December 2024 arXiv papers — page 143

Ren Ejima, Philipp Gubler, Chihiro Sasaki, Kenta Shigaki

The degeneracy of chiral partners is an ideal signal for measuring the restoration of the spontaneously broken chiral symmetry in QCD. In this work, we investigate the observability of the $\phi$ - $f_1(1420)$ degeneracy in the J-PARC E16 experiment, which measures di-electrons emitted from 30 GeV pA collisions. We for this purpose make use of an effective L

Damian Clancy

We consider stochastic population processes that are almost surely absorbed at the origin within finite time. Our interest is in the quasistationary distribution, $\boldsymbol{u}$, and the expected time, $\tau$, from quasistationarity to extinction, both of which we study via WKB approximation. This approach involves solving a Hamilton-Jacobi partial differe

Ananga Mohan Datta, Kurt Busch, Armando Perez-Leija

Photon-subtracted two-mode squeezed vacuum states, a significant quantum resource, exhibit intricate correlations and unique quantum properties. In this work, we propose a theoretical yet experimentally feasible model to engineer these states using a waveguide trimer. Our study uncovers distinct characteristics of the photon-subtracted state depending on whe

Nils Berglund

Lecture notes (in French) of a master 2 level course in applied mathematics. Contents: Part I. Markov chains on a countable space. 1. Examples 2. Summary of basic properties. 3. Spectral theory and speed of convergence. 4. Lyapunov functions and speed of convergence. 5. MCMC algorithms. Part II. Markov chains on continuous space. 6. Definitions and examples.

Wenlin Qiu, Xiangcheng Zheng, Kassem Mustapha

This work considers the Galerkin approximation and analysis for a hyperbolic integrodifferential equation, where the non-positive variable-sign kernel and nonlinear-nonlocal damping with both the weak and viscous damping effects are involved. We derive the long-time stability of the solution and its finite-time uniqueness. For the semi-discrete-in-space Gale

Junyong Chen, Ling-I Wu, Minyu Chen, Xiaoying Qian

Automated Rule Checking (ARC) plays a crucial role in advancing the construction industry by addressing the laborious, inconsistent, and error-prone nature of traditional model review conducted by industry professionals. Manual assessment against intricate sets of rules often leads to significant project delays and expenses. In response to these challenges,

Dongfang Li, Zetian Sun, Xinshuo Hu, Baotian Hu

Large Language Models (LLMs) need to adapt to the continuous changes in data, tasks, and user preferences. Due to their massive size and the high costs associated with training, LLMs are not suitable for frequent retraining. However, updates are necessary to keep them in sync with rapidly evolving human knowledge. To address these challenges, this paper prop

Muhayy Ud Din, Ahsan B. Bakht, Waseem Akram, Yihao Dong

Vision-based target tracking is crucial for unmanned surface vehicles (USVs) to perform tasks such as inspection, monitoring, and surveillance. However, real-time tracking in complex maritime environments is challenging due to dynamic camera movement, low visibility, and scale variation. Typically, object detection methods combined with filtering techniques

Ahmed Luqman, Khuzemah Qazi, Murray Patterson, Malik Jahan Khan

Despite the success of CNN models on a variety of Image classification and segmentation tasks, their extensive computational and storage demands pose considerable challenges for real-world deployment on resource-constrained devices. Quantization is one technique that aims to alleviate these large storage requirements and speed up the inference process by red

Malin Sjodahl

A complication in the treatment of any strongly charged particle is the SU(3) color structure. For the standard model quarks antiquarks and gluons there are various well-known strategies for dealing with the color structure, including orthogonal multiplet bases. For exotic representations, beyond triplets, antitriplets and octets, non-orthogonal bases have b

Daniel A. Kiefer, Georg Watzl, Katharina Burgholzer, Martin Ryzy

Electroelastic waves in piezoelectric media are widely used in sensing and filtering applications. Despite extensive research, computing the guided wave dispersion remains challenging. This paper presents semi-analytical approaches based on spectral methods to efficiently and reliably compute dispersion curves. We systematically assess the impact of electric

Willemijn Klaassen, Bram van Dijk, Marco Spruit

Artificially intelligent systems optimized for speech conversation are appearing at a fast pace. Such models are interesting from a healthcare perspective, as these voice-controlled assistants may support the elderly and enable remote health monitoring. The bottleneck for efficacy, however, is how well these devices work in practice and how the elderly exper

Churan Wang, Fei Gao, Lijun Yan, Siwen Wang

Magnetic resonance imaging (MRI) is indispensable for diagnosing and planning treatment in various medical conditions due to its ability to produce multi-series images that reveal different tissue characteristics. However, integrating these diverse series to form a coherent analysis presents significant challenges, such as differing spatial resolutions and c

Alan Sun, Ethan Sun, Warren Shepard

Zero-shot capabilities of large language models make them powerful tools for solving a range of tasks without explicit training. It remains unclear, however, how these models achieve such performance, or why they can zero-shot some tasks but not others. In this paper, we shed some light on this phenomenon by defining and investigating algorithmic stability i

Ellington Kirby, Mickael Chen, Renaud Marlet, Nermin Samet

The generation of LiDAR scans is a growing topic with diverse applications to autonomous driving. However, scan generation remains challenging, especially when compared to the rapid advancement of image and 3D object generation. We consider the task of LiDAR object generation, requiring models to produce 3D objects as viewed by a LiDAR scan. It focuses LiDAR

Florin Condrea, Saikiran Rapaka, Marius Leordeanu

Pulmonary Embolism (PE) are a leading cause of cardiovascular death. Computed tomographic pulmonary angiography (CTPA) is the gold standard for PE diagnosis, with growing interest in AI-based diagnostic assistance. However, these algorithms are limited by scarce fine-grained annotations of thromboembolic burden. We address this challenge with iExplain, a wea

Gesualdo Delfino

The Nishimori point of the random bond Ising model is a prototype of renormalization group fixed points with strong disorder. We show that the exact correlation length and crossover critical exponents at this point can be identified in two and three spatial dimensions starting from properties of the Nishimori line. These are the first exact exponents for fru

Seongmin Park, Mincheol Yoon, Minjin Choi, Jongwuk Lee

In sequential recommendation (SR), neural models have been actively explored due to their remarkable performance, but they suffer from inefficiency inherent to their complexity. On the other hand, linear SR models exhibit high efficiency and achieve competitive or superior accuracy compared to neural models. However, they solely deal with the sequential orde

Farzaneh Farrokhzad, Nex C. X. Stuhlmüller, Piotr Kuświk, Maciej Urbaniak

We measure the dynamical behavior of colloidal singlets and dumbbells on an inclined magnetic moir\'e pattern, subject to a precessing external homogeneous magnetic field. At low external field strength single colloidal particles and dumbbells move everywhere on the pattern: At stronger external field strengths colloidal singlets and dumbbells are localized

D. Delicato, D. Angelone, L. Bandiera, M. Calvo

Cryogenic phonon detectors are adopted in experiments searching for dark matter interactions or coherent elastic neutrino-nucleus scattering, thanks to the low energy threshold they can achieve. The phonon-mediated sensing of particle interactions in passive silicon absorbers has been demonstrated with Kinetic Inductance Detectors (KIDs). Targets with neutro

Jacob Hume, Laura Balzano

Discovering and tracking communities in time-varying networks is an important task in network science, motivated by applications in fields ranging from neuroscience to sociology. In this work, we characterize the celebrated family of spectral methods for static clustering in terms of the low-rank approximation of high-dimensional node embeddings. From this p

Naoki Negishi, Daisuke Yokogawa

We formulate frequency fluctuations of intramolecular vibrations of a solute by exploring the fluctuation of the electrostatic potential by solvents. We present a numerical methodology for estimating the frequency fluctuations; the methodology is based on the reference interaction site model self-consistent field with constrained spatial electron density dis

Jinlu Zhang, Jiji Tang, Rongsheng Zhang, Tangjie Lv

Story visualization has gained increasing attention in artificial intelligence. However, existing methods still struggle with maintaining a balance between character identity preservation and text-semantics alignment, largely due to a lack of detailed semantic modeling of the story scene. To tackle this challenge, we propose a novel knowledge graph, namely C

Thomas Lavigne, Stéphane Urcun, Emmanuelle Jacquet, Jérôme Chambert

This paper proposes a proof of concept application of a biphasic constitutive model to identify the mechanical properties of in vivo human skin under extension. Although poromechanics theory has been extensively used to model other soft biological tissues, only a few studies have been published for skin, and most have been limited to ex vivo or in silico con

M. J. Rickard, R. Hainich, D. Pauli, W. -R. Hamann

NGC 346 is a young cluster with numerous hot OB stars. It is part of the Small Magellanic Cloud (SMC), and has an average metallicity that is one-seventh of the Milky Way's. A detailed study of its stellar content provides a unique opportunity to understand the stellar and wind properties of massive stars in low-metallicity environments, and enables us to im

Yu Yan, Sheng Sun, Junqi Tong, Min Liu

Metaphor serves as an implicit approach to convey information, while enabling the generalized comprehension of complex subjects. However, metaphor can potentially be exploited to bypass the safety alignment mechanisms of Large Language Models (LLMs), leading to the theft of harmful knowledge. In our study, we introduce a novel attack framework that exploits

Tomer Goldfriend, Israel Reichental, Amir Naveh, Lior Gazit

We present a scalable, robust approach to creating quantum programs of arbitrary size and complexity. The approach is based on the true abstraction of the problem. The quantum program is expressed in terms of a high-level model together with constraints and objectives on the final program. Advanced synthesis algorithms transform the model into a low-level qu

Wenhang Ge, Jiantao Lin, Guibao Shen, Jiawei Feng

We propose PRM, a novel photometric stereo based large reconstruction model to reconstruct high-quality meshes with fine-grained local details. Unlike previous large reconstruction models that prepare images under fixed and simple lighting as both input and supervision, PRM renders photometric stereo images by varying materials and lighting for the purposes,

Svantje Voit, Gerald Enzner

Problems of linear system identification have closed-form solutions, e.g., using least-squares or maximum-likelihood methods on input-output data. However, already the seemingly simplest problems of nonlinear system identification present more difficulties related to the optimisation of the furrowed error surface. Those cases include the Hammerstein plant wi

Rongqing Li, Changsheng Li, Yuhang Li, Hanjie Li

Trajectory prediction of agents is crucial for the safety of autonomous vehicles, whereas previous approaches usually rely on sufficiently long-observed trajectory to predict the future trajectory of the agents. However, in real-world scenarios, it is not realistic to collect adequate observed locations for moving agents, leading to the collapse of most pred

Fangchao Yang, Wei Hong, Yujie Zhao

Precision space inertial sensors are imperative for Earth geodesy missions, gravitational wave observations, and fundamental physics experiments in space. In these missions, free-falling test masses(TMs) are susceptible to parasitic electrostatic forces and torques, with significant contributions from the interaction between stray electric fields and TM char

Haruya Kokubo, Kenichi Kasamatsu, Hiromitsu Takeuchi

We study theoretically the critical velocity $U_c$ for quantum vortex generation by a thin plate-shaped obstacle moving through a uniform Bose-Einstein condensate. Our results based on the Gross-Pitaevskii theory reveal that the critical velocity monotonically decreases with increasing plate size $L$. In the limit of large $L$, the critical velocity is asymp

Jian Liao, Yu Feng, Yujin Zheng, Jun Zhao

The subtlety of emotional expressions makes implicit emotion analysis (IEA) particularly sensitive to user-specific characteristics. Current studies personalize emotion analysis by focusing on the author but neglect the impact of the intended reader on implicit emotional feedback. In this paper, we introduce Personalized IEA (PIEA) and present the RAPPIE mod

Keng-Wei Chang, Yih-Liang Shen, Tai-Shi Chi

The head-related transfer function (HRTF) characterizes the frequency response of the sound traveling path between a specific location and the ear. When it comes to estimating HRTFs by neural network models, angle-specific models greatly outperform global models but demand high computational resources. To balance the computational resource and performance, w

Bowen Zhang, Fengping Luo, Yuxin Liu, Jin Wang

Experimental results show significant difference between neutrons and ions irradiation of alloys, while the underlying reasons remain unclear. Herein, we performed object kinetic Monte Carlo (OKMC) simulations on void evolution in Fe-Cr alloys under neutron and ion irradiations, focusing on the effects of dose rate, irradiation particle type and temperature.

D. A. Pimanov, A. L. Pankratov, A. V. Gordeeva, A. V. Chiginev

Cold electron bolometers have shown their suitability for use in modern fundamental physical experiments. Fabrication and measurements of the samples with cold-electron bolometers integrated into coplanar antennas are performed in this study. The bolometric layer was made using combined aluminum-hafnium technology to improve quality of aluminum oxide layer a

T. Oshio, R. Nishimoto, T. Higuchi, K. Hayasaka

The quantum charge-coupled device (QCCD) is one of the notable architectures to achieve large-scale trapped-ion quantum computers. To realize QCCD architecture, ions must be transported quickly while minimizing motional excitation. High-voltage sources are necessary to achieve such high-quality ion transport through a high secular frequency. In this study, w

A. Kruv, M. J. van Setten, A. Chasin, D. Matsubayashi

Integrating In-Ga-Zn-oxide (IGZO) channel transistors in silicon-based ecosystems requires the resilience of the channel material to hydrogen treatment. Standard IGZO, containing 40% In (metal ratio) suffers from degradation under forming gas anneal (FGA) and hydrogen (H) driven positive bias temperature instability (PBTI). We demonstrate scaled top-gated AL

Saroj Prasad Chhatoi, Didier Henrion, Swann Marx, Nicolas Seguin

We prove that there is no relaxation gap between a quasi-dissipative nonlinear evolution equation in a Hilbert space and its linear Liouville equation reformulation on probability measures. In other words, strong and generalized solutions of such equations are unique in the class of measure-valued solutions. As a major consequence, non-convex numerical optim

Xuerui Qiu, Man Yao, Jieyuan Zhang, Yuhong Chou

Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-temporal features. Point clouds are sparse 3D spatial data, which suggests that SNNs should be well-suited for processing them. However, when applying SNNs to point clouds, they often exhibit limited performance and fewer application scenarios. We attribute this to inappropri

George C. Alexandropoulos, Bo Kum Jung, Panagiotis Gavriilidis, Sérgio Matos

Reconfigurable Intelligent Surfaces (RISs) are expected to play a pivotal role in future indoor ultra high data rate wireless communications as well as highly accurate three-dimensional localization and sensing, mainly due to their capability to provide flexible, cost- and power-efficient coverage extension, even under blockage conditions. However, when cons

Christophe Cornut

We give a simple description of the category of sheaves on the small etale site of an irreducible scheme whose local rings are geometrically unibranch and henselian, which affords a characterization of representable sheaves.

David Philipp Klüner, Marius Molz, Alexandru Kampmann, Stefan Kowalewski

This paper offers a tutorial on current middlewares in automated vehicles. Our aim is to provide the reader with an overview of current middlewares and to identify open challenges in this field. We start by explaining the fundamentals of software architecture in distributed systems and the distinguishing requirements of Automated Vehicles. We then distinguis

Raphaël Côte, Clémentine Courtès, Guillaume Ferriere, Ludovic Godard-Cadillac

In this article, we investigate a simple model of notched ferromagnetic nanowires using tools from calculus of variations and critical point theory. Specifically, we focus on the case of a single unimodal notch and establish the existence and uniqueness of the critical point of the energy. This is achieved through a lifting argument, which reduces the proble

Jiwei Zhang, Yuxiang Zhang, Tao Jiang, Huiwen Gong

Reconfigurable Intelligent Surface (RIS) is considered as a promising technology for 6G due to its ability to actively modify the electromagnetic propagation environment. Accurate channel modeling is essential for the design and evaluation of RIS assisted communication systems. Most current research models the RIS channel as a cascade of Tx-RIS and RIS-Rx su

Andrea Caria

This perspective article aims at providing an outline of the state of the art and future developments towards the integration of cutting-edge predictive language models with BCI. A synthetic overview of early and more recent linguistic models, from natural language processing (NLP) models to recent LLM, that to a varying extent improved predictive writing sy

Bibhas Adhikari, Namita Behera, Dilli Ram Chhetri, Raj Bhawan Yadav

An arithmetical structure on a finite and connected graph G is a pair (d, r) of positive integer vectors such that r is primitive (the gcd of its entries is 1) and (diag(d) - A)r = 0, where A is the adjacency matrix of G. In this article, we investigate arithmetical structures on the wheel graphs.

Miriam Mendoza Delgado, Lucas Tsunaki, Shaul Michaelson, Mohan K. Kuntumalla

Nitrogen-vacancy (NV) centers in diamonds have been an epicenter of research for diverse applications in quantum technologies. It is therefore imperative that their fabrication techniques are well understood and characterized for the technological scalability of these applications. A comparative study of the optical and spin properties of NVs created by ion

Luca Bianchi, Carlo Marconi, Jan Sperling, Davide Bacco

Bell measurements, entailing the projection onto one of the Bell states, play a key role in quantum information and communication, where the outcome of a variety of protocols crucially depends on the success probability of such measurements. Although in the case of qubit systems, Bell measurements can be implemented using only linear optical components, the

Jad Beyhum, Martin Mugnier

Approximating time-varying unobserved heterogeneity by discrete types has become increasingly popular in economics. Yet, provably valid post-clustering inference for target parameters in models that do not impose an exact group structure is still lacking. This paper fills this gap in the leading case of a linear panel data model with nonseparable two-way uno

Davide Sangiorgi

Up-to techniques' represent enhancements of the coinduction proof method and are widely used on coinductive behavioural relations such as bisimilarity. Abstract formulations of these coinductive techniques exist, using fixed-points or category theory. A proposal has been recently put forward for transporting the enhancements onto the concrete realms of induc

Eda Alici

The investigation of flavour-changing neutral current transitions(FCNC) involving the top quark are only possible with new theoretical frameworks that extend the Standard Model(SM), given that these transitions are almost entirely suppressed within the SM. In this regard, examining these transitions with extended theories beyond the SM may provide significan

Ziqi Yang, Lihua Xie

This letter presents a nonlinear disturbance observer-parameterized control barrier function (DOp-CBF) designed for a robust safety control system under external disturbances. This framework emphasizes that the safety bounds are relevant to the disturbances, acknowledging the critical impact of disturbances on system safety. This work incorporates a disturba

Arman Abgaryan, Utkarsh Sharma

IntraLayer presents an innovative framework that enables comprehensive interconnectivity in digital finance. The proposed framework comprises a core underlying infrastructure and an overarching strategy to create a pioneering "platform of platforms", serving as an algorithmic fiduciary. By design, this infrastructure optimises transactional efficiency for a

Tim Bürchner, Simon Schmid, Lukas Bergbreiter, Ernst Rank

Phased array ultrasound is a widely used technique in non-destructive testing. Using piezoelectric elements as both sources and receivers provides a significant gain in information and enables more accurate defect detection. When all source-receiver combinations are used, the process is called full matrix capture. The total focusing method~(TFM), which explo

Mikhail Yu. Emelin, Mikhail Yu. Ryabikin

The below-threshold harmonic generation in the multiphoton ionization regime for a helium atom driven by the elliptically polarized laser field is studied numerically within the framework of two-dimensional (2D) and three-dimensional (3D) models. It is shown that, regardless of the specific type of atomic potential and the model dimensionality, there is a se

Laurence Cliffe

This article presents and discusses the results from visitors' interactions with two audio augmented reality experiences containing audio augmented objects; physical, real-world objects to which virtual audio sources have been attached. It then proceeds to discusses the commonly identified themes arising from the observation of visitors' behaviour within the

Matti Krüger, Yutaka Oshima, Yu Fang

The visible orientation of human eyes creates some transparency about people's spatial attention and other mental states. This leads to a dual role of the eyes as a means of sensing and communication. Accordingly, artificial eye models are being explored as communication media in human-machine interaction scenarios. One challenge in the use of eye models for

Thomas Barois, A. Boucherie, L. Tadrist, H. Kellay

We present a locomotion mechanism that uses the stick-slip transition of a soft passive structure with an internal mechanical resonance. The structure is harmonically driven by a global vertical shaking and, because of its resonance dephasing and the threshold response of stick-slip transition, it can either move forward or backward. We establish a relation

Xuping Wang, Xuan Zhao, Hong-lin Liao

The main theoretical obstacle to establish the original energy dissipation laws of Runge-Kutta methods for phase-field equations is to verify the maximum norm boundedness of the stage solutions without assuming global Lipschitz continuity of the nonlinear bulk. We present a unified theoretical framework for the energy stability of three effective classes of

Gaëtan Regaud, Martin Zimmermann

HyperQPTL and HyperQPTL$^+$ are expressive specification languages for hyperproperties, properties that relate multiple executions of a system. Tight complexity bounds are known for HyperQPTL finite-state satisfiability and model-checking. Here, we settle the complexity of satisfiability for HyperQPTL as well as satisfiability, finite-state satisfiability, a

Maria N. Koryazhkina, Albina V. Lebedeva, Darina D. Pakhomova, Ivan N. Antonov

The influence of the epileptiform neuronal activity on the response of a CMOS-integrated ZrO2-based memristive crossbar and its conductivity was studied. Epileptiform neuronal activity was obtained in vitro in the hippocampus slices of laboratory mice using 4-aminopyridine experimental model. Synaptic plasticity of the memristive crossbar induced by epilepti

Yanyi Nie, Tao Lin, Yanbing Liu, Wei Wang

Voluntary vaccination is essential to protect oneself from infection and suppress the spread of infectious diseases. Voluntary vaccination behavior is influenced by factors such as age and interaction patterns. Differences in health consciousness and risk perception based on age result in heterogeneity in vaccination behavior among different age groups. High

Lorenzo Cima, Alessio Miaschi, Amaury Trujillo, Marco Avvenuti

AI-generated counterspeech offers a promising and scalable strategy to curb online toxicity through direct replies that promote civil discourse. However, current counterspeech is one-size-fits-all, lacking adaptation to the moderation context and the users involved. We propose and evaluate multiple strategies for generating tailored counterspeech that is ada

Swati Choudhary, Ujjwal Sen, Saronath Halder

We investigate the inseparability of states generated by superposition of a multipartite pure entangled state with a product state. In particular, we identify specific multipartite entangled states that will always produce inseparability after superposition with an arbitrary completely product state. Thus, these entangled states are unconditionally superposi

Huiwen Gong, Jianhua Zhang, Yuxiang Zhang, Guangyi Liu

As 6G research advances, the growing demand leads to the emergence of novel technologies such as integrated sensing and communication (ISAC), new antenna arrays like extremely large MIMO (XL-MIMO) and reconfigurable intelligent surfaces (RIS), along with multi-frequency bands (new mid-band, above 100 GHz). Standardized unified channel models are crucial for

Wentao Qu, Lingchen Kong, Linglong Kong, Bei Jiang

With the rapid growth of data volume and the increasing demand for real-time analysis, online subspace clustering has emerged as an effective tool for processing dynamic data streams. However, existing online subspace clustering methods often struggle to capture the complex and evolving distribution of such data due to their reliance on rigid dictionary lear

Pedro H. V. Valois, Lincon S. Souza, Erica K. Shimomoto, Kazuhiro Fukui

Interpretability is a key challenge in fostering trust for Large Language Models (LLMs), which stems from the complexity of extracting reasoning from model's parameters. We present the Frame Representation Hypothesis, a theoretically robust framework grounded in the Linear Representation Hypothesis (LRH) to interpret and control LLMs by modeling multi-token

Ondřej Procházka, Filip Novák, Tomáš Báča, Parakh M. Gupta

This paper proposes a novel trajectory generation method based on Model Predictive Control (MPC) for agile landing of an Unmanned Aerial Vehicle (UAV) onto an Unmanned Surface Vehicle (USV)'s deck in harsh conditions. The trajectory generation exploits the state predictions of the USV to create periodically updated trajectories for a multirotor UAV to precis

Nikolaos Manginas, George Paliouras, Luc De Raedt

Neurosymbolic (NeSy) AI has emerged as a promising direction to integrate neural and symbolic reasoning. Unfortunately, little effort has been given to developing NeSy systems tailored to sequential/temporal problems. We identify symbolic automata (which combine the power of automata for temporal reasoning with that of propositional logic for static reasonin

Victor Buchstaber, Ilia Gaiur, Vladimir Rubtsov

The theory of a two-valued algebraic group structure on a complex plane and complex projective line is developed. In this theory, depending on the choice of the neutral element, the local multiplication law is given by the Buchstaber polynomial or the generalized Kontsevich polynomial. One of the most exciting results of our studies is a simple construction

A. A. Saharian

Cosmic strings are the most popular topological defects arising from the spontaneous breaking of fundamental symmetries in the early Universe. They are the source of a number of interesting effects in cosmology and astrophysics. An interesting effect is the polarization of the vacuum state for quantum fields induced by the non-trivial topology of the spaceti

De-Zhang Li, Xin Wang, Xiao-Bao Yang

Low-temperature expansion of Ising model has long been a topic of significant interest in condensed matter and statistical physics. In this paper we present new results of the coefficients in the low-temperature series of the Ising partition function on the square lattice, in the cases of a zero field and of an imaginary field $i(\pi/2)k_BT$. The coefficient

Lennart P. L. Landsmeer, Mario Negrello, Said Hamdioui, Christos Strydis

Computational neuroscience relies on large-scale dynamical-systems models of neurons, with a vast amount of offline, pre-simulation, tuned parameters, with models often tied to their brain simulators. These fixed parameters lead to stiff models, that show unnatural behaviour when introduced to new environments, or when combined into larger networks. In contr

Yael Itzhakev, Amit Giloni, Yuval Elovici, Asaf Shabtai

Machine learning models trained on tabular data are vulnerable to adversarial attacks, even in realistic scenarios where attackers only have access to the model's outputs. Since tabular data contains complex interdependencies among features, it presents a unique challenge for adversarial samples which must maintain coherence and respect these interdependenci

Sandra Müller, Grigor Sargsyan

G\"odel proved in the 1930s in his famous Incompleteness Theorems that not all statements in mathematics can be proven or disproven from the accepted ZFC axioms. A few years later he showed the celebrated result that Cantor's Continuum Hypothesis is consistent. Afterwards, G\"odel raised the question whether, despite the fact that there is no reasonable axio

Chang-Jin Li, Jiyuan Zhang, Yun Tang, Jian Li

Personality assessment through situational judgment tests (SJTs) offers unique advantages over traditional Likert-type self-report scales, yet their development remains labor-intensive, time-consuming, and heavily dependent on subject matter experts. Recent advances in large language models (LLMs) have shown promise for automatic item generation (AIG). Build

Daokun Zhang, Russell Tsuchida, Dino Sejdinovic

Label distribution learning (LDL) provides a framework wherein a distribution over categories rather than a single category is predicted, with the aim of addressing ambiguity in labeled data. Existing research on LDL mainly focuses on the task of point estimation, i.e., finding an optimal distribution in the probability simplex conditioned on the given sampl

Sanjay Chakraborty

Transitioning from Education 1.0 to Education 5.0, the integration of generative artificial intelligence (GenAI) revolutionizes the learning environment by fostering enhanced human-machine collaboration, enabling personalized, adaptive and experiential learning, and preparing students with the skills and adaptability needed for the future workforce. Our unde

Aiman Al-Eryani, Sarah Heinzelmann, Kilian Fraboulet, Friedrich Krien

We generalize the recently introduced single-boson exchange formalism to nonlocal interactions. In the functional renormalization group application to the extended Hubbard model in two dimensions, we show that the flow of the rest function can be neglected up to moderate interaction strengths. We explore the physics arising from the interplay between onsite

Peizhen Bai, Filip Miljković, Xianyuan Liu, Leonardo De Maria

Inverse protein folding generates valid amino acid sequences that can fold into a desired protein structure, with recent deep-learning advances showing strong potential and competitive performance. However, challenges remain, such as predicting elements with high structural uncertainty, including disordered regions. To tackle such low-confidence residue pred

Kartik Singhal, Gautam Shroff

The Abstraction and Reasoning Corpus (ARC) poses a significant challenge to artificial intelligence, demanding broad generalization and few-shot learning capabilities that remain elusive for current deep learning methods, including large language models (LLMs). While LLMs excel in program synthesis, their direct application to ARC yields limited success. To

Hong-lin Liao, Tao Tang, Xuping Wang, Tao Zhou

One of main obstacles in verifying the energy dissipation laws of implicit-explicit Runge-Kutta (IERK) methods for phase field equations is to establish the uniform boundedness of stage solutions without the global Lipschitz continuity assumption of nonlinear bulk. With the help of discrete orthogonal convolution kernels, an updated time-space splitting tech

Shanlin Sun, Gabriel De Araujo, Jiaqi Xu, Shenghan Zhou

3D human motion generation has seen substantial advancement in recent years. While state-of-the-art approaches have improved performance significantly, they still struggle with complex and detailed motions unseen in training data, largely due to the scarcity of motion datasets and the prohibitive cost of generating new training examples. To address these cha

Neeraj K. Dhanwani, Pankaj Kapari, Kashyap Rajeevsarathy, Ravi Tomar

Let $S_g$ be the closed oriented surface of genus $g \geq 0$, and let $\mathrm{Mod}(S_g)$ be the mapping class group of $S_g$. For $g\geq 2$, we develop an algorithm to obtain a finite generating set for the liftable mapping class group $\mathrm{LMod}_p(S_g)$ of a regular abelian cover $p$ of $S_g$. A key ingredient of our method is a result that provides a

Marco Benini, Victor Carmona, Alastair Grant-Stuart, Alexander Schenkel

This paper revisits the equivalence problem between algebraic quantum field theories and prefactorization algebras defined over globally hyperbolic Lorentzian manifolds. We develop a radically new approach whose main innovative features are 1.) a structural implementation of the additivity property used in earlier approaches and 2.) a reduction of the global

Zekai Li, Wei Bian

In this paper, we consider the Anderson acceleration method for solving the contractive fixed point problem, which is nonsmooth in general. We define a class of smoothing functions for the original nonsmooth fixed point mapping, which can be easily formulated for many cases (see section3). Then, taking advantage of the Anderson acceleration method, we propos

Rui Zhou, Akinori Ito, Takashi Nose

Speech-to-Speech Translation (S2ST) refers to the conversion of speech in one language into semantically equivalent speech in another language, facilitating communication between speakers of different languages. Speech-to-Discrete Unit Translation (S2UT), a mainstream approach for end-to-end S2ST, addresses challenges such as error propagation across modules

Zsolt Páles, Paweł Pasteczka

The purpose of this paper is to extend the definition of quasiarithmetic means by taking a strictly monotone generating function instead of a strictly monotone and continuous one. We establish the properties of such means and compare them to the analogous properties of standard quasiarithmetic means. The comparability and equality problems of generalized qua

Kourosh Nozari, Sara Saghafi, Mohammad Hassani

In astrophysics, accretion is the process by which a massive object acquires matter. The infall leads to the extraction of gravitational energy. Accretion onto dark compact objects such as black holes, neutron stars, and white dwarfs is a crucial process in astrophysics as it turns gravitational energy into radiation. The accretion process is an effective te

Nikita P. Dobronravov

We construct a probability measure $\mu$ supported on a set of zero $2d/p$-Hausdorff measure such that $\hat{\mu}\in L_{p}(\mathbb{R}^d)$.

Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos, Christos Diou

EXplainable Artificial Intelligence (XAI) approaches are widely applied for identifying fairness issues in Artificial Intelligence (AI) systems. However, in the context of facial analysis, existing XAI approaches, such as pixel attribution methods, offer explanations for individual images, posing challenges in assessing the overall behavior of a model, which

Jonathan García, Philipp Petersen

We prove that a classifier with a Barron-regular decision boundary can be approximated with a rate of high polynomial degree by ReLU neural networks with three hidden layers when a margin condition is assumed. In particular, for strong margin conditions, high-dimensional discontinuous classifiers can be approximated with a rate that is typically only achieva

Adrian Hjältén, Ibrahim Sadiek, Aleksandra Foltynowicz

Nitrous oxide is a long-lived greenhouse gas. Its isotopic composition provides valuable insights into sources and sinks, and about the mechanism of formation. A major challenge in the spectroscopic analysis of the isotopocule compositions is the availability of accurate spectroscopic parameters, particularly for the minor $^{15}$N isotopocules. In this work

Wojciech Szumiński, Adel A. Elmandouh

The objective of this work is to examine the integrability of Hamiltonian systems in $2D$ spaces with variable curvature of certain types. Based on the differential Galois theory, we announce the necessary conditions of the integrability. They are given in terms of arithmetic restrictions on values of the parameters describing the system. We apply the obtain

Anja Alfano, Nick Evans

We use a simple holographic model to discuss approaching the edge of the conformal window in strongly coupled gauge theories to draw lessons for lattice studies. Walking gauge theories have a gap between the scale where they enter the strong coupling regime and the scale of chiral symmetry breaking. We highlight that there can also be a gap between the scale

Jeffrey Hatley, Anwesh Ray

We study the distribution of ranks of elliptic curves in quadratic twist families using Iwasawa-theoretic methods, contributing to the understanding of Goldfeld's conjecture. Given an elliptic curve $ E/\mathbb{Q} $ with good ordinary reduction at $ 2 $ and $ \lambda_2(E/\mathbb{Q}) = 0 $, we use Matsuno's Kida-type formula to construct quadratic twists $ E^

Ceren Gürbüz Can, Sebaheddin Şevgin

This study examines the effect of a partially protective vaccine on COVID-19 infection with the original and mutant virus with the help of a deterministic mathematical model developed. The model we developed consists of five compartments and thirteen parameters. The model consists of S (susceptible), V (vaccinated), I_1 (infected with original virus), I_2 (i

Mickael Binois, Arindam Fadikar, Abby Stevens

This chapter presents specific aspects of Gaussian process modeling in the presence of complex noise. Starting from the standard homoscedastic model, various generalizations from the literature are presented: input varying noise variance, non-Gaussian noise, or quantile modeling. These approaches are compared in terms of goal, data availability and inference

N. A. Bogoslovskiy, P. V. Petrov, N. S. Averkiev

We present a theoretical study of the exchange interaction in a system of spatially disordered magnetic moments. A typical example of such a system is an impurity semiconductor, whose magnetic properties are associated with the exchange interaction of the impurity atoms. In this study, we consider the case of antiferromagnetic exchange interaction, which we