February 2024 arXiv papers — page 7

Weijun Xu, Wenhao Zhao, Shuhan Zhou

We revisit the interface fluctuation problem for the $1$D Allen-Cahn equation perturbed by a small space-time white noise. We show that if the initial data is a standing wave solution to the deterministic equation, then under proper long time scale, the solution is still close to the family of traveling wave solutions. Furthermore, the motion of the interfac

M. J. Rutala, C. M. Jackman, M. J. Owens, C. Tao

How the solar wind influences the magnetospheres of the outer planets is a fundamentally important question, but is difficult to answer in the absence of consistent, simultaneous monitoring of the upstream solar wind and the large-scale dynamics internal to the magnetosphere. To compensate for the relative lack of in-situ data, propagation models are often u

Jana Camprová Turjanicová, Eduard Rohan

This paper presents a new homogenized model of two-component electrolyte transport through a weakly piezoelectric porous medium. The model relevant to the microscopic scale describes quasi-stationary states of the medium while reflecting essential physical phenomena, such as electrochemical interactions in a dilute Newtonian solvent under assumptions of slow

Audrey Fovelle

We prove that if $Y$ is a locally asymptotically midpoint uniformly convex Banach space which has either a normalized, symmetric basic sequence that is not equivalent to the unit vector basis in $\ell_1$, or a normalized sequence with upper p-estimates for some $p>1$, then $Y$ does not satisfy Lindenstrauss' property B.

V. P. Berezovoj, A. J. Nurmagambetov

We fill some of existed gaps in the correspondence between Supersymmetric Quantum Mechanics and the Inverse Scattering Transform by extending the consideration to the case of paired stationary and non-stationary Hamiltonians. We formulate the corresponding to the case Goursat problem and explicitly construct the kernel of the non-local Inverse Scattering Tra

Leonie Kallabis, Bruno Baruque-Zanón, Heinrich Klocke, Ana María Lara-Palma

Video games elicit emotions which can be influenced by color stimuli as shown by previous studies. However, little research has been conducted on whether this applies to mobile games played by adolescents. Therefore, we examined the influence of color stimuli hue and saturation on mobile game play. Adolescents (n=21) played a mobile platformer game with vary

A. Rettaroli, D. Alesini, D. Babusci, C. Braggio

We report the first experimental results obtained with the new haloscope of the QUAX experiment located at Laboratori Nazionali di Frascati of INFN (LNF). The haloscope is composed of a OFHC Cu resonant cavity cooled down to about 30 mK and immersed in a magnetic field of 8 T. The cavity frequency was varied in a 6 MHz range between 8.831496 and 8.83803 GHz.

Sarina Thomas, Cristiana Tiago, Børge Solli Andreassen, Svein Arne Aase

To facilitate diagnosis on cardiac ultrasound (US), clinical practice has established several standard views of the heart, which serve as reference points for diagnostic measurements and define viewports from which images are acquired. Automatic view recognition involves grouping those images into classes of standard views. Although deep learning techniques

Hongxia Li, Wei Huang, Jingya Wang, Ye Shi

Prompt learning in pretrained visual-language models has shown remarkable flexibility across various downstream tasks. Leveraging its inherent lightweight nature, recent research attempted to integrate the powerful pretrained models into federated learning frameworks to simultaneously reduce communication costs and promote local training on insufficient data

Liuzhenghao Lv, Wei Fang, Li Yuan, Yonghong Tian

Spiking Neural Networks (SNNs) have emerged as a promising third generation of neural networks, offering unique characteristics such as binary outputs, high sparsity, and biological plausibility. However, the lack of effective learning algorithms remains a challenge for SNNs. For instance, while converting artificial neural networks (ANNs) to SNNs circumvent

M. Alvioli, V. Guzey, M. Strikman

We argue that measurements of forward neutrons from nuclear breakup in inclusive high energy photon-nucleus ($\gamma A$) scattering provide a novel way to study small-$x$ dynamics of QCD in heavy-ion ultraperipheral collisions (UPCs). Using models for hadronic fluctuations of the real photon and neutron emission in nuclear fragmentation, we calculate the dis

Jiahao Zhou, Chen Long, Yue Xie, Jialiang Wang

End-to-end models capable of handling multiple sub-tasks in parallel have become a new trend, thereby presenting significant challenges and opportunities for the integration of multiple tasks within the domain of 3D vision. The limitations of 3D data acquisition conditions have not only restricted the exploration of many innovative research problems but have

Anas Shrinah, Masoud S. Bahraini, Fahad Khan, Seemal Asif

Effective communication between humans and collaborative robots is essential for seamless Human-Robot Collaboration (HRC). In noisy industrial settings, nonverbal communication, such as gestures, plays a key role in conveying commands and information to robots efficiently. While existing literature has thoroughly examined gesture recognition and robots' resp

Jingxiao Chen, Weiji Xie, Weinan Zhang, Yong yu

Offline Reinforcement Learning (RL) enables policy improvement from fixed datasets without online interactions, making it highly suitable for real-world applications lacking efficient simulators. Despite its success in the single-agent setting, offline multi-agent RL remains a challenge, especially in competitive games. Firstly, unaware of the game structure

Ahmed Bhayat, Johannes Schoisswohl, Michael Rawson

Classically, in saturation-based proof systems, unification has been considered atomic. However, it is also possible to move unification to the calculus level, turning the steps of the unification algorithm into inferences. For calculi that rely on unification procedures returning large or even infinite sets of unifiers, integrating unification into the calc

Graham Woan, Joseph Bayley

We present a new analysis of the positions of holes beneath the calendar ring of the Antikythera mechanism, as measured by Budiselic et al. (2020). We significantly refine their estimate for the number of holes that were present in the full ring. Our $68\%$-credible estimate for this number, taking account of all the data, is $355.24^{ +1.39 }_{ -1.36 }$. If

Mauro Nacinovich, Egmont Porten

We introduce a notion of locally approximable continuous CR functions on locally closed subsets of reduced complex spaces, generalizing both holomorphic functions and CR functions on CR submanifolds. Under additional assumptions of set-theoretical weak pseudoconcavity we prove optimal maximum modulus principles for these functions. Restricting to real subman

Hagop Karakazian, Toni Sayah, Faouzi Triki

In this paper we consider the time dependent Porous Medium Equation, $u_t = \Delta u^\gamma$ with real polytropic exponent $\gamma>1$, subject to a homogeneous Dirichlet boundary condition. We are interested in recovering $\gamma$ from the knowledge of the solution $u$ at a given large time $T$. Based on an asymptotic inequality satisfied by the solution $u(

Wen-Yang Sun, A-Min Ding, Juan He, Jiadong Shi

In this work, we delve into the dynamic traits of the relative entropy of quantum coherence (REQC) as the quantum system interacts with the different noisy channels, drawing comparisons with entanglement (concurrence). The research results demonstrate the broader prevalence and stronger robustness of the REQC as opposed to concurrence. It's worth noting that

Yang Xu, Yunlin Tan, Cheng Zhang, Kai Chi

Embedding watermarks into models has been widely used to protect model ownership in federated learning (FL). However, existing methods are inadequate for protecting the ownership of personalized models acquired by clients in personalized FL (PFL). This is due to the aggregation of the global model in PFL, resulting in conflicts over clients' private watermar

Marta Dell'Atti, Thomas Kecker

Some new Hamiltonian systems of quasi-Painlev\'e type are presented and the analogue of Okamoto's space of initial conditions computed. Using the geometric approach that was introduced originally for the identification problem of Painlev\'e equations, comparing the irreducible components of the inaccessible divisors arising in the blow-up process, we find bi

Prottay Kumar Adhikary, Aseem Srivastava, Shivani Kumar, Salam Michael Singh

Comprehensive summaries of sessions enable an effective continuity in mental health counseling, facilitating informed therapy planning. Yet, manual summarization presents a significant challenge, diverting experts' attention from the core counseling process. This study evaluates the effectiveness of state-of-the-art Large Language Models (LLMs) in selectivel

Orfeu Bertolami, Robertus Potting, Paulo M. Sá

In this work, we discuss the de Sitter swampland conjectures in the context of the generalized Chaplygin-inspired inflationary model. We demonstrate that these conjectures can be satisfied, but only in the region of the parameter space far away from the General Relativity limit. The cosmic microwave background data had already been found to restrict the allo

Roman Cherniha, Vasyl' Davydovych, John R. King

We study a simplification of the well-known Shigesada-Kawasaki-Teramoto model, which consists of two nonlinear reaction-diffusion equations with cross-diffusion. A complete set of Q-conditional (nonclassical) symmetries is derived using an algorithm adopted for the construction of conditional symmetries. The symmetries obtained are applied for finding a wide

Tanya Sharma, Rutvij Bhavsar, Jayanth Ramakrishnan, Pooja Chandravanshi

In theory, quantum key distribution (QKD) provides unconditional security; however, its practical implementations are susceptible to exploitable vulnerabilities. This investigation tackles the constraints in practical QKD implementations using weak coherent pulses. We improve on the conventional approach of using decoy pulses by integrating it with the coinc

Geoffry Gifari, Parada T. P. Hutauruk, Terry Mart

In this paper, we report the results of our study on the nuclear medium modifications of the meson electromagnetic form factors in the framework of the Nambu--Jona-Lasinio (NJL) model with the help of the Schwinger proper-time regularization scheme to tame the loop divergence and simulate the effect of QCD confinement. In our current approach, the meson stru

Nicola Muca Cirone, Antonio Orvieto, Benjamin Walker, Cristopher Salvi

Structured state-space models (SSMs) such as S4, stemming from the seminal work of Gu et al., are gaining popularity as effective approaches for modeling sequential data. Deep SSMs demonstrate outstanding performance across a diverse set of domains, at a reduced training and inference cost compared to attention-based transformers. Recent developments show th

Mariana Nold, Florian Meinfelder, David Kaplan

Model uncertainty is pervasive in real world analysis situations and is an often-neglected issue in applied statistics. However, standard approaches to the research process do not address the inherent uncertainty in model building and, thus, can lead to overconfident and misleading analysis interpretations. One strategy to incorporate more flexible models is

Francesco Puccioni, Johannes Pausch, Paul Piho, Philipp Thomas

Fractional killing in response to drugs is a hallmark of non-genetic cellular heterogeneity. Yet how individual lineages evade drug treatment, as observed in bacteria and cancer cells, is not quantitatively understood. We analyse a stochastic population model with age-dependent division and death rates and characterise the emergence of fractional killing as

David Skuddis, Norbert Haala

We propose a new method for fine registering multiple point clouds simultaneously. The approach is characterized by being dense, therefore point clouds are not reduced to pre-selected features in advance. Furthermore, the approach is robust against small overlaps and dynamic objects, since no direct correspondences are assumed between point clouds. Instead,

Paul Friedrich, Julia Wolleb, Florentin Bieder, Alicia Durrer

Due to the three-dimensional nature of CT- or MR-scans, generative modeling of medical images is a particularly challenging task. Existing approaches mostly apply patch-wise, slice-wise, or cascaded generation techniques to fit the high-dimensional data into the limited GPU memory. However, these approaches may introduce artifacts and potentially restrict th

Fabian Hofmann, Christoph Tries, Fabian Neumann, Elisabeth Zeyen

Hydrogen and carbon dioxide transport can both play an essential role in climate-neutral energy systems. Hydrogen networks help serve regions with high energy demand, while excess emissions are transported away in carbon dioxide networks. For the synthesis of carbonaceous fuels, it is less clear which input should be transported: hydrogen to carbon point sou

P. Hill, N. Anantrasirichai, A. Achim, D. R. Bull

Atmospheric turbulence poses a challenge for the interpretation and visual perception of visual imagery due to its distortion effects. Model-based approaches have been used to address this, but such methods often suffer from artefacts associated with moving content. Conversely, deep learning based methods are dependent on large and diverse datasets that may

Igor Antoniazzi, Tomasz Woźniak, Amit Pawbake, Natalia Zawadzka

The effect of pressure on Raman scattering (RS) in the bulk HfS$_2$ is investigated under hydrostatic and non-hydrostatic conditions. The RS lineshape does not change significantly in the hydrostatic regime, showing a systematic blueshift of the spectral features. In a non-hydrostatic environment, seven peaks emerge in the spectrum ($P$=7 GPa) dominating the

Phusit Nualpijit, Bumned Soodchomshom

We investigate the electronic properties of MXenes by three bands tight-binding model of \d_{z^2} , \d_{xy} , and \d_{x^2-y^2} orbitals. The three corresponding bands touch each other at high symmetry K point in the case of absence of spin-orbit interaction. The proper parameters can be obtained by Slater-Koster parameters related to chemical bonding, \pi, \

Emeralda Sesari, Federica Sarro, Ayushi Rastogi

Software practitioners discuss problems at work with peers, in-person and online. These discussions can be technical (e.g., how to fix a bug?) and social (e.g., how to assign work fairly?). While there is a growing body of knowledge exploring fairness problems and solutions in the human and social factors of software engineering, most focus has been on speci

Giuseppe Chiari, Davide Galli, Francesco Lattari, Matteo Matteucci

Side-channel attacks allow extracting secret information from the execution of cryptographic primitives by correlating the partially known computed data and the measured side-channel signal. However, to set up a successful side-channel attack, the attacker has to perform i) the challenging task of locating the time instant in which the target cryptographic p

Stefano Rizzelli, Judith Rousseau, Sonia Petrone

In applications of Bayesian procedures, once a class of priors has been chosen, it may be tempting to fix the prior's hyperparameters from the data, in an empirical Bayes (EB) fashion, usually by their maximum marginal likelihood estimates (MMLE). This is a quite common but questionable practice, lacking a rigorous theoretical basis. We provide a theoretical

S. V. Kozyrev

A model of population genetics of the Lotka-Volterra type with mutations on a statistical manifold is introduced. Mutations in the model are described by diffusion on a statistical manifold with a generator in the form of a Laplace-Beltrami operator with a Fisher-Rao metric, that is, the model combines population genetics and information geometry. This model

Claude Duhr, Albrecht Klemm, Florian Loebbert, Christoph Nega

We generalise the geometric analysis of square fishnet integrals in two dimensions to the case of hexagonal fishnets with three-point vertices. Our results support the conjecture that fishnet Feynman integrals in two dimensions, together with their associated geometry, are completely fixed by their Yangian and permutation symmetries. As a new feature for the

Carlos A. Pérez Aparicio

In this study, we derive the infinite product representation of the $\operatorname{sinc}(\mathrm{z})$ function by expressing it in a trigonometric form, evoking similarities to Morrie's Law and Euler's Product formula, along with their generalizations. The results presented in this investigation are entirely novel and are believed to introduce new insights i

Charbel Toumieh, Dario Floreano

Coordinated flight of multiple drones allows to achieve tasks faster such as search and rescue and infrastructure inspection. Thus, pushing the state-of-the-art of aerial swarms in navigation speed and robustness is of tremendous benefit. In particular, being able to account for unexplored/unknown environments when planning trajectories allows for safer flig

Ying Wai Lee, Andrew Scoones

Many results related to quantitative problems in the metric theory of Diophantine approximation are asymptotic, such as the number of rational solutions to certain inequalities grows with the same rate almost everywhere modulo an asymptotic error term. The error term incorporates an implicit constant that varies from one point to another. This means that app

Andrea Braides, Gianni Dal Maso, Claude Le Bris

In this work we examine the stability of some classes of integrals, and in particular with respect to homogenization. The prototypical case is the homogenization of quadratic energies with periodic coefficients perturbed by a term vanishing at infinity, which has been recently examined in the framework of elliptic PDE. We use localization techniques and high

Samuel O. Scalet

We consider the problem of approximating the free energy density of a translation-invariant, one-dimensional quantum spin system with finite range. While the complexity of this problem is nontrivial due to its close connection to problems with known hardness results, a classical subpolynomial-time algorithm has recently been proposed [Fawzi et al., 2022]. Co

Lynn Roy LaMotte

Type III methods, introduced by SAS in 1976, formulate estimable functions that substitute, somehow, for classical ANOVA effects in multiple linear regression models. They have been controversial since, provoking wide use and satisfied users on the one hand and skepticism and scorn on the other. Their essential mathematical properties have not been establish

Gianluca Redondi, Alessandro Cimatti, Alberto Griggio, Kenneth McMillan

This paper addresses the problem of checking invariant properties for a large class of symbolic transition systems, defined by a combination of SMT theories and quantifiers. State variables can be functions from an uninterpreted sort (finite, but unbounded) to an interpreted sort, such as the the integers under the theory of linear arithmetic. This formalism

Ilias Tsingenopoulos, Jacopo Cortellazzi, Branislav Bošanský, Simone Aonzo

ML-based malware detection on dynamic analysis reports is vulnerable to both evasion and spurious correlations. In this work, we investigate a specific ML architecture employed in the pipeline of a widely-known commercial antivirus company, with the goal to harden it against adversarial malware. Adversarial training, the sole defensive technique that can con

Jiangming Shi, Xiangbo Yin, Yachao Zhang, Zhizhong Zhang

Unsupervised visible-infrared person re-identification (USVI-ReID) aims to match specified people in infrared images to visible images without annotations, and vice versa. USVI-ReID is a challenging yet under-explored task. Most existing methods address the USVI-ReID using cluster-based contrastive learning, which simply employs the cluster center as a repre

Riccardo Pala, Esteban García-Cuesta

The notion of robustness in XAI refers to the observed variations in the explanation of the prediction of a learned model with respect to changes in the input leading to that prediction. Intuitively, if the input being explained is modified slightly subtly enough so as to not change the prediction of the model too much, then we would expect that the explanat

Sina Feldmann, Thomas Chatagnon, Juliane Adrian, Julien Pettré

In high-density crowds, local motion can propagate, amplify, and lead to macroscopic phenomena, including 'density waves'. These density waves only occur when individuals interact, and impulses are transferred to neighbours. How this impulse is passed on by the human body and which effects this has on individuals is still not fully understood. To further inv

Han Wang, Yiming Zhou, Eduardo Perez, Florian Roemer

Strategic subsampling has become a focal point due to its effectiveness in compressing data, particularly in the Full Matrix Capture (FMC) approach in ultrasonic imaging. This paper introduces the Joint Deep Probabilistic Subsampling (J-DPS) method, which aims to learn optimal selection matrices simultaneously for transmitters, receivers, and Fourier coeffic

Yi Tao, Ting Chen, Yi Xie, Hongyang Wang

In trapped ion system, accurate thermometry of ion is crucial for evaluating the system state and precisely performing quantum operations. However, when the motional state of a single ion is far away from the ground state, the spatial dimension of the phonon state sharply increases, making it difficult to realize accurate and mode-resolved thermometry with e

Valentin Kilian, Tabea Rebafka, Fanny Villers

For the problem of inferring a Gaussian graphical model (GGM), this work explores the application of a recent approach from the multiple testing literature for graph inference. The main idea of the method by Rebafka et al. (2022) is to model the data by a latent variable model, the so-called noisy stochastic block model (NSBM), and then use the associated ${

Jianxin Lei, Dongze Wu, Chengcai Xu, Hongcheng Gu

Hand-held light field (LF) cameras often exhibit low spatial resolution due to the inherent trade-off between spatial and angular dimensions. Existing supervised learning-based LF spatial super-resolution (SR) methods, which rely on pre-defined image degradation models, struggle to overcome the domain gap between the training phase -- where LFs with natural

Takeo Sudo, Satoki Ishiai, Yuuki Ishiwatari, Takahiro Yokoyama

Amphiphilic molecules spontaneously form self-assembled structures of various shapes depending on their molecular structures, the temperature, and other physical conditions. The functionalities of these structures are dictated by their formations and their properties must be evaluated for reproduction using molecular simulations. However, the assessment of s

Adam Klukowski, Vladimir Marković

Let $\Sigma^p_g$ denote a surface of genus $g$ and with $p$ punctures. Our main result is that the fraction of degree $n$ covers of $\Sigma^p_g$ which have the Putman-Wieland property tends to $1$ as $n\to \infty$. In addition, we show that the monodromy of a random cover of $\Sigma^p_g$ is asymptotically almost surely tangle free.

Carlos A. Perez Aparicio

We derive the infinite product of the tangent function expressed in terms of trigonometric expressions such as Eulers Sinc function and Vietes formula, along with their generalizations. All the results presented in this work are novel.

S. Plaszczynski, B. Grammaticos, M. Badoual

We consider the duration of discussions in face-to-face contacts and propose a stochastic model to describe it. It is based on the points of a Levy flight where the duration of each contact corresponds to the size of the clusters produced during the walk. When confronting it to the data measured from proximity sensors, we show that several datasets obtained

Ajinkya Kiran Mulay, Xiaojun Lin

Sparse basis recovery is a classical and important statistical learning problem when the number of model dimensions $p$ is much larger than the number of samples $n$. However, there has been little work that studies sparse basis recovery in the Federated Learning (FL) setting, where the client data's differential privacy (DP) must also be simultaneously prot

Łukasz Płociniczak, Marek A. Teuerle

The fractional material derivative appears as the fractional operator that governs the dynamics of the scaling limits of L\'evy walks - a stochastic process that originates from the famous continuous-time random walks. It is usually defined as the Fourier-Laplace multiplier, therefore, it can be thought of as a pseudo-differential operator. In this paper, we

Xin Li, Yunfei Wu, Xinghua Jiang, Zhihao Guo

Recently, the advent of Large Visual-Language Models (LVLMs) has received increasing attention across various domains, particularly in the field of visual document understanding (VDU). Different from conventional vision-language tasks, VDU is specifically concerned with text-rich scenarios containing abundant document elements. Nevertheless, the importance o

Shihui Yu, Chubing Lv, Yueke Yang, Yuchen Pan

This work performs the design, real-time hardware realization, and experimental evaluation of a positioning system by ultra-violet (UV) communication under photon-level signal detection. The positioning is based on time-difference of arrival (TDOA) principle. Time division-based transmission of synchronization sequence from three transmitters with known posi

Matteo Palazzo, Luca Roversi

Concerning classical computational models able to express all the Primitive Recursive Functions (PRF), there are interesting results regarding limits on their algorithmic expressiveness or, equivalently, efficiency, namely the ability to express algorithms with minimal computational cost. By introducing the reversible programming model Forest, at our knowled

Jingwen Fan, Yi He, Bo Tang, Qi Li

Smart home IoT systems utilize trigger-action platforms, e.g., IFTTT, to manage devices from various vendors. However, they may be abused by triggering malicious rule execution with forged IoT devices or events violating the execution integrity and the intentions of the users. To address this issue, we propose a ledger based IoT platform called Ruledger, whi

J. Kluson

We present manifestly reparametrization invariant action for theory of gravity with dynamical determinant of metric. We show that it is similar to a reparametrization invariant action for unimodular gravity. We determine canonical form of the action and study structure of constraints.

Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu

The vast applications of deep generative models are anchored in three core capabilities -- generating new instances, reconstructing inputs, and learning compact representations -- across various data types, such as discrete text/protein sequences and continuous images. Existing model families, like variational autoencoders (VAEs), generative adversarial netw

Andrea Priulla, Alessandro Albano, Nicoletta D'Angelo, Massimo Attanasio

This paper explores the influence of Italian high school students' proficiency in mathematics and the Italian language on their university enrolment choices, specifically focusing on STEM (Science, Technology, Engineering, and Mathematics) courses. We distinguish between students from scientific and humanistic backgrounds in high school, providing valuable i

Shin Watanabe, Takenori Furumoto, Wataru Horiuchi, Tadahiro Suhara

Background: Nuclear deformation provides a crucial characteristic of nuclear structure. Conventionally, the quadrupole deformation length of a nucleus, $\delta_{2}$, has often been determined based on a macroscopic model through a deformed nuclear potential with the deformation length $\delta^{\rm (pot)}_{2}$, which is determined to reproduce the nuclear sca

Ji Ma, Hongming Dai, Yao Mu, Pengying Wu

Zero-Shot Object Navigation (ZSON) requires agents to autonomously locate and approach unseen objects in unfamiliar environments and has emerged as a particularly challenging task within the domain of Embodied AI. Existing datasets for developing ZSON algorithms lack consideration of dynamic obstacles, object attribute diversity, and scene texts, thus exhibi

B. Barsbay, K. Azizi, H. Sundu

We investigate the light quarkonium hybrid mesons of various spin-parities in QCD. Considering different interpolating currents made of the valence light quarks and single gluon, we calculate the mass and current coupling of the strange and nonstrange members of light hybrid mesons by including into computations the nonperturbative quark and gluon condensate

Wun-Yi Chen, Ke-Jung Chen, Masaomi Ono

Shock breakout is the first electromagnetic signal from supernovae (SNe), which contains important information on the explosion energy and the size and chemical composition of the progenitor star. This paper presents the first two-dimensional (2D) multi-wavelength radiation hydrodynamics simulations of SN 1987A shock breakout by using the $\texttt{CASTRO}$ c

Jie Zhang, Xubing Yang, Rui Jiang, Wei Shao

The development of high-resolution remote sensing satellites has provided great convenience for research work related to remote sensing. Segmentation and extraction of specific targets are essential tasks when facing the vast and complex remote sensing images. Recently, the introduction of Segment Anything Model (SAM) provides a universal pre-training model

Nabajit Talukdar, Kukil Kalpa Rajkhowa

We investigate the finite groups $G$ for which $\chi(1)^{2}=|G:Z(\chi)|$ for all characters $\chi \in Irr(G)$ and $|cd(G)|=2$. We obtain some alternate characterizations of these groups and we obtain some information regarding the structure of these groups.

Amar Fadillah, Ching-Lin Lee, Zhi-Xuan Wang, Kuan-Ting Lai

Predicting the future trajectories of pedestrians on the road is an important task for autonomous driving. The pedestrian trajectory prediction is affected by scene paths, pedestrian's intentions and decision-making, which is a multi-modal problem. Most recent studies use past trajectories to predict a variety of potential future trajectory distributions, wh

Xinyi Fang, Xu Yang, Chak Fong Chong, Kei Long Wong

Accurate classification of laryngeal vascular as benign or malignant is crucial for early detection of laryngeal cancer. However, organizations with limited access to laryngeal vascular images face challenges due to the lack of large and homogeneous public datasets for effective learning. Distinguished from the most familiar works, which directly transfer th

Pénélope Azuelos

We study finitely generated pairs of groups $H \leq G$ such that the Schreier graph of $H$ has at least two ends and is \emph{narrow}. Examples of narrow Schreier graphs include those that are quasi-isometric to finitely ended trees or have linear growth. Under this hypothesis, we show that $H$ is a virtual fiber subgroup if and only if $G$ contains infinite

Jingyi Liao, Xun Xu, Manh Cuong Nguyen, Adam Goodge

Existing approaches towards anomaly detection~(AD) often rely on a substantial amount of anomaly-free data to train representation and density models. However, large anomaly-free datasets may not always be available before the inference stage; in which case an anomaly detection model must be trained with only a handful of normal samples, a.k.a. few-shot anom

Dario Corona, Roberto Giambò, Orlando Luongo

We explore the characteristics of two novel regular spacetimes that exhibit a non-zero vacuum energy term, under the form of a (quasi) anti-de Sitter phase. Specifically, the first metric is spherical, while the second, derived by applying the generalized Newman-Janis algorithm to the first, is axisymmetric. We show that the equations of state of the effecti

Feng Tang, Jingjun Wu, Tom Albrow-Owen, Hanxiao Cui

Optical spectroscopy plays an essential role across scientific research and industry for non-contact materials analysis1-3, increasingly through in-situ or portable platforms4-6. However, when considering low-light-level applications, conventional spectrometer designs necessitate a compromise between their resolution and sensitivity7,8, especially as device

Rui Huang, Sikun Yang, Heinz Koeppl

Modeling count-valued time series has been receiving increasing attention since count time series naturally arise in physical and social domains. Poisson gamma dynamical systems (PGDSs) are newly-developed methods, which can well capture the expressive latent transition structure and bursty dynamics behind count sequences. In particular, PGDSs demonstrate su

Kade M. Heckel, Thomas Nowotny

As the role of artificial intelligence becomes increasingly pivotal in modern society, the efficient training and deployment of deep neural networks have emerged as critical areas of focus. Recent advancements in attention-based large neural architectures have spurred the development of AI accelerators, facilitating the training of extensive, multi-billion p

Philipp Dorau, Rainer Verch

We extend the concept of the Kodama symmetry, a quasi-local time translation symmetry for dynamical spherically symmetric spacetimes, to a specific class of dynamical axisymmetric spacetimes, namely the families of Kerr-Vaidya and Kerr-Vaidya-de Sitter spacetimes. We study some geometrical properties of the asymptotically flat Kerr-Vaidya metric, such as the

Sudip Kumar Sarkar, P. D. Babu, V. K. Sharma, S. D. Kaushik

Polycrystalline Ni-Co-Mn-Sn based ferromagnetic shape memory alloys (FSMAs) show promise as actuator materials, but their practical application involving magnetic field induced strain (MFIS) is often limited by three factors: the requirement for high magnetic fields (> 5 T), martensitic transition temperature away from room temperature, and limited recovery

Biel Martinez, Silvano de Franceschi, Yann-Michel Niquet

The scalability of spin qubit devices is conditioned by qubit-to-qubit variability. Disorder in the host materials indeed affects the wave functions of the confined carriers, which leads to variations in their charge and spin properties. Charge disorder in the amorphous oxides is particularly detrimental owing to its long-range influence. Here we analyze the

Ernst Paunzen

The chemically peculiar (CP) stars of the upper main sequence are excellent astrophysical laboratories for investigating the diffusion, mass loss, rotational mixing, and pulsation in the presence and absence of a stable local magnetic field. For this, we need a homogeneous set of parameters, such as effective temperature and surface gravity, to locate the st

L. Schamriß, M. R. Walther, K. P. Schmidt

Directly evaluated enhanced perturbative continuous unitary transformations (deepCUTs) are used to calculate non-perturbatively extrapolated numerical data for the ground-state energy and the energy gap. The data coincides with the perturbative series up to the order with respect to which the deepCUT is truncated. We develop a general scheme to extract quant

Ingo Weber, Hendrik Linka, Daniel Mertens, Tamara Muryshkin

Since OpenAI's release of ChatGPT, generative AI has received significant attention across various domains. These AI-based chat systems have the potential to enhance the productivity of knowledge workers in diverse tasks. However, the use of free public services poses a risk of data leakage, as service providers may exploit user input for additional training

Quentin d'Armagnac de Castanet, Cyrille Des Cognets, Romain Arguel, Simon Templier

The exquisite precision of atom interferometers has sparked the interest of a large community for use cases ranging from fundamental physics to geodesy and inertial navigation. However, their practical use for onboard applications is still limited, not least because rotation and acceleration are intertwined in a single phase shift in free-fall atom interfero

Yungang Lu

We provide an explicit formulation for the solution to the Catalan's triangle system using Catalan's trapezoids and a specified boundary condition. Additionally, we study this system with various boundary conditions obtained by utilizing different types of Fock spaces.

Zhengyao Gu, Diego Troy Lopez, Lilas Alrahis, Ozgur Sinanoglu

Graph neural network-based network intrusion detection systems have recently demonstrated state-of-the-art performance on benchmark datasets. Nevertheless, these methods suffer from a reliance on target encoding for data pre-processing, limiting widespread adoption due to the associated need for annotated labels--a cost-prohibitive requirement. In this work,

Vyacheslav Mozolenko, Lev Shchur

We present a modification of the Rose-Machta algorithm (Phys. Rev. E 100 (2019) 063304) and estimate the density of states for a two-dimensional Blume-Capel model, simulating $10^5$ replicas in parallel for each set of parameters. We perform a finite-size analysis of the specific heat and Binder cumulant, determine the critical temperature along the critical

Sung-Soo Byun, Seong-Mi Seo, Meng Yang

We consider a planar Coulomb gas ensemble of size $N$ with the inverse temperature $\beta=2$ and external potential $Q(z)=|z|^2-2c \log|z-a|$, where $c>0$ and $a \in \mathbb{C}$. Equivalently, this model can be realised as $N$ eigenvalues of the complex Ginibre matrix of size $(c+1) N \times (c+1) N$ conditioned to have deterministic eigenvalue $a$ with mult

Charles-Edouard Bréhier, David Cohen

We consider a class of linear Vlasov partial differential equations driven by Wiener noise. Different types of stochastic perturbations are treated: additive noise, multiplicative It\^o and Stratonovich noise, and transport noise. We propose to employ splitting integrators for the temporal discretization of these stochastic partial differential equations. Th

Christian Brahms, John C. Travers

Ultrafast laser sources in the far ultraviolet (100 nm to 300 nm) have been the subject of intense experimental efforts for several decades, driven primarily by the requirements of advanced experiments in ultrafast science. Resonant dispersive wave emission from high-energy laser pulses undergoing soliton self-compression in a gas-filled hollow capillary fib

Xiaolan Chen, Ziwei Zhao, Weiyi Zhang, Pusheng Xu

Artificial intelligence (AI) has gained significant attention in healthcare consultation due to its potential to improve clinical workflow and enhance medical communication. However, owing to the complex nature of medical information, large language models (LLM) trained with general world knowledge might not possess the capability to tackle medical-related t

Robert F. H. Fischer

In this paper, we consider the generation and utilization of helper data for physical unclonable functions (PUFs) that provide real-valued readout symbols. Compared to classical binary PUFs, more entropy can be extracted from each basic building block (PUF node), resulting in longer keys/fingerprints and/or a higher reliability. To this end, a coded modulati

V. V. Ryazanov

Neutrons in a nuclear reactor move along trajectories corresponding to Cayley trees associated with branching random processes. The probability of percolation, the appearance of such a state of the Bethe lattice in which there is at least one continuous path through neighboring conducting nodes through the entire lattice, corresponds to the probability of th

F. Matković, R. Brajša, M. Kuhar, A. O. Benz

The Atacama Large Millimeter/submillimeter Array (ALMA) allows for solar observations in the wavelength range of 0.3$-$10 mm, giving us a new view of the chromosphere. The measured brightness temperature at various frequencies can be fitted with theoretical models of density and temperature versus height. We use the available ALMA and Mets\"ahovi measurement

Shambhavi Dikshit, Sudipta Pattanayak, Shradha Mishra, Sanjay Puri

We perform a comprehensive study on the role of thermal noise on the ordering kinetics of a collection of active Brownian particles modeled using coarse-grained conserved active model B (AMB). The ordering kinetics of the system is studied for the critical mixture when quenched from high to a low temperature. The structure of the growing domains changes from