May 2024 arXiv papers — page 141

Shima Esfandiari, Seyed Mostafa Fakhrahmad

Graph mining is an important technique that used in many applications such as predicting and understanding behaviors and information dissemination within networks. One crucial aspect of graph mining is the identification and ranking of influential nodes, which has applications in various fields including marketing, social communications, and disease control.

Heng Zhang, Zhu An, Jingjun Zhu, Hong Huang

Absolute measurements were conducted to study the bremsstrahlung emission from ~5-25 keV electrons incident on three thick solid conductive compounds of MoSi$_2$, TiB$_2$ and ZrB$_2$. The additivity approximation was applied in the Monte Carlo PENELOPE simulations for compounds and mixtures. The results showed that in general the experimental bremsstrahlung

Yiqi Chen, Tobias Oechtering, Holger Boche, Mikael Skoglund

Distribution-preserving integrated sensing and communication with secure reconstruction is investigated in this paper. In addition to the distortion constraint, we impose another constraint on the distance between the reconstructed sequence distribution and the original state distribution to force the system to preserve the statistical property of the channe

Nitya Sathyavageeswaran, Roy D. Yates, Anand D. Sarwate, Narayan Mandayam

Future real-time applications like smart cities will use complex Machine Learning (ML) models for a variety of tasks. Timely status information is required for these applications to be reliable. Offloading computation to a mobile edge cloud (MEC) can reduce the completion time of these tasks. However, using the MEC may come at a cost such as related to use o

U. Özdem

We systematically explore their electromagnetic characteristics to improve our understanding of the quark-gluon dynamics underlying the complex and controversial nature of multiquark systems. In this study, the magnetic dipole moments of $ D \Sigma_c$, $ D \Sigma_c^{*}$ and $ D^{*} \Sigma_c$ doubly-charmed pentaquarks are extracted, which are directly relate

Jiayi Chen, Chunhua Deng

With the advancement of video analysis technology, the multi-object tracking (MOT) problem in complex scenes involving pedestrians is gaining increasing importance. This challenge primarily involves two key tasks: pedestrian detection and re-identification. While significant progress has been achieved in pedestrian detection tasks in recent years, enhancing

Xiaolei Zhang

In this note, we show that a ring $R$ is $S$-coherent if and only if every finitely presented $R$-module is $S$-coherent, providing a positive answer to a question proposed in [D. Bennis, M. El Hajoui, {\it On $S$-coherence}, J. Korean Math. Soc. \textbf{55} (2018), no.6, 1499-1512]. Besides, we show that $c$-$S$-coherent rings are $S$-coherent, and give an

A. Rezaei-Aghdam, A. Taghavi

We construct an integrable sigma model with a generalized $\mathcal{F}$ structure, which involves a generalized Nijenhuis structure $\mathcal{J}$ satisfying $\mathcal{J}^{3}=-\mathcal{J}$. Utilizing the expression of the generalized complex structure on the metric Lie group manifold $G$ in terms of operator relations on its Lie algebra $\mathfrak{g}$, we for

Mohamed Zaki, Mostafa Abouricha, Said Amrane

In this study, we revealed the impact of the pumping scheme, fiber length, pumping power, and reflectivity of the output fiber Bragg grating on the performance of a Tm^3+ -doped fiber laser (TDFL) operating at a wavelength of 1.72 \mu m. Using numerical simulations, we optimized the output power and reduced losses due to reabsorption; as well as amplified sp

S. Bittner, M. Sciamanna

Broad-area semiconductor lasers are employed in many high-power applications, however, their spatio-temporal dynamics is complex and intrinsically unstable due to the interaction of several transverse lasing modes. A dynamical and spatio-spectral analysis with ultra-high resolution of commercial broad-area lasers reveals multiplets of phase-locked first- and

Kiroong Choe, Eunhye Kim, Sangwon Park, Jinwook Seo

Visualizing citation relations with network structures is widely used, but the visual complexity can make it challenging for individual researchers trying to navigate them. We collected data from 18 researchers with an interface that we designed using network simplification methods and analyzed how users browsed and identified important papers. Our analysis

Tanner Andrulis, Gohar Irfan Chaudhry, Vinith M. Suriyakumar, Joel S. Emer

Photonics is a promising technology to accelerate Deep Neural Networks as it can use optical interconnects to reduce data movement energy and it enables low-energy, high-throughput optical-analog computations. To realize these benefits in a full system (accelerator + DRAM), designers must ensure that the benefits of using the electrical, optical, analog, and

Nicholas Jäger, Andreas Aßmuth

We propose a decentralized authentication system for networks of unmanned aerial vehicles. A blockchain-based public key infrastructure allows the usage of public key cryptography and public key based authentication protocols. The blockchain provides a common storage of the public keys and their relations and can provide the required information for the auth

V. Arvind Rameshwar, Nir Weinberger

We investigate the fundamental limits of reliable communication over multi-view channels, in which the channel output is comprised of a large number of independent noisy views of a transmitted symbol. We consider first the setting of multi-view discrete memoryless channels and then extend our results to general multi-view channels (using multi-letter formula

Eyal Orbach, Lev Haikin, Nelly David, Avi Faizakof

Dense vector representations for sentences made significant progress in recent years as can be seen on sentence similarity tasks. Real-world phrase retrieval applications, on the other hand, still encounter challenges for effective use of dense representations. We show that when target phrases reside inside noisy context, representing the full sentence with

Yaxiong Liu, Zhuo Liu, Hui Yang, Xiangyu Zhou

In this paper, we obtain a Le Potier-type isomorphism theorem twisted with multiplier submodule sheaves, which relates a holomorphic vector bundle endowed with a strongly Nakano semipositive singular Hermitian metric to the tautological line bundle with the induced metric. As applications, we obtain a Koll\'ar-type injectivity theorem, a Nadel-type vanishing

Xiang Li, Jian Song, Zhigang Zhao, Chunxiao Wang

This study introduces a novel Supervised Info-enhanced Contrastive Learning framework for EEG based Emotion Recognition (SICLEER). SI-CLEER employs multi-granularity contrastive learning to create robust EEG contextual representations, potentiallyn improving emotion recognition effectiveness. Unlike existing methods solely guided by classification loss, we p

Tanner Andrulis, Joel S. Emer, Vivienne Sze

Compute-In-Memory (CiM) is a promising solution to accelerate Deep Neural Networks (DNNs) as it can avoid energy-intensive DNN weight movement and use memory arrays to perform low-energy, high-density computations. These benefits have inspired research across the CiM stack, but CiM research often focuses on only one level of the stack (i.e., devices, circuit

Alena Romanova, Peter van Loock

We address the challenge of incorporating encoded quantum memories into an exact secret key rate analysis for small and intermediate-scale quantum repeaters. To this end, we introduce the check matrix model and quantify the resilience of stabilizer codes of up to eleven qubits against Pauli noise, obtaining analytical expressions for effective logical error

Mohammad Amaz Uddin, Muhammad Nazrul Islam, Leandros Maglaras, Helge Janicke

SMS, or short messaging service, is a widely used and cost-effective communication medium that has sadly turned into a haven for unwanted messages, commonly known as SMS spam. With the rapid adoption of smartphones and Internet connectivity, SMS spam has emerged as a prevalent threat. Spammers have taken notice of the significance of SMS for mobile phone use

Changpeng Cai, Guinan Guo, Jiao Li, Junhao Su

Most earlier researches on talking face generation have focused on the synchronization of lip motion and speech content. However, head pose and facial emotions are equally important characteristics of natural faces. While audio-driven talking face generation has seen notable advancements, existing methods either overlook facial emotions or are limited to spe

Xin Du, Lixin Xiu, Kumiko Tanaka-Ishii

We apply an information-theoretic perspective to reconsider generative document retrieval (GDR), in which a document $x \in X$ is indexed by $t \in T$, and a neural autoregressive model is trained to map queries $Q$ to $T$. GDR can be considered to involve information transmission from documents $X$ to queries $Q$, with the requirement to transmit more bits

Suruchi Kumari, Pravendra Singh

Semi-supervised medical image segmentation has gained growing interest due to its ability to utilize unannotated data. The current state-of-the-art methods mostly rely on pseudo-labeling within a co-training framework. These methods depend on a single pseudo-label for training, but these labels are not as accurate as the ground truth of labeled data. Relying

Jinhong Kim, Yongjun Ahn, Seungnyun Kim, Byonghyo Shim

Terahertz (THz) communications is considered as one of key solutions to support extremely high data demand in 6G. One main difficulty of the THz communication is the severe signal attenuation caused by the foliage loss, oxygen/atmospheric absorption, body and hand losses. To compensate for the severe path loss, multiple-input-multiple-output (MIMO) antenna a

A. N. Panov

For an arbitrary equidimensional quiver representation, we proposed the method of construction of a system of free generators of the field of $U$-invariants. The construction of the section and system of generators depends on the choice of a map that assign to each vertex one of the arrows incident to it.

Silouanos Brazitikos, Giorgos Chasapis

We establish a new comparison between the Legendre transform of the cumulant generating function and the half-space depth of an arbitrary log-concave probability distribution on the real line, that carries on to the multidimensional setting. Combined with sharp estimates for the Cram\'{e}r transform of rotationally invariant measures, we are led to some new

Shlomi Vituri, Meir Feder

In this paper we consider the problem of universal {\em batch} learning in a misspecification setting with log-loss. In this setting the hypothesis class is a set of models $\Theta$. However, the data is generated by an unknown distribution that may not belong to this set but comes from a larger set of models $\Phi \supset \Theta$. Given a training sample, a

M. Koussour, Abdelghani Errehymy, O. Donmez, K. Myrzakulov

In this study, we investigate the role of bulk viscosity in $f(Q,T)$ gravity in explaining late-time cosmic acceleration. This model, an extension of symmetric teleparallel gravity, introduces viscosity into cosmic matter dynamics for a more realistic representation. Specifically, we consider the linear form of $f (Q, T) =\alpha Q + \beta T$, where $\alpha$

Anjaly Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri

Cloud providers introduce features (e.g., Spot VMs, Harvest VMs, and Burstable VMs) and optimizations (e.g., oversubscription, auto-scaling, power harvesting, and overclocking) to improve efficiency and reliability. To effectively utilize these features, it's crucial to understand the characteristics of workloads running in the cloud. However, workload chara

Alon Sardas, Michael Moshe, Cy Maor

Miura-Ori, a celebrated origami pattern that facilitates functionality in matter, has found multiple applications in the field of mechanical metamaterials. Modifications of Miura-Ori pattern can produce curved configurations during folding, thereby enhancing its potential functionalities. Thus, a key challenge in designing generalized Miura-Ori structures is

Nikolay B Petrov, Gregory Serapio-García, Jason Rentfrow

The humanlike responses of large language models (LLMs) have prompted social scientists to investigate whether LLMs can be used to simulate human participants in experiments, opinion polls and surveys. Of central interest in this line of research has been mapping out the psychological profiles of LLMs by prompting them to respond to standardized questionnair

Tatsuya Horiguchi

Let $G$ be a complex semisimple linear algebraic group. Fix a subset $\Theta$ of simple roots. Given a lower ideal $I$ in positive roots, one can define the regular nilpotent Hessenberg variety $\mbox{Hess}(N,I)$ in the full flag variety $G/B$. For a $\Theta$-ideal $I$ (which is a special lower ideal), we can define the regular nilpotent partial Hessenberg v

Hironari Nagayoshi, Warit Asavanant, Ryuhoh Ide, Kosuke Fukui

Continuous-variable (CV) quantum information processing is a promising candidate for large-scale fault-tolerant quantum computation. However, analysis of CV quantum process relies mostly on direct computation of the evolution of operators in the Heisenberg picture, and the features of CV space has yet to be thoroughly investigated in an intuitive manner. One

Matthew Andres Moreno, Santiago Rodriguez-Papa, Emily Dolson

Evolutionary dynamics are shaped by a variety of fundamental, generic drivers, including spatial structure, ecology, and selection pressure. These drivers impact the trajectory of evolution, and have been hypothesized to influence phylogenetic structure. Here, we set out to assess (1) if spatial structure, ecology, and selection pressure leave detectable sig

Gábor Antal, Zoltán Tóth, Péter Hegedűs, Rudolf Ferenc

Bug prediction aims at finding source code elements in a software system that are likely to contain defects. Being aware of the most error-prone parts of the program, one can efficiently allocate the limited amount of testing and code review resources. Therefore, bug prediction can support software maintenance and evolution to a great extent. In this paper,

Zhao-feng Ge, Feng-Yan Niu, Jin-Lei Yang

This study investigates the excesses observed in the CMS diphoton and ditau data around 95 GeV within the framework of the flavor-dependent U(1)X model. The model introduces a singlet scalar to explain the nonzero neutrino masses. This newly introduced Higgs interacts directly with the quark sector, motivated by the aim to explain the flavor numbers of the f

Abhi Kumar Sharma, Shayan Srinivasa Garani

We propose fault-tolerant encoders for quantum low-density parity check (LDPC) codes. By grouping qubits within a quantum code over contiguous blocks and applying preshared entanglement across these blocks, we show how transversal implementation can be realized. The proposed encoder reduces the error propagation while using multi-qubit gates and is applicabl

Matthew Andres Moreno, Santiago Rodriguez Papa, Charles Ofria

Continuing generation of novelty, complexity, and adaptation are well-established as core aspects of open-ended evolution. However, it has yet to be firmly established to what extent these phenomena are coupled and by what means they interact. In this work, we track the co-evolution of novelty, complexity, and adaptation in a case study from the DISHTINY sim

Karsten Kruse, Jean-Pierre Eckmann, Wilson C. K. Poon

We introduce a lattice model to probe the effect of active self-disassembly on equilibrium self-assembly. Surprisingly, we find conditions under which active self-disassembly enhances the yield of a target structure above that achieved by self-assembly alone when the latter is already favoured thermodynamically. We discuss biological implications of our find

Vasileios Alevizos, Sabrina Edralin, Akebu Simasiku, Dimitra Malliarou

Dyslexia and dysgraphia are learning disabilities that profoundly impact reading, writing, and language processing capabilities. Dyslexia primarily affects reading, manifesting as difficulties in word recognition and phonological processing, where individuals struggle to connect sounds with their corresponding letters. Dysgraphia, on the other hand, affects

Jianhua Shan, Yuhao Sun, Shixin Zhang, Fuchun Sun

Deformable object manipulation is a classical and challenging research area in robotics. Compared with rigid object manipulation, this problem is more complex due to the deformation properties including elastic, plastic, and elastoplastic deformation. In this paper, we describe a new deformable object manipulation method including soft contact simulation, ma

Guillaume Pourcel, Mirko Goldmann, Ingo Fischer, Miguel C. Soriano

Recurrent Neural Networks excel at predicting and generating complex high-dimensional temporal patterns. Due to their inherent nonlinear dynamics and memory, they can learn unbounded temporal dependencies from data. In a Machine Learning setting, the network's parameters are adapted during a training phase to match the requirements of a given task/problem in

Dian Jiao, Li Cai, Jingsheng Huang, Wenqiao Zhang

Retrieval-Augmented Generation (RAG) methods augment the input of Large Language Models (LLMs) with relevant retrieved passages, reducing factual errors in knowledge-intensive tasks. However, contemporary RAG approaches suffer from irrelevant knowledge retrieval issues in complex domain questions (e.g., HotPot QA) due to the lack of corresponding domain know

Shu-Min Wu, Rui-Di Wang, Xiao-Li Huang, Zejun Wang

We study quantum steering and Bell nonlocality harvested by the local interaction of two Unruh-DeWitt detectors with the vacuum massless scalar field, both in the presence of gravitational waves and in Minkowski spacetime. It is shown that quantum steerability under the influence of gravitational waves can be greater than or less than quantum steerability in

Ranjan Saikia, Jayanta Kumar Sarma

Exclusive diffractive processes, such as exclusive vector meson production, serve as excellent probes of hadron structure within the perturbative regime of quantum chromodynamics (QCD). The exclusive process involving light and heavy vector mesons, $e p \rightarrow e V(V=J/\Psi,\rho,\phi)$, has been investigated at the HERA accelerator facility. In this stud

Bin Lu, Ze Zhao, Luyu Han, Xiaoying Gan

Accurately reconstructing the global ocean deoxygenation over a century is crucial for assessing and protecting marine ecosystem. Existing expert-dominated numerical simulations fail to catch up with the dynamic variation caused by global warming and human activities. Besides, due to the high-cost data collection, the historical observations are severely spa

Raja Giryes, Lior Shafir, Avishai Wool

Distributed Denial of Service (DDoS) attacks are getting increasingly harmful to the Internet, showing no signs of slowing down. Developing an accurate detection mechanism to thwart DDoS attacks is still a big challenge due to the rich variety of these attacks and the emergence of new attack vectors. In this paper, we propose a new tree-based DDoS detection

Jef Pauwels, Stefano Pironio, Armin Tavakoli

The quantum prepare-and-measure scenario has been studied under various physical assumptions on the emitted states. Here, we first discuss how different assumptions are conceptually and formally related. We then identify one that can serve as a relaxation of all others, corresponding to a limitation on the one-shot accessible information of the state ensembl

A. Albert, S. Alves, M. André, M. Ardid

Position calibration in the deep sea is typically done by means of acoustic multilateration using three or more acoustic emitters installed at known positions. Rather than using hydrophones as receivers that are exposed to the ambient pressure, the sound signals can be coupled to piezo ceramics glued to the inside of existing containers for electronics or me

Xiaocui Yang, Wenfang Wu, Shi Feng, Ming Wang

The emergence of multimodal large language models (MLLMs) has triggered extensive research in model evaluation. While existing evaluation studies primarily focus on unimodal (vision-only) comprehension and reasoning capabilities, they overlook critical assessments of complex multimodal reasoning tasks that require integrated understanding of both visual and

Kapil Kumar, Naokant Deo, Durvesh Kumar Verma

This paper offers a newly created integral approach for operators employing the orthogonal modified Laguerre polynomials and P\u{a}lt\u{a}nea basis. These operators approximate the functions over the interval $[0,\infty)$. Further, the moments are established for the proposed operators, and the universal Korovkin's theorem is used to derive the approximation

Noemi David, Alpár R. Mészáros, Filippo Santambrogio

Nowadays a vast literature is available on the Hele-Shaw or incompressible limit for nonlinear degenerate diffusion equations. This problem has attracted a lot of attention due to its applications to tissue growth and crowd motion modelling as it constitutes a way to link soft congestion (or compressible) models to hard congestion (or incompressible) descrip

Jayanthi Vajiram, Aishwarya Senthil

The paper discusses the use of MRI for segmentation techniques, specifically focusing on brain tumor detection. It discusses the use of convolutional neural networks (CNN) for automatic segmentation but also discusses challenges such as non-isotropic resolution, Rician noise, and bias field effects. The paper proposes models like VGG16, ResNet50, and ResU-ne

Xinbiao Wang, Yuxuan Du, Kecheng Liu, Yong Luo

The No-Free-Lunch (NFL) theorem, which quantifies problem- and data-independent generalization errors regardless of the optimization process, provides a foundational framework for comprehending diverse learning protocols' potential. Despite its significance, the establishment of the NFL theorem for quantum machine learning models remains largely unexplored,

Shota Aoki, Takahiro Katagiri, Satoshi Ohshima, Masatoshi Kawai

Concerns have arisen regarding the unregulated utilization of artificial intelligence (AI) outputs, potentially leading to various societal issues. While humans routinely validate information, manually inspecting the vast volumes of AI-generated results is impractical. Therefore, automation and visualization are imperative. In this context, Explainable AI (X

Jean Michel Menjanahary, Eriola Hoxhaj, Rimvydas Krasauskas

Triple orthogonal coordinate systems having coordinate lines as circles or straight lines are considered. Technically, they are represented by trilinear rational quaternionic maps and are called Dupin cyclidic cubes, naturally generalizing the bilinear rational quaternionic parametrizations of principal patches of Dupin cyclides. Dupin cyclidic cubes and the

Davide Legacci, Panayotis Mertikopoulos, Bary Pradelski

In view of the complexity of the dynamics of learning in games, we seek to decompose a game into simpler components where the dynamics' long-run behavior is well understood. A natural starting point for this is Helmholtz's theorem, which decomposes a vector field into a potential and an incompressible component. However, the geometry of game dynamics - and,

Changhong Wang, Xudong Yu, Chenjia Bai, Qiaosheng Zhang

In Reinforcement Learning (RL), training a policy from scratch with online experiences can be inefficient because of the difficulties in exploration. Recently, offline RL provides a promising solution by giving an initialized offline policy, which can be refined through online interactions. However, existing approaches primarily perform offline and online le

Stefano Markidis

Central to the power of quantum computing is the concept of quantum parallelism: quantum systems can explore and process multiple computational paths simultaneously. In this paper, we discuss the elusive nature of quantum parallelism, drawing parallels with classical parallel computing models to elucidate its fundamental characteristics and implications for

Tsuneo Suzuki

The violation of non-Abelian Bianchi identity is equal to 8 Abelian monopole currents of the Dirac type satisfying Abelian conservation rules kinematically. There exist magnetic $U(1)_m^8$ symmetries in non-Abelian $SU(3)$ QCD. When the magnetic $U(1)_m^8$ symmetries are broken spontaneously, only states which are invariant under all $U(1)_e$ subgroups of $S

Inwoo Hwang, Yunhyeok Kwak, Yeon-Ji Song, Byoung-Tak Zhang

Conditional independence provides a way to understand causal relationships among the variables of interest. An underlying system may exhibit more fine-grained causal relationships especially between a variable and its parents, which will be called the local independence relationships. One of the most widely studied local relationships is Context-Specific Ind

Anthony Poëls

Let $n$ be a positive integer and $\xi$ a transcendental real number. We are interested in bounding from above the uniform exponent of polynomial approximation $\widehat{\omega}_n(\xi)$. Davenport and Schmidt's original 1969 inequality $\widehat{\omega}_n(\xi)\leq 2n-1$ was improved recently, and the best upper bound known to date is $2n-2$ for each $n\geq 1

Sishen Yuan, Guang Li, Baijia Liang, Lailu Li

Capsule endoscopes, predominantly serving diagnostic functions, provide lucid internal imagery but are devoid of surgical or therapeutic capabilities. Consequently, despite lesion detection, physicians frequently resort to traditional endoscopic or open surgical procedures for treatment, resulting in more complex, potentially risky interventions. To surmount

Gábor Antal, Balázs Mosolygó, Norbert Vándor, Péter Hegedüs

The number of people accessing online services is increasing day by day, and with new users, comes a greater need for effective and responsive cyber-security. Our goal in this study was to find out if there are common patterns within the most widely used programming languages in terms of security issues and fixes. In this paper, we showcase some statistics b

Kostas Lakis, Johannes Lengler, Kalina Petrova, Leon Schiller

In this paper, we study graph distances in the geometric random graph models scale-free percolation SFP, geometric inhomogeneous random graphs GIRG, and hyperbolic random graphs HRG. Despite the wide success of the models, the parameter regime in which graph distances are polylogarithmic is poorly understood. We provide new and improved lower bounds. In a ce

Sishen Yuan, Baijia Liang, Po Wa Wong, Mingjing Xu

Helicobacter pylori, a pervasive bacterial infection associated with gastrointestinal disorders such as gastritis, peptic ulcer disease, and gastric cancer, impacts approximately 50% of the global population. The efficacy of standard clinical eradication therapies is diminishing due to the rise of antibiotic-resistant strains, necessitating alternative treat

Geyu Mo, Qingqing Wang, Xin Ren, Weitong Yan

Harada proposed a modified theory of gravity called Cotton gravity, and argued that it successfully explains the rotation curves of $84$ galaxies without the need of dark matter. In this work we use galaxy-galaxy lensing technique to test whether the modification effect of Cotton gravity can indeed be a viable substitute for dark matter. Using the sphericall

Yuanyuan Lian

In this paper, we obtain the interior pointwise $C^{k,\alpha}$ ($k\geq 0$, $0<\alpha<1$) regularity for weak solutions of elliptic and parabolic equations in divergence form. The compactness method and perturbation technique are employed. The pointwise regularity is proved in a very simple way and the results are optimal. In addition, these pointwise regular

Rudolf Ferenc, Péter Hegedűs, Péter Gyimesi, Gábor Antal

The rapid rise of cyber-crime activities and the growing number of devices threatened by them place software security issues in the spotlight. As around 90% of all attacks exploit known types of security issues, finding vulnerable components and applying existing mitigation techniques is a viable practical approach for fighting against cyber-crime. In this p

Gaurav Singh, Kavitesh Kumar Bali

This paper explores the seamless integration of Generative AI (GenAI) and Evolutionary Algorithms (EAs) within the domain of large-scale multi-objective optimization. Focusing on the transformative role of Large Language Models (LLMs), our study investigates the potential of LLM-Assisted Inference to automate and enhance decision-making processes. Specifical

Boris Tsvelikhovskiy, Ilya Safro, Yuri Alexeev

Constructing an optimal mixer for Quantum Approximate Optimization Algorithm (QAOA) Hamiltonian is crucial for enhancing the performance of QAOA in solving combinatorial optimization problems. We present a systematic methodology for constructing the QAOA tailored mixer Hamiltonian, ensuring alignment with the inherent symmetries of classical optimization pro

V. G. Kurbatov, I. V. Kurbatova

Let $B$ and $C$ be square complex matrices. The differential equation \begin{equation*} x''(t)+Bx'(t)+Cx(t)=f(t) \end{equation*} is considered. A solvent is a matrix solution $X$ of the equation $X^2+BX+C=\mathbf0$. A pair of solvents $X$ and $Z$ is called complete if the matrix $X-Z$ is invertible. Knowing a complete pair of solvents $X$ and $Z$ allows us t

Pengbo Xia, Dongdong Zhang, Xin Ren, Bo Wang

We perform a cosmological test of Cotton gravity, which describes gravity by cotton tensor. We assume in Cotton gravity the background evolution is the same as the flat FLRW background. We derive the cosmological perturbation theory of the scalar mode at the linear level, where the difference from the $\Lambda$CDM model is characterized by the parameter $\be

Gaoqing Cao

Previously, it was found that pion superfluidity could be realized in the QCD epoch of the early universe, when lepton flavor asymmetry $|l_{\rm e}+l_\mu|$ is large enough to generate a charge chemical potential $|\mu_{\rm Q}|$ larger than vacuum pion mass. By following the same logic, kaon superfluidity might also be possible when $|l_{\rm e}+l_\mu|$ is so

Guozheng Dai, Zhonggen Su

This paper is devoted to uniform versions of the Hanson-Wright inequality for a random vector with independent centered $\alpha$-subexponential entries, $0<\alpha\le 1$. Our method relies upon a novel decoupling inequality and a comparison of weak and strong moments. As an application, we use the derived inequality to prove the restricted isometry property o

Gábor Antal, Péter Hegedűs, Zoltán Tóth, Rudolf Ferenc

The popularity and wide adoption of JavaScript both at the client and server side makes its code analysis more important than ever before. Most of the algorithms for vulnerability analysis, coding issue detection, or type inference rely on the call graph representation of the underlying program. Despite some obvious advantages of dynamic analysis, static alg

Parnashree Ghosh, Neena Gupta, Ananya Pal

Linear hypersurfaces over a field $k$ have been playing a central role in the study of some of the challenging problems on affine spaces. Breakthroughs on such problems have occurred by examining two difficult questions on linear polynomials of the form $H:=\alpha(X_1,\dots,X_m)Y - F(X_1,\dots, X_m,Z,T)\in D:=k[X_1,\ldots,X_m, Y,Z,T]$: (i) Whether $H$ define

Roman Novikov

We consider a radiation solution $\psi$ for the Helmholtz equation in an exterior region in $\mathbb R^3$. We show that the restriction of $\psi$ to any ray $L$ in the exterior region is uniquely determined by its imaginary part $\Im\psi$ on an interval of this ray. As a corollary, the restriction of $\psi$ to any plane $X$ in the exterior region is uniquely

Gábor Antal, Dávid Havas, István Siket, Árpád Beszédes

Newer technologies - programming languages, environments, libraries - change very rapidly. However, various internal and external constraints often prevent projects from quickly adopting to these changes. Customers may require specific platform compatibility from a software vendor, for example. In this work, we deal with such an issue in the context of the C

S. Bertelli, F. Bossi, B. Buonomo, R. De Sangro

This paper presents a detailed characterization of the positron beam delivered by the Beam Test Facility at Laboratori Nazionali of Frascati to the PADME experiment during Run III, which took place from October to December 2022. It showcases the methodology used to measure the main beam parameters such as the position in space, the absolute momentum scale, t

Shentong Mo, Haofan Wang, Huaxia Li, Xu Tang

Video-language pre-training is a typical and challenging problem that aims at learning visual and textual representations from large-scale data in a self-supervised way. Existing pre-training approaches either captured the correspondence of image-text pairs or utilized temporal ordering of frames. However, they do not explicitly explore the natural synchroni

Haoming Chen, Zhizhong Zhang, Yanyun Qu, Ruixin Zhang

An effective pre-training framework with universal 3D representations is extremely desired in perceiving large-scale dynamic scenes. However, establishing such an ideal framework that is both task-generic and label-efficient poses a challenge in unifying the representation of the same primitive across diverse scenes. The current contrastive 3D pre-training m

Sidharth SS, Keerthana AR, Gokul R, Anas KP

Accurate approximation of complex nonlinear functions is a fundamental challenge across many scientific and engineering domains. Traditional neural network architectures, such as Multi-Layer Perceptrons (MLPs), often struggle to efficiently capture intricate patterns and irregularities present in high-dimensional functions. This paper presents the Chebyshev

Yuanyuan Lian, Kai Zhang

In this paper, we study the regularity for viscosity solutions of locally uniformly elliptic equations and obtain a series of interior pointwise $C^{k,\alpha}$ ($k\geq 1$, $0<\alpha<1$) regularity with smallness assumptions on the solution and the right-hand term. As applications, we obtain various interior pointwise regularity for several classical elliptic

Stefano Longhi

Mobility edges (ME), separating Anderson-localized states from extended states, are known to arise in the single-particle energy spectrum of certain one-dimensional lattices with aperiodic order. Dephasing and decoherence effects are widely acknowledged to spoil Anderson localization and to enhance transport, suggesting that ME and localization are unlikely

Mu-Te Lau, Chin-Yi Cheng, Cheng-Hua Lu, Chia-Hsu Chuang

In this paper, we introduce a new quantum circuit synthesis (QCS) framework, Qsyn, for developers to research, develop, test, experiment, and then contribute their QCS algorithms and tools to the framework. Our framework is more developer-friendly than other modern QCS frameworks in three aspects: (1) We design a rich command-line interface so that developer

Narasimha Raghavan Veeraragavan, Mohammad Hossein Tabatabaei, Severin Elvatun, Vibeke Binz Vallevik

Synthetic data generation is increasingly recognized as a crucial solution to address data related challenges such as scarcity, bias, and privacy concerns. As synthetic data proliferates, the need for a robust evaluation framework to select a synthetic data generator becomes more pressing given the variety of options available. In this research study, we inv

Sandeep Sricharan Mukku, Manan Soni, Jitenkumar Rana, Chetan Aggarwal

We propose InsightNet, a novel approach for the automated extraction of structured insights from customer reviews. Our end-to-end machine learning framework is designed to overcome the limitations of current solutions, including the absence of structure for identified topics, non-standard aspect names, and lack of abundant training data. The proposed solutio

Kai Liu, Ruohui Wang, Jianfei Gao, Kai Chen

Over the past few years, as large language models have ushered in an era of intelligence emergence, there has been an intensified focus on scaling networks. Currently, many network architectures are designed manually, often resulting in sub-optimal configurations. Although Neural Architecture Search (NAS) methods have been proposed to automate this process,

Elmo Benedetto, Christian Corda, Ignazio Licata

Chae's analyses on GAIA observations of wide binary stars have fortified the paradigm of extended gravity with particular attention to MOND-like theories. We recall that, starting from the origin of Einstein's general relativity, the request of Mach on the structure of the theory has been the core of the foundational debate. This issue is strictly connected

Dongju Shin, Sunghee Lee, Namwoo Kang

Design is a factor that plays an important role in consumer purchase decisions. As the need for understanding and predicting various preferences for each customer increases along with the importance of mass customization, predicting individual design preferences has become a critical factor in product development. However, current methods for predicting desi

Stefano Longhi

Random walks behave very differently for classical and quantum particles. Here we unveil a ubiquitous distinctive behavior of random walks of a photon in a one-dimensional lattice in the presence of a finite number of traps, at which the photon can be destroyed and the walk terminates. While for a classical random walk the photon is unavoidably destroyed by

Stefano Merzi, Fabio Acerbi, C. Aicardi, D. Fiore

Silicon Photomultipliers (SiPMs) are single photon detectors that gained increasing interest in many applications as an alternative to photomultiplier tubes. In particular in the field of space experiments, where volume, weight and power consumption are a major constraint, their advantages like compactness, ruggedness, and their potential to achieve high qua

Daisuke Toyouchi, Kenta Hotokezaka, Kohei Inayoshi, Rolf Kuiper

Radiation-driven outflows play a crucial role in extracting mass and angular momentum from binary systems undergoing rapid mass transfer at super-Eddington rates. To study the mass transfer process from a massive donor star to a stellar-mass black hole (BH), we perform multi-dimensional radiation-hydrodynamical simulations that follow accretion flows from th

Shahriar Hassan, Umme Farhana, Md Karam Newaz

In wireless communication Multiple Input Multiple Output (MIMO) technology has brought significant improvement in service by adopting Orthogonal Frequency Division Multiplexing (OFDM), a digital modulation technique. To achieve great performance with MIMO efficiently gathering channel state information (CSI) plays a vital role. Among different approach of ch

Zihui Liang, Bakh Khoussainov, Mingyu Xiao

Regular games form a well-established class of games for analysis and synthesis of reactive systems. They include coloured Muller games, McNaughton games, Muller games, Rabin games, and Streett games. These games are played on directed graphs $\mathcal G$ where Player 0 and Player 1 play by generating an infinite path $\rho$ through the graph. The winner is

C. -W. Lian, Y. Ji, R. Yan, J. Li

The two-plasmon-decay instability (TPD) is a critical target preheating risk in direct-drive inertial confinement fusion. In this paper, TPD collectively driven by a normal-incidence laser beam (Beam-N) and a large-angle-incidence laser beam (Beam-L) is investigated via particle-in-cell simulations. Significant TPD growth is found able to develop in this reg

Mark van der Laan, Sky Qiu, Jens Magelund Tarp, Lars van der Laan

We consider the problem of estimating the average treatment effect (ATE) when both randomized control trial (RCT) data and external real-world data (RWD) are available. We decompose the ATE estimand as the difference between a pooled-ATE estimand that integrates RCT and RWD and a bias estimand that captures the conditional effect of RCT enrollment on the out

Meng-Long Song, Xue-Ke Song, Liu Ye, Dong Wang

In this study, we investigate the effectiveness of entropic uncertainty relations (EURs) in discerning the energy variation in quantum batteries (QBs) modelled by battery-charger-field in the presence of bosonic and fermionic reservoirs. Our results suggest that the extractable works (exergy and ergotropy) have versatile characteristics in different scenario

Masamitsu Ohnishi, Makoto Shimoshimizu

This paper examines a trade execution game for two large traders in a generalized price impact model. We incorporate a stochastic and sequentially dependent factor that exogenously affects the market price into financial markets. Our model accounts for how strategic and environmental uncertainties affect the large traders' execution strategies. We formulate