed to be passive in nature and backtracks to the source of information by eavesdropping the message signals. In this work, we

Chong Zhang, Yukun Ma, Qian Chen, Wen Wang

We introduce InspireMusic, a framework integrated super resolution and large language model for high-fidelity long-form music generation. A unified framework generates high-fidelity music, songs, and audio, which incorporates an autoregressive transformer with a super-resolution flow-matching model. This framework enables the controllable generation of high-

Francesca Mantese, Lorenzo Martini

A classical result due to Morita and Azumaya establishes that given two arbitrary rings, any duality between their finitely generated modules is representable by a faithfully balanced bimodule which is a finitely generated injective cogenerator of both rings and, equivalently, these latter are one-sided artinian. We extend this well-known result to the case

Yifan Zhong, Xuchuan Huang, Ruochong Li, Ceyao Zhang

Dexterous grasping remains a fundamental yet challenging problem in robotics. A general-purpose robot must be capable of grasping diverse objects in arbitrary scenarios. However, existing research typically relies on restrictive assumptions, such as single-object settings or limited environments, showing constrained generalization. We present DexGraspVLA, a

N. Ashurbekov, I. dePedro-Embid, A. Pitanti, M. Msall

On-chip laterally confined GHz acoustic modes with tunable helicity open the way for advanced optomechanical functionalities. Here, we demonstrate a novel concept for the implementation of these functionalites through the electrical excitation of GHz membrane-like drum modes. Our concept relies on the strong dependence of the frequency spectrum of Lamb acous

Luise Mehner, Lena Alicija Philine Fiedler, Sabine Ammon, Dorothea Kolossa

The widespread application of Large Language Models (LLMs) involves ethical risks for users and societies. A prominent ethical risk of LLMs is the generation of unfair language output that reinforces or exacerbates harm for members of disadvantaged social groups through gender biases (Weidinger et al., 2022; Bender et al., 2021; Kotek et al., 2023). Hence, t

Matthias Orlikowski, Jiaxin Pei, Paul Röttger, Philipp Cimiano

People naturally vary in their annotations for subjective questions and some of this variation is thought to be due to the person's sociodemographic characteristics. LLMs have also been used to label data, but recent work has shown that models perform poorly when prompted with sociodemographic attributes, suggesting limited inherent sociodemographic knowledg

Alexander Dobler, Jakob Roithinger

We consider the task of drawing a graph on multiple horizontal layers, where each node is assigned a layer, and each edge connects nodes of different layers. Known algorithms determine the orders of nodes on each layer to minimize crossings between edges, increasing readability. Usually, this is done by repeated one-sided crossing minimization for each layer

W. Yang, K. T. Wong, H. Wiesemeyer, K. M. Menten

Strong laser emission from hydrogen cyanide (HCN) at 805 and 891 GHz has been discovered towards carbon-rich (C-rich) AGB stars, originating from the Coriolis-coupled system between two (1,1^{1e},0) and (0,4^0,0) vibrational states. However, other lines (at 894, 964, 968 and 1055 GHz) in this system remained unexplored due to observational challenges. Using

Y. Gong, C. Henkel, C. T. Bop, J. G. Mangum

Understanding the chemistry of molecular clouds is pivotal to elucidate star formation and galaxy evolution. As one of the important molecular ions, HCNH+ plays an important role in this chemistry. Yet, its behavior and significance under extreme conditions, such as in the CMZs of external galaxies, are still largely unexplored. We aim to reveal the physical

Yangyi Ye, Lin Li, Pengcheng Xie, Haijun Yu

Multiple solutions are common in various non-convex problems arising from industrial and scientific computing. Nonetheless, understanding the nontrivial solutions' qualitative properties seems limited, partially due to the lack of efficient and reliable numerical methods. In this paper, we design a dedicated numerical method to explore these nontrivial solut

Jiwon Park, Sourav Mridha, Dukjae Jang, Mayukh R. Gangopadhyay

The isotropy and homogeneity of our Universe are the cardinal principles of modern cosmology built on the definition of metric through the prescription by Friedmann-Lema$\hat{i}$tre-Robertson-Walker (FLRW). From the aspects of geometry, the presence of anisotropy, inhomogeneity, or both are allowed in the metrics defined as the Bianchi type I and V metrics.

Ainesh Sewak, Vanda Inacio, Joanne Wuu, Michael Benatar

Identifying reliable biomarkers for predicting clinical events in longitudinal studies is important for accurate disease prognosis and for guiding development of new treatments. However, prognostic studies are often observational, making it difficult to account for patient heterogeneity. In amyotrophic lateral sclerosis (ALS), factors such as age, site of on

Hong-Hao Ma, Zheng-Kui Tao, Juan-Juan Niu

The indirect production mechanisms of fully charmed tetraquark are analyzed using the NRQCD factorization and Suzuki approach, respectively. The process first produces a heavy charm quark through Higgs, $W^+$, or $Z^0$ decay, and then the resulting charm quark evolves into an $S$-wave fully charmed tetraquark state with quantum number $J^{PC}$, including $0^

Donato Bini, Giampiero Esposito

After studying properties of the Nariai solution, including its geodesics, in spherical and de Sitter coordinates, two kinds of accelerated motion are investigated in detail: either observers at rest with respect to the coordinates, or observers in radial motion. Next, massless scalar perturbations of Nariai spacetime in absence of sources are worked out, an

Shawxing Kwok

Given a weighted bipartite graph $G = (L, R, E, w)$, the maximum weight matching (MWM) problem seeks to find a matching $M \subseteq E$ that maximizes the total weight $\sum_{e \in M} w(e)$. This paper presents a novel algorithm with a time complexity of $O(\min(X^3 + E, XE + X^2\log X))$, where $X = \min(|L|, |R|)$. Unlike many existing algorithms, our appr

Z. Z. Alisultanov, E. G. Idrisov, A. V. Kavokin

We explore the nontrivial thermoelectric properties of two-dimensional topological systems. For the Chern insulator, we show that the Seebeck coefficient is fully determined by the Kelvin formula, while the Nernst coefficient vanishes. For a two-dimensional electron gas with Rashba spin-orbit interactions we reveal how the Berry curvature affects the thermoe

Roman Pol, Piotr Zakrzewski, Lyubomyr Zdomskyy

We prove that it is consistent with ZFC that for every non-decreasing function $f:[0,1]\to [0,1]$, each subset of $[0,1]$ of cardinality $\mathfrak c$ contains a set of cardinality $\mathfrak c$ on which $f$ is uniformly continuous. We show that this statement follows from the assumptions that $\mathfrak d^* < \mathfrak c$ and $\mathfrak c$ is regular, where

Qiyu Zeng, Xiaoxiang Yu, Bo Chen, Shen Zhang

Extreme electron-ion non-equilibrium states, generated by ultrafast laser excitation, lead to melting processes that are fundamentally different from those under conventional thermal equilibrium and remain not fully understood. Through neural network-enhanced multiscale simulations of tungsten and gold nanofilms, we identify electronic pressure relaxation as

Amadou S. Sangare, Nicolas Dunou, Jhony H. Giraldo, Fragkiskos D. Malliaros

Self-supervised learning has become a key method for training deep learning models when labeled data is scarce or unavailable. While graph machine learning holds great promise across various domains, the design of effective pretext tasks for self-supervised graph representation learning remains challenging. Contrastive learning, a popular approach in graph s

A. Ballesteros, I. Gutiérrez-Sagredo, V. Mariscal, J. J. Relancio

The Kittel--Shore (KS) Hamiltonian describes $N$ spins with long-range interactions that are identically coupled; therefore, this (mean-field) model is also known as the Heisenberg XXX model on the complete graph. In this paper, the underlying $U(\mathfrak{su}(2))$ coalgebra symmetry of the KS model is demonstrated for arbitrary spins, and the quantum deform

Chinmay Patwardhan, Jonas Kusch

Thermal radiative transfer models physical phenomena ranging from supernovas in astrophysics to radiation from a hohlraum striking a fusion target in plasma physics. Transport and absorption of particles in radiative transfer at different rates lead to a complex interaction between the material and particles that involves highly varying time scales. Resolvin

Yuandou Wang, Zhiming Zhao

Federated Learning (FL) has recently emerged as a collaborative learning paradigm that can train a global model among distributed participants without raw data exchange to satisfy varying requirements. However, there remain several challenges in managing FL in a decentralized environment, where potential candidates exhibit varying motivation levels and relia