December 2023 arXiv papers — page 80

Yang Zhong, Weiping Dou, Andrew Cohen, Dia'a Bisharat

To extend the antenna design on printed circuit boards (PCBs) for more engineers of interest, we propose a simple method that models PCB antennas with a few basic components. By taking two separate steps to decide their geometric dimensions and positions, antenna prototypes can be facilitated with no experience required. Random sampling statistics relate to

Ian Magnusson, Akshita Bhagia, Valentin Hofmann, Luca Soldaini

Evaluations of language models (LMs) commonly report perplexity on monolithic data held out from training. Implicitly or explicitly, this data is composed of domains--varying distributions of language. We introduce Perplexity Analysis for Language Model Assessment (Paloma), a benchmark to measure LM fit to 546 English and code domains, instead of assuming pe

Tom Simon Rodemund, Síle Nic Chormaic, Martina Hentschel

Coupled cavities are of interest as they expose qualitatively new effects, such as non-Hermitian properties, that are beyond the possibilitie of individual cavities. Here, we investigate the coupling between two dielectric two-dimensional microdisk cavities and compare circular vs. deformed (lima\c{c}on) resonator shapes as a function of their distance and a

Adam McCaw, Jacob Ewaniuk, Bhavin J. Shastri, Nir Rotenberg

Quantum photonic integrated circuits, composed of linear-optical elements, offer an efficient way for encoding and processing quantum information on-chip. At their core, these circuits rely on reconfigurable phase shifters, typically constructed from classical components such as thermo- or electro-optical materials, while quantum solid-state emitters such as

Simon Ghysbrecht, Bettina G. Keller

For a detailed understanding of chemical processes in nature and industry, we need accurate models of chemical reactions in complex environments. While Eyring transition state theory is commonly used for modeling chemical reactions, it is most accurate for small molecules in the gas phase. A wide range of alternative rate theories exist that can better captu

Vishal Rana, Jianhao Peng, Chao Pan, Hanbaek Lyu

Dictionary learning (DL) is commonly used in computational biology to tackle ubiquitous clustering problems due to its conceptual simplicity and relatively low computational complexity. However, DL algorithms produce results that lack interpretability and are not optimized for large-scale graph-structured data. We propose a novel DL algorithm called online c

B M Tazbiul Hassan Anik, Md Mobasshir Rashid, Md Jamil Ahsan

Drivers can sustain serious injuries in traffic accidents. In this study, traffic crashes on Florida's Interstate-95 from 2016 to 2021 were gathered, and several classification methods were used to estimate the severity of driver injuries. In the feature selection method, logistic regression was applied. To compare model performances, various model assessmen

Matthew Perez, Duc Le, Amrit Romana, Elise Jones

Paraphasias are speech errors that are often characteristic of aphasia and they represent an important signal in assessing disease severity and subtype. Traditionally, clinicians manually identify paraphasias by transcribing and analyzing speech-language samples, which can be a time-consuming and burdensome process. Identifying paraphasias automatically can

Simon Barazer, Alessandro Giacchetto, Mingkun Liu

We study the length of short cycles on uniformly random metric maps (also known as ribbon graphs) of large genus using a Teichm\"uller theory approach. We establish that, as the genus tends to infinity, the length spectrum converges to a Poisson point process with an explicit intensity. This result extends the work of Janson and Louf to the multi-faced case.

Dominic Joyce, Markus Upmeier

This is the second paper of a series that develops a bordism-theoretic point of view on orientations in enumerative geometry. The first paper is arXiv:2312.06818. This paper focuses on those applications to gauge theory that can be established purely using formal arguments and calculations from algebraic topology. We prove that the orientability of moduli sp

Wentao Li, Danpei Zhao, Bo Yuan, Yue Gao

Fine-grained object detection (FGOD) extends object detection with the capability of fine-grained recognition. In recent two-stage FGOD methods, the region proposal serves as a crucial link between detection and fine-grained recognition. However, current methods overlook that some proposal-related procedures inherited from general detection are not equally s

Luca Franzoi, Riccardo Montalto

We construct time almost-periodic solutions (global in time) with finite regularity to the incompressible Euler equations on the torus $\T^d$, with $d=3$ and $d\in\N$ even.

Chun-Chi Lin, Dung The Tran

This paper addresses the problems of spline interpolation on smooth Riemannian manifolds, with or without the inclusion of least-squares fitting. Our unified approach utilizes gradient flows for successively connected curves or networks, providing a novel framework for tackling these challenges. This method notably extends to the variational spline interpola

Muhammad Azeem Khan, Howard H. Yang, Zihan Chen, Antonio Iera

Data possesses significant value as it fuels advancements in AI. However, protecting the privacy of the data generated by end-user devices has become crucial. Federated Learning (FL) offers a solution by preserving data privacy during training. FL brings the model directly to User Equipments (UEs) for local training by an access point (AP). The AP periodical

N. F. Pedersen, G. Filatrella, V. Pierro, M. P. Sorensen

Regions with negative differential resistance can arise in the IV curve of Josephson junctions and this phenomenon plays an essential role for applications, in particular for THz radiation emission. For the measurement of high frequency radiation from Josephson junctions, a cavity - either internal or external - is often used. A cavity may also induce a nega

Daniel Peralta-Salas, Miguel Vaquero

In this work we study Beltrami fields with non-constant proportionality factor on $\mathbb{R}^3$. More precisely, we analyze the existence of vector fields $X$ satisfying the equations $curl(X)=fX$ and $div(X)=0$ for a given $f\in C^\infty(\mathbb R^3)$ in a neighborhood of a point $p\in\mathbb{R}^3$. Since the regular case has been treated previously, we fo

Mario A. Rodriguez-Meza, Alejandro Aviles, Hernan E. Noriega, Cheng-Zong Ruan

Modified gravity models with scale-dependent linear growth typically exhibit an enhancement in the power spectrum beyond a certain scale. The conventional methods for extracting cosmological information usually involve inferring modified gravity effects via Redshift Space Distortions (RSD), particularly through the time evolution of $f\sigma_8$. However, cla

Christian Arends, Jan Frahm, Joachim Hilgert

On a finite regular graph, (co)resonant states are eigendistributions of the transfer operator associated to the shift on one-sided infinite non-backtracking paths. We introduce two pairings of resonant and coresonant states, the vertex pairing which involves only the dependence on the initial/terminal vertex of the path, and the geodesic pairing which is gi

Mengxin Zheng, Jiaqi Xue, Yi Sheng, Lei Yang

Deep learning models have been incorporated into high-stakes sectors, including healthcare diagnosis, loan approvals, and candidate recruitment, among others. Consequently, any bias or unfairness in these models can harm those who depend on such models. In response, many algorithms have emerged to ensure fairness in deep learning. However, while the potentia

Timofei Snegirev

A non-relativistic (Galilei-invariant) model of a perfect fluid coupled to a solenoidal field in arbitrary spatial dimension is considered. It contains an arbitrary parameter $\kappa$ and in the particular case of $\kappa=1$ it describes a perfect fluid coupled to a magnetic field. For a special value of $\kappa$, the theory admits the Schrodinger symmetry g

Vladimir Yu. Protasov, Rinat Kamalov

If a linear switching system with frequent switches is stable, will it be stable under arbitrary switches? In general, the answer is negative. Nevertheless, this question can be answered in an explicit form for any concrete system. This is done by finding the mode-dependent critical lengths of switching intervals after which any enlargement does not influenc

Yongliang Zhang

We contribute to the classification of Hopf algebras with finite Gelfand-Kirillov dimension, GK-dimension for short, through the study of Nichols algebras over Q 8 ,the quaternion group . We find all the irreducible Yetter-Drinfeld modules V over Q 8 , and determine which Nichols algebras B(V ) of V are finite GK-dimensional, and which Nichols algebras B(V )

Chi Zhang, Wenkai Xiang, Xingzhi Guo, Baojian Zhou

Given a dynamic graph, the efficient tracking of anomalous subgraphs via their node embeddings poses a significant challenge. Addressing this issue necessitates an effective scoring mechanism and an innovative anomalous subgraph strategy. Existing methods predominantly focus on designing scoring strategies or employing graph structures that consider nodes in

Feng Bao, Guannan Zhang, Zezhong Zhang

This paper tackles the intricate task of jointly estimating state and parameters in data assimilation for stochastic dynamical systems that are affected by noise and observed only partially. While the concept of ``optimal filtering'' serves as the customary approach to estimate the state of the target dynamical system, traditional methods such as Kalman filt

Giuliano Orso, Jakub Zakrzewski, Piotr Deuar

The long-time behavior of weakly interacting bosons moving in a two-dimensional optical lattice and coupled to a lossy cavity is investigated numerically via the truncated Wigner method, which allows us to take into full account the dynamics of the cavity mode, quantum fluctuations, cavity-boson correlations, and self-organization of individual runs. We firs

Vibhav Narayan Singh, Mohammad Hasan, Mohammad Umar, Bhabani Prasad Mandal

In this paper, we introduce and analyze the Smith-Volterra-Cantor potential of power \( n \), denoted as SVC\(\left(\rho, n\right)\). Bridging the gap between the general Cantor and SVC systems, this novel potential offers a fresh perspective on Cantor-like potential systems within quantum mechanics that unify fractal and non-fractal potentials. Utilizing th

Yihang Zhai, Haixin Wang, Jianlong Chang, Xinlong Yang

Instruction tuning has shown promising potential for developing general-purpose AI capabilities by using large-scale pre-trained models and boosts growing research to integrate multimodal information for creative applications. However, existing works still face two main limitations: the high training costs and heavy computing resource dependence of full mode

Philippe Moustrou, Cordian Riener, Thorsten Theobald, Hugues Verdure

The classes of sums of arithmetic-geometric exponentials (SAGE) and of sums of nonnegative circuit polynomials (SONC) provide nonnegativity certificates which are based on the inequality of the arithmetic and geometric means. We study the cones of symmetric SAGE and SONC forms and their relations to the underlying symmetric nonnegative cone. As main results,

Martin Bladt, Igor Rodionov

A novel and comprehensive methodology designed to tackle the challenges posed by extreme values in the context of random censorship is introduced. The main focus is on the analysis of integrals based on the product-limit estimator of normalized upper order statistics, called extreme Kaplan--Meier integrals. These integrals allow for the transparent derivatio

Jonas Flechsig

A result of Allock [1](arXiv:math/9907194) states that certain orbifold braid groups contain Artin groups of type $D_n$, $\tilde{B}_n$ and $\tilde{D}_n$ as finite index subgroups. The underlying orbifolds have at most two cone points of order two. Based on [10](arXiv:2305.04273) and [12](arXiv:2305.04273), we generalize this result allowing cone points of ar

Sanidhay Bhambay, Burak Büke, Arpan Mukhopadhyay

The Join-the-Shortest-Queue (JSQ) load balancing scheme is known to minimise the average response time of jobs in homogeneous systems with identical servers. However, for {\em heterogeneous} systems with servers having different processing speeds, finding an optimal load balancing scheme remains an open problem for finite system sizes. Recently, for systems

Benjamin Alvarez, Jacob Schach Møller

We consider a class of toy models describing a fermion field coupled with a boson field. The model can be viewed as a Yukawa model but with scalar fermions. As in our first paper, the interaction kernels are assumed bounded in the fermionic momentum variable and decaying like $|q|^{-p}$ for large boson momenta $q$. With no restrictions on the coupling streng

Niklas Schmid, Marta Fochesato, Sarah H. Q. Li, Tobias Sutter

We consider the problem of optimally controlling stochastic, Markovian systems subject to joint chance constraints over a finite-time horizon. For such problems, standard Dynamic Programming is inapplicable due to the time correlation of the joint chance constraints, which calls for non-Markovian, and possibly stochastic, policies. Hence, despite the popular

Michael Potter, Miru Jun

We implement a Bayesian inference process for Neural Networks to model the time to failure of highly reliable weapon systems with interval-censored data and time-varying covariates. We analyze and benchmark our approach, LaplaceNN, on synthetic and real datasets with standard classification metrics such as Receiver Operating Characteristic (ROC) Area Under C

Mengzhao Jia, Can Xie, Liqiang Jing

Despite commendable achievements made by existing work, prevailing multimodal sarcasm detection studies rely more on textual content over visual information. It unavoidably induces spurious correlations between textual words and labels, thereby significantly hindering the models' generalization capability. To address this problem, we define the task of out-o

Juefei Wu, Bangshuai Zhu, Chi Ding, Cuiying Pei

The research on hydrogen-rich ternary compounds attract tremendous attention for it paves new route to room-temperature superconductivity at lower pressures. Here, we study the crystal structures, electronic structures, and superconducting properties of the ternary Ca-U-H system, combining crystal structure predictions with ab-initio calculations under high

Samad Noeiaghdam, Aliona I. Dreglea, Denis N. Sidorov

This study aims to discuss the existence and uniqueness of solution of fuzzy Volterra integral equation with piecewise continuous kernel. Such problems appears in many balance problems for hereditary dynamic systems, e.g. in electric load leveling. The method of successive approximations is applied and the main theorems are proved based on the method. Some e

Arash Vaezi, Ali Movaghar, Mohammad Ghodsi, Seyed Mohammad Hussein Kazemi

Scientists have demonstrated that quantum computing has presented novel approaches to address computational challenges, each varying in complexity. Adapting problem-solving strategies is crucial to harness the full potential of quantum computing. Nonetheless, there are defined boundaries to the capabilities of quantum computing. This paper concentrates on ag

Michael P. Evers, Markus Kontny

We provide a novel representation of the total n-th derivative of the multivariate composite function $f \circ g$, i.e. a generalized Fa\`a di Bruno's formula. To this end, we make use of properties of the Kronecker product and the n-th derivative of the left-composite $f$, which allow the use of a multivariate form of partial Bell polynomials to represent t

Jiangbin Lyu, Xu Chen, Jiefeng Zhang, Liqun Fu

Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations (ABSs) to provide wireless connectivity for ground users (GUs) in various emergency scenarios. However, it is a NP-hard problem with exponential complexity in $M$ and $N$, in order to maximize the coverage rate of $M$ GUs by jointly placing $N$ ABSs with limited coverage range. The probl

Lingxiao Zhao, Cuiying Pei, Juefei Wu, Yi Zhao

Tellurium (Te) is one of the p-orbital chalcogens, which shows attractive physical properties at ambient pressure. Here, we systematically investigate both structural and electronic evolution of Te single crystal under high pressure up to 40 GPa. The pressure dependence of the experimental Raman spectrum reveals the occurrence of multiple phase transitions,

Dongmei Wei, Hailing Liu, Yongmei Li, Sujuan Qin

Applications of Time-Fractional Schrodinger Equations (TFSEs) to quantum processes are instructive for understanding and describing the time behavior of real physical systems. By applying three popular TFSEs, namely Naber's TFSE I, Naber's TFSE II, and XGF's TFSE, to a basic open system model of a two-level system (qubit) coupled resonantly to a dissipative

Peter Knaus, Sylvia Frühwirth-Schnatter

Many existing shrinkage approaches for time-varying parameter (TVP) models assume constant innovation variances across time points, inducing sparsity by shrinking these variances toward zero. However, this assumption falls short when states exhibit large jumps or structural changes, as often seen in empirical time series analysis. To address this, we propose

Seunghwan Min, Jihoon Jang, Kunsoo Park, Dora Giammarresi

Real-time analysis of graphs containing temporal information, such as social media streams, Q&A networks, and cyber data sources, plays an important role in various applications. Among them, detecting patterns is one of the fundamental graph analysis problems. In this paper, we study time-constrained continuous subgraph matching, which detects a pattern with

Sandip Das, Florent Foucaud, Sk Samim Islam, Joydeep Mukherjee

For a graph $ G = (V, E) $ with a vertex set $ V $ and an edge set $ E $, a function $ f : V \rightarrow \{0, 1, 2, . . . , diam(G)\} $ is called a \emph{broadcast} on $ G $. For each vertex $ u \in V $, if there exists a vertex $ v $ in $ G $ (possibly, $ u = v $) such that $ f (v) > 0 $ and $ d(u, v) \leq f (v) $, then $ f $ is called a dominating broadcas

Amine Ahriche

In this work, we investigate the possibility to address the excess observed around 95 GeV in the $\gamma\gamma$, $\tau\tau$, and $b\bar{b}$ channels as a scalar resonance(s) within the Georgi-Machacek (GM) model. In our analysis, we find that the excess can be easily accommodated in the channels ($\gamma\gamma$ and $b\bar{b}$) simultaneously, where the 95 Ge

Christoph Schiller

Quantum theory suggests that the three observed gauge groups U(1), SU(2) and SU(3) are related to the three Reidemeister moves: twists, pokes and slides. The background for the relation is provided. It is then shown that twists generate the group U(1), whereas pokes generate SU(2). Emphasis is placed on proving the relation between slides, the Gell-Mann matr

Chia Shuo Chang, Tian Sheuan Chang, Jiun Lin Yan, Li Ko

Intracranial hemorrhages in head CT scans serve as a first line tool to help specialists diagnose different types. However, their types have diverse shapes in the same type but similar confusing shape, size and location between types. To solve this problem, this paper proposes an all attention U-Net. It uses channel attentions in the U-Net encoder side to en

Rachid Aliradi, Abdealmalik Ouamane, Abdeslam Amrane

the paper presents a new method color MS-BSIF learning and MS-LBP for the kinship verification is the machine's ability to identify the genetic and blood the relationship and its degree between the facial images of humans. Facial verification of kinship refers to the task of training a machine to recognize the blood relationship between a pair of faces paren

Susana Furtado, Charles Johnson

We focus upon the relationship between Hamiltonian cycle products and efficient vectors for a reciprocal matrix $A$, to more deeply understand the latter. This facilitates a new description of the set of efficient vectors (as a union of convex subsets), greater understanding of convexity within this set and of order reversals in efficient vectors. A straight

Jiahao Cao, Xinwei Li, Tianwei Mao, Wenxin Xu

Quantum metrology employs entanglement to enhance measurement precision. The focus and progress so far have primarily centered on estimating a single parameter. In diverse application scenarios, the estimation of more than one single parameter is often required. Joint estimation of multiple parameters can benefit from additional advantages for further enhanc

Jingyi Zhou, Jie Zhou, Jiabao Zhao, Siyin Wang

Few-shot text classification has attracted great interest in both academia and industry due to the lack of labeled data in many fields. Different from general text classification (e.g., topic classification), few-shot sentiment classification is more challenging because the semantic distances among the classes are more subtle. For instance, the semantic dist

Guillermo A. Lobos, Mynor Melara, Maria R. B. Santos

We determine a Simons' type formula for spacelike submanifolds within a broad class of semiRiemannian warped products. This formula extends the Simons' type formulas initially introduced by Nomizu and Smyth in 1969 for constant mean curvature hypersurfaces in space forms. Furthermore, it incorporates the 2013 extension by Fetcu and Rosenberg for submanifolds

Xiaodong Song, Lizhen Hou, Ruizhe Liu, Noman Akhtar

The measurement of adhesion energy between nanolayers and substrates holds significant importance for the design, fabrication, and stability assessment of micro-/nanoscale devices relying on nanolayers. In this study, we propose a nanowire-supported bridging method based on an optical microscope-based nanomanipulation technique to quantitatively measure the

Pierre Pelletier, Kevin Wirtz

This paper investigates the relationship between scientists' cognitive profile and their ability to generate innovative ideas and gain scientific recognition. We propose a novel author-level metric based on the semantic representation of researchers' past publications to measure cognitive diversity both at individual and team levels. Using PubMed Knowledge G

Xintong Chen, Jiangbin Lyu, Liqun Fu

Intelligent reflecting surface (IRS) is regarded as a revolutionary paradigm that can reconfigure the wireless propagation environment for enhancing the desired signal and/or weakening the interference, and thus improving the quality of service (QoS) for communication systems. In this paper, we propose an IRS-aided sectorized BS design where the IRS is mount

Yang Huang, Michael Widom

Liquid state entropy formulas based on configurational probability distributions are examined for Lennard-Jones fluids across a range temperatures and densities. These formulas are based on expansions of the entropy in series of $n$-body distribution functions. We focus on two special cases. One, which we term the ``perfect gas'' series, starts with the entr

Ken Chen, Qiang Luo, Bin Xi, Hong-Gang Luo

The noncollinear spin textures provide promising avenues to stabilize exotic magnetic phases and excitations. They have attracted vast attention owning to their nontrivial band topology in the past decades. Distinct from the conventional route of involving the Dzyaloshinskii-Moriya interaction in a honeycomb magnet, the interplay of bond-dependent Kitaev and

Ruining Zhang, Haoran Han, Maolong Lv, Qisong Yang

Extensive utilization of deep reinforcement learning (DRL) policy networks in diverse continuous control tasks has raised questions regarding performance degradation in expansive state spaces where the input state norm is larger than that in the training environment. This paper aims to uncover the underlying factors contributing to such performance deteriora

Amrita Goswami, Alejandro Peña-Torres, Elvar Ö. Jónsson, Sergei A. Egorov

The structure of the solvation shell of aqueous Fe$^{+3}$ ion has been a subject of controversy due to discrepancies between experiments and different levels of theory. We address this issue by performing simulations for a wide range of ion concentrations, using various empirical potential energy functions, as well as density functional theory calculations o

Akram Abderraouf Gharbi, Ammar Chouchane, Mohcene Bessaoudi, Abdelmalik Ouamane

In this paper, we present a novel person reidentification (PRe-ID) system that based on tensor feature representation and multilinear subspace learning. Our approach utilizes pretrained CNNs for high-level feature extraction, along with Local Maximal Occurrence (LOMO) and Gaussian Of Gaussian (GOG ) descriptors. Additionally, Cross-View Quadratic Discriminan

Wang Zhang, Ziwen Ma, Subhro Das, Tsui-Wei Weng

Neural networks are powerful tools in various applications, and quantifying their uncertainty is crucial for reliable decision-making. In the deep learning field, the uncertainties are usually categorized into aleatoric (data) and epistemic (model) uncertainty. In this paper, we point out that the existing popular variance attenuation method highly overestim

Cosmin Constantin Popescu, Kiumars Aryana, Parth Garud, Khoi Phuong Dao

Programmable and reconfigurable optics hold significant potential for transforming a broad spectrum of applications, spanning space explorations to biomedical imaging, gas sensing, and optical cloaking. The ability to adjust the optical properties of components like filters, lenses, and beam steering devices could result in dramatic reductions in size, weigh

Mengxin Zheng, Jiaqi Xue, Xun Chen, YanShan Wang

Prompt tuning is one of the most effective solutions to adapting a fixed pre-trained language model (PLM) for various downstream tasks, especially with only a few input samples. However, the security issues, e.g., Trojan attacks, of prompt tuning on a few data samples are not well-studied. Transferring established data poisoning attacks directly to few-shot

Run-Ze Fan, Yixing Fan, Jiangui Chen, Jiafeng Guo

Automatic mainstream hashtag recommendation aims to accurately provide users with concise and popular topical hashtags before publication. Generally, mainstream hashtag recommendation faces challenges in the comprehensive difficulty of newly posted tweets in response to new topics, and the accurate identification of mainstream hashtags beyond semantic correc

Jane R. Rigby, Joaquin D. Vieira, Kedar A. Phadke, Taylor A. Hutchison

This paper gives an overview of TEMPLATES, a JWST Early Release Science program that targeted four extremely bright, gravitationally lensed galaxies: two extremely dusty, two with low attenuation, as templates for galaxy evolution studies with JWST. TEMPLATES obtains a common set of spectral diagnostics for these 1.3 < z < 4.2 galaxies, in particular H alpha

Maksim Zhdanov, Stanislav Dereka, Sergey Kolesnikov

Uncertainty estimation is crucial in safety-critical applications, where robust out-of-distribution (OOD) detection is essential. Traditional Bayesian methods, though effective, are often hindered by high computational demands. As an alternative, Laplace approximation offers a more practical and efficient approach to uncertainty estimation. In this paper, we

Dairui Liu, Boming Yang, Honghui Du, Derek Greene

News recommendations heavily rely on Natural Language Processing (NLP) methods to analyze, understand, and categorize content, enabling personalized suggestions based on user interests and reading behaviors. Large Language Models (LLMs) like GPT-4 have shown promising performance in understanding natural language. However, the extent of their applicability t

Belabbaci El Ouanas, Khammari Mohammed, Chouchane Ammar, Mohcene Bessaoudi

Kinship verification from face images is a novel and formidable challenge in the realms of pattern recognition and computer vision. This work makes notable contributions by incorporating a preprocessing technique known as Multiscale Retinex (MSR), which enhances image quality. Our approach harnesses the strength of complementary deep (VGG16) and shallow text

Chuangchuang Tan, Huan Liu, Yao Zhao, Shikui Wei

Recently, the proliferation of highly realistic synthetic images, facilitated through a variety of GANs and Diffusions, has significantly heightened the susceptibility to misuse. While the primary focus of deepfake detection has traditionally centered on the design of detection algorithms, an investigative inquiry into the generator architectures has remaine

Friedrich Philipp, Manuel Schaller, Karl Worthmann, Sebastian Peitz

Extended Dynamic Mode Decomposition (EDMD) is a popular data-driven method to approximate the Koopman operator for deterministic and stochastic (control) systems. This operator is linear and encompasses full information on the (expected stochastic) dynamics. In this paper, we analyze a kernel-based EDMD algorithm, known as kEDMD, where the dictionary consist

Dongrui Yu, Ziyang Chen, Xuan Yang, Yunlong Xu

High-precision time-interval measurement is a fundamental technique in many advanced applications, including time and distance metrology, particle physics, and ultra-precision machining. However, many of these applications are confined by the imprecise time-interval measurement of electrical signals, restricting the performance of the ultimate system to a fe

Ameen Ali, Hakan Cevikalp, Lior Wolf

Despite much research, Graph Neural Networks (GNNs) still do not display the favorable scaling properties of other deep neural networks such as Convolutional Neural Networks and Transformers. Previous work has identified issues such as oversmoothing of the latent representation and have suggested solutions such as skip connections and sophisticated normaliza

Kaiyou Song, Shan Zhang, Tong Wang

The development of autoregressive modeling (AM) in computer vision lags behind natural language processing (NLP) in self-supervised pre-training. This is mainly caused by the challenge that images are not sequential signals and lack a natural order when applying autoregressive modeling. In this study, inspired by human beings' way of grasping an image, i.e.,

Shangtong Cao, Ningyu He, Xinyu She, Yixuan Zhang

Wasm runtime is a fundamental component in the Wasm ecosystem, as it directly impacts whether Wasm applications can be executed as expected. Bugs in Wasm runtime bugs are frequently reported, thus our research community has made a few attempts to design automated testing frameworks for detecting bugs in Wasm runtimes. However, existing testing frameworks are

Danny Marfatia, Ye-Ling Zhou

We perform a phenomenological comparison of the gravitational wave (GW) spectrum expected from cosmic gauge string networks and superstring networks comprised of multiple string types. We show how violations of scaling behavior and the evolution of the number of relativistic degrees of freedom in the early Universe affect the GW spectrum. We derive simple an

Zhong-Kai Guo, Xiao-Yong Wang

We examined the output of a quantum Michelson interferometer incorporating the combined effects of nonlinear optomechanical interaction and time-varying gravitational fields. Our findings indicate a deviation from the standard relationship between the phase shift of the interferometer's output and the amplitude of gravitational waves. This deviation, a sligh

Xi Luo, Yu-Ge Chen, Ziqiang Wang, Yue Yu

Superconductors (SCs) with nontrivial topological band structures in the normal state have been discovered recently in bulk materials. When such SCs are made into thin films, quantum tunneling and Cooper pairing take place between the topological surface states (TSSs) on the opposing surfaces. Here, we find that chiral topological superconductivity with spon

M. Bhuyan, Raj Kumar, Shilpa Rana, D. Jain

In reply to the Comment made by M. V. Chushnyakova et al. on our paper [Phys. Rev. C 101, 044603 (2020)], we argue that the calculations, results and conclusions of our paper remain valid. We have shown here the calculations for one reaction using the deformed densities and the R3Y nucleon-nucleon potential obtained within the relativistic mean-field (RMF) f

E. Monteblanco, F. Garcia-Sanchez, M. Romera, D. Gusakova

We report the dynamic characterization of the spin-torque-driven in-plane precession modes of a spin-torque nano-oscillator based on two different synthetic ferrimagnets: a pinned one characterized by a strong RKKY interaction which is exchange coupled to an antiferromagnetic layer; and a second one, non-pinned characterized by weak RKKY coupling. The microw

Tobias Hurth, Robert Szafron

The subleading so-called resolved contributions represent the largest uncertainty in the inclusive decay mode $\bar B \to X_s \gamma$. However there had been no complete proof of factorization of these subleading contributions. This failure of factorisation can be traced back to endpoint divergences and cured by recently proposed refactorisation techniques.

Abhishek Pandey, Sudhir K. Pandey

The presence of complexity in the electronic structure of strongly correlated electron system NdCoO$_3$ (NCO) have sparked interest in the investigation of its physical properties. Here, we study the the Seebeck coefficient ($\alpha $) of NCO by using the combined experimental and DFT+$U$ based methods. The experimentally measured $\alpha $ is found to be $\

Xueying Du, Mingwei Liu, Hanlin Wang, Juntao Li

Software crash bugs cause unexpected program behaviors or even abrupt termination, thus demanding immediate resolution. However, resolving crash bugs can be challenging due to their complex root causes, which can originate from issues in the source code or external factors like third-party library dependencies. Large language models (LLMs) have shown promise

Asish Bera, Debotosh Bhattacharjee, Mita Nasipuri

Biometrics is indispensable in this modern digital era for secure automated human authentication in various fields of machine learning and pattern recognition. Hand geometry is a promising physiological biometric trait with ample deployed application areas for identity verification. Due to the intricate anatomic foundation of the thumb and substantial inter-

Marco Bagnara

We perturb the 3D Euler equations by a particular non-linear Stratonovich noise. We show the existence and uniqueness of a global-in-time (i.e. no blow-up) smooth solution. The result is a corollary of a more general theorem valid in an abstract framework, where the addition of such noise prevents the blow-up possibly induced by a drift with super-linear gro

Marco Salas-Nino, Grant Ritter, Daniel Hamdan, Tao Wang

As the digital world evolves, so do the threats to our security do too. Keyloggers were once a large threat to the cyber world. Though undergoing many transformations alongside the technological advancements of today, it is important to raise questions about the importance of Anti-Keyloggers in our current state of cyber security. This survey dives into the

Zi-Hao Li, Li-Li Zheng, Ying Wu, Xin-You Lü

The Schr\"{o}dinger cat state produced differently in two directions is anticipated to be a critical quantum resource in quantum information technologies. By exploring the interplay between quantum nonreciprocity and topology in a one-dimensional microcavity array, we obtain the Schr\"{o}dinger cat state ({\it a pure quantum state}) in a chosen direction at

Ricardo Escobedo, Roberto Santos-Silva, Claudia Moreno, Rafael Hernández-Jiménez

In this article, we analyze a 7-dimensional $BF$ theory that, upon dimensional reduction, transforms into an effective 4-dimensional action in which a generic metric is involved. A constraint is imposed in such a way that this is the Friedmann-Lema\^{i}tre-Robertson-Walker metric characterized by a scale factor $a(t)=\mathrm{exp}(H_0 t)$ with a Hubble consta

Fatma Kader Bingöl, Anne Quéguiner-Mathieu

We characterize isotropic trialitarian triples in terms of the Schur indices of the underlying algebras over a base field $F$ of arbitrary characteristic satisfying $I_q^3 F=0$. We also construct anisotropic trialitarian triples over such fields.

Amir M. Ahmadian, Matvey Soloviev, Musard Balliu

When specifying security policies for databases, it is often natural to formulate disjunctive dependencies, where a piece of information may depend on at most one of two dependencies P1 or P2, but not both. A formal semantic model of such disjunctive dependencies, the Quantale of Information, was recently introduced by Hunt and Sands as a generalization of t

Rhea Sanjay Sukthanker, Arjun Krishnakumar, Mahmoud Safari, Frank Hutter

Weight sharing is a fundamental concept in neural architecture search (NAS), enabling gradient-based methods to explore cell-based architectural spaces significantly faster than traditional black-box approaches. In parallel, weight-entanglement has emerged as a technique for more intricate parameter sharing amongst macro-architectural spaces. Since weight-en

Ruohuan Fang, Guansong Pang, Xiao Bai

Open-Vocabulary Object Detection (OVOD) aims to detect novel objects beyond a given set of base categories on which the detection model is trained. Recent OVOD methods focus on adapting the image-level pre-trained vision-language models (VLMs), such as CLIP, to a region-level object detection task via, eg., region-level knowledge distillation, regional promp

Wentao Yu, Hengtao He, Xianghao Yu, Shenghui Song

Holographic MIMO (HMIMO) is being increasingly recognized as a key enabling technology for 6G wireless systems through the deployment of an extremely large number of antennas within a compact space to fully exploit the potentials of the electromagnetic (EM) channel. Nevertheless, the benefits of HMIMO systems cannot be fully unleashed without an efficient me

Ashmin Bhattarai, Anuj Sedhai, Devraj Neupane, Manish Khadka

Tender notices are usually sought by most of the companies at regular intervals as a means for obtaining the contracts of various projects. These notices consist of all the required information like description of the work, period of construction, estimated amount of project, etc. In the context of Nepal, tender notices are usually published in national as w

Mads J. Damgaard

We carry out a Dirac sea reinterpretation of a discretized version of the Hamiltonian of quantum electrodynamics (QED), and analyze the perturbed vacuum in the continuum limit. We argue that if certain operators can be shown to be the self-adjoint, the perturbed vacuum will have solutions that converge nicely in this limit to states of the infinitesimal subs

Daniil Chivilikhin, Artem Pavlenko, Alexander Semenov

In the article, within the framework of the Boolean Satisfiability problem (SAT), the problem of estimating the hardness of specific Boolean formulas w.r.t. a specific complete SAT solving algorithm is considered. Based on the well-known Strong Backdoor Set (SBS) concept, we introduce the notion of decomposition hardness (d-hardness). If $B$ is an arbitrary

Shunsuke Horii, Yoichi Chikahara

Estimating heterogeneous treatment effects across individuals has attracted growing attention as a statistical tool for performing critical decision-making. We propose a Bayesian inference framework that quantifies the uncertainty in treatment effect estimation to support decision-making in a relatively small sample size setting. Our proposed model places Ga

Jun Liu, Tobias Tolle, Davide Zuzio, Jean-Luc Estivalezes

Geometric flux-based Volume-of-Fluid (VOF) methods are widely considered consistent in handling two-phase flows with high density ratios. However, although the conservation of mass and momentum is consistent for two-phase incompressible single-field Navier-Stokes equations without phase-change, discretization may easily introduce small inconsistencies that r

Oskar Henriksson, Lisa Seccia, Teresa Yu

Motivated by previous work on moment varieties for Gaussian distributions and their mixtures, we study moment varieties for two other statistically important two-parameter distributions: the inverse Gaussian and gamma distributions. In particular, we realize the moment varieties as determinantal varieties and find their degrees and singularities. We also pro

Ruibin Zeng, Minglong Lei, Lingfeng Niu, Lan Cheng

Combinatorial optimization (CO) on graphs is a classic topic that has been extensively studied across many scientific and industrial fields. Recently, solving CO problems on graphs through learning methods has attracted great attention. Advanced deep learning methods, e.g., graph neural networks (GNNs), have been used to effectively assist the process of sol