May 2022 arXiv papers — page 52

Mirella Aoun, Olivier Guibé

In this paper we study the convergence of a finite volume approximation of a convective diffusive elliptic problem with Neumann boundary conditions and L 1 data. To deal with the non-coercive character of the equation and the low regularity of the right hand-side we mix the finite volume tools and the renormalized techniques. To handle the Neumann boundary c

Tongzheng Ren, Fuheng Cui, Sujay Sanghavi, Nhat Ho

The Expectation-Maximization (EM) algorithm has been predominantly used to approximate the maximum likelihood estimation of the location-scale Gaussian mixtures. However, when the models are over-specified, namely, the chosen number of components to fit the data is larger than the unknown true number of components, EM needs a polynomial number of iterations

Kingman Cheung, C. J. Ouseph

We investigate the effects of the transitional magnetic dipole moment of the active-to-heavy-neutrino associated with a new neutral gauge boson $Z'$ on neutrino-nucleon scattering at the ForwArd Search ExpeRiment-$\nu$ (FASER$\nu$). We consider the neutral-current neutrino-nucleon scattering ($\nu A\rightarrow N A$) as the production mechanism of the heavy n

Amritanshu Prasad, Samrith Ram

We enumerate the number of $T$-splitting subspaces of dimension $m$ for an arbitrary operator $T$ on a $2m$-dimensional vector space over a finite field. When $T$ is regular split semisimple, comparison with an alternate method of enumeration leads to a new proof of the Touchard-Riordan formula for enumerating chord diagrams by their number of crossings.

Yeonsu Jeong, Soo Min Oh, Young Sul Cho

A giant cluster emerges discontinuously in bond percolation in various networks when the growth of large clusters is globally suppressed. It was recently revealed that this phenomenon occurs even in a scale-free (SF) network, where hubs accelerate the growth of large clusters. The SF network used in the previous study was disassortative, though, so it is nec

Evgeny Kochurin, Guillaume Ricard, Nikolay Zubarev, Eric Falcon

We report on three-dimensional direct numerical simulation of wave turbulence on the free surface of a magnetic fluid subjected to an external horizontal magnetic field. A transition from capillarywave turbulence to anisotropic magneto-capillary wave turbulence is observed for an increasing field. At high enough field, wave turbulence becomes highly anisotro

Jia-Xuan Liu, Hai-Long Shi, Yun-Hao Shi, Xiao-Hui Wang

We consider a central-spin battery where $N_b$ central spins serve as battery cells and $N_c$ bath spins serve as charging units. It is shown that the energy stored in the battery that can be extractable is quantified by the ergotropy, and that battery-charger entanglement is quantified via the Von Neumann entropy. By using an exact approach to a one-cell an

STAR Collaboration, M. S. Abdallah, B. E. Aboona, J. Adam

Azimuthal anisotropy of produced particles is one of the most important observables used to access the collective properties of the expanding medium created in relativistic heavy-ion collisions. In this paper, we present second ($v_{2}$) and third ($v_{3}$) order azimuthal anisotropies of $K_{S}^{0}$, $\phi$, $\Lambda$, $\Xi$ and $\Omega$ at mid-rapidity ($|

Akhil Uniyal, Reggie C. Pantig, Ali Övgün

Non-linear interaction between the electromagnetic fields (EMF) occurs when vacuum polarization in quantum electrodynamics (QED) happens. The field of non-linear electrodynamics, which may result from this interaction, could have important effects on black hole physics. This paper considers the asymptotically flat black hole solution in Einstein-nonlinear el

Fanfan Ye, Liang Ma, Qiaoyong Zhong, Di Xie

Exemplar-free incremental learning is extremely challenging due to inaccessibility of data from old tasks. In this paper, we attempt to exploit the knowledge encoded in a previously trained classification model to handle the catastrophic forgetting problem in continual learning. Specifically, we introduce a so-called knowledge delegator, which is capable of

Douglas D. DiJulio, Mamad Eshraqi, Wolfgang Hees, Yvonne Hinrichsen

A central component of the European Spallation Source is the high-power proton accelerator. The accelerator aims in the future to provide 2 GeV protons to a rotating tungsten target for the production of neutrons at 5 MW of average beam power for neutron scattering studies. Extensive shielding surrounds the accelerator, in order to provide sufficient safety

Tamoghna Ojha, Theofanis P. Raptis, Marco Conti, Andrea Passarella

The recent advances in wireless energy transfer (WET) provide an alternate and reliable option for replenishing the battery of pervasive and portable devices, such as smartphones. The peer-to-peer (P2P) mode of WET brings improved flexibility to the charging process among the devices as they can maintain their mobility while replenishing their battery. Few e

Miklos Laczkovich

A polygon $P$ is called a reptile, if it can be decomposed into $k\ge 2$ nonoverlapping and congruent polygons similar to $P$. We prove that if a cyclic quadrilateral is a reptile, then it is a trapezoid. Comparing with results of U. Betke and I. Osburg we find that every convex reptile is a triangle or a trapezoid.

Jacek Dziarmaga

Time evolution of an infinite 2D many body quantum lattice system can be described by the Suzuki-Trotter decomposition applied to the infinite projected entangled pair state (iPEPS). Each Trotter gate increases the bond dimension of the tensor network, $D$, that has to be truncated back in a way that minimizes a suitable error measure. This paper goes beyond

Frédéric Bayart, Sebastián Tapia-García

In this paper we provide a full characterization of cyclic composition operators defined on the d-dimensional Fock space $\mathcal F(\mathbb C^d)$ in terms of their symbol. Also, we study the supercyclicity and convex-cyclicity of this type of operators. We end this work by computing the approximation numbers of compact composition operators defined on $\mat

Daniel C. Bowden, Andreas Fichtner, Thomas Nikas, Adonis Bogris

Distributed Acoustic Sensing (DAS) has become a popular method of observing seismic wavefields: backscattered pulses of light reveal strains or strain-rates at any location along a fiber-optic cable. In contrast, a few newer systems transmit light through a cable and collect integrated phase delays over the entire cable, such as the Microwave Frequency Fiber

Jarkko Peltomäki, Frankie Spencer, Ivan Porres

WOGAN is an online test generation algorithm based on Wasserstein generative adversarial networks. In this note, we present how WOGAN works and summarize its performance in the SBST 2022 CPS tool competition concerning the AI of a self-driving car.

Ehtesham Iqbal, Asim Niaz, Asif Aziz Memon, Usman Asim

Active contour models have achieved prominent success in the area of image segmentation, allowing complex objects to be segmented from the background for further analysis. Existing models can be divided into region-based active contour models and edge-based active contour models. However, both models use direct image data to achieve segmentation and face man

Elias Gabriel Minian

We introduce a Morse theory for posets of Bestvina-Brady type combining matchings and height functions. This theory generalizes Forman's discrete Morse theory for regular CW-complexes and extends previous results on Morse theory for $h$-regular posets to all finite posets. We also develop a relative version of Morse theory which allows us to compare the topo

Giuliano Vitali

An experimental field cropped with sugar-beet with a wide spreading of weeds has been used to test vegetation identification from drone visible imagery. Expert masked and hue-filtered pictures have been used to train several Machine Learning algorithms to develop a semi-automatic methodology for identification and mapping species at high resolution. Results

Jarkko Peltomäki, Frankie Spencer, Ivan Porres

We propose a novel online test generation algorithm WOGAN based on Wasserstein Generative Adversarial Networks. WOGAN is a general-purpose black-box test generator applicable to any system under test having a fitness function for determining failing tests. As a proof of concept, we evaluate WOGAN by generating roads such that a lane assistance system of a ca

Ofek Hober, Ealeal Bear, Noam Soker

We simulate the response of a main sequence star to the explosion of a stripped-envelope (type Ib or Ic) core collapse supernova (CCSN) when the main sequence star orbits the core at a distance of 10-20Ro at explosion. We use the stellar evolution code MESA to follow the response of main sequence stars of masses 3Mo and 7Mo to energy deposition and mass remo

Yu-Wen Li, Li-Juan Li, Xue-Ke Song, Dong Wang

The violation of Leggett-Garg inequalities tested the quantumness of neutrino oscillations (NOs) across macroscopic distances. The quantumness can be quantified by using the tools of the quantum resource theories. Recently, a new genuine tripartite entanglement measure [S. B. Xie et al., Phys. Rev. Lett. 127, 040403 (2021)], concurrence fill, is defined as t

Jarkko Peltomäki, Ivan Porres

We consider the problem of falsifying safety requirements of Cyber-Physical Systems expressed in signal temporal logic (STL). This problem can be turned into an optimization problem via STL robustness functions. In this paper, our focus is in falsifying systems with multiple requirements. We propose to solve such conjunctive requirements using online generat

Stephen Lack, Giacomo Tendas

We provide a new characterization of enriched accessible categories by introducing the two new notions of virtual reflectivity and virtual orthogonality as a generalization of the usual reflectivity and orthogonality conditions for locally presentable categories. The word virtual refers to the fact that the reflectivity and orthogonality conditions are given

Tianyi Zhang, Mina Lee, Lisa Li, Ende Shen

While pretrained language models (PLMs) have greatly improved text generation, they have also been known to produce unfaithful or inappropriate content. In contrast, classic template-based systems provide strong guarantees of faithfulness at the cost of fluency. We propose TempLM, which achieves the best of both worlds by distilling a PLM into a template-bas

Francis Borceux, Federico Campanini, Marino Gran

We propose a construction of a stable category for any pretorsion theory in a lextensive category. We prove the universal property of the stable category, that extends previous results obtained for the stable category of internal preorders in a pretopos. Some examples are provided in the categories of topological spaces and of (small) categories.

Penghui Cao

Multi-principal element alloys (MPEAs), commonly termed as medium- or high-entropy alloys containing three or more components in high concentrations, render a tunable chemical short-range order (SRO). Leveraging large-scale atomistic simulations, we probe the limit of Hall-Petch strengthening and deformation mechanisms in a model CrCoNi alloy and unravel che

Sriramkrishnan Muralikrishnan, Matthias Frey, Alessandro Vinciguerra, Michael Ligotino

We perform a scaling and performance portability study of the particle-in-cell scheme for plasma physics applications through a set of mini-apps we name "Alpine", which can make use of exascale computing capabilities. The mini-apps are based on Independent Parallel Particle Layer, a framework that is designed around performance portable and dimension indepen

Xiaoyu Chen, Yao Mu, Ping Luo, Shengbo Li

Partially Observable Markov Decision Process (POMDP) provides a principled and generic framework to model real world sequential decision making processes but yet remains unsolved, especially for high dimensional continuous space and unknown models. The main challenge lies in how to accurately obtain the belief state, which is the probability distribution ove

Liuming Wei, Zhe Zhao, Yonggang Li, Qirong Zheng

To evaluate the radiation tolerance of nanocrystalline (NC) materials, the damage effects of Fe and W as typical body-centered cubic (BCC) metals under uniform irradiation are studied by a sequential multi-scale modelling framework. An ideal descriptor, the absorption bias (the ratio of the absorption abilities of grain boundaries (GBs) to interstitials (I)

Daiki Tanabe, Masaya Hasegawa, Masashi Hazumi, Nobuhiko Katayama

We present a precise thermometry system to monitor room-temperature components of a telescope for radio-astronomy such as cosmic microwave background (CMB) observation. The system realizes precision of 1 mK${\rm \sqrt{s}}$ on a timescale of 20 seconds at 300 K. We achieved this high precision by tracking only relative fluctuation and combining thermistors wi

Wenbo Su, Yuanxing Zhang, Yufeng Cai, Kaixu Ren

High-concurrency asynchronous training upon parameter server (PS) architecture and high-performance synchronous training upon all-reduce (AR) architecture are the most commonly deployed distributed training modes for recommendation models. Although synchronous AR training is designed to have higher training efficiency, asynchronous PS training would be a bet

Yunzhi Lin, Jonathan Tremblay, Stephen Tyree, Patricio A. Vela

We propose a single-stage, category-level 6-DoF pose estimation algorithm that simultaneously detects and tracks instances of objects within a known category. Our method takes as input the previous and current frame from a monocular RGB video, as well as predictions from the previous frame, to predict the bounding cuboid and 6-DoF pose (up to scale). Interna

Chusei Kiumi, Kei Saito, Yohei Tanaka

It is recently shown by Asahara-Funakawa-Seki-Tanaka that existing index theory for chirally symmetric (discrete-time) quantum walks can be extended to the setting of non-unitary quantum walks. More precisely, they consider a certain non-unitary variant of the two-phase split-step quantum walk as a concrete one-dimensional example, and give a complete classi

Koji Aoyama, Masashi Toyoda

In this paper, we show a mean convergence theorem for a mapping with an attractive point in a Hilbert space by using a quasinonexpansive extension of the mapping and a mean convergence theorem for a quasinonexpansive mapping.

Jaehun Song, Min-hwan Oh, Hyung-Sin Kim

Personalized Federated Learning (FL) is an emerging research field in FL that learns an easily adaptable global model in the presence of data heterogeneity among clients. However, one of the main challenges for personalized FL is the heavy reliance on clients' computing resources to calculate higher-order gradients since client data is segregated from the se

Fengqiao Luo

We consider the coordinated vehicle platooning problem on a tree network with time constraints while the routes of vehicles are given. The problem is to coordinate the departure time of each vehicle to enable platoon formation hence maximizing the total fuel saving. For this problem setting, relative time windows can be defined for all vehicles to which an e

J. X. Hu, Y. L. Han, X. Chi, G. J. Omar

Spin-polarized two-dimensional materials with large and tunable spin-splitting energy promise the field of 2D spintronics. While graphene has been a canonical 2D material, its spin properties and tunability are limited. Here, we demonstrate the emergence of robust spin-polarization in graphene with large and tunable spin-splitting energy of up to 132 meV at

Liujie Guo, Fei Gao, Hui Zhan

This paper studies the properties of weak solutions to a class of space-time fractional parabolic-elliptic Keller-Segel equations with logistic source terms in $\mathbb{R}^{n}$, $n\geq 2$. The global existence and $L^{\infty}$-bound of weak solutions are established. We mainly divide the damping coefficient into two cases: (i) $b>1-\frac{\alpha}{n}$, for any

Hui Zhan, Fei Gao, Liujie Guo

The global boundedness and asymptotic behavior are investigate for the solution of time-space fractional non-local reaction-diffusion equation (TSFNRDE) $$ \frac{\partial^{\alpha }u}{\partial t^{\alpha }}=-(-\Delta)^{s} u+\mu u^{2}(1-kJ*u)-\gamma u, \qquad(x,t)\in\mathbb{R}^{N}\times(0,+\infty),$$ where $s\in(0,1),\alpha\in(0,1), N \leq 2$. The operator $\pa

Xueyuan Lin, Haihong E, Gengxian Zhou, Tianyi Hu

Current best performing models for knowledge graph reasoning (KGR) introduce geometry objects or probabilistic distributions to embed entities and first-order logical (FOL) queries into low-dimensional vector spaces. They can be summarized as a center-size framework (point/box/cone, Beta/Gaussian distribution, etc.). However, they have limited logical reason

Swadesh Poddar, Md. Tanvir Hasan, Md. Ragib Shakil Rafi

This article aims at discussing computational approach to design magnet-free nonreciprocal metamaterial. Detailed mathematical derivation on floquet mode analysis is presented for Faraday and Kerr rotation. Non-reciprocity in the designed metasurface is achieved in the presence of biased transistor loaded in the gap of circular ring resonator. Based on the s

M. M. Sharma, Poonam Rani, V. P. S. Awana

Materials exhibiting bulk superconductivity along with magnetoresistance (MR) in their normal state have emerged as suitable candidates for topological superconductivity. In this article, we report a flux free method to synthesize single crystal of topological superconductor candidate Sn4Au. The phase purity and single crystalline nature are confirmed throug

Silvia Vicentini

Vacuum decay in de Sitter space is a process of great physical interest, as it allows to rule out cosmological models in the early and current Universe. Its rate may be described in terms of an instanton in Euclidean space called bounce and it is usually interpreted as thermally assisted quantum tunneling. According to analytical and numerical evidence in th

Jae-Hwan Choi, Kyeong-Hun Kim, Junhee Ryu

We study the zero exterior problem for the elliptic equation $$ \Delta^{\alpha/2}u-\lambda u=f, \quad x\in D\,; \quad u|_{D^c}=0 $$ as well as for the parabolic equation $$ u_t=\Delta^{\alpha/2}u+f, \quad t>0,\, x\in D \,; \quad u(0,\cdot)|_D=u_0, \,u|_{[0,T]\times D^c}=0. $$ Here, $\alpha\in (0,2)$, $\lambda \geq 0$ and $D$ is a $C^{1,1}$ open set. We prove

Fuyuki Kitagawa, Ryo Nishimaki

We initiate the study of software watermarking against quantum adversaries. A quantum adversary generates a quantum state as a pirate software that potentially removes an embedded message from a classical marked software. Extracting an embedded message from quantum pirate software is difficult since measurement could irreversibly alter the quantum state. In

Md Sarowar Morshed

We propose two variants of Newton method for solving unconstrained minimization problem. Our method leverages optimization techniques such as penalty and augmented Lagrangian method to generate novel variants of the Newton method namely the Penalty Newton method and the Augmented Newton method. In doing so, we recover several well-known existing Newton metho

Roque Ruiz-Carmona, Itai Sfaradi, Assaf Horesh

Context: The study of radio emission from core-collapse supernovae (SNe) probes the interaction of the ejecta with the circumstellar medium (CSM) and reveals details of the mass-loss history of the progenitor. Aims: We report observations of the type IIP supernova SN\,2016X during the plateau phase, at ages between 21 and 75 days, obtained with the Karl G. J

Subas Chhatkuli, Iris Jiang, Kyohei Kamiyama

In addition to body weight and Body Mass Index (BMI), body composition is an essential data point that allows people to understand their overall health and body fitness. However, body composition is largely made up of muscle, fat, bones, and water, which makes estimation not as easy and straightforward as measuring body weight. In this paper, we introduce a

Yihang Gao, Huafeng Liu, Michael K. Ng, Mingjie Zhou

Wide applications of differentiable two-player sequential games (e.g., image generation by GANs) have raised much interest and attention of researchers to study efficient and fast algorithms. Most of the existing algorithms are developed based on nice properties of simultaneous games, i.e., convex-concave payoff functions, but are not applicable in solving s

Liangtai Sun, Xingyu Chen, Lu Chen, Tianle Dai

Task-oriented dialogue (TOD) systems have been widely used by mobile phone intelligent assistants to accomplish tasks such as calendar scheduling or hotel reservation. Current TOD systems usually focus on multi-turn text/speech interaction, then they would call back-end APIs designed for TODs to perform the task. However, this API-based architecture greatly

Xiaodong Gu, Chengzhou Tang, Weihao Yuan, Zuozhuo Dai

3D motion estimation including scene flow and point cloud registration has drawn increasing interest. Inspired by 2D flow estimation, recent methods employ deep neural networks to construct the cost volume for estimating accurate 3D flow. However, these methods are limited by the fact that it is difficult to define a search window on point clouds because of

Soham S. Sarpotdar

Cardiomegaly is indeed a medical disease in which the heart is enlarged. Cardiomegaly is better to handle if caught early, so early detection is critical. The chest X-ray, being one of the most often used radiography examinations, has been used to detect and visualize abnormalities of human organs for decades. X-ray is also a significant medical diagnosis to

Jianxiong Li, Xianyuan Zhan, Haoran Xu, Xiangyu Zhu

In offline reinforcement learning (RL), one detrimental issue to policy learning is the error accumulation of deep Q function in out-of-distribution (OOD) areas. Unfortunately, existing offline RL methods are often over-conservative, inevitably hurting generalization performance outside data distribution. In our study, one interesting observation is that dee

Vedant Malolan Srinivas

Growth economies continue to be more reliant on roadways than ever before. Over 30,000 miles of road are added yearly to the already enormous road system that exists in the United States. As roads segment habitats, animals have no option but to walk across them for food, water and companionship. In this process they end up becoming roadkill. Wherever wildlif

Maria Tackett

As data have become more prevalent in academia, industry, and daily life, it is imperative that undergraduate students are equipped with the skills needed to analyze data in the modern environment. In recent years there has been a lot of work innovating introductory statistics courses and developing introductory data science courses; however, there has been

Jun Lu, Xuanyu Ye

In this paper, we introduce a probabilistic model for learning nonnegative matrix factorization (NMF) that is commonly used for predicting missing values and finding hidden patterns in the data, in which the matrix factors are latent variables associated with each data dimension. The nonnegativity constraint for the latent factors is handled by choosing prio

Rishabh Bhardwaj, Amrita Saha, Steven C. H. Hoi, Soujanya Poria

Prompt Tuning has been largely successful as a parameter-efficient method of conditioning large-scale pre-trained language models to perform downstream tasks. Thus far, soft prompt tuning learns a fixed set of task-specific continuous vectors, i.e., soft tokens that remain static across the task samples. A fixed prompt, however, may not generalize well to th

Xiaoyu Liu, Jinu Jang, Neel Sundaresan, Miltiadis Allamanis

In software development, it is common for programmers to copy-paste or port code snippets and then adapt them to their use case. This scenario motivates the code adaptation task -- a variant of program repair which aims to adapt variable identifiers in a pasted snippet of code to the surrounding, preexisting source code. However, no existing approach has bee

Yoshihiko Matsumoto

We elaborate the tractor calculus for compatible almost CR structures (also known as strictly pseudoconvex partially integrable almost CR structures) on contact manifolds, and as an application, express the first BGG invariant differential operator $D_0$ explicitly in some cases, i.e., for some tractor connections. An interesting outcome is the fact that the

Yayi Lin, Zhenyue She, Zhiwen Chen, Xianzhe Li

Realization of practical terahertz wireless communications still faces many challenges. The receiver with high sensitivity is important for THz wireless communications. Here we demonstrate a terahertz receiver based on the cesium Rydberg atoms in a room-temperature vapor cell. The minimum detectable THz electric field is calibrated. With this receiver, the p

Rohitash Chandra, Mukul Ranjan

A distinct feature of Hindu religious and philosophical text is that they come from a library of texts rather than single source. The Upanishads is known as one of the oldest philosophical texts in the world that forms the foundation of Hindu philosophy. The Bhagavad Gita is core text of Hindu philosophy and is known as a text that summarises the key philoso

Yu Wang, Fang Liu

The current work on reinforcement learning (RL) from demonstrations often assumes the demonstrations are samples from an optimal policy, an unrealistic assumption in practice. When demonstrations are generated by sub-optimal policies or have sparse state-action pairs, policy learned from sub-optimal demonstrations may mislead an agent with incorrect or non-l

Lalita Kumari, Sukhdeep Singh, Vaibhav Varish Singh Rathore, Anuj Sharma

In this study, we have presented an efficient procedure using two state-of-the-art approaches from the literature of handwritten text recognition as Vertical Attention Network and Word Beam Search. The attention module is responsible for internal line segmentation that consequently processes a page in a line-by-line manner. At the decoding step, we have adde

Alexander I. Bufetov, Gabriel Nivasch, Fedor Pakhomov

Erickson defined the fusible numbers as a set $\mathcal F$ of reals generated by repeated application of the function $\frac{x+y+1}{2}$. Erickson, Nivasch, and Xu showed that $\mathcal F$ is well ordered, with order type $\varepsilon_0$. They also investigated a recursively defined function $M\colon \mathbb{R}\to\mathbb{R}$. They showed that the set of point

Youjun Xu, Jinchuan Xiao, Chia-Han Chou, Jianhang Zhang

Molecular structures are always depicted as 2D printed form in scientific documents like journal papers and patents. However, these 2D depictions are not machine-readable. Due to a backlog of decades and an increasing amount of these printed literature, there is a high demand for the translation of printed depictions into machine-readable formats, which is k

Thi Xinh Dinh, Luu Y Nhi Nguyen, Lakshmi J. Mohan, Serdar Boztas

The issue of repairing Reed-Solomon codes currently employed in industry has been sporadically discussed in the literature. In this work we carry out a systematic study of these codes and investigate important aspects of repairing them under the trace repair framework, including which evaluation points to select and how to implement a trace repair scheme eff

Arash Tavakoli, Arsalan Heydarian

Recent studies have pointed out the importance of mitigating drivers stress and negative emotions. These studies show that certain road objects such as big vehicles might be associated with higher stress levels based on drivers subjective stress measures. Additionally, research shows strong correlations between drivers stress levels and increased heart rate

Chenyang Chen, Hao Ge

We consider a stochastic interacting vortex system of $N$ particles, approximating the vorticity formulation of 2-D Navier-Stokes equation on torus. The singular interaction kernel is given by the Biot-Savart law. We only require the initial state to have finite energy, and obtain a sample-path large deviation principle for the empirical measure when the num

Yasushi Ota, Yu Jiang, Daiki Maki

No--arbitrage property provides a simple method for pricing financial derivatives. However, arbitrage opportunities exist among different markets in various fields, even for a very short time. By knowing that an arbitrage property exists, we can adopt a financial trading strategy. This paper investigates the inverse option problems (IOP) in the extended Blac

Yan-Hong Qin, Xiaoman Zhang, Liming Ling, Li-Chen Zhao

Dark soliton is usually seen as one of the simplest topological solitons, due to the phase jump across its density dip. We investigate the phase jump properties of dark solitons in a single mode optical fiber with the third-order dispersion and delayed nonlinear response, based on exact analytical solutions of Hirota equation. Our analysis indicates that a s

Kai-Jia Sun, Wen-Hao Zhou, Lie-Wen Chen, Che Ming Ko

Using a relativistic transport model to describe the evolution of the quantum chromodynamic matter produced in Au+Au collisions at $\sqrt{s_{NN}}=3-200$ GeV, we study the effect of a first-order phase transition in the equation of state of this matter on the yield ratio $N_tN_p/ N_d^2$ ($tp/d^2$) of produced proton ($p$), deuteron ($d$), and triton ($t$). We

Luccas Campos, Jason Murphy, Tim Van Hoose

We establish global-in-time averaging for the $L^2$-critical dispersion-managed nonlinear Schr\"odinger equation in the fast dispersion management regime. In particular, in the case of nonzero average dispersion, we establish averaging with any subcritical data, while in the case of a strictly positive dispersion map, we obtain averaging for data in $L^2$.

Peilin Zhou, Dading Chong, Helin Wang, Qingcheng Zeng

The past ten years have witnessed the rapid development of text-based intent detection, whose benchmark performances have already been taken to a remarkable level by deep learning techniques. However, automatic speech recognition (ASR) errors are inevitable in real-world applications due to the environment noise, unique speech patterns and etc, leading to sh

KangKang Li, Zhaoxin Liang

Dimensionality serves as an indispensable ingredient in any attempt to formulate the low-dimensional physics, and studying the dimensional crossover at a fundamental level is challenging. The purpose of this work is to study the hierarchical dimensional crossovers, namely the crossover from three dimensions (3D) to quasi-2D and then to 1D. Our system consist

Fei Lu, Qingci An, Yue Yu

Nonlocal operators with integral kernels have become a popular tool for designing solution maps between function spaces, due to their efficiency in representing long-range dependence and the attractive feature of being resolution-invariant. In this work, we provide a rigorous identifiability analysis and convergence study for the learning of kernels in nonlo

Yuchao Li, Fuli Luo, Chuanqi Tan, Mengdi Wang

With the dramatically increased number of parameters in language models, sparsity methods have received ever-increasing research focus to compress and accelerate the models. While most research focuses on how to accurately retain appropriate weights while maintaining the performance of the compressed model, there are challenges in the computational overhead

Brian Montambault, Camelia D. Brumar, Michael Behrisch, Remco Chang

Anomaly detection remains an open challenge in many application areas. While there are a number of available machine learning algorithms for detecting anomalies, analysts are frequently asked to take additional steps in reasoning about the root cause of the anomalies and form actionable hypotheses that can be communicated to business stakeholders. Without th

Xiao-Mei Kuang, Ali Övgün

Motivated by (i) more and more interest in strong gravitational lensing by supermassive black holes due to the achievement of EHT observations, (ii) the ongoing popular topic on the possibility of Lorentz symmetry being broken in gravitation and its consequences, we will apply the Einstein bumblebee gravity with Lorentz violation (LV) to the study of strong

F. Harrathi, S. Mabrouk, O. Ncib, S. Silvestrov

The main goal of this work is to introduce the notion of Hom-M-dendriform algebras which are the dendriform version of Hom-Malcev algebras. In fact they are the algebraic structures behind the $\mathcal{O}$-operator of Hom-pre-Malcev algebras. They also fit into a bigger framework as Hom-Malcev algebraic analogues of Hom-L-dendriform algebras. Furthermore, w

Egor Lappo

We define smooth notions of concordance and sliceness for spatial graphs. We prove that sliceness of a spatial graph is equivalent to a condition on a set of linking numbers together with sliceness of a link associated to the graph. This generalizes the result of Taniyama for $\theta$-curves.

Shuji Watanabe

In the preceding papers, imposing certain complicated and strong conditions, the present author showed that the solution to the BCS-Bogoliubov gap equation in superconductivity is twice differentiable only on the neighborhoods of absolute zero temperature and the transition temperature so as to show that the phase transition is of the second order from the v

Oliver Knill

The number of rooted spanning forests divided by the number of spanning rooted trees in a graph G with Kirchhoff matrix K is the spectral quantity tau(G)= det(1+K)/det(K) of G by the matrix tree and matrix forest theorems. We prove that that under Barycentric refinements, the tree index T(G)=log(det(K))/n and forest index F(G)=log(det(1+K))/n and so the tree

Michal Yemini, Rajarshi Saha, Emre Ozfatura, Deniz Gündüz

We present a semi-decentralized federated learning algorithm wherein clients collaborate by relaying their neighbors' local updates to a central parameter server (PS). At every communication round to the PS, each client computes a local consensus of the updates from its neighboring clients and eventually transmits a weighted average of its own update and tho

Wei Dai, Mingcheng Zhang, Kin Huat Low

Electric Take-Off and Landing (eVTOL) aircraft is considered as the major aircraft type in the emerging urban air mobility. Accurate power consumption estimation is crucial to eVTOL, supporting advanced power management strategies and improving the efficiency and safety performance of flight operations. In this study, a framework for power consumption modeli

W. Qi, P. Seshaiyer, J. Wang

A new weak Galerkin finite element method, called generalized weak Galerkin method ({g}WG), is introduced for Stokes equations in this paper by using a new definition of the weak gradient. Error estimates in energy norm and $L^2$ norm for the velocity and $L^2$ norm for the pressure are derived for elements with arbitrary combination of polynomials. Some num

Teng Ji, Xiang-Kun Dong, Feng-Kun Guo, Bing-Song Zou

Lots of charmonium-like structures have been observed in the last two decades. Most of them have quantum numbers that can be formed by a pair of charm and anticharm quarks, thus it is difficult to unambiguously identify the exotic ones among them. In this Letter, by exploiting heavy quark spin symmetry, we present a robust prediction of the hadronic molecula

Ya-Wen Tsai, Yao-Ting Wang, Emanuele Galiffi, Andrea Alù

We investigate symmetry-selective surface-mode excitation in a general periodically time-modulated double-layer system, where the modulation of the two layers has a constant phase difference. By deriving a semi-analytic trans-fer matrix formalism of a Drude-dispersive double-layer structure with periodic time-modulation, we calculate the scattering amplitude

Shanshan Shan, Yang Gao, Paul Z. Y. Liu, Brendan Whelan

Magnetic resonance imaging (MRI) is increasingly utilized for image-guided radiotherapy due to its outstanding soft-tissue contrast and lack of ionizing radiation. However, geometric distortions caused by gradient nonlinearity (GNL) limit anatomical accuracy, potentially compromising the quality of tumour treatments. In addition, slow MR acquisition and reco

Anirudh Ramchandran, Likang Yin, Vladimir Filkov

Open Source Software (OSS) is a major component of our digital infrastructure, yet more than 80% of such projects fail. Seeking less uncertainty, many OSS projects join established software communities, e.g., the Apache Software Foundation (ASF), with established rules and community support to guide projects toward sustainability. In their nascent stage, ASF

Alessandro R. Mazza, Jason Lapano, Harry M. Meyer, Christopher T. Nelson

Understanding the effects of interfacial modification to the functional properties of magnetic topological insulator thin films is crucial for developing novel technological applications from spintronics to quantum computing. Here, we report that a large electronic and magnetic response is induced in the intrinsic magnetic topological insulator MnBi2Te4 by c

Lei Zhang, Yu Pan, Yi Liu, Qibin Zheng

The existing network attack and defense method can be regarded as game, but most of the game only involves network domain, not multiple domain cyberspace. To address this challenge, this paper proposed a multiple domain cyberspace attack and defense game model based on reinforcement learning. We define the multiple domain cyberspace include physical domain,

Thomas Tuloup, Raditya Weda Bomantara, Jiangbin Gong

In this work we explore the effects of nonlinearity on three-dimensional topological phases. Of particular interest are the so-called Weyl semimetals, known for their Weyl nodes, i.e., point-like topological charges which always exist in pairs and demonstrate remarkable robustness against general perturbations. It is found that the presence of onsite nonline

Fanrong Lin, Jiabin Qiao, Junye Huang, Jiawei Liu

Localized electrons subject to applied magnetic fields can restart to propagate freely through the lattice in delocalized magnetic Bloch states (MBSs) when the lattice periodicity is commensurate with the magnetic length. Twisted graphene superlattices with moir\'e wavelength tunability enable experimental access to the unique delocalization in a controllabl

Shawn Means, Carlo Laing

We consider directed networks of Winfree oscillators with power law distributed in- and out-degree distributions. Gaussian and power law distributed intrinsic frequencies are considered, and these frequencies are positively correlated with oscillators' in-degrees. The Ott/Antonsen ansatz is used to derive degree-based mean field equations for the expected dy

Jiazhi Xu, Sheng Huang, Fengtao Zhou, Luwen Huangfu

Multi-Label Image Classification (MLIC) approaches usually exploit label correlations to achieve good performance. However, emphasizing correlation like co-occurrence may overlook discriminative features of the target itself and lead to model overfitting, thus undermining the performance. In this study, we propose a generic framework named Parallel Self-Dist

Takeshi Kajiwara, Kazuya Kato, Chikara Nakayama

We construct the fine moduli space of log abelian varieties with PEL structure, which gives a toroidal compactification of the moduli space of abelian varieties with PEL structure.

Kenji Takamichi, Yoshihiko Susuki, Marcos Netto, Atsushi Ishigame

This paper proposes a mode-in-state contribution factor for a class of nonlinear dynamical systems by utilizing spectral properties of the Koopman operator and sensitivity analysis. Using eigenfunctions of the Koopman operator for a target nonlinear system, we show that the relative contribution between modes and state variables can be quantified beyond a li

H. Yanaoka, K. Nakayama

In this study, we perform a numerical analysis of the instability of a ligament in shear flow and investigate the effects of air-liquid shear on the growth rate of the ligament interface, breakup time, and droplet diameter formed by the breakup. The ligament is stretched in the flow direction by the shearing of airflow. Furthermore, as the influence of the s