December 2023 arXiv papers — page 15

Yuanchen Zhao, Dong E. Liu

The robustness of quantum memory against physical noises is measured by two methods: the exact and approximate quantum error correction (QEC) conditions for error recoverability, and the decoder-dependent error threshold which assesses if the logical error rate diminishes with system size. Here we unravel their relations and propose a unified framework to ex

Yegor Zenkevich

We extend the dictionary between Type IIB branes and representations of the Ding-Iohara-Miki (DIM) algebra to the case when one of the space directions is a circle. It is well-known that the worldvolume theory on branes wrapping the circle is a 5d $\mathcal{N}=1$ gauge theory with adjoint matter, or more generally of cyclic quiver type, and the corresponding

Changming Huang, Ce Shang, Yaroslav V. Kartashov, Fangwei Ye

The existence of thresholdless vortex solitons trapped at the core of disclination lattices that realize higher-order topological insulators is reported. The study demonstrates the interplay between nonlinearity and higher-order topology in these systems, as the vortex state in the disclination lattice bifurcates from its linear topological counterpart, whil

Frederik Pfeiffer, Max Werninghaus, Christian Schweizer, Niklas Bruckmoser

To control and measure the state of a quantum system it must necessarily be coupled to external degrees of freedom. This inevitably leads to spontaneous emission via the Purcell effect, photon-induced dephasing from measurement back-action, and errors caused by unwanted interactions with nearby quantum systems. To tackle this fundamental challenge, we make u

Chen Gao, Haifeng Li, Xu Liu, Xiaodi Tan

We apply the U-Net model for compressive light field synthesis. Compared to methods based on stacked CNN and iterative algorithms, this method offers better image quality, uniformity and less computation.

Wei Hao, M. B. N. Kouwenhoven, Rainer Spurzem, Pau Amaro Seoane

Supermassive black holes (SMBHs) play an important role in galaxy evolution. Binary and triple SMBHs can form after galaxy mergers. A third SMBH may accelerate the SMBH merging process, possibly through the Kozai mechanism. We use N -body simulations to analyze oscillations in the orbital elements of hierarchical triple SMBHs with surrounding star clusters i

Kinyua Gikunda

This paper explores the dynamic landscape of Artificial Intelligence (AI) adoption in Africa, analysing its varied applications in addressing socio-economic challenges and fostering development. Examining the African AI ecosystem, the study considers regional nuances, cultural factors, and infrastructural constraints shaping the deployment of AI solutions. C

Federico Belliardo, Fabio Zoratti, Florian Marquardt, Vittorio Giovannetti

Quantum sensors offer control flexibility during estimation by allowing manipulation by the experimenter across various parameters. For each sensing platform, pinpointing the optimal controls to enhance the sensor's precision remains a challenging task. While an analytical solution might be out of reach, machine learning offers a promising avenue for many sy

Herbert De Gersem, Thomas Weiland

The air-gap macro element is reformulated such that rotation, rotor or stator skewing and rotor eccentricity can be incorporated easily. The air-gap element is evaluated using Fast Fourier Transforms which in combination with the Conjugate Gradient algorithm leads to highly efficient and memory inexpensive iterative solution scheme. The improved air-gap elem

Taicai Chen, Yue Duan, Dong Li, Lei Qi

Variational Autoencoder based Bayesian Optimization (VAE-BO) has demonstrated its excellent performance in addressing high-dimensional structured optimization problems. However, current mainstream methods overlook the potential of utilizing a pool of unlabeled data to construct the latent space, while only concentrating on designing sophisticated models to l

Tony J. Puthenpurakal

Let $(A,\mathfrak{m})$ be a regular local ring of dimension $d \geq 1$, $I$ an $\mathfrak{m}$-primary ideal. Let $N$ be a non-zero finitely generated $A$-module. Consider the functions \[ t^I(N, n) = \sum_{i = 0}^{ d}\ell(\text{Tor}^A_i(N, A/I^n)) \ \text{and}\ e^I(N, n) = \sum_{i = 0}^{ d}\ell(\text{Ext}_A^i(N, A/I^n)) \] of polynomial type and let their de

Xiaojian Yang, Yajun Zhu, Chang Liu, Kun Xu

The multi-frequency radiation transport equation (RTE) system models the photon transport and the energy exchange process between the background material and different frequency photons. In this paper, the unified gas-kinetic wave-particle (UGKWP) method for multi-frequency RTE is developed to capture the multiscale non-equilibrium transport in different opt

Taha Emre, Arunava Chakravarty, Antoine Rivail, Dmitrii Lachinov

Self-supervised learning (SSL) has emerged as a powerful technique for improving the efficiency and effectiveness of deep learning models. Contrastive methods are a prominent family of SSL that extract similar representations of two augmented views of an image while pushing away others in the representation space as negatives. However, the state-of-the-art c

Meixi Zheng, Xuanchen Yan, Zihao Zhu, Hongrui Chen

Adversarial examples are well-known tools to evaluate the vulnerability of deep neural networks (DNNs). Although lots of adversarial attack algorithms have been developed, it's still challenging in the practical scenario that the model's parameters and architectures are inaccessible to the attacker/evaluator, i.e., black-box adversarial attacks. Due to the p

Siddhartha Prasad, Ben Greenman, Tim Nelson, Shriram Krishnamurthi

Context: Students often misunderstand programming problem descriptions. This can lead them to solve the wrong problem, which creates frustration, obstructs learning, and imperils grades. Researchers have found that students can be made to better understand the problem by writing examples before they start programming. These examples are checked against corre

Tommaso Bradde, Stefano Grivet-Talocia, Quirin Aumann, Ion Victor Gosea

In recent years, the Adaptive Antoulas-Anderson AAA algorithm has established itself as the method of choice for solving rational approximation problems. Data-driven Model Order Reduction (MOR) of large-scale Linear Time-Invariant (LTI) systems represents one of the many applications in which this algorithm has proven to be successful since it typically gene

Reiner Hähnle, Ludovic Henrio

The context of this work is cooperative scheduling, a concurrency paradigm, where task execution is not arbitrarily preempted. Instead, language constructs exist that let a task voluntarily yield the right to execute to another task. The inquiry is the design of provably fair schedulers and suitable notions of fairness for cooperative scheduling languages. T

Nóra Szakács

We show that the category of $X$-generated $E$-unitary inverse monoids with greatest group image $G$ is equivalent to the category of $G$-invariant, finitary closure operators on the set of connected subgraphs of the Cayley graph of $G$. Analogously, we study $F$-inverse monoids in the extended signature $(\cdot, 1, ^{-1}, ^\mathfrak{m})$, and show that the

Jonas Rieger, Kostiantyn Yanchenko, Mattes Ruckdeschel, Gerret von Nordheim

Pre-trained language models (PLM) based on transformer neural networks developed in the field of natural language processing (NLP) offer great opportunities to improve automatic content analysis in communication science, especially for the coding of complex semantic categories in large datasets via supervised machine learning. However, three characteristics

Yeuk Hay Joshua Lam, Federico Moretti, Giovanni Passeri

Suppose $Y$ is a smooth variety equipped with a top form. We prove a simple theorem giving a sharp lower bound on the geometric genus of a family of subvarieties of $Y$, in terms of the dimension of this family. Two elementary applications are presented. On the one hand, we show that for a very general curve $C$ and a very general hypersurface $Y\subset \mat

Javier E. Pimás, Stefan Marr, Diego Garbervetsky

Object-oriented languages often use virtual machines (VMs) that provide mechanisms such as just-in-time (JIT) compilation and garbage collection (GC). These VM components are typically implemented in a separate layer, isolating them from the application. While this approach brings the software engineering benefits of clear separation and decoupling, it intro

Shao-Feng Ge, Pedro Pasquini, Liang Tan

We thoroughly explore the cosmic gravitational focusing of cosmic neutrino fluid (C$\nu$F) by dark matter (DM) halo using both general relativity for a point source of gravitational potential and Boltzmann equations for continuous overdensities. Derived in the general way for both relativistic and non-relativistic neutrinos, our results show that the effect

Qi Hao, Di Zhou, Min Sheng, Yan Shi

Multi-layer ultra-dense satellite networks (MLUDSNs) have soared this meteoric to provide vast throughputd for globally diverse services. Differing from traditional monolayer constellations, MLUDSNs emphasize the spatial integration among layers, and its throughput may not be simply the sum of throughput of each layer. The hop-count of cross-layer communicat

D. L. Mihaylov, J. Haidenbauer, V. Mantovani Sarti

This work provides the first combined analysis of low-energy p$\Lambda$ scattering, considering both cross section and correlation data. The obtained results establish the most stringent constraints to date on the two-body p$\Lambda$ interaction, pointing to a weaker attraction than so far accepted. The best set of scattering lengths for the spin singlet and

Zeynab Samandari, Seyyedeh Fatemeh Molaeezadeh

Potassium disorders are generally asymptomatic, potentially lethal, and common in patients with renal or cardiac disease. The morphology of the electrocardiogram (ECG) signal is very sensitive to the changes in potassium ions, so ECG has a high potential for detecting dyskalemias before laboratory results. In this regard, this paper introduces a new system f

Chiara Cignarella, Davide Campi, Nicola Marzari

One-dimensional materials have gained much attention in the last decades: from carbon nanotubes to ultrathin nanowires, to few-atom atomic chains, these can all display unique electronic properties and great potential for next-generation applications. Exfoliable bulk materials could naturally provide a source for one-dimensional wires with well defined struc

John Rankin, Vadim Kravtsov, Fabio Muleri, Juri Poutanen

X-ray binary systems consist of a companion star and a compact object in close orbit. Thanks to their copious X-ray emission, these objects have been studied in detail using X-ray spectroscopy and timing. The inclination of these systems is a major uncertainty in the determination of the mass of the compact object using optical spectroscopic methods. In this

Ajjath A H, Ekta Chaubey, Hua-Sheng Shao

We present the analytic and compact two-loop helicity amplitudes for QCD and QED corrections to the light-by-light scattering process with massive internal fermions. We express the master integrals either in terms of multiple polylogarithms or in terms of iterated integrals with dlog one-forms. We also elaborate on optimizing the analytic results for each ph

Hichem Sahbi

We introduce a novel interactive satellite image change detection algorithm based on active learning. The proposed method is iterative and consists in frugally probing the user (oracle) about the labels of the most critical images, and according to the oracle's annotations, it updates change detection results. First, we consider a probabilistic framework whi

Nicolás Honorato-Droguett, Kazuhiro Kurita, Tesshu Hanaka, Hirotaka Ono

In well-studied graph modification problems, adding and deleting vertices and edges are used as graph editing operations. We propose a model for graph modification on geometric intersection graphs called Geometric Graph Edit Distance that moves objects as an edit operation. Our results are mainly focused on interval graphs. In particular, we give a linear-ti

Yichong Xia, Yujun Huang, Bin Chen, Haoqian Wang

Multi-view compression technology, especially Stereo Image Compression (SIC), plays a crucial role in car-mounted cameras and 3D-related applications. Interestingly, the Distributed Source Coding (DSC) theory suggests that efficient data compression of correlated sources can be achieved through independent encoding and joint decoding. This motivates the rapi

Kiran V, Toby Joseph

A Brownian particle moving in a staircase-like potential with feedback control offers a way to implement Maxwell's demon. An experimental demonstration of such a system using sinusoidal periodic potential carried out by Toyabe et al. has shown that information about the particle's position can be converted to useful work. In this paper, we carry out a numeri

Yuming Wei, Han Zhang

Via multilinear algebra, we formulate a criterion for connectedness in the parametric geometry of numbers in terms of pencils, which are certain algebraic varieties in the space of matrices. As a consequence, we obtain a connectedness result for generic lattices arising from Diophantine approximation on analytic submanifolds, and sharpen Schmidt and Summerer

Yamato Arai, Yuma Ichikawa, Koji Hukushima

This study proposes the "adaptive flip graph algorithm", which combines adaptive searches with the flip graph algorithm for finding fast and efficient methods for matrix multiplication. The adaptive flip graph algorithm addresses the inherent limitations of exploration and inefficient search encountered in the original flip graph algorithm, particularly when

Irfan Manisali, Okyanus Oral, Figen S. Oktem

Near-field multiple-input multiple-output (MIMO) radar imaging systems have recently gained significant attention. In this paper, we develop novel non-iterative deep learning-based reconstruction methods for real-time near-field MIMO imaging. The goal is to achieve high image quality with low computational cost at compressive settings. The developed approach

Marzia Mazzotta

This survey aims to collect the main results of the theory of the set-theoretical solutions to the pentagon equation obtained up to now in the literature. In particular, we present some classes of solutions and raise some questions.

Yuki Yamaguchi, Toshiaki Aoki

Recently, the evolution of deep learning has promoted the application of machine learning (ML) to various systems. However, there are ML systems, such as autonomous vehicles, that cause critical damage when they misclassify. Conversely, there are ML-specific attacks called adversarial attacks based on the characteristics of ML systems. For example, one type

Ajjath A H, Ekta Chaubey, Mathijs Fraaije, Valentin Hirschi

The recent experimental observation of Light-by-Light (LbL) scattering at the Large Hadron Collider has revived interest in this fundamental process, and especially of the accurate prediction of its cross-section, which we present here for the first time at Next-to-Leading Order (NLO) in both QCD and QED. We compare two radically different computational appr

Dongfen Bian, Emmanuel Grenier

This article gathers notes of two lectures given at Grenoble's University in June $2023$, and is an introduction to recent works on shear layers, in collaboration with D. Bian, Y. Guo, T. Nguyen and B. Pausader.

Yue Han, Jinguang Han, Weizhi Meng, Jianchang Lai

Public key searchable encryption (PKSE) scheme allows data users to search over encrypted data. To identify illegal users, many traceable PKSE schemes have been proposed. However, existing schemes cannot trace the keywords which illegal users searched and protect users' privacy simultaneously. In some practical applications, tracing both illegal users' ident

Zeyi Wang, Wenxin Zhang, Brian S Caffo, Martin Lindquist

We introduce the Meta Highly-Adaptive-Lasso Minimum Loss Estimator (M-HAL-MLE), a novel ensemble approach for estimating functional parameters of realistically modeled data distribution from independent and identically distributed observations. Given $J$ initial estimators, candidate ensembles are generated by finite-sectional-variation cadlag functions. Usi

Yan Ding, Hao Cheng, Ziliang Ye, Ruyi Feng

We propose Adjustable Molecular Representation (AdaMR), a new large-scale uniform pre-training strategy for small-molecule drugs, as a novel unified pre-training strategy. AdaMR utilizes a granularity-adjustable molecular encoding strategy, which is accomplished through a pre-training job termed molecular canonicalization, setting it apart from recent large-

Huyen Thanh Phan, Keiki Koizumi, Feng Liu, Katsunori Wakabayashi

The biphenylene network (BPN) has a unique two-dimensional atomic structure, where hexagonal unit cells are arranged on a square lattice. Inspired by such a BPN structure, we design a counterpart in the fashion of photonic crystals (PhCs), which we refer to as the BPN PhC. We study the photonic band structure using the finite element method and characterize

Kyoji Saito

We construct second homotopy classes associated with twins of non-cancellative tuples of a monoid, where the monoid is defined by the semi-positive fundamental relations of the fundamental group of a CW-complex. As an application, we reconstruct the second homotopy classes for the complement of generic lines arrangement studied by Akio Hattori. We aim to app

Alexander Alexandrov, Boris Bychkov, Petr Dunin-Barkowski, Maxim Kazarian

We introduce a new concept of logarithmic topological recursion that provides a patch to topological recursion in the presence of logarithmic singularities and prove that this new definition satisfies the universal $x-y$ swap relation. This result provides a vast generalization and a proof of a very recent conjecture of Hock. It also uniformly explains (and

Geyan Ye, Xibao Cai, Houtim Lai, Xing Wang

Recently, the impressive performance of large language models (LLMs) on a wide range of tasks has attracted an increasing number of attempts to apply LLMs in drug discovery. However, molecule optimization, a critical task in the drug discovery pipeline, is currently an area that has seen little involvement from LLMs. Most of existing approaches focus solely

James H. Muten, Louise H. Frankland, Edward McCann

We model the electronic properties of thin films of binary compounds with stacked layers where each layer is a two-dimensional honeycomb lattice with two atoms per unit cell. The two atoms per cell are assigned different onsite energies in order to consider six different stacking orders: ABC, ABA, AA, ABC$^{\prime}$, ABA$^{\prime}$, and AA$^{\prime}$. Using

Dexie Lin

For a compact K\"ahler manifold, it is well-established that its de Rham cohomology satisfies the Hard Lefschetz condition, which is reflected in the equality between the Betti numbers and the Hodge numbers. A special subclass of symplectic manifolds also adheres to this condition. Cirici and Wilson \cite{CW20} employ the variant Hodge number to propose a su

Federico Cantero-Morán, Sergio García-Rodrigo, Marithania Silvero

As part of their construction of the Khovanov spectrum, Lawson, Lipshitz and Sarkar assigned to each cube in the Burnside category of finite sets and finite correspondences, a finite cellular spectrum. In this paper we extend this assignment to cubes in Burnside categories of infinite sets. This is later applied to the work of Akhmechet, Krushkal and Willis

Pinjun Zheng, Xing Liu, Yuchen Zhang, Jiguang He

The contemporary landscape of wireless technology underscores the critical role of precise localization services. Traditional global navigation satellite systems (GNSS)-based solutions, however, fall short when it comes to indoor environments, and existing indoor localization techniques such as electromagnetic fingerprinting methods face challenges of additi

Saibal Ray, R. Bhattacharya, Sanjay K. Sahay, Abdul Aziz

In this paper, we review the theoretical basis for generation of gravitational waves and the detection techniques used to detect a gravitational wave. To materialize this goal in a thorough way we first start with a mathematical background for general relativity from which a clue for gravitational wave was conceived by Einstein. Thereafter we give the classi

Ron Erez

Piatetski-Shapiro the concept of CAP representations was introduced, elucidating the Saito-Kurokawa representations of $PGSp(4)$. In this paper we present a family of CAP representations for the group $Sp_{4n}(\mathbb A)$ through the application of the theta correspondence and Howe duality to the reductive dual pair $(O_{2n}(\mathbb A) , Sp_{4n}(\mathbb A))$

Roger A. Sauer, Zhihui Zou, Thomas J. R. Hughes

This work presents a new hybrid discretization approach to alleviate membrane locking in isogeometric finite element formulations for Kirchhoff-Love shells. The approach is simple, and requires no additional dofs and no static condensation. It does not increase the bandwidth of the tangent matrix and is effective for both linear and nonlinear problems. It co

Mingxiang Cao, Weiying Xie, Jie Lei, Jiaqing Zhang

Deep learning has driven significant progress in object detection using Synthetic Aperture Radar (SAR) imagery. Existing methods, while achieving promising results, often struggle to effectively integrate local and global information, particularly direction-aware features. This paper proposes SAR-Net, a novel framework specifically designed for global fusion

Maria Frasca, Davide La Torre, Gabriella Pravettoni, Ilaria Cutica

Parkinson's disease is a neurological condition that occurs in nearly 1% of the world's population. The disease is manifested by a drop in dopamine production, symptoms are cognitive and behavioural and include a wide range of personality changes, depressive disorders, memory problems, and emotional dysregulation, which can occur as the disease progresses. E

Ashish Mor, Surbhi Gupta, Manju Kashyap

This research paper focuses on exploring two Complex-valued function's fractional derivative, specifically the Hurwitz Zeta function and Jacobi theta function. The study is based on the Complex Generalization of Grunwald-Letnikov Fractional derivative which adheres to the generalized version of the Leibniz rule. Within this paper, we present and establish an

Luisa Andreis, Gianmarco Bet, Maxence Phalempin

We study the near-critical behavior of the sparse Erd\H{o}s-R\'enyi random graph $\mathcal{G}(n,p)$ on $n\gg1$ vertices, where the connection probability $p$ satisfies $np = 1+\theta(b_n^2/n)^{1/3}$, with $n^{3/10}\ll {b_n}\ll n^{1/2}$, and $\theta\in\mathbb{R}$. To this end, we introduce an empirical measure that describes connected components of $\mathcal{

Amirhossein Javaheri, Arash Amini, Farokh Marvasti, Daniel P. Palomar

Learning a graph from data is the key to taking advantage of graph signal processing tools. Most of the conventional algorithms for graph learning require complete data statistics, which might not be available in some scenarios. In this work, we aim to learn a graph from incomplete time-series observations. From another viewpoint, we consider the problem of

Dongfen Bian, Emmanuel Grenier

The aim of this paper is to describe the long time behavior of solutions of linearized Navier Stokes equations near a concave shear layer profile in the long waves regime, namely for small horizontal Fourier variable $\alpha$, when the viscosity $\nu$ vanishes. We show that the solutions converge exponentially to $0$, except in some range of $\alpha$, namely

Hua Xiao, Long Ji, Peng Zhang, Lorenzo Ducci

We report timing and spectral studies of the high mass X-ray binary 4U 1700-37 using Insight-HXMT observations carried out in 2020 during its out-of-eclipse state. We found significant variations in flux on a time-scale of kilo-seconds, while the hardness (count rate ratio between 10-30 keV and 2-10 keV) remains relatively stable. No evident pulsations were

Qi Xu

Driven by the term "the arrow of time" as a general topic, the article develops a musical discussion by referring to the etymological origin of the term: philosophy (epistemology) and physics (thermodynamics). In particular, the article explores two specific conditions: distinguishability and unique orientability, from which the article derives respective mu

Davide Bianchi, Davide Evangelista, Stefano Aleotti, Marco Donatelli

We investigate a variational method for ill-posed problems, named $\texttt{graphLa+}\Psi$, which embeds a graph Laplacian operator in the regularization term. The novelty of this method lies in constructing the graph Laplacian based on a preliminary approximation of the solution, which is obtained using any existing reconstruction method $\Psi$ from the lite

Antônio Junior Alves Caiado, Michael Hahsler

$ $The usage of generative artificial intelligence (AI) tools based on large language models, including ChatGPT, Bard, and Claude, for text generation has many exciting applications with the potential for phenomenal productivity gains. One issue is authorship attribution when using AI tools. This is especially important in an academic setting where the inapp

Xinyu Ma, Chijie Zhuang, She Wang, Rong Zeng

Integrated optical electric field sensors (IOES) play a crucial role in electric field measurement. This paper introduces the principles of the IOES and quantitatively evaluates the impact of humidity on measurement accuracy. Sensors with different levels of hydrophobicity coatings and hygroscopicity shells are fabricated and tested across the relative humid

José Luis Carmona Jiménez, Marco Castrillón López, José Carlos Díaz-Ramos

We characterize isometric actions whose principal orbits are hypersurfaces through the existence of a linear connection satisfying a set of covariant equations in the same spirit as the Ambrose-Singer Theorem for homogeneous space. These results are then used to describe isometric cohomogeneity one foliations in terms of such connections. Finally, we provide

Jianping Jiang, Xinyu Zhou, Peiqi Duan, Boxin Shi

Event cameras and RGB cameras exhibit complementary characteristics in imaging: the former possesses high dynamic range (HDR) and high temporal resolution, while the latter provides rich texture and color information. This makes the integration of event cameras into middle- and high-level RGB-based vision tasks highly promising. However, challenges arise in

V. S. Lamego, D. G. Braga, W. F. Balthazar, J. A. O. Huguenin

We perform an experimental investigation of Quantum Discord with Spin-Orbit X-states. These states are prepared through the incoherent superposition of different laser beans, where a two-level system is encoded in polarization and the first-order Hermitian-Gaussian modes, as proposed in Phys. Rev. A 103,0022411 (2022). We characterize different classes of sp

Yuhang Zhang, Yuang Deng, Xiaopeng Zhang, Jie Li

Active learning has been demonstrated effective to reduce labeling cost, while most progress has been designed for image recognition, there still lacks instance-level active learning for object detection. In this paper, we rethink two key components, i.e., localization and recognition, for object detection, and find that the correctness of them are highly re

Ekaterina Poslavskaya, Alexey Korolev

Categorical features are present in about 40% of real world problems, highlighting the crucial role of encoding as a preprocessing component. Some recent studies have reported benefits of the various target-based encoders over classical target-agnostic approaches. However, these claims are not supported by any statistical analysis, and are based on a single

Wei Wang

This paper studies eight families of infinite series involving hyperbolic functions. Under some conditions, these series are linear combinations of derivatives of Eisenstein series. The paper gives a systematic method for computing the values of these series at CM points. The approach utilizes complex multiplication theory, the structure of the rings of modu

Aekta Aggarwal, Helge Holden, Ganesh Vaidya

We discuss a class of coupled systems of nonlocal nonlinear balance laws modeling multilane traffic, with the nonlocality present in both convective and source terms. The uniqueness and existence of the entropy solution are proven via doubling of the variables arguments and convergent finite volume approximations, respectively. The primary goal is to establi

Genadi Levin

We apply some methods and technique of complex dynamics to study the set of symmetries of attractors of holomorphic Iterated Function Systems (IFS), as well as relations between IFS sharing the same attractor.

Marina Kholod, Nikita Mokrenko

Consumer choice modeling takes center stage as we delve into understanding how personal preferences of decision makers (customers) for products influence demand at the level of the individual. The contemporary choice theory is built upon the characteristics of the decision maker, alternatives available for the choice of the decision maker, the attributes of

Renchi Yang, Jieming Shi

A bipartite graph contains inter-set edges between two disjoint vertex sets, and is widely used to model real-world data, such as user-item purchase records, author-article publications, and biological interactions between drugs and proteins. k-Bipartite Graph Clustering (k-BGC) is to partition the target vertex set in a bipartite graph into k disjoint clust

Chao Wang, Nan Jian, Meijie Yin, Xi Zhang

The emergence of bulk carbon ferromagnetism is long-expected over years. At nanoscale, carbon ferromagnetism was detected by analyzing the magnetic edge states via scanning tunneling microscopy(STM), and its origin can be explained by local redistribution of electron wave function. In larger scale, carbon ferromagnetism can be created by deliberately produci

Saugata Barat, Jean-Michel Désert, Allona Vazan, Robin Baeyens

Young transiting exoplanets offer a unique opportunity to characterize the atmospheres of fresh and evolving products of planet formation. We present the transmission spectrum of V1298 Tau b; a 23 Myr old warm Jovian sized planet orbiting a pre-main sequence star. We detect a primordial atmosphere with an exceptionally large atmospheric scale height and a wa

Julián Haddad, Alexander Koldobsky

Generalizing the slicing inequality for functions on convex bodies from [11], it was proved in [4] that there exists an absolute constant $c$ so that for any $n\in \mathbb N$, any $q\in [0,n-1)$ which is not an odd integer, any origin-symmetric convex body $K$ of volume one in $\mathbb R^n$ and any infinitely smooth probability density $f$ on $K$ we have $$\

Alberto Natali, Geert Leus

In this paper, we present a novel convolution theorem which encompasses the well known convolution theorem in (graph) signal processing as well as the one related to time-varying filters. Specifically, we show how a node-wise convolution for signals supported on a graph can be expressed as another node-wise convolution in a frequency domain graph, different

Shi-Xian Sun, Yong-Qiang Wang

In this article, we investigate the stationary, soliton-like solutions in the model of the Einstein gravity coupled to a free and complex scalar field, and extend chains of mini-boson stars to the rotating case. These solutions manifest as multiple rotating mini-boson stars uniformly arranged along the rotation axis. Through numerical methods, we obtain chai

Yoshiaki Misugi, Shu-ichiro Inutsuka, Doris Arzoumanian, Yusuke Tsukamoto

The angular momentum of molecular cloud cores plays a key role in the star formation process. However, the evolution of the angular momentum of molecular cloud cores formed in magnetized molecular filaments is still unclear. In this paper, we perform three-dimensional magnetohydrodynamics simulations to reveal the effect of the magnetic field on the evolutio

Chuangqiang Hu, Xiao-Min Huang

The primary objective of this paper is to derive explicit formulas for rank one and rank two Drinfeld modules over a specific domain denoted by A. This domain corresponds to the projective line associated with an infinite place of degree two. To achieve the goals, we construct a pair of standard Drinfeld modules whose coefficients are in the Hilbert class fi

Qingqing Wu, Beixiong Zheng, Changsheng You, Lipeng Zhu

Intelligent surfaces (ISs) have emerged as a key technology to empower a wide range of appealing applications for wireless networks, due to their low cost, high energy efficiency, flexibility of deployment and capability of constructing favorable wireless channels/radio environments. Moreover, the recent advent of several new IS architectures further expande

Dixiang Zhang, Junyu Lu, Pingjian Zhang

Integrating lexicon into character-level sequence has been proven effective to leverage word boundary and semantic information in Chinese named entity recognition (NER). However, prior approaches usually utilize feature weighting and position coupling to integrate word information, but ignore the semantic and contextual correspondence between the fine-graine

Chaojie Mao, Zeyinzi Jiang

Res-Tuning introduces a flexible and efficient paradigm for model tuning, showing that tuners decoupled from the backbone network can achieve performance comparable to traditional methods. Existing methods commonly construct the tuner as a set of trainable low-rank decomposition matrices, positing that a low-rank subspace suffices for adapting pre-trained fo

Włodzimierz J. Charatonik, Aleksandra Kwiatkowska, Robert P. Roe, Shujie Yang

We continue the study of projective Fra\"iss\'e limits developed by Irwin-Solecki and Panagiotopoulos-Solecki by investigating families of epimorphisms between finite trees and finite rooted trees. Ideas of monotone, confluent, and light mappings from continuum theory as well as several properties of continua are modified so as to apply them to topological g

Gaosheng Liu, Lin Wang

The rising demand for sustainable IoT has promoted the adoption of battery-free devices intermittently powered by ambient energy for sensing. However, the intermittency poses significant challenges in sensing data collection. Despite recent efforts to enable one-to-one communication, routing data across multiple intermittently-powered battery-free devices, a

Ga-Eun Kim, Chang-Hwan Son

The pests captured with imaging devices may be relatively small in size compared to the entire images, and complex backgrounds have colors and textures similar to those of the pests, which hinders accurate feature extraction and makes pest identification challenging. The key to pest identification is to create a model capable of detecting regions of interest

Mahmoud AlHallak

In this work we present a new framework of the gravity sector by considering the extension $F(R,w)$, in which $R$ is the Ricci scalar and $w$ is the equation of state. Three different choices of function $F(R,w)$ are investigated under the Palatini formalism. The models appear equivalent to $F(R)$ models of gravity with effective momentum-energy tensors. For

Rain Jha, Nishchal Dwivedi

Novae, explosive events in binary star systems involving a white dwarf and a companion star, offer profound insights into extreme astrophysical conditions. During the eruption of a nova, material accreted onto the white dwarf's surface undergoes a thermonuclear runaway reaction resulting in the ejection of matter into space and the formation of a luminous sh

Lorenzo Taggi, Wei Wu

We study a generalisation of the double-dimer model that encompasses several models of interest, including the monomer double-dimer model, spatial random permutations, the dimer model, and the spin $O(N)$ model, and which is also related to the loop $O(N)$ model. We show that on two-dimensional-like graphs (such as slabs), both the correlation function and t

Subrat Senapati, Anuradha Banerjee, R. Rajesh

Acoustic emission (AE) activity data resulting from the fracture processes of brittle materials is valuable real time information regarding the evolving state of damage in the material. Here, through a combined experimental and computational study we explore the possibility of utilising the statistical signatures of AE activity data for characterisation of d

Jin Mao, Ke Xiong, Ming Liu, Zhijin Qin

Recently, semantic communication (SC) has been regarded as one of the potential paradigms of 6G. Current SC frameworks require channel state information (CSI) to handle severe signal distortion induced by channel fading. Since the channel estimation overhead for obtaining CSI cannot be neglected, we therefore propose a generative adversarial network (GAN) ba

Yi Li, Xiutao Feng, Qiang Wang

Permutation polynomials with few terms (especially permutation binomials) attract many people due to their simple algebraic structure. Despite the great interests in the study of permutation binomials, a complete characterization of permutation binomials is still unknown. In this paper, we give a classification of permutation binomials of the form $x^i+ax$ o

Hongyi Sun, Dehua Wen

The tidal deformability and the radius of neutron stars are observables, which have been used to constrain the neutron star equation of state and explore the composition in neutron stars. We investigated the radius and tidal deformability of dark matter admixed neutron stars (DANSs) by utilizing the two-fluid TOV equations. Assuming that the dark matter mode

Wenyi Tan, Yang Li, Chenxing Zhao, Zhunga Liu

Object detection is a fundamental task in various applications ranging from autonomous driving to intelligent security systems. However, recognition of a person can be hindered when their clothing is decorated with carefully designed graffiti patterns, leading to the failure of object detection. To achieve greater attack potential against unknown black-box m

Sungyoon Cho, Qiao He, Zhiyu Zhang

In this article, we prove that a version of Tate conjectures for certain Deligne-Lusztig varieties implies the Kudla-Rapoport conjecture for unitary Shimura varieties with maximal parahoric level at unramified primes. Furthermore, we prove that the Kudla-Rapoport conjecture holds unconditionally for several new cases in any dimension.

Cheng-En Wu, Azadeh Davoodi, Yu Hen Hu

This paper presents a novel approach to network pruning, targeting block pruning in deep neural networks for edge computing environments. Our method diverges from traditional techniques that utilize proxy metrics, instead employing a direct block removal strategy to assess the impact on classification accuracy. This hands-on approach allows for an accurate e

Sho Takase, Shun Kiyono, Sosuke Kobayashi, Jun Suzuki

Loss spikes often occur during pre-training of large language models. The spikes degrade the performance of large language models and sometimes ruin the pre-training. Since the pre-training needs a vast computational budget, we should avoid such spikes. Based on the assumption that the loss spike is caused by the sudden growth of the gradient norm, we explor

Kaiyue Zhou, Ming Dong, Peiyuan Zhi, Shengjin Wang

Numerous point-cloud understanding techniques focus on whole entities and have succeeded in obtaining satisfactory results and limited sparsity tolerance. However, these methods are generally sensitive to incomplete point clouds that are scanned with flaws or large gaps. In this paper, we propose an end-to-end architecture that compensates for and identifies

Ratchaphat Nakarachinda, Chakrit Pongkitivanichkul, Daris Samart, Lunchakorn Tannukij

In this work, the holographic dark energy model is constructed by using the non-extensive nature of the Schwarzschild black hole via the R\'enyi entropy. Due to the non-extensivity, the black hole can be stable under the process of fixing the non-extensive parameter. A change undergoing such a process would then motivate us to define the energy density of th