August 2022 arXiv papers — page 54

Oren Louidor, Chanwoo Oh, Eviatar B. Procaccia

In this paper, we consider a non-homogeneous discrete-time Markov chain which can be seen as a toy model for the growth of the arms of the DLA (Diffusion limited aggregation) process in a sub-linear wedge. It is conjectured that in a thin enough linear wedge there is only one infinite arm in the DLA cluster and we demonstrate this phenomenon in our model. Th

Minghua Pan, Bin Wang, Xiaoling Tao, Shenggen Zheng

Quantum computing holds tremendous potential for processing high-dimensional data, capitalizing on the unique capabilities of superposition and parallelism within quantum states. As we navigate the noisy intermediate-scale quantum (NISQ) era, the exploration of quantum computing applications has emerged as a compelling frontier. One area of particular intere

Yang Lu, Yiliang Zhang, Bo Han, Yiu-ming Cheung

Label noise is one of the key factors that lead to the poor generalization of deep learning models. Existing label-noise learning methods usually assume that the ground-truth classes of the training data are balanced. However, the real-world data is often imbalanced, leading to the inconsistency between observed and intrinsic class distribution with label no

Ruhee D'Cunha, T. Daniel Crawford, Mario Motta, Julia E. Rice

Advances in quantum computation for electronic structure, and particularly heuristic quantum algorithms, create an ongoing need to characterize the performance and limitations of these methods. Here we discuss some potential pitfalls connected with the use of hardware-efficient Ansatze in variational quantum simulations of electronic structure. We illustrate

Benoît Fauqué, Clément Collignon, Hyeok Yoon, Ravi

Dilute superconductivity survives in bulk strontium titanate when the Fermi temperature falls well below the Debye temperature. Here, we show that the onset of the superconducting dome is dopant-dependent. When mobile electrons are introduced by removing oxygen atoms, the superconducting transition survives down to $2 \times 10^{17}$ cm$^{-3}$, but when they

Junghun Kim, Jihie Kim

Learning expressive representation is crucial in deep learning. In speech emotion recognition (SER), vacuum regions or noises in the speech interfere with expressive representation learning. However, traditional RNN-based models are susceptible to such noise. Recently, Graph Neural Network (GNN) has demonstrated its effectiveness for representation learning,

Peter De Roovere, Rembert Daems, Jonathan Croenen, Taoufik Bourgana

We introduce CenDerNet, a framework for 6D pose estimation from multi-view images based on center and curvature representations. Finding precise poses for reflective, textureless objects is a key challenge for industrial robotics. Our approach consists of three stages: First, a fully convolutional neural network predicts center and curvature heatmaps for eac

Yang Liu, Zequn Sun, Guangyao Li, Wei Hu

Knowledge graph (KG) embedding seeks to learn vector representations for entities and relations. Conventional models reason over graph structures, but they suffer from the issues of graph incompleteness and long-tail entities. Recent studies have used pre-trained language models to learn embeddings based on the textual information of entities and relations,

Shuhao Zhang, Juan Soto, Volker Markl

Transactional stream processing (TSP) strives to create a cohesive model that merges the advantages of both transactional and stream-oriented guarantees. Over the past decade, numerous endeavors have contributed to the evolution of TSP solutions, uncovering similarities and distinctions among them. Despite these advances, a universally accepted standard appr

Rotem Assouline, Bo'az Klartag

Given two non-empty subsets $A$ and $B$ of the hyperbolic plane $\mathbb{H}^2$, we define their horocyclic Minkowski sum with parameter $\lambda=1/2$ as the set $[A:B]_{1/2} \subseteq \mathbb{H}^2$ of all midpoints of horocycle curves connecting a point in $A$ with a point in $B$. These horocycle curves are parameterized by hyperbolic arclength, and the horo

Lintong Zhang, Michael Helmberger, Lanke Frank Tarimo Fu, David Wisth

Simultaneous Localization and Mapping (SLAM) is being deployed in real-world applications, however many state-of-the-art solutions still struggle in many common scenarios. A key necessity in progressing SLAM research is the availability of high-quality datasets and fair and transparent benchmarking. To this end, we have created the Hilti-Oxford Dataset, to p

Benjamin Koch, Enrique Muñoz, Alessandro Santoni

We consider Very Special Relativity corrections to the energy spectrum of a $C-$invariant Dirac Fermion in a static and homogeneous magnetic field $\vec B$. First, in the case of $\vec B$ parallel to the spatial VSR preferred direction $\vec n$, finding that the expression for the energy spectrum stays the same, except for a correction to the mass arising fr

Venkatesh Rammamoorthy, Geng Zhao, Bharathi Reddy, Ming-Yang Lin

The advent of deep learning has resulted in a number of applications which have transformed the landscape of the research area in which it has been applied. However, with an increase in popularity, the complexity of classical deep neural networks has increased over the years. As a result, this has leads to considerable problems during deployment on devices w

Yang Zhao, Peng Guo, Han Gao, Xiuwan Chen

Unsupervised domain adaptation (UDA) is an approach to minimizing domain gap. Generative methods are common approaches to minimizing the domain gap of aerial images which improves the performance of the downstream tasks, e.g., cross-domain semantic segmentation. For aerial images, the digital surface model (DSM) is usually available in both the source domain

Jianyu Yao, Boqian Shi, Chunyang Xiang, Haipeng Jia

GEMM with the small size of input matrices is becoming widely used in many fields like HPC and machine learning. Although many famous BLAS libraries already supported small GEMM, they cannot achieve near-optimal performance. This is because the costs of pack operations are high and frequent boundary processing cannot be neglected. This paper proposes an inpu

Ismail Lotfi, Hongyang Du, Dusit Niyato, Sumei Sun

Joint radar and communication (JRC) is a promising technique for spectrum re-utilization, which enables radar sensing and data transmission to operate on the same frequencies and the same devices. However, due to the multi-objective property of JRC systems, channel allocation to JRC nodes should be carefully designed to maximize system performance. Additiona

Sourodeep De, Amruta Mishra

The in-medium masses of the open charm ($D$ and $\bar D$) mesons in magnetized isospin asymmetric nuclear matter are investigated within a chiral effective model, including the contributions of the Dirac sea (DS) to the self-energies of the nucleons. Within the model, the masses of these mesons are calculated from their interactions with the nucleons and the

Gi-Soo Kim, Hyun-Joon Yang, Jane P. Kim

Bandit algorithms are widely used in sequential decision problems to maximize the cumulative reward. One potential application is mobile health, where the goal is to promote the user's health through personalized interventions based on user specific information acquired through wearable devices. Important considerations include the type of, and frequency wit

Ying Gao, Qingqing Wu, Wen Chen, Derrick Wing Kwan Ng

In this letter, we study a rate-splitting multiple access (RSMA)-based intelligent reflecting surface (IRS)-aided multi-user multiple-input single-output (MISO) secure communication system with a potential eavesdropper (Eve). Aiming to maximize the minimum secrecy rate (SR) among all the legitimate users (LUs), a design problem for jointly optimizing the tra

Haeseong Moon, Wen-Xin Zhou

The composite quantile regression (CQR) was introduced by Zou and Yuan [Ann. Statist. 36 (2008) 1108--1126] as a robust regression method for linear models with heavy-tailed errors while achieving high efficiency. Its penalized counterpart for high-dimensional sparse models was recently studied in Gu and Zou [IEEE Trans. Inf. Theory 66 (2020) 7132--7154], al

Pintu Bhunia, Kallol Paul, Anirban Sen

We obtain several upper and lower bounds for the numerical radius of sectorial matrices. We also develop several numerical radius inequalities of the sum, product and commutator of sectorial matrices. The inequalities obtained here are sharper than the existing related inequalities for general matrices. Among many other results we prove that if $A$ is an $n\

Xinhan Di, Pengqian Yu

Recent years have witnessed great success for hand reconstruction in real-time applications such as visual reality and augmented reality while interacting with two-hand reconstruction through efficient transformers is left unexplored. In this paper, we propose a method called lightweight attention hand (LWA-HAND) to reconstruct hands in low flops from a sing

Hideaki Iiduka

Practical results have shown that deep learning optimizers using small constant learning rates, hyperparameters close to one, and large batch sizes can find the model parameters of deep neural networks that minimize the loss functions. We first show theoretical evidence that the momentum method (Momentum) and adaptive moment estimation (Adam) perform well in

Sheng Xu, Junkang Wei, Yu Li

Single-strand breaks (SSBs) are the major DNA damage in the genome arising spontaneously as the outcome of genotoxins and intermediates of DNA transactions. SSBs play a crucial role in various biological processes and show a non-random distribution in the genome. Several SSB detection approaches such as S1 END-seq and SSiNGLe-ILM emerged to characterize the

A. Jacob, C. Müller, A. B. Voitkiv

It is generally assumed that for ionization processes, which occur in slow atomic collisions, the coupling of the colliding system to the quantum radiation field is irrelevant. Here we show, however, that -- contrary to expectations -- such a coupling can strongly influence ionization of a beam of atomic species A slowly traversing a gas of atomic species B

Sherry Raj, Tejinder P. Singh

Building on earlier work, we propose an elementary Lagrangian for the unification of the standard model with pre-gravitation, assumed to have an unbroken $E_8 \times E_8$ symmetry. The Lagrangian is patterned after the kinetic energy of a free particle in Newtonian dynamics, generalising it to the matrix-valued Lagrangian dynamics of a 2-brane on a split bio

Mu-Yao Li, Li Wang, Wen-Jie Xie, Wei-Xing Zhou

The importance of fertilizers to agricultural production is undeniable, and most economies rely on international trade for fertilizer use. The stability of fertilizer trade networks is fundamental to food security. We use three valid methods to measure the temporal stability of the overall network and different functional sub-networks of the three fertilizer

Yan Gu, Ziyang Men, Zheqi Shen, Yihan Sun

This paper studies parallel algorithms for the longest increasing subsequence (LIS) problem. Let $n$ be the input size and $k$ be the LIS length of the input. Sequentially, LIS is a simple problem that can be solved using dynamic programming (DP) in $O(n\log n)$ work. However, parallelizing LIS is a long-standing challenge. We are unaware of any parallel LIS

V. K. Suman, Soumyo Sengupta, P. Sundaram, Aditi Sengupta

The analysis of Lax-Wendroff (LW) method is performed by the generic modified differential equation (MDE) approach in the spectral plane using Fourier transform. In this approach, the concept of dispersion relation plays a major role relating spatial and temporal dependence of the governing differential equation, including initial and boundary conditions in

Kai Shao

In this paper, we consider two types of topological solitons in a generalized Born-Infeld-Higgs model. We explore the self-dual structure of the model and prove the existence of planar vortex solutions. Furthermore, we couple the system with the Einstein equations and study the cosmic strings problem over $\mathbb R^{1,1}\times S$, where $S$ is a Riemann sur

Efstathios Konstantinos Chrontsios Garitsis, AJ Hildebrand

Motivated by applications in number theory, analysis, and fractal geometry, we consider regularity properties and dimensions of graphs associated with Fourier series of the form $F(t)=\sum_{n=1}^\infty f(n)e^{2\pi i nt}/n$, for a large class of coefficient functions $f$. Our main result states that if, for some constants $C$ and $\alpha$ with $0<\alpha<1$, w

Sushan Konar

It is proposed that GLEAM-X~J162759.5-523504.3, the newly discovered radio transient with an unusually long spin-period (P$_s$ = 1091.1690s), can be identified to be a Radio Magnetar which has a dipolar surface magnetic field of $2.5 \times 10^{16}$~G. It is shown that - a) it is possible to anchor such a strong field at the core-crust boundary of a neutron

Xiaoxiang Zhou, Yongkai Li, Xinwei Fan, Jiahao Hao

The kagome metals $A$V$_{3}$Sb$_{5}$ ($A$ = K, Rb, Cs) have attracted enormous interest as they exhibit intertwined charge-density wave (CDW) and superconductivity. The alkali-metal dependence of these characteristics contains pivotal information about the CDW and its interplay with superconductivity. Here, we report optical studies of $A$V$_{3}$Sb$_{5}$ acr

Hengzhao Ma, Jianzhong Li, Xiangyu Gao, Tianpeng Gao

The input/output complexity, which is the complexity of data exchange between the main memory and the external memory, has been elaborately studied by a lot of former researchers. However, the existing works failed to consider the input/output complexity in a computation model point of view. In this paper we remedy this by proposing three variants of Turing

Xinrui Yan, Jiangyan Yi, Jianhua Tao, Jie Chen

The rapid progress of deep speech synthesis models has posed significant threats to society such as malicious manipulation of content. This has led to an increase in studies aimed at detecting so-called deepfake audio. However, existing works focus on the binary detection of real audio and fake audio. In real-world scenarios such as model copyright protectio

Aneesh Tickoo, Shweta Chauhan, Gagan Raj Gupta

In today's modern digital world, we have a number of online Question and Answer platforms like Stack Exchange, Quora, and GFG that serve as a medium for people to communicate and help each other. In this paper, we analyzed the effectiveness of Stack Overflow in helping newbies to programming. Every user on this platform goes through a journey. For the first

Amit Rothschild, Nadav Am-Shalom, Nirel Bernstein, Mayan Meron

We present a new ferromagnetic resonance (FMR) method that we term the Ferris FMR. It is wideband, has significantly higher sensitivity as compared to conventional FMR systems, and measures the absorption line rather than its derivative. It is based on large-amplitude modulation of the externally applied magnetic field that effectively magnifies signatures o

Sambuddha Majumder, Sooraj Ravindran

In this study, we designed and optimized the performance of pin junction GaAs/AlGaAs heterojunction nanowire solar cell arrays. It is done by performing coupled optoelectronic simulations to find the optimal doping for the GaAs core and AlGaAs shell, and to see the influence of GaAs and AlGaAs shell thickness and junction positions on the solar cell performa

Jiachen Sun, Weili Nie, Zhiding Yu, Z. Morley Mao

3D Point cloud is becoming a critical data representation in many real-world applications like autonomous driving, robotics, and medical imaging. Although the success of deep learning further accelerates the adoption of 3D point clouds in the physical world, deep learning is notorious for its vulnerability to adversarial attacks. In this work, we first ident

Alan Ehret, Jacob Abraham, Mihailo Isakov, Michel A. Kinsy

Despite the numerous efforts of security researchers, memory vulnerabilities remain a top issue for modern computing systems. Capability-based solutions aim to solve whole classes of memory vulnerabilities at the hardware level by encoding access permissions with each memory reference. While some capability systems have seen commercial adoption, little work

Isa Atas, Cuneyt Ozdemir, Musa Atas, Yahya Dogan

Dental age is one of the most reliable methods to identify an individual's age. By using dental panoramic radiography (DPR) images, physicians and pathologists in forensic sciences try to establish the chronological age of individuals with no valid legal records or registered patients. The current methods in practice demand intensive labor, time, and qualifi

Nur Nasuha Daud, Siti Hafizah Ab Hamid, Chempaka Seri, Muntadher Saadoon

Link prediction analysis becomes vital to acquire a deeper understanding of events underlying social networks interactions and connections especially in current evolving and large-scale social networks. Traditional link prediction approaches underperformed for most large-scale social networks in terms of its scalability and efficiency. Spark is a distributed

Vaseem A. Shaik, Zhiwei Peng, John F. Brady, Gwynn J. Elfring

We analyze a dilute suspension of active particles confined between walls and subjected to fields that can modulate particle speed as well as orientation. Generally, the particle distribution is different in the bulk compared to near the walls. In the bulk, particles tend to accumulate in the regions of low speed, but in the presence of an orienting field, p

Aditya Agarwal, Bipasha Sen, Rudrabha Mukhopadhyay, Vinay Namboodiri

Many people with some form of hearing loss consider lipreading as their primary mode of day-to-day communication. However, finding resources to learn or improve one's lipreading skills can be challenging. This is further exacerbated in the COVID19 pandemic due to restrictions on direct interactions with peers and speech therapists. Today, online MOOCs platfo

Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong

Early classification algorithms help users react faster to their machine learning model's predictions. Early warning systems in hospitals, for example, let clinicians improve their patients' outcomes by accurately predicting infections. While early classification systems are advancing rapidly, a major gap remains: existing systems do not consider irregular t

Weisong Dong

In this paper, we study the Dirichlet problem for $p$-convex hypersurfaces with prescribed curvature. We prove that there exists a graphic hypersurface satisfying the prescribed curvature equation with homogeneous boundary condition. An interior curvature estimate is also obtained.

Xuelin Yang, Louis Abraham, Sejin Kim, Petr Smirnov

The Cox proportional hazards model is a canonical method in survival analysis for prediction of the life expectancy of a patient given clinical or genetic covariates -- it is a linear model in its original form. In recent years, several methods have been proposed to generalize the Cox model to neural networks, but none of these are both numerically correct a

Kai Wu, J. Andrew Zhang, Xiaojing Huang, Y. Jay Guo

Beamspace millimeter-wave (mmWave) and terahertz (THz) massive MIMO constitute attractive schemes for next-generation communications, given their abundant bandwidth and high throughput. However, their user and beam selection problem has to be efficiently addressed. Inspired by this challenge, we develop low-complexity solutions explicitly. We introduce the d

Kai Wu, J. Andrew Zhang, Zhitong Ni, Xiaojing Huang

Joint communication and sensing (JCAS) has the potential to improve the overall energy, cost and frequency efficiency of IoT systems. As a first effort, we propose to optimize the MIMO-OFDM data symbols carried by sub-carriers for better time- and spatial-domain signal orthogonality. This not only boosts the availability of usable signals for JCAS, but also

Shiping Shao, Farshad Harirchi, Devang Dave, Abhishek Gupta

We develop a new algorithm for scheduling the charging process of a large number of electric vehicles (EVs) over a finite horizon. We assume that EVs arrive at the charging stations with different charge levels and different flexibility windows. The arrival process is assumed to have a known distribution and that the charging process of EVs can be preemptive

Marcos M. Flores, Alexander Kusenko, Lauren Pearce, Graham White

We show that viable electroweak baryogenesis can be realized without a first-order phase transition if plasma is heated inhomogeneously by nongravitational structure formation in some particle species. Yukawa interactions can mediate relatively long-range attractive forces in the early Universe. This creates an instability and leads to growth of structure in

Aditya Agarwal, Bipasha Sen, Rudrabha Mukhopadhyay, Vinay Namboodiri

Doubles play an indispensable role in the movie industry. They take the place of the actors in dangerous stunt scenes or scenes where the same actor plays multiple characters. The double's face is later replaced with the actor's face and expressions manually using expensive CGI technology, costing millions of dollars and taking months to complete. An automat

Wang Ping, Wen Yang, Renbao Liu

Projective quantum nondemolition (QND) measurement is important for quantum technologies. Here we propose a method for constructing projective QND measurement on a nuclear spin via the measurement of an axillary electron spin in generic electron-nuclear spin systems coupled through weak hyperfine interaction. The key idea is to apply suitable quantum control

Xue-Feng Zhu, Tianyang Xu, Zhangyong Tang, Zucheng Wu

RGB-D object tracking has attracted considerable attention recently, achieving promising performance thanks to the symbiosis between visual and depth channels. However, given a limited amount of annotated RGB-D tracking data, most state-of-the-art RGB-D trackers are simple extensions of high-performance RGB-only trackers, without fully exploiting the underly

Wang Chao, Liu Weisong, Li Xueqiong, Wang Xiang

Radar signal deinterleaving has been extensively and thoroughly investigated in the electronic reconnaissance field. In this work, a new radar signal multiparameter-based deinterleaving method is proposed. In this method, semantic information composed of the pulse repetition interval (PRI), pulse width (PW), radio frequency (RF), and pulse amplitude (PA) of

Jun Yu, Shunqing Zhang, Jiayun Sun, Shugong Xu

Multi-stream carrier aggregation is a key technology to expand bandwidth and improve the throughput of the fifth-generation wireless communication systems. However, due to the diversified propagation properties of different frequency bands, the traffic migration task is much more challenging, especially in hybrid sub-6 GHz and millimeter wave bands scenario.

Noel A. Clark, Xi Chen, Joseph E. Maclennan, Matthew A. Glaser

Numerous measurements of the dielectric constant $\epsilon$ of the recently discovered ferroelectric nematic ($N_F$) liquid crystal (LC) phase report extraordinarily large values of $\epsilon^\prime$ (up to ~30,000). We show that what is in fact being measured in such experiments is the high capacitance of the non-ferroelectric, interfacial, insulating layer

Dachuan Wu, Bowen Yu, Venus Kakdarvishi, Yasha Yi

Traditional photonic integrated circuit (PIC) inherits the mature CMOS fabrication process from the electronic integrated circuit (IC) industry. However, this process also limits the PIC structure to a single-waveguide-layer configuration. In this work, we explore the possibility of the multi-waveguide-layer PIC by proposing and demonstrating a true 3-D opti

Kai Wu, J. Andrew Zhang, Xiaojing Huang, Robert W. Heath

Joint communications and sensing (JCAS) is potentially a hallmark technology for the sixth generation mobile network (6G). Most existing JCAS designs are based on digital arrays, analog arrays with tunable phase shifters, or hybrid arrays, which are effective but are generally complicated to design and power inefficient. This article introduces the energy-ef

Ahmed S. Alahmed, Lang Tong, Qing Zhao

The co-optimization of behind-the-meter distributed energy resources is considered for prosumers under the net energy metering tariff. The distributed energy resources considered include renewable generations, flexible demands, and battery energy storage systems. An energy management system co-optimizes the consumptions and battery storage based on locally a

Ming Li, Junfeng Wang, Youjin Deng

Explosive percolation in the Achlioptas process has recently attracted much research attention. From extensive simulations in an event-based ensemble, we find that, in dimensions from $2$ to $6$ and on random graphs, the Achlioptas processes all have two scaling windows and multiple fractal structures. The mixing of these multiple scalings successfully expla

Jun Zhuang, Mohammad Al Hasan

Node classification using Graph Neural Networks (GNNs) has been widely applied in various real-world scenarios. However, in recent years, compelling evidence emerges that the performance of GNN-based node classification may deteriorate substantially by topological perturbation, such as random connections or adversarial attacks. Various solutions, such as top

Jesin James, Isabella Shields, Vithya Yogarajan, Peter J. Keegan

Te reo M\=aori (referred to as M\=aori), New Zealand's indigenous language, is under-resourced in language technology. M\=aori speakers are bilingual, where M\=aori is code-switched with English. Unfortunately, there are minimal resources available for M\=aori language technology, language detection and code-switch detection between M\=aori-English pair. Bot

Longrui Dong, Gang Zeng

The ability for a moving agent to localize itself in environment is the basic demand for emerging applications, such as autonomous driving, etc. Many existing methods based on multiple sensors still suffer from drift. We propose a scheme that fuses map prior and vanishing points from images, which can establish an energy term that is only constrained on rota

Yohan Beugin, Quinn Burke, Blaine Hoak, Ryan Sheatsley

Millions of consumers depend on smart camera systems to remotely monitor their homes and businesses. However, the architecture and design of popular commercial systems require users to relinquish control of their data to untrusted third parties, such as service providers (e.g., the cloud). Third parties therefore can (and in some instances have) access the v

Binu Abeysinghe, Jesin James, Catherine I. Watson, Felix Marattukalam

With the recent developments in speech synthesis via machine learning, this study explores incorporating linguistics knowledge to visualise and evaluate synthetic speech model training. If changes to the first and second formant (in turn, the vowel space) can be seen and heard in synthetic speech, this knowledge can inform speech synthesis technology develop

Layton A. Hall, Ayman F. Abouraddy

Introducing angular dispersion into a pulsed field associates each frequency with a particular angle with respect to the propagation axis. A perennial yet implicit assumption is that the propagation angle is differentiable with respect to the frequency. Recent work has shown that the existence of a frequency at which the derivative of the propagation angle d

Willie Aboumrad

We extend a quantized skew Howe duality result for Type $\mathbf{A}$ algebras to orthogonal types via a seesaw. We develop an operator commutant version of the First Fundamental Theorem of invariant theory for $U_q(\mathfrak{so}_n)$ using a double centralizer property inside a quantized Clifford algebra. We obtain a multiplicity-free decomposition of tensor

Shupei Lin, Yong He, Delong Feng, Marek Piliarik

We report that flat substrates such as glass coverslips with surface roughness well below 0.5 nm feature notable speckle patterns when observed with high-sensitivity interference microscopy. We uncover that these speckle patterns unambiguously originate from the subnanometer surface undulations, and develop an intuitive model to illustrate how subnanometer n

V. A. Abakumova, S. L. Lyakhovich

We consider a class of theories with unfree gauge symmetry, whose gauge parameters are restricted by differential equations. We demonstrate that such theories admit global conserved quantities, whose on-shell values are defined by asymptotics of the fields rather than Cauchy data. The global conserved quantities can be deduced proceeding from the equations r

Pengcheng He, Baolin Peng, Liyang Lu, Song Wang

This paper presents Z-Code++, a new pre-trained language model optimized for abstractive text summarization. The model extends the state of the art encoder-decoder model using three techniques. First, we use a two-phase pre-training process to improve model's performance on low-resource summarization tasks. The model is first pre-trained using text corpora f

Dirceu Bagio, Luís Martínez, Héctor Pinedo

The main purpose of this paper is to investigate epsilon-strongly graded rings that are partial crossed products. Let $G$ be a group, $A=\oplus_{g\in G}\,A_g$ an epsilon-strongly graded ring and ${\bf pic}{R}$ the Picard semigroup of $R:=A_1$. We prove that the isomorphism class $[A_g]$ is an element of ${\bf pic}{R}$, for all $g\in G$. Thus, the association

Aurelien Gribinski

We introduce a finite version of free probability for rectangular matrices that amounts to operations on singular values of polynomials. We show that we can replicate the transforms from free probability, and that asymptotically there is convergence from rectangular finite free probability to rectangular free probability. Lastly, we show that classical distr

Adrià Grabulosa, Xavier Porte, Erik Jung, Johnny Moughames

We report single-mode 3D optical couplers leveraging adiabatic power transfer towards up to 4 output ports. We use the CMOS compatible additive (3+1)D \emph{flash}-TPP printing for fast and scalable fabrication. Coupling optical losses of such devices are reduced below $\sim$~0.06~dB by tailoring the coupling and waveguides geometry, and we demonstrate almos

Kiyoung Jo, Emanuele Marino, Jason Lynch, Zhiqiao Jiang

Strong light-matter interactions in localized nano-emitters when placed near metallic mirrors have been widely reported via spectroscopic studies in the optical far-field. Here, we report a near-field nano-spectroscopic study of the localized nanoscale emitters on a flat Au substrate. We observe strong-coupling of the excitonic dipoles in quasi 2-dimensional

Moritz Pflüger, Daniel Brunner, Tobias Heuser, James A. Lott

Networks of optically coupled semiconductor lasers are of high interest for fundamental investigations and for enabling numerous technological applications in material processing, lighting and information processing. Still, experimental realizations of large networks of such elements employing a scalable concepts have so far been been lacking. Here, we prese

Mordechai Guri

It is known that malware can leak data from isolated, air-gapped computers to nearby smartphones using ultrasonic waves. However, this covert channel requires access to the smartphone's microphone, which is highly protected in Android OS and iOS, and might be non-accessible, disabled, or blocked. In this paper we present `GAIROSCOPE,' an ultrasonic covert ch

Mingchen Liu, Robert M. Gray, Luis Costa, Charles R. Markus

Dual-comb spectroscopy has been proven a powerful tool in molecular characterization, which remains challenging to implement in the mid-infrared region due to difficulties in the realization of two mutually locked comb sources and efficient photodetection. Moreover, the detection capability of dual-comb spectroscopy is fundamentally limited by the strong exc

Brian Mintz, Feng Fu

Under constant selection, each trait has a fixed fitness, and small mutation rates allow populations to efficiently exploit the optimal trait. Therefore it is reasonable to expect mutation rates will evolve downwards. However, we find this need not be the case, examining several models of mutation. While upwards evolution of mutation rate has been found with

F. Dai, E. Kosov, V. Temlyakov

The paper addresses a problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization results under a standard assumption formulated in terms of the Nikol'skii-type inequality. {In particular, we obtain} some upper bounds on the number of sample points sufficient fo

Katherine Zhiyuan Zhang

We consider the relativistic Vlasov-Maxwell system (RVM) on a general axisymmetric spatial domain with perfect conducting boundary which reflects particles specularly, assuming axisymmetry in the problem. We construct continuous global parametric solution sets for the time-independent RVM. The solutions in these sets have arbitrarily large electromagnetic fi

Michael DiPasquale, Bryan R. Gillespie, Chris Peterson

A common tool in the theory of numerical semigroups is to interpret a desired class of semigroups as the integer lattice points in a rational polyhedron in order to leverage computational and enumerative techniques from polyhedral geometry. Most arguments of this type make use of a parametrization of numerical semigroups with fixed multiplicity $m$ in terms

Charlotte Frenkel, Giacomo Indiveri

A robust real-world deployment of autonomous edge devices requires on-chip adaptation to user-, environment- and task-induced variability. Due to on-chip memory constraints, prior learning devices were limited to static stimuli with no temporal contents. We propose a 0.45-mm$^2$ spiking RNN processor enabling task-agnostic online learning over seconds, which

Krzysztof Pomorski

The mathematical equivalence between finite state stochastic machine and non-dissipative and dissipative quantum tight-binding and Schroedinger model is derived. Stochastic Finite state machine is also expressed by classical epidemic model and can reproduce the quantum entanglement emerging in the case of electrostatically coupled qubits described by von-Neu

S. N. Klimin, J. Tempere, T. Repplinger, H. Kurkjian

We consider collective excitations in the superfluid state of Fermi condensed charged gases. The dispersion and damping of collective excitations at nonzero temperatures are examined, and the coexistence and interaction of different branches of collective excitations: plasma oscillations, pair-breaking Higgs modes, and Carlson-Goldman phonon-like excitations

Hua-Shu Dou

The Navier-Stokes equation can be written in a form of Poisson equation. For laminar flow in a channel (plane Poiseuille flow), the Navier-Stokes equation has a non-zero source term and a non-zero solution within the domain. For transitional flow, the velocity profile is distorted, and an inflection point or kink appears on the velocity profile, at a suffici

Raida Karim, Edgar Lopez, Elin A. Björling, Maya Cakmak

The intersection of data visualization and human-robot interaction (HRI) is a burgeoning field. Understanding, communicating, and processing different kinds of data for creating versatile visualizations can benefit HRI. Conversely, expressing different kinds of data generated from HRI through effective visualizations can provide interesting insights. Our wor

Alceu Bissoto, Catarina Barata, Eduardo Valle, Sandra Avila

Deep Learning failure cases are abundant, particularly in the medical area. Recent studies in out-of-distribution generalization have advanced considerably on well-controlled synthetic datasets, but they do not represent medical imaging contexts. We propose a pipeline that relies on artifacts annotation to enable generalization evaluation and debiasing for t

Aly Mostafa, Omar Mohamed, Ali Ashraf, Ahmed Elbehery

This research is the second phase in a series of investigations on developing an Optical Character Recognition (OCR) of Arabic historical documents and examining how different modeling procedures interact with the problem. The first research studied the effect of Transformers on our custom-built Arabic dataset. One of the downsides of the first research was

Joshua Ballew, Gautam Iyer, C. David Levermore, Hailiang Liu

The Kompaneets equation governs dynamics of the photon energy spectrum in certain high temperature (or low density) plasmas. We prove several results concerning the long-time convergence of solutions to Bose--Einstein equilibria and the failure of photon conservation. In particular, we show the total photon number can decrease with time via an outflux of pho

Mahdi Morafah, Saeed Vahidian, Weijia Wang, Bill Lin

Classical federated learning approaches yield significant performance degradation in the presence of Non-IID data distributions of participants. When the distribution of each local dataset is highly different from the global one, the local objective of each client will be inconsistent with the global optima which incur a drift in the local updates. This phen

Sangwoong Yoon, Jinwon Choi, Yonghyeon Lee, Yung-Kyun Noh

A reliable evaluation method is essential for building a robust out-of-distribution (OOD) detector. Current robustness evaluation protocols for OOD detectors rely on injecting perturbations to outlier data. However, the perturbations are unlikely to occur naturally or not relevant to the content of data, providing a limited assessment of robustness. In this

Senbao Jiang, Xiaofan Li

In this paper we propose and analyze a general arbitrarily high-order modified trapezoidal rule for a class of weakly singular integrals of the forms $I = \int_{\mathbb{R}^n}\phi(x)s(x)dx$ in $n$ dimensions, where $\phi\in C_c^N(\mathbb{R}^n)$ for some sufficiently large $N$ and $s$ is the weakly singular kernel. The admissible class of weakly singular kerne

Viktor Lopatkin

We give a bijection between meanders and special sorts of Gauss diagrams which aroused from the Thurston generators of braid groups. It allows us to give an algorithm to construct such diagrams and to code meanders by matrices which are exactly incident matrices of the corresponding adjacency graphs of the diagrams. Finally, we show that these matrices are i

Zhuowen Zhao, Tanny Chavez, Elizabeth A. Holman, Guanhua Hao

Machine learning (ML) algorithms are showing a growing trend in helping the scientific communities across different disciplines and institutions to address large and diverse data problems. However, many available ML tools are programmatically demanding and computationally costly. The MLExchange project aims to build a collaborative platform equipped with ena

Z. Fan, D. N. Puzyrev, D. V. Skryabin

Designing metamaterials with the required band structure, topology and chirality using nano-fabrication technology revolutionises modern science and impacts daily life. The approach of this work is, however, different. We take a periodic sequence, i.e., metacrystal, of the dissipative optical solitons rotating in a single ring microresonator and demonstrate

Rony Bou Rouphael, Maël Le Treust

In decentralized decision-making problems, communicating agents choose their actions based on locally available information and knowledge about decision rules or strategies of other agents. In this work, we consider a strategic communication game between an informed encoder and two decoders communicating via a Gray-Wyner network. All three agents are assumed

A. Maafa, H. Mellah, K. Ghedamsi, D. Aouzellag

The current paper presents a Sliding Mode Controller (SMC) for indirect field-oriented Cascaded Doubly Fed Induction Generator (CDFIG) powered through a Matrix Converter (MC). The proposed SMC employs a continuous control strategy to accomplish free chattering fractional-order sliding-mode control and to ensure that the control of the first DFIG stator's rea

Tong Liu, Yuanming Zhu, Anil Korkmaz, Siamak Delshadpour

A linear redriver circuit implements multi-band equalization techniques to efficiently compensate for high-frequency channel loss and extend high-speed wireline link reach. Input and output stage emitter-follower buffers with dual AC and DC paths provide programmable low-frequency peaking for channel skin effect, while a continuous-time linear equalizer (CTL

Ioannis Anagnostides, Gabriele Farina, Tuomas Sandholm

In this paper, we establish efficient and uncoupled learning dynamics so that, when employed by all players in multiplayer perfect-recall imperfect-information extensive-form games, the trigger regret of each player grows as $O(\log T)$ after $T$ repetitions of play. This improves exponentially over the prior best known trigger-regret bound of $O(T^{1/4})$,