January 2022 arXiv papers — page 23

Penglei Gao, Xi Yang, Rui Zhang, John Y. Goulermas

In this paper, we develop a novel transformer-based generative adversarial neural network called U-Transformer for generalised image outpainting problem. Different from most present image outpainting methods conducting horizontal extrapolation, our generalised image outpainting could extrapolate visual context all-side around a given image with plausible str

Gustavo P. de Brito, Astrid Eichhorn

We explore the effect of quantum gravity on matter within a Renormalization Group framework. First, our results provide an explicit example of how misleading conclusions can be drawn by analyzing the gravitational contributions to beta functions, instead of analyzing universal quantities, such as critical exponents, that can be extracted from the beta functi

Heinz-Jürgen Schmidt, Christian Schröder

The classical spin system consisting of three spins with Heisenberg interaction is an example of a completely integrable mechanical system. In this paper we explicitly calculate thermodynamic quantities as density of states, specific heat, susceptibility and spin autocorrelation functions. These calculations are performed (semi-)analytically and shown to agr

Chunyong Yang, Pengfei Liu, Yanli Chen, Hongbin Wang

This paper presents our MSXF TTS system for Task 3.1 of the Audio Deep Synthesis Detection (ADD) Challenge 2022. We use an end to end text to speech system, and add a constraint loss to the system when training stage. The end to end TTS system is VITS, and the pre-training self-supervised model is wav2vec 2.0. And we also explore the influence of the speech

Dheeraj Pratap, Jitendra Kumar Pradhan, Subramanium Anantha Ramakrishna

In this article, we demonstrate experimentally and verified numerically the excitation of Berreman modes that propagate in a dielectric film of uniaxial anisotropic nanoporous alumina grown on an aluminium substrate. It is an air-dielectric-metal asymmetric polaritonic system with a real part of the effective permittivity having a value near zero. The modes

Rahul Basu, Dipanjan Mitra, George I. Melikidze

The pulsar profile is characterised by two distinct emission components, the core and the cone. The standard model of a pulsar radio emission beam originating from dipolar magnetic fields, places the core at the centre surrounded by concentric layers of inner and outer conal components. The core emission is expected to have steeper spectra compared to the co

Ryutaro Tsuji, Yasumichi Aoki, Ken-Ichi Ishikawa, Yoshinobu Kuramashi

We present preliminary results for the axial, scalar and tensor charges of the nucleon measured in 2+1 flavor QCD with the physical light quarks ($m_\pi=135$ MeV). Our simulations are carried out with gauge configurations generated by the PACS Collaboration with the stout-smeared $O(a)$ improved Wilson fermions and Iwasaki gauge action at a single lattice sp

N. Li, R. R. Neumann, S. K. Guang, Q. Huang

The thermal Hall effect, defined as a heat current response transversal to an applied temperature gradient, is a central experimental probe of exotic electrically insulating phases of matter. A key question is how the interplay between magnetic and structural degrees of freedom gives rise to a nonzero thermal Hall conductivity (THC). Here, we present evidenc

Ozan Günyüz

This paper primarily concerns the variance estimate of zeros of systems of random holomorphic sections associated with a sequence of smooth Hermitian holomorphic line bundles on a compact Kahler manifold X. The probability measures taken into consideration in this paper satisfy a certain condition which makes it much more general(possibly the most general) t

Koichi Miyamoto

Finance is one of the promising field for industrial application of quantum computing. In particular, quantum algorithms for calculation of risk measures such as the value at risk and the conditional value at risk of a credit portfolio have been proposed. In this paper, we focus on another problem in credit risk management, calculation of risk contributions,

Shikma Bressler, Federico De Vito Halevy, Yosef Nir

The $R(D^{(*)})$ puzzle stands for a $\sim3\sigma$ violation of lepton flavor universality between the decay rates of $B\to D^{(*)}\tau\nu$ and $B\to D^{(*)}\ell\nu$, where $\ell=e,\mu$. If it is accounted for by new physics, there is no reason in general that the relevant neutrinos are, respectively, $\nu_\tau$ and $\nu_\ell$. We study whether the $\tau$ re

M. Fenucci, G. F. Gronchi, M. Saillenfest

Proper elements are quasi-integrals of motion, meaning that they can be considered constant over a certain timespan, and they permit to describe the long-term evolution with a few parameters. Near-Earth objects (NEOs) generally have a large eccentricity and therefore they can cross the orbits of the planets. Moreover, some of them are known to be currently i

Jivnesh Sandhan, Ayush Daksh, Om Adideva Paranjay, Laxmidhar Behera

Nowadays, the interest in code-mixing has become ubiquitous in Natural Language Processing (NLP); however, not much attention has been given to address this phenomenon for Speech Translation (ST) task. This can be solely attributed to the lack of code-mixed ST task labelled data. Thus, we introduce Prabhupadavani, which is a multilingual code-mixed ST datase

Hans van Haren

The passionate plea for the use of scientific colour maps misses some aspects in the visual presentation of scientific data. While a linear colour map based on scientific human colour perception is useful for the presentation of some images, like the three examples given of the topography of the earth, an apple and a passport photograph, scientific data are

Mikhail Lifshits, Arman Tadevosian

We describe the behavior of the expectation of the maximum for a random assignment process built upon a square matrix with independent entries. Under mild assumptions on the underlying distribution, the answer is expressed in terms of its quantile function.

Dionne Takudzwa Chasi, Mkhuseli Ngxande

In the age of streaming and surveillance compressed video enhancement has become a problem in need of constant improvement. Here, we investigate a way of improving the Multi-Frame Quality Enhancement approach. This approach consists of making use of the frames that have the peak quality in the region to improve those that have a lower quality in that region.

Feng Yang, Yichao Cao, Qifan Xue, Shuai Jin

Learning a powerful representation from point clouds is a fundamental and challenging problem in the field of computer vision. Different from images where RGB pixels are stored in the regular grid, for point clouds, the underlying semantic and structural information of point clouds is the spatial layout of the points. Moreover, the properties of challenging

K. Feijen, S. Einecke, G. Rowell, C. Braiding

HESS J1804-216 is one of the brightest yet most mysterious TeV gamma-ray sources discovered to date. Previous arc-minute scale studies of the interstellar medium (ISM) surrounding this TeV gamma-ray source revealed HESS J1804-216 is likely powered by a mature supernova remnant (SNR) or pulsar, hence its origin remains uncertain. In this paper, we focus on th

Liwei Duan

A scheme for implementing the discrete-time quantum walk on the Bloch sphere is proposed, which is closely related to the SU(2) group. A spin cluster serves as the walker, whereas its location on the Bloch sphere is described by the spin coherent state. An additional spin that interacts with the spin cluster plays the role of a coin, whose state determines t

Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi

The 5G wireless networks are potentially revolutionizing future technologies. The 5G technologies are expected to foresee demands of diverse vertical applications with diverse requirements including high traffic volume, massive connectivity, high quality of service, and low latency. To fulfill such requirements in 5G and beyond, new emerging technologies suc

Samuel Pinilla, Kumar Vijay Mishra, Brian M. Sadler, Henry Arguello

The ability of a radar to discriminate in both range and Doppler velocity is completely characterized by the ambiguity function (AF) of its transmit waveform. Mathematically, it is obtained by correlating the waveform with its Doppler-shifted and delayed replicas. We consider the inverse problem of designing a radar transmit waveform that satisfies the speci

Yen-Chi Lee, Min-Hsiu Hsieh

Recent advancements in understanding the impulse response of the first arrival position (FAP) channel in molecular communication (MC) have illuminated its Shannon capacity. While Lee et al. shed light on FAP channel capacities with vertical drifts, the zero-drift scenario remains a conundrum, primarily due to the challenges associated with the heavy-tailed C

Paul Schwarzbach, Jonas Ninnemann, Oliver Michler

In this paper, the necessity for application-oriented development and evaluation of Joint Communication and Sensing (JC&S) applications, especially in transportation, is addressed. More specifically, an integrative evaluation chain for immersively testing JC&S location capabilities, reaching from early-stage testing, over model- and scenario-enabled ray trac

Kazuhiro Seki, Yuichi Otsuka, Seiji Yunoki

We propose a quantum-classical hybrid scheme for implementing the nonunitary Gutzwiller factor using a discrete Hubbard-Stratonovich transformation, which allows us to express the Gutzwiller factor as a linear combination of unitary operators involving only single-qubit rotations, at the cost of the sum over the auxiliary fields. To perform the sum over the

Maxim Koroteev, Kirill Aistov

We study samples of natural images for which a set of statistical characteristics is computed and scale-invariant properties of samples are demonstrated computationally. Computations of the power spectrum are carried out and a power-law decaying power spectrum is observed on samples taken from van Hateren images of natural scenes. We propose a dynamic model

Tiansheng Huang, Shiwei Liu, Li Shen, Fengxiang He

Federated learning (FL) is vulnerable to heterogeneously distributed data, since a common global model in FL may not adapt to the heterogeneous data distribution of each user. To counter this issue, personalized FL (PFL) was proposed to produce dedicated local models for each individual user. However, PFL is far from its maturity, because existing PFL soluti

Dvir Ginzburg, Dan Raviv

We present a novel non-iterative learnable method for partial-to-partial 3D shape registration. The partial alignment task is extremely complex, as it jointly tries to match between points and identify which points do not appear in the corresponding shape, causing the solution to be non-unique and ill-posed in most cases. Until now, two principal methodologi

Shuang Feng, Li-Yong Shen

Let $f(t,y,y')=\sum_{i=0}^n a_i(t,y)y'^i=0$ be an irreducible first order ordinary differential equation with polynomial coefficients. Eremenko in 1998 proved that there exists a constant $C$ such that every rational solution of $f(t,y,y')=0$ is of degree not greater than $C$. Examples show that this degree bound $C$ depends not only on the degrees of $f$ in

Daniel Genkin, William Kosasih, Fangfei Liu, Anna Trikalinou

Over the last two decades, the danger of sharing resources between programs has been repeatedly highlighted. Multiple side-channel attacks, which seek to exploit shared components for leaking information, have been devised, mostly targeting shared caching components. In response, the research community has proposed multiple cache designs that aim at curbing

Christian Malacaria, Yash Bhargava, Joel B. Coley, Lorenzo Ducci

Accreting X-ray pulsars (XRPs) undergo luminous X-ray outbursts during which the luminosity-dependent spectral and timing features of the neutron star's emission can be analyzed in detail, thus shedding light on the accretion regime at work. We took advantage of a monitoring campaign performed with NuSTAR, Swift/XRT, AstroSat and NICER, to follow the Be/X-ra

Giuseppe Rizzelli, Pablo Torres Ferrera, Roberto Gaudino

In this letter, we propose the extension of a previously presented analytical model for the estimation of the signal-to-noise ratio (SNR) at the output of an adaptive equalizer in coherent optical transmission systems when transmission is modeled as a generic 2x2 matrix transfer functions, to be applied to polarization multiplexed communications based on adv

Mohamed Saidi

We show the non-existence of sections of arithmetic fundamental groups of open p-adic annuli of small radii, this implies the non-existence of sections of arithmetic fundamental groups of formal boundaries of formal germs of p-adic curves.

Jivnesh Sandhan, Laxmidhar Behera, Pawan Goyal

In this work, we focus on low-resource dependency parsing for multiple languages. Several strategies are tailored to enhance performance in low-resource scenarios. While these are well-known to the community, it is not trivial to select the best-performing combination of these strategies for a low-resource language that we are interested in, and not much att

Boris Botvinnik, Tadayuki Watanabe

We study families of diffeomorphisms detected by trivalent graphs via the Kontsevich classes. We specify some recent results and constructions of the second named author to show that those non-trivial elements in homotopy groups $\pi_*(B\mathrm{Diff}_{\partial}(D^d))\otimes \mathbb{Q}$ are lifted to homotopy groups of the moduli space of $h$-cobordisms $\pi_

Heon Lee

Recently, a bundle theoretic description of massive single-particle state spaces, which is better suited for Relativistic Quantum Information Theory than the ordinary Hilbert space description, has been suggested. However, the mathematical framework presented in that work does not apply to massless particles. It is because, unlike massive particles, massless

Tomoki Nakanishi

This is a first step guide to the theory of cluster algebras. We especially focus on basic notions, techniques, and results concerning seeds, cluster patterns, and cluster algebras.

Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi

The blockchain is a distributed technology which allows establishing trust among unreliable users who interact and perform transactions with each other. While blockchain technology has been mainly used for crypto-currency, it has emerged as an enabling technology for establishing trust in the realm of the Internet of Things (IoT). Nevertheless, a naive usage

Ting-Chun Lin, Min-Hsiu Hsieh

A locally testable code (LTC) is an error correcting code with a property tester. The tester tests if a word is codeword by reading constant random bits and rejects the word with probability proportional to the distance from the word to the closest codeword. An important open question until recently is whether there exist $c^3$-LTCs which are LTCs with const

Hajar Moudoud, Lyes Khoukhi, Soumaya Cherkaoui

Security in the fifth generation (5G) networks has become one of the prime concerns in the telecommunication industry. 5G security challenges come from the fact that 5G networks involve different stakeholders using different security requirements and measures. Deficiencies in security management between these stakeholders can lead to security attacks. Theref

Yihe Wang, Yitong Li, Yasheng Wang, Fei Mi

Real human conversation data are complicated, heterogeneous, and noisy, from which building open-domain dialogue systems remains a challenging task. In fact, such dialogue data still contains a wealth of information and knowledge, however, they are not fully explored. In this paper, we show existing open-domain dialogue generation methods that memorize conte

Min Zhuang, Jiahao Huang, Chaohong Lee

Invariance under Lorentz transformations is fundamental to both the standard model and general relativity. Testing Lorentz-symmetry violation (LSV) via atomic systems attracts extensive interests in theory and experiment. Some recent proposals for testing LSV present that the effects of violation can be described as a local interaction. Further, the test pre

Daniel Blanquicett

Consider a $p$-random subset $A$ of initially infected vertices in the discrete cube $[L]^3$, and assume that the neighbourhood of each vertex consists of the $a_i$ nearest neighbours in the $\pm e_i$-directions for each $i \in \{1,2,3\}$, where $a_1\le a_2\le a_3$. Suppose we infect any healthy vertex $v\in [L]^3$ already having $r$ infected neighbours, and

Arnold J. T. M. Mathijssen, Maciej Lisicki, Vivek N. Prakash, Endre J. L. Mossige

Innovations in fluid mechanics are leading to better food since ancient history, while creativity in cooking inspires applied and fundamental science. Here, we review how recent advances in hydrodynamics are changing food science, and we highlight how the surprising phenomena that arise in the kitchen lead to discoveries and technologies across the disciplin

S. X. Wang, J. J. Zang, W. Jiang, S. J. Lei

The Dark Matter Particle Explorer (DAMPE) has been undergoing a stable on-orbit operation for more than 6 years and acquired observation of over 11 billion events. And a better understanding of the overall radiation environment on the DAMPE orbit is crucial for both simulation data production and flight data analysis. In this work, we study the radiation env

Jack Cai, Amirali Amirsoleimani, Roman Genov

We present a novel cryptography architecture based on memristor crossbar array, binary hypervectors, and neural network. Utilizing the stochastic and unclonable nature of memristor crossbar and error tolerance of binary hypervectors and neural network, implementation of the algorithm on memristor crossbar simulation is made possible. We demonstrate that with

Keita Kunikawa, Yohei Sakurai

Bamler-Zhang have developed geometric analysis on Ricci flow with scalar curvature bound. The aim of this paper is to extend their work to various geometric flows. We generalize some of their results to super Ricci flow whose Muller quantity is non-negative, and obtain Gaussian heat kernel estimates.

Tapaswini Patro, Kaushiki Mukherjee, Mohd Asad Siddiqui, Indranil Chakrabarty

Fully entangled fraction (FEF) is a significant figure of merit for density matrices. In bipartite $ d \otimes d $ quantum systems, the threshold value FEF $ > 1/d $, carries significant implications for quantum information processing tasks. Like separability, the value of FEF is also related to the choice of global basis of the underlying Hilbert space. A s

Xiangyu Jiao, Wen Zheng

In this paper we mainly study the vertex operator algebra $\mathbb{C} \mathrm{VA}(e, f)$ generated by two Ising vectors $e$ and $f$ with $\langle e, f\rangle=\frac{5}{2^{10}}$. We prove $\mathbb{C} \mathrm{VA}(e, f)$ is isomorphic to the $6A$-algebra $\mathcal{U}_{6A}$ constructed by Lam-Yamada-Yamauchi. We also discuss the cases $\langle e, f\rangle=\frac{1

Carlos Mougan, Jose M. Alvarez, Salvatore Ruggieri, Steffen Staab

Past research has demonstrated that the explicit use of protected attributes in machine learning can improve both performance and fairness. Many machine learning algorithms, however, cannot directly process categorical attributes, such as country of birth or ethnicity. Because protected attributes frequently are categorical, they must be encoded as features

Heiko Gimperlein, Magnus Goffeng, Nikoletta Louca

We study a Dirichlet boundary problem related to the fractional Laplacian in a manifold. Its variational formulation arises in the study of magnitude, an invariant of compact metric spaces given by the reciprocal of the ground state energy. Using recent techniques developed for pseudodifferential boundary problems we discuss the structure of the solution ope

Chaithya G R, Philippe Ciuciu

We benchmark the current existing methods to jointly learn non-Cartesian k-space trajectory and reconstruction: PILOT, BJORK, and compare them with those obtained from the recently developed generalized hybrid learning (HybLearn) framework. We present the advantages of using projected gradient descent to enforce MR scanner hardware constraints as compared to

Julian von Schleinitz, Thomas Schwarzhuber, Lukas Wörle, Michael Graf

Professional race drivers are still superior to automated systems at controlling a vehicle at its dynamic limit. Gaining insight into race drivers' vehicle handling process might lead to further development in the areas of automated driving systems. We present a method to study and evaluate race drivers on a driver-in-the-loop simulator by analysing tire gri

Yilimiranmu Rouzhahong, Chao Liang, Chong Li, Biao Wang

Quantum materials have exhibited attractive electro-mechanical responses, but their piezoelectric coefficients are far from satisfactory due to the lack of fundamental mechanisms to benefit from the quantum effects. We discovered the valley piezoelectric mechanism that is absent in traditional piezoelectric theory yet promising to overcome this challenge. A

Ting Hu

The spatial and spectral degradation functions are critical to hyper- and multi-spectral image fusion. However, few work has been payed on the estimation of the degradation functions. To learn the spatial response function and the point spread function from the image pairs to be fused, we propose a Dirichlet network, where both functions are properly constra

Imke Botha, Robert Kohn, Leah South, Christopher Drovandi

Sequential Monte Carlo squared (SMC$^2$) methods can be used for parameter inference of intractable likelihood state-space models. These methods replace the likelihood with an unbiased particle filter estimator, similarly to particle Markov chain Monte Carlo (MCMC). As with particle MCMC, the efficiency of SMC$^2$ greatly depends on the variance of the likel

Jialiang Gao, Charles-Henri Lambert, Richard Schlitz, Manfred Fiebig

The possibility of electrically exciting and detecting magnon currents in magnetic insulators has opened exciting perspectives for transporting spin information in electronic devices. However, the role of the magnetic field and the nonlocal thermal gradients on the magnon transport remain unclear. Here, by performing nonlocal harmonic voltage measurements, w

Chao Zhang, Tao Zhu, Xiongjun Fang, Anzhong Wang

Gravitational waves emitted from the gravitational ringing of supermassive black holes are important targets to test general relativity and probe the matter environment surrounding such black holes. The main components of the ringing waveform are black hole quasi-normal modes. In this paper, we study the effects of the dark matter halos with three different

Seung Park, Cheol-Hwan Yoo, Yong-Goo Shin

In recent years, generative adversarial network (GAN)-based image generation techniques design their generators by stacking up multiple residual blocks. The residual block generally contains a shortcut, \ie skip connection, which effectively supports information propagation in the network. In this paper, we propose a novel shortcut method, called the gated s

Zeying Zhang, Zhi-Ming Yu, Gui-Bin Liu, Yugui Yao

The irreducible representation of band structure is important for physical properties. Based on phonopy and recently developed SpaceGroupIrep package, we developed a package PhononIrep, which can get the band irreducible representation for arbitrary $\boldsymbol{k}$ point at first-principles level. As an application, we for the first time predict the cubic c

Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi

Graph Convolutional Networks (GCNs) have recently attracted vast interest and achieved state-of-the-art performance on graphs, but its success could typically hinge on careful training with amounts of expensive and time-consuming labeled data. To alleviate labeled data scarcity, self-training methods have been widely adopted on graphs by labeling high-confid

Chen Zhou

In this paper we give a new, and shorter, proof of Huber's theorem which affirms that for a connected open Riemann surface endowed with a complete conformal Riemannian metric, if the negative part of its Gaussian curvature has finite mass, then the Riemann surface is homeomorphic to the interior of a compact surface with boundary, and thus it has finite topo

Miho Mukohara

Suzuki recently gave constructions of non-discrete examples of locally compact C*-simple groups and Raum showed C*-simplicity of the relative profinite completions of the Baumslag-Solitar groups by using Suzuki's results. We extend this result to some fundamental groups of graphs of groups called generalized Baumslag-Solitar groups. In this article, we focus

Poushali Pal, Devabalaji K. R, S. Priyadarshini

Battery management system plays an important role for modern battery-powered application such as Electric vehicles, portable electronic equipment and storage for renewable energy sources. It also increases the life-cycle of the battery, battery state and efficiency. Monitoring the state of charge of the battery is a crucial factor for battery management syst

Yingchao Pan, Ouhan Huang, Qinghao Ye, Zhongjin Li

Video summarization aims to automatically generate a diverse and concise summary which is useful in large-scale video processing. Most of the methods tend to adopt self-attention mechanism across video frames, which fails to model the diversity of video frames. To alleviate this problem, we revisit the pairwise similarity measurement in self-attention mechan

Jihyeug Jang, Donghyun Kim, Jang Soo Kim, Minho Song

If a sequence indexed by nonnegative integers satisfies a linear recurrence without constant terms, one can extend the indices of the sequence to negative integers using the recurrence. Recently, Cigler and Krattenthaler showed that the negative version of the number of bounded Dyck paths is the number of bounded alternating sequences. In this paper we provi

Adrian Redder, Arunselvan Ramaswamy, Holger Karl

Iterative distributed optimization algorithms involve multiple agents that communicate with each other, over time, in order to minimize/maximize a global objective. In the presence of unreliable communication networks, the Age-of-Information (AoI), which measures the freshness of data received, may be large and hence hinder algorithmic convergence. In this p

Dimitrios Sikeridis, Michael Devetsikiotis

Ensuring public safety in a Smart City (SC) environment is a critical and increasingly complicated task due to the involvement of multiple agencies and the city's expansion across cyber and social layers. In this paper, we propose an extensive form perfect information game to model interactions and optimal city resource allocations when a Terrorist Organizat

Jianyu Xu, Yu-Xiang Wang

In feature-based dynamic pricing, a seller sets appropriate prices for a sequence of products (described by feature vectors) on the fly by learning from the binary outcomes of previous sales sessions ("Sold" if valuation $\geq$ price, and "Not Sold" otherwise). Existing works either assume noiseless linear valuation or precisely-known noise distribution, whi

Kunal Shastri, Orad Reshef, Robert W. Boyd, Jeff S. Lundeen

Spaceplates are novel flat-optic devices that implement the optical response of a free-space volume over a smaller length, effectively "compressing space" for light propagation. Together with flat lenses such as metalenses or diffractive lenses, spaceplates have the potential to enable a drastic miniaturization of any free-space optical system. While the fun

Simon G. Robson, Paul Räcke, Alexander M. Jakob, Nicholas Collins

The demonstration of universal quantum logic operations near the fault-tolerance threshold establishes ion-implanted near-surface donor atoms as a plausible platform for scalable quantum computing in silicon. The next technological step forward requires a deterministic fabrication method to create large-scale arrays of donors, featuring few hundred nanometre

Lei-dong Cheng, Hong Zhang, Shou-shan Bao

The mass of the axion-like particles could be constrained by the observed black hole spin distribution. In this work, we update the previous calculations using the recently improved superradiance formula, which is much more accurate. The effect of the merger time scale is also carefully investigated with Bayesian analysis. After integration of the merger tim

Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi

Recently, blockchain has gained momentum as a novel technology that gives rise to a plethora of new decentralized applications (e.g., Internet of Things (IoT)). However, its integration with the IoT is still facing several problems (e.g., scalability, flexibility). Provisioning resources to enable a large number of connected IoT devices implies having a scal

Debabrata Biswas

The factors that contribute to the accuracy of the cold field emission current within the contemporary frameworks are investigated. It is found that so long as the net current is evaluated using an expression for the local current density obtained by linearizing the Gamow factor, the primary source of error is the choice of the energy at which the Taylor exp

Keigo Takeuchi

This paper proves the convergence of Bayes-optimal orthogonal/vector approximate message-passing (AMP) to a fixed point in the large system limit. The proof is based on Bayes-optimal long-memory (LM) message-passing (MP) that is guaranteed to converge systematically. The dynamics of Bayes-optimal LM-MP is analyzed via an existing state evolution framework. T

Mamta Rani, Avnish K. Sharma, Sharwan K. Tiwari, Anupama Panigrahi

Let $r$, $n$ be positive integers, $k$ be a non-negative integer and $q$ be any prime power such that $r\mid q^n-1.$ An element $\alpha$ of the finite field $\mathbb{F}_{q^n}$ is called an {\it $r$-primitive} element, if its multiplicative order is $(q^n-1)/r$, and it is called a {\it $k$-normal} element over $\mathbb{F}_q$, if the greatest common divisor of

Luzhe Huang, Xilin Yang, Tairan Liu, Aydogan Ozcan

Deep learning-based methods in computational microscopy have been shown to be powerful but in general face some challenges due to limited generalization to new types of samples and requirements for large and diverse training data. Here, we demonstrate a few-shot transfer learning method that helps a holographic image reconstruction deep neural network rapidl

Junying Ma, Feng Gu, Ying Xu, Jiaming Le

A high-sensitive DC Magneto-Optical Kerr Effect (MOKE) apparatus is described in this letter. Via detailed analysis on several dominating noise sources, we have proposed solutions that significantly lower the MOKE noise, and a sensitivity of $1.5\times10^{-7} \text{rad}/\sqrt{\text{Hz}}$ is achieved with long-term stability. The sensitivity of the apparatus

Hongbin Ye, Ningyu Zhang, Shumin Deng, Xiang Chen

Few-shot Learning (FSL) is aimed to make predictions based on a limited number of samples. Structured data such as knowledge graphs and ontology libraries has been leveraged to benefit the few-shot setting in various tasks. However, the priors adopted by the existing methods suffer from challenging knowledge missing, knowledge noise, and knowledge heterogene

Da Chen Emily Koo, Heather Bowling, Kenneth Ashworth, David J. Heeger

Epistemic AI accelerates biomedical discovery by finding hidden connections in the network of biomedical knowledge. The Epistemic AI web-based software platform embodies the concept of knowledge mapping, an interactive process that relies on a knowledge graph in combination with natural language processing (NLP), information retrieval, relevance feedback, an

Geng Liu, Saumil Patel, Ramesh Balakrishnan, Taehun Lee

The US Department of Energy launched the Exascale Computing Project (ECP) in 2016 as part of a coordinated effort to achieve the next generation of high-performance computing (HPC) and to accelerate scientific discovery. The Exascale Proxy Applications Project began within the ECP to: (1) improve the quality of proxies created by the ECP (2) provide small, s

Quynh T. Nguyen, Bobak T. Kiani, Seth Lloyd

Many quantum algorithms for numerical linear algebra assume black-box access to a block-encoding of the matrix of interest, which is a strong assumption when the matrix is not sparse. Kernel matrices, which arise from discretizing a kernel function $k(x,x')$, have a variety of applications in mathematics and engineering. They are generally dense and full-ran

Kensuke Ishitani, Tokufuku Rin, Shun Yanashima

The purpose of this paper is to introduce the construction of a stochastic process called "$\delta$-dimensional Bessel house-moving" and its properties. We study the weak convergence of $\delta$-dimensional Bessel bridges conditioned from above, and we refer to this limit as $\delta$-dimensional Bessel house-moving. Applying this weak convergence result, we

chengran Yang, Bowen Xu, Junaed younus Khan, Gias Uddin

APIs (Application Programming Interfaces) are reusable software libraries and are building blocks for modern rapid software development. Previous research shows that programmers frequently share and search for reviews of APIs on the mainstream software question and answer (Q&A) platforms like Stack Overflow, which motivates researchers to design tasks and ap

Xu T. Liu, Jesun Firoz, Sinan Aksoy, Ilya Amburg

Hypergraphs offer flexible and robust data representations for many applications, but methods that work directly on hypergraphs are not readily available and tend to be prohibitively expensive. Much of the current analysis of hypergraphs relies on first performing a graph expansion -- either based on the nodes (clique expansion), or on the edges (line graph)

Han Liang, Predrag Cvitanović

Motivated by Gutzwiller's semiclassical quantization, in which unstable periodic orbits of low-dimensional deterministic dynamics serve as a WKB `skeleton' for chaotic quantum mechanics, we construct the corresponding deterministic skeleton for infinite-dimensional lattice-discretized scalar field theories. In the field-theoretical formulation, there is no e

Haidong Li, Anzhi Sheng, Yijie Peng, Long Wang

In this work, we study stochastic non-cooperative games, where only noisy black-box function evaluations are available to estimate the cost function for each player. Since each player's cost function depends on both its own decision variables and its rivals' decision variables, local information needs to be exchanged through a center/network in most existing

Chong-Sun Chu, Asuka Ito

If supersymmetry is broken in metastable vacua, it is not clear why we are now in there rather than supersymmetric vacua. Moreover, it is natural to expect that we were in supersymmetric vacua, which have higher symmetry than metastable vacua, in the early universe. In this paper, we reexamine and improve the previous analysis on the cosmological evolution o

Anilatmaja Aryasomayajula, Baskar Balasubramanyam

In this article, we derive a sub convexity estimate of Hecke eigen cusp forms associated to certain cocompact arithmetic subgroups of SL(2,R). The main result can be considered as the holomorphic version of the estimate of Hecke eigen Maass forms, derived in a famous paper of Iwaniec and Sarnak. A stronger estimate was derived by Khayutin and Steiner in arXi

Cheng-Feng Yang, Yong-Bo Huang, Ji-Lei Xu, Di-Ru Wu

The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose neutrino experiment. One of the main goals is to determine the neutrino mass ordering by precisely measuring the energy spectrum of reactor antineutrinos. For reactor antineutrino detection, cosmogenic backgrounds such as $^9$Li/$^8$He and fast neutrons induced by cosmic muons should be

Alvaro Joaquín Gaona, Pedro David Arini

In this work, a novel stack of well-known technologies is presented to determine an automatic method to segment the heart sounds in a phonocardiogram (PCG). We will show a deep recurrent neural network (DRNN) capable of segmenting a PCG into its main components and a very specific way of extracting instantaneous frequency that will play an important role in

Fahad Rahman Amik, Ahnaf Ismat Tasin, Silvia Ahmed, M. M. Lutfe Elahi

Knowledge Distillation is a technique which aims to utilize dark knowledge to compress and transfer information from a vast, well-trained neural network (teacher model) to a smaller, less capable neural network (student model) with improved inference efficiency. This approach of distilling knowledge has gained popularity as a result of the prohibitively comp

Shuangliang Li, Yugang Tian, Hao Xia, Qingwei Liu

The hyperspectral image (HSI) has been widely used in many applications due to its fruitful spectral information. However, the limitation of imaging sensors has reduced its spatial resolution that causes detail loss. One solution is to fuse the low spatial resolution hyperspectral image (LR-HSI) and the panchromatic image (PAN) with inverse features to get t

Tharaj Thaj, Emanuele Viterbo

This paper presents a low complexity detector for multiple-input multiple-output (MIMO) systems based on the recently proposed orthogonal time frequency space (OTFS) modulation. In the proposed detector, the copies of the transmitted symbol-vectors received through the different diversity branches (propagation paths and receive antennas) are linearly combine

Moyuru Yamada, Vanessa D'Amario, Kentaro Takemoto, Xavier Boix

Transformers achieve great performance on Visual Question Answering (VQA). However, their systematic generalization capabilities, i.e., handling novel combinations of known concepts, is unclear. We reveal that Neural Module Networks (NMNs), i.e., question-specific compositions of modules that tackle a sub-task, achieve better or similar systematic generaliza

Osamu Fujino

We discuss the minimal model program for projective morphisms of complex analytic spaces. Roughly speaking, we show that the results obtained by Birkar--Cascini--Hacon--M\textsuperscript{c}Kernan hold true for projective morphisms between complex analytic spaces. We also treat some related topics.

Jun Dai, Zhentong Li, Ya Wang, Zhe Xu

We present an investigation of partial filament eruption on 2012 June 17 in the active region NOAA 11504. For the first time, we observed the vertical splitting process during the partial eruption with high resolution narrow band images at 10830 . The active filament was rooted in a small sunspot of the active region. Particularly, it underwent the partial e

Chen Wu, Ming Yan

Semantic code search is the task of retrieving relevant code snippet given a natural language query. Different from typical information retrieval tasks, code search requires to bridge the semantic gap between the programming language and natural language, for better describing intrinsic concepts and semantics. Recently, deep neural network for code search ha

Bin Li, Yunlong Fan, Yikemaiti Sataer, Zhiqiang Gao

Higher-order features bring significant accuracy gains in semantic dependency parsing. However, modeling higher-order features with exact inference is NP-hard. Graph neural networks (GNNs) have been demonstrated to be an effective tool for solving NP-hard problems with approximate inference in many graph learning tasks. Inspired by the success of GNNs, we in

Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi

Federated learning (FL) is a distributed machine learning (ML) technique that enables collaborative training in which devices perform learning using a local dataset while preserving their privacy. This technique ensures privacy, communication efficiency, and resource conservation. Despite these advantages, FL still suffers from several challenges related to

Jian Zhang, Mengxue Bai

By introducing and solving two correlative constrained variational problems as well as spectrum analysis, an approach to fix soliton frequency from the prescribed mass for nonlinear Schr\"odinger equations is found, and an open problem in normalized solutions is answered. Then existence and orbital stability of big solitons depending on frequencies for nonli