July 2022 arXiv papers — page 145

Ting Li, Bin Wang

This paper is devoted to the numerical symplectic approximation of the charged-particle dynamics (CPD) with arbitrary electromagnetic fields. By utilizing continuous-stage methods and exponential integrators, a general class of symplectic methods is formulated for CPD under a homogeneous magnetic field. Based on the derived symplectic conditions, two practic

Dingzhu Wen, Peixi Liu, Guangxu Zhu, Yuanming Shi

This paper studies a new multi-device edge artificial-intelligent (AI) system, which jointly exploits the AI model split inference and integrated sensing and communication (ISAC) to enable low-latency intelligent services at the network edge. In this system, multiple ISAC devices perform radar sensing to obtain multi-view data, and then offload the quantized

Vinod Kumar Bhardwaj, Priyanka Garg, Anirudh Pradhan, Syamala Krishnannair

In the present work, we investigate the power-law entropy corrected holographic dark energy (PLECHDE) model with Hubble horizon cutoff. We use 46 observational Hubble data points in the redshift range $0 \leq z \leq 2.36$ to determine the present Hubble constant $H_0$ and the model parameter $n$. It represents a phase transition of the universe from decelera

Yong Xiao

In modified theories of gravity, higher curvature terms may be added to the Einstein-Hilbert action. Conventionally, the effects of the higher curvature terms on the black hole thermodynamics are rather difficult to obtain. In this paper, we show that, at least at the first order level, the corrections to the thermodynamics of the Schwarzschild black hole ca

Chris Schwiegelshohn, Omar Ali Sheikh-Omar

Coresets are among the most popular paradigms for summarizing data. In particular, there exist many high performance coresets for clustering problems such as $k$-means in both theory and practice. Curiously, there exists no work on comparing the quality of available $k$-means coresets. In this paper we perform such an evaluation. There currently is no algori

Zhangkai Ni, Wenhan Yang, Hanli Wang, Shiqi Wang

Getting rid of the fundamental limitations in fitting to the paired training data, recent unsupervised low-light enhancement methods excel in adjusting illumination and contrast of images. However, for unsupervised low light enhancement, the remaining noise suppression issue due to the lacking of supervision of detailed signal largely impedes the wide deploy

P. Laskos-Patkos, P. S. Koliogiannis, A. Kanakis-Pegios, Ch. C. Moustakidis

Over the last few years, the detection of gravitational waves from binary neutron star systems has rekindled our hopes for a deeper understanding of the unknown nature of ultradense matter. In particular, gravitational wave constraints on the tidal deformability of a neutron star can be translated into constraints on several neutron star properties using a s

Jiajun Chai, Yuanheng Zhu, Dongbin Zhao

Communication-based multi-agent reinforcement learning (MARL) provides information exchange between agents, which promotes the cooperation. However, existing methods cannot perform well in the large-scale multi-agent system. In this paper, we adopt neighboring communication and propose a Neighboring Variational Information Flow (NVIF) to provide efficient co

Anders Karlsson

A general fixed point theorem for isometries in terms of metric functionals is proved under the assumption of the existence of a conical bicombing. It is new even for isometries of Banach spaces as well as for non-locally compact CAT(0)-spaces and injective spaces. Examples of actions on non-proper CAT(0)-spaces come from the study of diffeomorphism groups,

Damián G. Hernández, Ahmed Roman, Ilya Nemenman

A fundamental problem in analysis of complex systems is getting a reliable estimate of entropy of their probability distributions over the state space. This is difficult because unsampled states can contribute substantially to the entropy, while they do not contribute to the Maximum Likelihood estimator of entropy, which replaces probabilities by the observe

Chang Sun, Zili Wang, Shuyou Zhang, Taotao Zhou

As one of the most widely used metal tube bending methods, the rotary draw bending (RDB) process enables reliable and high-precision metal tube bending forming (MTBF). The forming accuracy is seriously affected by the springback and other potential forming defects, of which the mechanism analysis is difficult to deal with. At the same time, the existing meth

Subhrajit Nag, Dhruv Makwana, Sai Chandra Teja R, Sparsh Mittal

As the integration density and design intricacy of semiconductor wafers increase, the magnitude and complexity of defects in them are also on the rise. Since the manual inspection of wafer defects is costly, an automated artificial intelligence (AI) based computer-vision approach is highly desired. The previous works on defect analysis have several limitatio

Kumar Vijay Mishra, Samuel Pinilla, Ali Pezeshki, A. Robert Calderbank

We investigate the theory of affine groups in the context of designing radar waveforms that obey the desired wideband ambiguity function (WAF). The WAF is obtained by correlating the signal with its time-dilated, Doppler-shifted, and delayed replicas. We consider the WAF definition as a coefficient function of the unitary representation of the group $a\cdot

Zhaoyuan Li

This paper studies John's test for sphericity of the error terms in large panel data models, where the number of cross-section units $n$ is large enough to be comparable to the number of times series observations $T$, or even larger. Based on recent random matrix theory results, John's test's asymptotic normality properties are established under both the nul

Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie

Gradient Descent Ascent (GDA) methods are the mainstream algorithms for minimax optimization in generative adversarial networks (GANs). Convergence properties of GDA have drawn significant interest in the recent literature. Specifically, for $\min_{\mathbf{x}} \max_{\mathbf{y}} f(\mathbf{x};\mathbf{y})$ where $f$ is strongly-concave in $\mathbf{y}$ and possi

Edith Cohen, Jelani Nelson, Tamás Sarlós, Uri Stemmer

CountSketch and Feature Hashing (the "hashing trick") are popular randomized dimensionality reduction methods that support recovery of $\ell_2$-heavy hitters (keys $i$ where $v_i^2 > \epsilon \|\boldsymbol{v}\|_2^2$) and approximate inner products. When the inputs are {\em not adaptive} (do not depend on prior outputs), classic estimators applied to a sketch

J. E. Lesnefsky, D. A. Easson, P. C. W. Davies

We discuss the question of whether or not inflationary spacetimes can be geodesically complete in the infinite past. Geodesic completeness is a necessary condition for averting an initial singularity during eternal inflation. It is frequently argued that cosmological models which are expanding sufficiently fast (having average Hubble expansion rate $H_{avg}>

Shi-Liang Wu, Cui-Xia Li

To our knowledge, the error and perturbation bounds of the general absolute value equations are not discussed. In order to fill in this study gap, in this paper, by introducing a class of absolute value functions, we study the error and perturbation bounds of two types of the general absolute value equations (AVEs): $Ax-B|x|=b$ and $Ax-|Bx|=b$. Some useful e

Maicol A. Ochoa

We investigate the energy distribution and quantum thermodynamics in periodically driven polaritonic systems in the stationary state at room temperature. Specifically, we consider an exciton strongly coupled to a harmonic oscillator and quantify the energy reorganization between these two systems and their interaction as a function of coupling strength, driv

Jinming Zhao, Hao Yang, Ehsan Shareghi, Gholamreza Haffari

End-to-end speech-to-text translation models are often initialized with pre-trained speech encoder and pre-trained text decoder. This leads to a significant training gap between pre-training and fine-tuning, largely due to the modality differences between speech outputs from the encoder and text inputs to the decoder. In this work, we aim to bridge the modal

Flavio Moraes, Gabriel H. M. de Aguiar, Emerson G. de Melo, Gustavo S. Wiederhecker

Due to recent development of growing and processing techniques for high-quality single crystal diamond, the large scale production of diamond optomechanical crystal cavities becomes feasible, enabling optomechanical devices that can operate in higher mechanical frequencies and be coupled to two-level systems based on diamond color centers. In this paper we d

Chen-Ming Chang, Jun-Jie Wei, Song-Bo Zhang, Xue-Feng Wu

Tight limits on the photon mass have been set through analyzing the arrival time differences of photons with different frequencies originating from the same astrophysical source. However, all these constraints have relied on using the first-order Taylor expansion of the dispersion due to a nonzero photon mass. In this work, we present an analysis of the nonz

Brendan K. Beare, Juwon Seo, Zhongxi Zheng

Opportunities for stochastic arbitrage in an options market arise when it is possible to construct a portfolio of options which provides a positive option premium and which, when combined with a direct investment in the underlying asset, generates a payoff which stochastically dominates the payoff from the direct investment in the underlying asset. We provid

Chia-Min Chung, Matteo M. Wauters, Michele Burrello

Superconducting devices subject to strong charging energy interactions and Coulomb blockade are one of the key elements for the development of nanoelectronics and constitute common building blocks of quantum computation platforms and topological superconducting setups. The study of their transport properties is non-trivial and some of their non-perturbative

Zhi-Gang Wang

Motivated by the analogous properties of the $Z_c(3900/3885)$ and $Z_{cs}(3985/4000)$, we tentatively assign the $Z_c(4020/4025)$ as the $A\bar{A}$-type hidden-charm tetraquark state with the $J^{PC}=1^{+-}$, where the $A$ denotes the axialvector diquark states, and explore the $A\bar{A}$-type tetraquark states without strange, with strange and with hidden-s

Sheng Yue, Dan-Yang Chen, Chenrong Liu, Ming Yang

We analytically study the ground-state phase diagrams of ultracold bosons with various values of the effective magnetic quantum number $m$ in a state-dependent hexagonal optical lattice by using the generalized effective-potential Landau theory, where the site-offset energy between the two triangular sublattice A and B is tunable. Our analytical calculations

Bhargav Ghanekar, Vishwanath Saragadam, Dushyant Mehra, Anna-Karin Gustavsson

We propose a compact snapshot monocular depth estimation technique that relies on an engineered point spread function (PSF). Traditional approaches used in microscopic super-resolution imaging such as the Double-Helix PSF (DHPSF) are ill-suited for scenes that are more complex than a sparse set of point light sources. We show, using the Cram\'er-Rao lower bo

Cong Yue, Tien Tuan Anh Dinh, Zhongle Xie, Meihui Zhang

Verifiable ledger databases protect data history against malicious tampering. Existing systems, such as blockchains and certificate transparency, are based on transparency logs -- a simple abstraction allowing users to verify that a log maintained by an untrusted server is append-only. They expose a simple key-value interface. Building a practical database f

Fuzhi Yang, Huan Yang, Yanhong Zeng, Jianlong Fu

Blind super-resolution (SR) aims to recover high-quality visual textures from a low-resolution (LR) image, which is usually degraded by down-sampling blur kernels and additive noises. This task is extremely difficult due to the challenges of complicated image degradations in the real-world. Existing SR approaches either assume a predefined blur kernel or a f

Nathaniel Hanson, Tarik Kelestemur, Deniz Erdogmus, Taskin Padir

Robots benefit from being able to classify objects they interact with or manipulate based on their material properties. This capability ensures fine manipulation of complex objects through proper grasp pose and force selection. Prior work has focused on haptic or visual processing to determine material type at grasp time. In this work, we introduce a novel p

Changbo Zhu, Jane-Ling Wang

Testing the homogeneity between two samples of functional data is an important task. While this is feasible for intensely measured functional data, we explain why it is challenging for sparsely measured functional data and show what can be done for such data. In particular, we show that testing the marginal homogeneity based on point-wise distributions is fe

Ying Hu, Yuwu Tang, Hao Huang, Liang He

Speech emotion recognition (SER) is an essential part of human-computer interaction. In this paper, we propose an SER network based on a Graph Isomorphism Network with Weighted Multiple Aggregators (WMA-GIN), which can effectively handle the problem of information confusion when neighbour nodes' features are aggregated together in GIN structure. Moreover, a

Huan Yee Koh, Jiaxin Ju, Ming Liu, Shirui Pan

Long documents such as academic articles and business reports have been the standard format to detail out important issues and complicated subjects that require extra attention. An automatic summarization system that can effectively condense long documents into short and concise texts to encapsulate the most important information would thus be significant in

Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele, Rene Vidal

There is a growing concern about typically opaque decision-making with high-performance machine learning algorithms. Providing an explanation of the reasoning process in domain-specific terms can be crucial for adoption in risk-sensitive domains such as healthcare. We argue that machine learning algorithms should be interpretable by design and that the langu

Mohammad Abu Khater, Dimitrios Peroulis

High-power interferers are one of the main hurdles in wideband communication channels. To that end, this paper presents a wideband interferer detection method. The presented technique operates by sampling the incoming signal as an input, and produces the frequency and the power readings of the detected interferer. The detection method relies on driving an op

Liang Tian, Chengzhi Zhang

COVID-19 has had a profound impact on the lives of all human beings. Emerging technologies have made significant contributions to the fight against the pandemic. An extensive review of the application of technology will help facilitate future research and technology development to provide better solutions for future pandemics. In contrast to the extensive su

Kuijun Zuo, Shuhui Bu, Weiwei Zhang, Jiawei Hu

In order to obtain the information about flow field, traditional computational fluid dynamics methods need to solve the Navier-Stokes equations on the mesh with boundary conditions, which is a time-consuming task. In this work, a data-driven method based on convolutional neural network and multi-head perceptron is used to predict the incompressible laminar s

Yu-An Tsai, Sheng D. Chao

We propose an extension of Wenzel-Kramers-Brillouin (WKB) approximation for solving the Schr\"odinger equation. A set of coupled differential equations is obtained by considering an ansatz of the wave function with an auxiliary condition on gauging its first derivative. It is shown that the alternating perturbation method can decouple the set of differential

Mingsheng Yin, Yaqi Hu, Tommy Azzino, Seongjoon Kang

Site-specific radio frequency (RF) propagation prediction increasingly relies on models built from visual data such as cameras and LIDAR sensors. When operating in dynamic settings, the environment may only be partially observed. This paper introduces a method to extract statistical channel models, given partial observations of the surrounding environment. W

Wei Tang, Margaret Martonosi

Quantum processing unit (QPU) has to satisfy highly demanding quantity and quality requirements on its qubits to produce accurate results for problems at useful scales. Furthermore, classical simulations of quantum circuits generally do not scale. Instead, quantum circuit cutting techniques cut and distribute a large quantum circuit into multiple smaller sub

Donghoon Jang

It is known that the complex projective space $\mathbb{CP}^n$ admits a spin structure if and only if $n$ is odd. In this paper, we provide another proof that $\mathbb{CP}^{2m}$ does not admit a spin structure, by using a circle action.

Hans Buehler, Phillip Murray, Ben Wood

We present an actor-critic-type reinforcement learning algorithm for solving the problem of hedging a portfolio of financial instruments such as securities and over-the-counter derivatives using purely historic data. The key characteristics of our approach are: the ability to hedge with derivatives such as forwards, swaps, futures, options; incorporation of

Jiaxin Wu, Pingfeng Wang

Interconnected complex systems usually undergo disruptions due to internal uncertainties and external negative impacts such as those caused by harsh operating environments or regional natural disaster events. To maintain the operation of interconnected network systems under both internal and external challenges, design for resilience research has been conduc

Sadjad Arzash, Abhinav Sharma, Fred C. MacKintosh

Biopolymer networks are common in biological systems from the cytoskeleton of individual cells to collagen in the extracellular matrix. The mechanics of these systems under applied strain can be explained in some cases by a phase transition from soft to rigid states. For collagen networks, it has been shown that this transition is critical in nature and it i

Toshiki Kawamoto, Hidetaka Kamigaito, Kotaro Funakoshi, Manabu Okumura

A repetition is a response that repeats words in the previous speaker's utterance in a dialogue. Repetitions are essential in communication to build trust with others, as investigated in linguistic studies. In this work, we focus on repetition generation. To the best of our knowledge, this is the first neural approach to address repetition generation. We pro

Qidan Zhu, Jing Li, Fei Yuan, Quan Gan

Aiming at the problem that the spatial-temporal hierarchical continuous sign language recognition model based on deep learning has a large amount of computation, which limits the real-time application of the model, this paper proposes a temporal super-resolution network(TSRNet). The data is reconstructed into a dense feature sequence to reduce the overall mo

Sepehr Assadi, Aaron Bernstein, Aditi Dudeja

We consider the problem of maintaining an approximate maximum integral matching in a dynamic graph $G$, while the adversary makes changes to the edges of the graph. The goal is to maintain a $(1+\epsilon)$-approximate maximum matching for constant $\epsilon>0$, while minimizing the update time. In the fully dynamic setting, where both edge insertion and dele

Meng Mei, Tao Yu, Yuan Jiang

Multiple testing has been a popular topic in statistical research. Although vast works have been done, controlling the false discoveries remains a challenging task when the corresponding test statistics are dependent. Various methods have been proposed to estimate the false discovery proportion (FDP) under arbitrary dependence among the test statistics. One

Maria Angelika-Nikita, Celso M. de Melo, Kazunori Terada, Gale Lucas

Social games like the prisoner's dilemma are often used to develop models of the role of emotion in social decision-making. Here we examine an understudied aspect of emotion in such games: how an individual's feelings are shaped by their partner's expressions. Prior research has tended to focus on other aspects of emotion. Research on felt-emotion has focuse

Canhong Wen, Qin Wang, Yuan Jiang

The reduced-rank regression model is a popular model to deal with multivariate response and multiple predictors, and is widely used in biology, chemometrics, econometrics, engineering, and other fields. In the reduced-rank regression modelling, a central objective is to estimate the rank of the coefficient matrix that represents the number of effective laten

Wei Zhang

In this paper, we consider the fractional sum of the divisor functions. We can improve previous results considered by Bordell\'{e}s \cite{Bo} and Liu-Wu-Yang \cite{LWY}.

Lennard F Bakker, Pedro Martins Rodrigues

We show that a collection of generalized Bowen-Franks group, what we call the principal Bowen-Franks $R$-modules, form a complete set of $R$-module invariants for the equivalence relation of profinite conjugacy for similar hyperbolic toral automorphisms. We also show that these principal generalized Bowen-Franks $R$-modules are the principal invariants in a

Vinay K Chaudhri

A computable contract is a contract that a computer can read, understand and execute. The financial services industry makes extensive use of contracts, for example, mortgage agreements, derivatives contracts, arbitration agreements, etc. Most of these contracts exist as text documents, making it difficult to automatically query, execute and analyze them. In

Junaid Rasheed, Michal Konečný

We give a process for verifying numerical programs against their functional specifications. Our implementation is capable of automatically verifying programs against tight error bounds featuring common elementary functions. We demonstrate and evaluate our implementation on several examples, yielding the first fully verified SPARK implementations of the sine

Evgeny Dantsin, Vladik Kreinovich, Alexander Wolpert

AlphaZero and its extension MuZero are computer programs that use machine-learning techniques to play at a superhuman level in chess, go, and a few other games. They achieved this level of play solely with reinforcement learning from self-play, without any domain knowledge except the game rules. It is a natural idea to adapt the methods and techniques used i

Shamil Asgarli, Dragos Ghioca, Zinovy Reichstein

Let $K$ be a finitely generated field. We construct an $n$-dimensional linear system $\mathcal{L}$ of hypersurfaces of degree $d$ in $\mathbb{P}^n$ defined over $K$ such that each member of $\mathcal{L}$ defined over $K$ is smooth, under the hypothesis that the characteristic $p$ does not divide $\gcd(d, n+1)$ (in particular, there is no restriction when $K$

Omer Aydin

The need for different energy sources has increased due to the decrease in the amount and the harm caused to the environment by its usage. Today, fossil fuels used as an energy source in land, sea or air vehicles are rapidly being replaced by different energy sources. The number and types of vehicles using energy sources other than fossil fuels are also incr

Pingxu Hu, Jin Tao, Dachun Yang

Let $p,q\in [1,\infty]$, $\alpha\in{\mathbb{R}}$, and $s$ be a non-negative integer. In this article, the authors introduce a new function space $\widetilde{JN}_{(p,q,s)_{\alpha}}(\mathcal{X})$ of John-Nirenberg-Campanato type, where $\mathcal{X}$ denotes $\mathbb{R}^n$ or any cube $Q_{0}$ of $\mathbb{R}^n$ with finite edge length. The authors give an equiva

Xiangfeng Zhu, Guozhen She, Bowen Xue, Yu Zhang

Service meshes play a central role in the modern application ecosystem by providing an easy and flexible way to connect different services that form a distributed application. However, because of the way they interpose on application traffic, they can substantially increase application latency and resource consumption. We develop a decompositional approach a

Mark Dalthorp

We prove a probabilistic generalization of the classic result that infinite power towers, $c^{c^{\dots}}$, converge if and only if $c\in[e^{-e},e^{1/e}]$. Given an i.i.d. sequence $\{A_i\}_{i\in\mathbb N}$, we find that convergence of the power tower $A_1^{A_2^{\dots}}$ is determined by the bounds of $A_1$'s support, $a=\inf(\mathrm{supp}(A_1))$ and $b=\sup(

Zoe Xi, William Kuszmaul

Dynamic Time Warping (DTW) is a widely used similarity measure for comparing strings that encode time series data, with applications to areas including bioinformatics, signature verification, and speech recognition. The standard dynamic-programming algorithm for DTW takes $O(n^2)$ time, and there are conditional lower bounds showing that no algorithm can do

Qiaoling Chen, Jun Zheng, Guchuan Zhu

For an arbitrary parameter $p\in [1,+\infty]$, we consider the problem of exponential stabilization in the spatial $L^{p}$-norm, and $W^{1,p}$-norm, respectively, for a class of anti-stable linear parabolic PDEs with space-time-varying coefficients in the absence of a Gevrey-like condition, which is often imposed on time-varying coefficients of PDEs and used

Zurab Khasidashvili

We propose a root-causing procedure for accelerating system-level debug using rule-based techniques. We describe the procedure and how it provides high quality debug hints for reducing the debug effort. This includes the heuristics for engineering features from logs of many tests, and the data analytics techniques for generating powerful debug hints. As a ca

Jinghang Lin, Yuan Huang, Shuangge Ma

If error distribution has heteroscedasticity, it voliates the assumption of linear regression. Expectile regression is a powerful tool for estimating the conditional expectiles of a response variable in this setting. Since multiple levels of expectile regression modelhas been well studied, we propose composite expectile regression by combining different leve

Yuhao Nie, Xiatong Li, Andea Scott, Yuchi Sun

Large-scale integration of photovoltaics (PV) into electricity grids is challenged by the intermittent nature of solar power. Sky-image-based solar forecasting using deep learning has been recognized as a promising approach to predicting the short-term fluctuations. However, there are few publicly available standardized benchmark datasets for image-based sol

Alejandra Garrido, Andrei Jaikin-Zapirain

Can one detect free products of groups via their profinite completions? We answer positively among virtually free groups. More precisely, we prove that a subgroup of a finitely generated virtually free group $G$ is a free factor if and only if its closure in the profinite completion of $G$ is a profinite free factor. This generalises results by Parzanchevski

Satvik Sharma, Ellen Novoseller, Vainavi Viswanath, Zaynah Javed

Simulation-to-reality transfer has emerged as a popular and highly successful method to train robotic control policies for a wide variety of tasks. However, it is often challenging to determine when policies trained in simulation are ready to be transferred to the physical world. Deploying policies that have been trained with very little simulation data can

Dmitri Scheglov

We provide a lower bound on the complexity function of a typical (in the Lebesgue measure sence) right triangular billiard.

Hassan Wagih, Mostafa Osman, Mohamed I. Awad, Sherif Hammad

In this paper, an approach for reducing the drift in monocular visual odometry algorithms is proposed based on a feedforward neural network. A visual odometry algorithm computes the incremental motion of the vehicle between the successive camera frames, then integrates these increments to determine the pose of the vehicle. The proposed neural network reduces

Yuntian Deng, Xingyu Zhou, Arnob Ghosh, Abhishek Gupta

To fully utilize the abundant spectrum resources in millimeter wave (mmWave), Beam Alignment (BA) is necessary for large antenna arrays to achieve large array gains. In practical dynamic wireless environments, channel modeling is challenging due to time-varying and multipath effects. In this paper, we formulate the beam alignment problem as a non-stationary

Claire Little, Mark Elliot, Richard Allmendinger

Most statistical agencies release randomly selected samples of Census microdata, usually with sample fractions under 10% and with other forms of statistical disclosure control (SDC) applied. An alternative to SDC is data synthesis, which has been attracting growing interest, yet there is no clear consensus on how to measure the associated utility and disclos

Anna Nguyen, Antonio Longa, Massimiliano Luca, Joe Kaul

Anticipating audience reaction towards a certain piece of text is integral to several facets of society ranging from politics, research, and commercial industries. Sentiment analysis (SA) is a useful natural language processing (NLP) technique that utilizes both lexical/statistical and deep learning methods to determine whether different sized texts exhibit

Gabriel Mercado-Vásquez, Denis Boyer, Satya N. Majumdar

During a random search, resetting the searcher's position from time to time to the starting point often reduces the mean completion time of the process. Although many different resetting models have been studied over the past ten years, only a few can be physically implemented. Here we study theoretically a protocol that can be realised experimentally and wh

Paul M. Alsing

In this work we explore the possibility of quantum bound states in a Schwarzschild gravitational field leveraging the analogy of the elementary derivation of bound states in the Coulomb potential as taught in an undergraduate course in Quantum Mechanics. For this we will also need to go beyond non-relativistic quantum mechanics and utilize the relativistic D

Zu-Jian Ying

Universality is a common quality in different physical parameters that is rooted in the deep nature of physical systems. Scaling relation is a typical universality for critical phenomena around a quantum phase transition, while topological classification provides another type of universality essentially different from the critical universality. Both classes

Seyyed Mostafa Mousavi Janbeh Sarayi, Mansour Nikkhah Bahrami

Gradient descent optimizations and backpropagation are the most common methods for training neural networks, but they are computationally expensive for real time applications, need high memory resources, and are difficult to converge for many networks and large datasets. [Pseudo]inverse models for training neural network have emerged as powerful tools to ove

Jamshid Sourati, James Evans

Neither artificial intelligence designed to play Turing's imitation game, nor augmented intelligence built to maximize the human manipulation of information are tuned to accelerate innovation and improve humanity's collective advance against its greatest challenges. We reconceptualize and pilot beneficial AI to radically augment human understanding by comple

Yichao Yang, Hagen Gress, Kamil L. Ekinci

Bacteria meticulously regulate their intracellular ion concentrations and create ionic concentration gradients across the bacterial membrane. These ionic concentration gradients provide free energy for many cellular processes and are maintained by transmembrane transport. Given the physical dimensions of a bacterium and the stochasticity in transmembrane tra

Tamir Shaqarin, Bernd R. Noack

We dramatically improve convergence speed and global exploration capabilities of particle swarm optimization (PSO) through a targeted position-mutated elitism (PSO-TPME). The three key innovations address particle classification, elitism, and mutation in the cognitive and social model. PSO-TPME is benchmarked against five popular PSO variants for multi-dimen

Marija Ivanovska, Andrej Kronovšek, Peter Peer, Vitomir Štruc

Images of morphed faces pose a serious threat to face recognition--based security systems, as they can be used to illegally verify the identity of multiple people with a single morphed image. Modern detection algorithms learn to identify such morphing attacks using authentic images of real individuals. This approach raises various privacy concerns and limits

Ding-fang Zeng

We suggest that behind the black hole information paradox is a new and universal radiation mechanism, Gravity Induced Spontaneous Radiation, or GISR hereafter. This mechanism happens to all kinds of compositional objects and it requires only their microscopic structure as the basis. It's always accompanied with such inner structures' variation and allows for

Anetta Jedlickova, Martin Loebl, David Sychrovsky

Distribution crises are manifested by a great discrepancy between the demand and the supply of a critically important good, for a period of time. In this paper, we suggest a hybrid market mechanism for minimising the negative consequences of sudden distribution crises.

200 Collaboration, S. Al Kharusi, G. Anton, I. Badhrees

We present a search for electron-recoil signatures from the charged-current absorption of fermionic dark matter using the EXO-200 detector. We report an average electron recoil background rate of $6.8 \times 10^{-4}\, \mathrm{cts}\,\mathrm{kg}^{-1}\mathrm{yr}^{-1}\mathrm{keV}^{-1}$ above $4\,\mathrm{MeV}$ and find no statistically significant excess over our

Maheshya Weerasinghe, Verena Biener, Jens Grubert, Aaron J Quigley

Learning vocabulary in a primary or secondary language is enhanced when we encounter words in context. This context can be afforded by the place or activity we are engaged with. Existing learning environments include formal learning, mnemonics, flashcards, use of a dictionary or thesaurus, all leading to practice with new words in context. In this work, we p

Akhlesh Lakhtakia, Tom G. Mackay, Waleed I. Waseer

Vanadium dioxide (VO2) transforms from purely monoclinic to purely tetragonal on being heated from 58 deg C to 72 deg C, the transformation being reversible but hysteretic. Electromagnetically, VO2 transforms from a dissipative dielectric to another dissipative dielectric if the free-space wavelength is less than 1100 nm, but from a dissipative dielectric to

Mohammad Masum, Md Jobair Hossain Faruk, Hossain Shahriar, Kai Qian

Malicious attacks, malware, and ransomware families pose critical security issues to cybersecurity, and it may cause catastrophic damages to computer systems, data centers, web, and mobile applications across various industries and businesses. Traditional anti-ransomware systems struggle to fight against newly created sophisticated attacks. Therefore, state-

Rabia Tahir, Syedah Afsheen Zahra, Usman Naeem, Syed Rizwan

Two-dimensional (2D) multiferroics are key candidate materials towards advancement of smart technology. Here, we employed a simple synthesis approach to address the long-awaited dream of developing ferroelectric and multiferroic 2D materials, specially in the new class of materials called MXenes. The etched Ti$_3$C$_2$T$_x$ MXene was first synthesized after

Md Jobair Hossain Faruk, Santhiya Subramanian, Hossain Shahriar, Maria Valero

Software Engineering is the process of a systematic, disciplined, quantifiable approach that has significant impact on large-scale and complex software development. Scores of well-established software process models have long been adopted in the software development life cycle that pour stakeholders towards the completion of final software product developmen

James E. McClure, Ming Fan, Steffen Berg, Ryan T. Armstrong

Relative permeability is commonly used to model immiscible fluid flow through porous materials. In this work we derive the relative permeability relationship from conservation of energy, assuming that the system to be non-ergodic at large length scales and relying on averaging in both space and time to homogenize the behavior. Explicit criteria are obtained

Tyson Brooks

Society is inextricably dependent on the Internet and other globally interconnected infrastructures used in the provisioning of information services. The growth of information technology (IT) and information systems (IS) over the past decades has created an unprecedented demand for access to information. The implication of wireless mobility are great, and th

Yash V. Mandlecha, Rajiv V. Gavai

We apply the physically more appealing MIT Bag boundary conditions to study the Casimir effect on the lattice. Employing the formalism of arXiv:2005.10758 to calculate the Casimir energy for free lattice fermions, we show that the results for the naive, Wilson and overlap fermions match the continuum expressions precisely in the zero lattice spacing limit, a

Anirban Chatterjee, Biswajit Jana, Abhijit Bandyopadhyay

It has been shown by \textit{Scherrer and Putter et.al} that, when dynamics of dark energy is driven by a homogeneous $k-$essence scalar field $\phi$, with a Lagrangian of the form $L = V_0F(X)$ with a constant potential $V_0$ and $X = \frac{1}{2}\nabla^\mu\phi \nabla_\mu\phi = \frac{1}{2}\dot{\phi}^2$, one obtains a scaling relation $X(dF/dX)^2 = Ca^{-6}$ ,

Xiaohao Xu, Jinglu Wang, Xiang Ming, Yan Lu

In the booming video era, video segmentation attracts increasing research attention in the multimedia community. Semi-supervised video object segmentation (VOS) aims at segmenting objects in all target frames of a video, given annotated object masks of reference frames. Most existing methods build pixel-wise reference-target correlations and then perform pix

Vassil Yorgov

Let H be the standard Hadamard matrix of order two and let K=2^{-1/2}H. It is known that the complete weight enumerator $\ W$ of a binary self-dual code of length $n$ is an eigenvector corresponding to an eigenvalue 1 of the Kronecker power $K^{[n]}.$ For every integer $t$ in the interval [0,n] we define the derivative of order $t$, $W_{<t>},$ of $W$ in such

Yuanyuan Li, Claudia Archetti, Ivana Ljubic

In this paper, we study a sequential decision-making problem faced by e-commerce carriers related to when to send out a vehicle from the central depot to serve customer requests, and in which order to provide the service, under the assumption that the time at which parcels arrive at the depot is stochastic and dynamic. The objective is to maximize the expect

Arnaud Beauville

Let C be a curve of genus g, and G a finite group of automorphisms of C . We prove that for g > 20 the quotient JC/G has canonical singularities, hence Kodaira dimension 0. On the other hand we give examples of curves C with g < 5 for which JC/G is uniruled.

Vikramjit Mitra, Hsiang-Yun Sherry Chien, Vasudha Kowtha, Joseph Yitan Cheng

Estimating dimensional emotions, such as activation, valence and dominance, from acoustic speech signals has been widely explored over the past few years. While accurate estimation of activation and dominance from speech seem to be possible, the same for valence remains challenging. Previous research has shown that the use of lexical information can improve

Kun Wei, Pengcheng Guo, Ning Jiang

Transformer-based models have demonstrated their effectiveness in automatic speech recognition (ASR) tasks and even shown superior performance over the conventional hybrid framework. The main idea of Transformers is to capture the long-range global context within an utterance by self-attention layers. However, for scenarios like conversational speech, such u

Christopher Penschke, John Thomas, Cord Bertram, Angelos Michaelides

Understanding the molecular and electronic structure of electrolytes at interfaces requires an analysis of the interactions between the electrode surface, the ions, and the solvent environment on equal footing. Here, we tackle this challenge by exploring the initial stages of Cs+ hydration on a Cu(111) surface by combining experiment and theory. Remarkably,

Narges Rashidi

By adopting the intermediate and power-law scale factors, we study the tachyon inflation with constant sound speed. We perform some numerical analysis on the perturbation and non-gaussianity parameters in this model and compare the results with observational data. By using the constraints on the scalar spectral index and tensor-to-scalar-ratio, obtained from