January 2022 arXiv papers — page 57

Rong Liang, Tiehua Zhang, Yujie Lu, Yuze Liu

Using the pre-trained language models to understand source codes has attracted increasing attention from financial institutions owing to the great potential to uncover financial risks. However, there are several challenges in applying these language models to solve programming language-related problems directly. For instance, the shift of domain knowledge be

Michael Cho, Afra Mashhadi

Mobile Crowdsensing has become main stream paradigm for researchers to collect behavioral data from citizens in large scales. This valuable data can be leveraged to create centralized repositories that can be used to train advanced Artificial Intelligent (AI) models for various services that benefit society in all aspects. Although decades of research has ex

Ryo Yamazaki, S. Matsukiyo, T. Morita, S. J. Tanaka

We present a new experimental method to generate quasi-perpendicular supercritical magnetized collisionless shocks. In our experiment, ambient nitrogen (N) plasma is at rest and well-magnetized, and it has uniform mass density. The plasma is pushed by laser-driven ablation aluminum (Al) plasma. Streaked optical pyrometry and spatially resolved laser collecti

Qiang Liu, Yuru Zhang, Haoxin Wang

High definition (HD) map needs to be updated frequently to capture road changes, which is constrained by limited specialized collection vehicles. To maintain an up-to-date map, we explore crowdsourcing data from connected vehicles. Updating the map collaboratively is, however, challenging under constrained transmission and computation resources in dynamic ne

Yue Hu, A. Lazarian, Q. Daniel Wang

Measuring magnetic fields in the interstellar medium and obtaining their distribution along line-of-sight is very challenging with the traditional techniques. The Velocity Gradient Technique (VGT), which utilizes anisotropy of magnetohydrodynamic (MHD) turbulence, provides an attractive solution. Targeting the central molecular zone (CMZ), we test this appro

Zhaoming Gan, Hui Li, Xiangrong Fu, Senbei Du

We study the existence and property of Fast magnetosonic modes in 3D compressible MHD turbulence by carrying out a number of simulations with compressible and incompressible driving conditions. We use two approaches to determine the presence of Fast modes: mode decomposition based on spatial variations only and spatio-temporal 4D-FFT analysis of all fluctuat

Joel Bierman, Yingzhou Li, Jianfeng Lu

We propose a quantum-classical hybrid variational algorithm, the quantum orbital minimization method (qOMM), for obtaining the ground state and low-lying excited states of a Hermitian operator. Given parameterized ansatz circuits representing eigenstates, qOMM implements quantum circuits to represent the objective function in the orbital minimization method

Dániel Kincses, Maria Stefaniak, Máté Csanád

Exploring the shape of the pair-source function for particles such as pions or kaons has been an important goal of heavy-ion physics, and substantial effort has been made in order to understand the underlying physics behind the experimental observations of non-Gaussian behavior. In experiments, since no direct measurement of the source function is possible,

Moisés Bravo-Gaete, Fabiano F. Santos, Henrique Boschi-Filho

In higher dimensions, we study Degenerate-Higher-Order-Scalar-Tensor theories and we derive solutions that resemble the Schwarzschild Anti-de Sitter black holes. We compute their thermodynamic quantities following the Wald formalism, satisfying the First Law of Thermodynamics and a higher dimensional Smarr relation. Constructing a Noether charge with a suita

Hiraku Nakajima

This is an introductory article for a mathematical definition of Coulomb branches of 3d N=4 SUSY gauge theories and geometric Satake correspondences for Kac-Moody Lie algebras based on Coulomb branches.

Evan Johnson, Alan Hastings

Ecologists have put forward many explanations for coexistence, but these are only partial explanations; nature is complex, so it is reasonable to assume that in any given ecological community, multiple mechanisms of coexistence are operating at the same time. Here, we present a methodology for quantifying the relative importance of different explanations for

Zarrin Tasnim Sworna, Chadni Islam, Muhammad Ali Babar

Security Orchestration, Automation, and Response (SOAR) platforms integrate and orchestrate a wide variety of security tools to accelerate the operational activities of Security Operation Center (SOC). Integration of security tools in a SOAR platform is mostly done manually using APIs, plugins, and scripts. SOC teams need to navigate through API calls of dif

Jaeyoung Lee, Sean Sedwards, Krzysztof Czarnecki

We consider the challenge of finding a deterministic policy for a Markov decision process that uniformly (in all states) maximizes one reward subject to a probabilistic constraint over a different reward. Existing solutions do not fully address our precise problem definition, which nevertheless arises naturally in the context of safety-critical robotic syste

Ying Sui, Weiqiang Wang, Huimin Yu

In this paper, vacuum and singularity formation are considered for compressible Euler equations with time-dependent damping. For $1<\gamma\leq 3$, by constructing some new control functions ingeniously, we obtain the lower bounds estimates on density for arbitrary classical solutions. Basing on these lower estimates, we succeed in proving the singular format

Cheng Hua, Wang Dandan

Objective: This study takes further step on understanding personality structure in order to cope with the mental health during the COVID-19 global pandemic situation. Methods: Categorized the independent variables into biological, family and cultural predictors according to the datasets of the Big-5 personality survey online. And established multiple regress

Diego Catalano Ferraioli

In this paper we report on a local classification of four dimensional Ricci solitons which have a $2$-dimensional Abelian Killing algebra $\mathcal{G}_{2}$, whose Killing leaves are non-null and orthogonally intransitive. The classification is obtained under the following additional assumptions: (i) the curvature vector field, of the submersion defined by $\

Xiaoxuan Yu, Yan Xu, Qiang Du

We study the propagation of singularities in solutions of linear convection equations with spatially heterogeneous nonlocal interactions. A spatially varying nonlocal horizon parameter is adopted in the model, which measures the range of nonlocal interactions. Via heterogeneous localization, this can lead to the seamless coupling of the local and nonlocal mo

Chenxu Jiang, Chenglong Fu, Zhenyu Zhao, Xiaojiang Du

Smart home IoT systems and devices are susceptible to attacks and malfunctions. As a result, users' concerns about their security and safety issues arise along with the prevalence of smart home deployments. In a smart home, various anomalies (such as fire or flooding) could happen, due to cyber attacks, device malfunctions, or human mistakes. These concerns

Z. Zheng, L. Lu, Y. Yu, R. C. de Lamare

For active impulsive noise control, a filtered-x recursive least $p$-power (FxRLP) algorithm is proposed by minimizing the weighted summation of the $p$-power of the \emph{a posteriori} errors. Since the characteristic of the target noise is investigated, the FxRLP algorithm achieves good performance and robustness. To obtain a better performance, we develop

William Anderson, Mohammad Farazmand

We consider reduced-order modeling of nonlinear dispersive waves described by a class of nonlinear Schrodinger (NLS) equations. We compare two nonlinear reduced-order modeling methods: (i) The reduced Lagrangian approach which relies on the variational formulation of NLS and (ii) The recently developed method of reduced-order nonlinear solutions (RONS). Firs

Antonio Lanteri, Andrea Luigi Tironi

Let $(X,L)$ be any Fano manifold polarized by a positive multiple of its fundamental divisor $H$. The polynomial defining the Hilbert curve of $(X,L)$ boils down to being the Hilbert polynomial of $(X,H)$, hence it is totally reducible over $\mathbb C$; moreover, some of the linear factors appearing in the factorization have rational coefficients, e.g. if $X

Yayong Li, Jie Yin, Ling Chen

Graph Neural Networks (GNNs) have achieved state-of-the-art results for semi-supervised node classification on graphs. Nevertheless, the challenge of how to effectively learn GNNs with very few labels is still under-explored. As one of the prevalent semi-supervised methods, pseudo-labeling has been proposed to explicitly address the label scarcity problem. I

Chun-Yi Wei, Yung Kai Wang

This study investigated relay-assisted mode 1 sidelink (SL) multicast transmission, which encounters interference from mode 2 SL transmission, for use in low-latency vehicle-to-everything communications. To accommodate mode 1--mode 2 SL traffic, we use the hybrid multiple access (MA) approach, which combines orthogonal MA (OMA) and nonorthogonal MA (NOMA) sc

Viet Hoang Pham, Hyo-Sung Ahn

In this paper, we design a stochastic Model Predictive Control (MPC) traffic signal control method for an urban traffic network when the uncertainties in the estimation of the exogenous (in/out)-flows and the turning ratios of downstream traffic flows are taken into account. Assuming that the traffic model parameters are random variables with known expectati

Haoran Ren

Polarisation holography generally demands polarisation-sensitive holograms for reconstructing either polarisation-multiplexed holographic images or polarisation-sensitive image channels. To date, polarisation holography is underpinned by the Jones matrix method that uses birefringent holograms, including ultrathin metasurface holograms, limiting the polarisa

Zong-Hui Gao, Zi-Xiao Wang, Dong-Yu Hou, Xin-Dian Liu

Ta-doped SnO$_2$ films with high conductivity and high optical transparency have been successfully fabricated using rf-sputtering method and their electrical transport properties have been investigated. All films reveal degenerate semiconductor (metal) characteristics in electrical transport properties. For the thick films ($t\sim 1\,\mu \rm{m}$ with $t$ bei

Yang Liu

We propose a systematic scheme for computing the variation of rearrangement operators arising in the recently developed spectral geometry on noncommutative tori and $\theta$-deformed Riemannian manifolds. It can be summarized as a category whose objects consists of spectral functions of the rearrangement operators and morphisms are generated by transformatio

Ertem Nusret Tas, David Tse, Fisher Yu, Sreeram Kannan

Bitcoin is the most secure blockchain in the world, supported by the immense hash power of its Proof-of-Work miners, but consumes huge amount of energy. Proof-of-Stake chains are energy-efficient, have fast finality and accountability, but face several fundamental security issues: susceptibility to non-slashable long-range safety attacks, non-slashable trans

Jinkyung Yoo, Zequn Sun, Michael Greenacre, Qin Ma

The study of immune cellular composition has been of great scientific interest in immunology because of the generation of multiple large-scale data. From the statistical point of view, such immune cellular data should be treated as compositional. In compositional data, each element is positive, and all the elements sum to a constant, which can be set to one

Qianhao Cong, Jing Tang, Yuming Huang, Lei Chen

Interactive graph search (IGS) uses human intelligence to locate the target node in hierarchy, which can be applied for image classification, product categorization and searching a database. Specifically, IGS aims to categorize an object from a given category hierarchy via several rounds of interactive queries. In each round of query, the search algorithm pi

Chaojin Qing, Qing Ye, Wenhui Liu, Jiafan Wang

Due to the discarding of downlink channel state information (CSI) amplitude and the employing of iteration reconstruction algorithms, 1-bit compressed sensing (CS)-based superimposed CSI feedback is challenged by low recovery accuracy and large processing delay. To overcome these drawbacks, this letter proposes a fusion learning scheme by exploiting the bi-d

Mitsuharu Uemoto, Hayato Adachi, Hiroshi Naganuma, Tomoya Ono

Graphene on $L1_0$-FePd(001), which has been experimentally studied in recent years, is a heterogeneous interface with a significant lattice symmetry mismatch between the honeycomb structure of graphene and tetragonal alloy surface. In this work, we report on the density functional study of its atomic-scale configurations, electronic and magnetic properties,

Cooper Jacobus, Minjun J. Choi, Ralph Kube

The emergence and dynamics of filamentary structures associated with edge-localized modes (ELMs) inside tokamak plasmas during high-confinement mode is regularly studied using Electron Cyclotron Emission Imaging (ECEI) diagnostic systems. ECEI allows inference of electron temperature variations, often across a poloidal cross-section. Previously, detailed ana

Steven Roberts, Adrian Sandu

When applied to stiff, linear differential equations with time-dependent forcing, Runge-Kutta methods can exhibit convergence rates lower than predicted by the classical order condition theory. Commonly, this order reduction phenomenon is addressed by using an expensive, fully implicit Runge-Kutta method with high stage order or a specialized scheme satisfyi

Ahasan Ahamed, Cesar Bartolo-Perez, Ahmed Sulaiman Mayet, Soroush Ghandiparsi

Controlling light penetration depth in Avalanche Photodiodes (APDs) and Single Photon Avalanche Diodes (SPADs) play a major role in achieving high multiplication gain by delivering light near the multiplication region where the electric field is the strongest. Such control in the penetration depth for a particular wavelength of light has been previously demo

Yeming Gu, Hui Shu, Rongkuan Ma, Lin Yan

The security research on Windows has received little attention in the academic circle. Most of the new methods are usually designed for Linux system, and are difficult to transplant to Windows. Fuzzing for Windows programs always suffering from its closed source. Therefore, we need to find an appropriate way to achieve feedback from Windows programs. To our

Haojie Huang, Ziyi Yang, Robert Platt

Shape completion, the problem of inferring the complete geometry of an object given a partial point cloud, is an important problem in robotics and computer vision. This paper proposes the Graph Attention Shape Completion Network (GASCN), a novel neural network model that solves this problem. This model combines a graph-based model for encoding local point cl

Hamoud Alhazmi, Ahmed Imran, Mohammad Abu Alsheikh

Digital privacy has become an essential component of information and communications technology (ICT) systems. There are many existing methods for digital privacy protection, including network security, cryptography, and access control. However, there is still a gap in the digital privacy protection levels available for users. This paper studies the digital p

Carmina Pérez-Guerrero, Adriana Palacios, Gilberto Ochoa-Ruiz, Christian Mata

Jet fires are relatively small and have the least severe effects among the diverse fire accidents that can occur in industrial plants; however, they are usually involved in a process known as the domino effect, that leads to more severe events, such as explosions or the initiation of another fire, making the analysis of such fires an important part of risk a

Liuhua Zhang

Breast cancer is in the most common malignant tumor in women. It accounted for 30% of new malignant tumor cases. Although the incidence of breast cancer remains high around the world, the mortality rate has been continuously reduced. This is mainly due to recent developments in molecular biology technology and improved level of comprehensive diagnosis and st

Miryana Grigorova, Hanwu Li

In this paper, we address the stochastic representation problem in discrete time under (non-linear) g-expectation. We establish existence and uniqueness of the solution, as well as a characterization of the solution. As an application, we investigate a new approach to the optimal stopping problem under g-expectation and the related pricing of American option

Jian Wang, Lingjie Liu, Weipeng Xu, Kripasindhu Sarkar

Egocentric 3D human pose estimation with a single fisheye camera has drawn a significant amount of attention recently. However, existing methods struggle with pose estimation from in-the-wild images, because they can only be trained on synthetic data due to the unavailability of large-scale in-the-wild egocentric datasets. Furthermore, these methods easily f

Andrew S. Morgan, Kaiyu Hang, Bowen Wen, Kostas Bekris

Constraining contacts to remain fixed on an object during manipulation limits the potential workspace size, as motion is subject to the hand's kinematic topology. Finger gaiting is one way to alleviate such restraints. It allows contacts to be freely broken and remade so as to operate on different manipulation manifolds. This capability, however, has traditi

Jiawei Qin, Takuru Shimoyama, Yusuke Sugano

Despite recent advances in appearance-based gaze estimation techniques, the need for training data that covers the target head pose and gaze distribution remains a crucial challenge for practical deployment. This work examines a novel approach for synthesizing gaze estimation training data based on monocular 3D face reconstruction. Unlike prior works using m

Evan Johnson, Alan Hastings

In this paper, we discuss the conceptual underpinnings of Modern Coexistence Theory (MCT), a quantitative framework for understanding ecological coexistence. In order to use MCT to infer how species are coexisting, one must relate a complex model (which simulates coexistence in the real world) to simple models in which previously proposed explanations for co

Keyi Wu, Thomas O'Leary-Roseberry, Peng Chen, Omar Ghattas

We address the solution of large-scale Bayesian optimal experimental design (OED) problems governed by partial differential equations (PDEs) with infinite-dimensional parameter fields. The OED problem seeks to find sensor locations that maximize the expected information gain (EIG) in the solution of the underlying Bayesian inverse problem. Computation of the

Elena Scire, Luisa Rebull, Seppo Laine

We present statistics on the number of refereed astronomy journal articles that used data from NASA's Spitzer Space Telescope through the end of the calendar year 2020. We discuss the various types of science programs and science categories that were used to collect data during the mission and discuss how operational changes brought on by the depletion of cr

Yifeng Xiong, Soon Xin Ng, Lajos Hanzo

Quantum error mitigation (QEM) is a class of promising techniques for reducing the computational error of variational quantum algorithms. In general, the computational error reduction comes at the cost of a sampling overhead due to the variance-boosting effect caused by the channel inversion operation, which ultimately limits the applicability of QEM. Existi

L. L. Sales, F. C. Carvalho, E. P. Bento, H. T. C. M. Souza

Tsallis' thermostatistical has received increasing attention due to its success in describing phenomena that manifest unusual thermodynamic properties. In this context, the generalized Saha equation must follow a condition of generalized thermal equilibrium of matter and radiation. The present work aims to explore the non-Gaussian effects on Saha's ionizatio

Bennet Yee, Dawn Song, Patrick McCorry, Chris Buckland

Blockchains combine a distributed append-only log with a virtual machine that defines how log entries are interpreted. By viewing transactions as state transformation functions for the virtual machine, we separate the naming of a state from the computation of its value and reaching consensus on that value. This distinction allows us to separate the notion of

Petr Jizba, Gaetano Lambiase, Giuseppe Gaetano Luciano, Luciano Petruzziello

The generalized uncertainty principle (GUP) is a phenomenological model whose purpose is to account for a minimal length scale (e.g., Planck scale or characteristic inverse-mass scale in effective quantum description) in quantum systems. In this Letter, we study possible observational effects of GUP systems in their decoherence domain. We first derive cohere

K. V. Antipin

Construction of genuinely entangled multipartite subspaces with certain characteristics has become a relevant task in various branches of quantum information. Here we show that such subspaces can be obtained from an arbitrary collection of bipartite entangled subspaces under joining of their adjacent subsystems. In addition, it is shown that direct sums of s

Eric S. Tellez, Guillermo Ruiz

This manuscript introduces an autotuned algorithm for searching nearest neighbors based on neighbor graphs and optimization metaheuristics to produce Pareto-optimal searches for quality and search speed automatically; the same strategy is also used to produce indexes that achieve a minimum quality. Our approach is described and benchmarked with other state-o

Drew Penney, Bin Li, Jaroslaw Sydir, Lizhong Chen

A growing number of service providers are exploring methods to improve server utilization and reduce power consumption by co-scheduling high-priority latency-critical workloads with best-effort workloads. This practice requires strict resource allocation between workloads to reduce contention and maintain Quality-of-Service (QoS) guarantees. Prior work demon

Muhammad Fahad, Daniel R. Fuhrmann

It is an experimental design problem in which there are two Poisson sources with two possible and known rates, and one counter. Through a switch, the counter can observe the sources individually or the counts can be combined so that the counter observes the sum of the two. The sensor scheduling problem is to determine an optimal proportion of the available t

Y. Muniz, P. P. Abrantes, L. Martín Moreno, F. A. Pinheiro

We investigate the two-plasmon spontaneous decay of a quantum emitter near single-walled carbon nanotubes (SWCNT) and graphene-coated wires (GCWs). We demonstrate efficient, enhanced generation of two-plasmon entangled states in SWCNTs due to the strong coupling between tunable guided plasmons and the quantum emitter. We predict two-plasmon emission rates mo

Wei Qi, Hwankoo Kim, Fanggui Wang, Mingzhao Chen

Let $R$ be a ring and $S$ a multiplicative subset of $R$. Then $R$ is called a uniformly $S$-Noetherian ($u$-$S$-Noetherian for abbreviation) ring provided there exists an element $s\in S$ such that for any ideal $I$ of $R$, $sI \subseteq K$ for some finitely generated sub-ideal $K$ of $I$. We give the Eakin-Nagata-Formanek Theorem for $u$-$S$-Noetherian rin

Jake Perazzone, Shiqiang Wang, Mingyue Ji, Kevin Chan

Federated learning (FL) is a useful tool in distributed machine learning that utilizes users' local datasets in a privacy-preserving manner. When deploying FL in a constrained wireless environment; however, training models in a time-efficient manner can be a challenging task due to intermittent connectivity of devices, heterogeneous connection quality, and n

Yazgan Tuna, Amer Al-Hiyasat, Jonathon Howard

Several techniques have been employed for the direct visualization of cytoskeletal filaments and their associated proteins. Total-internal-reflection-fluorescence (TIRF) microscopy has a high signal-to-background ratio, but it suffers from photobleaching and photodamage of the fluorescent proteins. Label-free techniques such as interference reflection micros

Rajasekhar Anguluri, Nima Taghipourbazargani, Oliver Kosut, Lalitha Sankar

We study the problem of localizing multiple sources of forced oscillations (FOs) and estimating their characteristics, such as frequency, phase, and amplitude, using noisy PMU measurements. For each source location, we model the input oscillation as a sum of unknown sinusoidal terms. This allows us to obtain a linear relationship between measurements and the

G. Fejos

We calculate the renormalization group flows of all perturbatively renormalizable interactions in the three-dimensional Ginzburg-Landau potential for the chiral phase transition of three-flavor quantum chromodynamics. On the contrary to the common belief we find a fixed point in the system that is able to describe a second-order phase transition in the infra

Christoph Reisinger, Jonathan Tam

We consider Markov decision processes where the state of the chain is only given at chosen observation times and of a cost. Optimal strategies involve the optimisation of observation times as well as the subsequent action values. We consider the finite horizon and discounted infinite horizon problems, as well as an extension with parameter uncertainty. By in

Rajasekhar Anguluri, Lalitha Sankar, Oliver Kosut

We model and study the problem of localizing a set of sparse forcing inputs for linear dynamical systems from noisy measurements when the initial state is unknown. This problem is of particular relevance to detecting forced oscillations in electric power networks. We express measurements as an additive model comprising the initial state and inputs grouped ov

Lee Kezar, Pei Zhou

There is little prior work on quantifying the relationships between facial expressions and emotionality in American Sign Language. In this final report, we provide two methods for studying these relationships through probability and prediction. Using a large corpus of natural signing manually annotated with facial features paired with lexical emotion dataset

Adithya Kulkarni, Nasim Sabetpour, Alexey Markin, Oliver Eulenstein

Diverse Natural Language Processing tasks employ constituency parsing to understand the syntactic structure of a sentence according to a phrase structure grammar. Many state-of-the-art constituency parsers are proposed, but they may provide different results for the same sentences, especially for corpora outside their training domains. This paper adopts the

A. P. Jovanović, M. N. Stankov, D. Loffhagen, M. M. Becker

MCPlas is introduced as a powerful tool for automated fluid model generation with application to the analysis of dielectric barrier discharges operating in different regimes. MCPlas consists of a number of MATLAB\textsuperscript{\textregistered} scripts and uses the COMSOL Multiphysics\textsuperscript{\textregistered} module LiveLink\textsuperscript{\texttra

Davidson Cheng

Price discrimination is a practice where firms utilize varying sensitivities to prices among consumers to increase profits. The welfare effects of price discrimination are not agreed on among economists, but identification of such actions may contribute to our standing of firms' pricing behaviors. In this letter, I use econometric tools to analyze whether Ap

Ehsan Qasemi, Lee Kezar, Jay Pujara, Pedro Szekely

Language models (LMs) show state of the art performance for common sense (CS) question answering, but whether this ability implies a human-level mastery of CS remains an open question. Understanding the limitations and strengths of LMs can help researchers improve these models, potentially by developing novel ways of integrating external CS knowledge. We dev

Samer T Alnussirat, Michael L Cherry

Transition radiation detectors (TRDs) have been used to identify high-energy particles (in particular, to separate electrons from heavier particles) in accelerator experiments. In space, they have been used to identify cosmic-ray electrons and measure the energies of cosmic-ray nuclei. To date, radiators have consisted of regular configurations of foils with

B. E. Grinyuk, K. A. Bugaev

Using the variational principle, we show that the condition of spatial collapse in a Bose gas is not determined by the value of the scattering length of the interaction potential between particles contrary to the result following from the Gross--Pitaevskii equation, where the collapse should take place at a negative scattering length.

Carol Neidle, Augustine Opoku, Dimitris Metaxas

The American Sign Language Linguistic Research Project (ASLLRP) provides Internet access to high-quality ASL video data, generally including front and side views and a close-up of the face. The manual and non-manual components of the signing have been linguistically annotated using SignStream(R). The recently expanded video corpora can be browsed and searche

K. E. L. de Farias, Azadeh Mohammadi, Herondy F. Santana Mota

In this paper, we study the finite-temperature quantum fluctuation of a classical liquid induced by the topology of an effective conical spacetime, as well as by a quasi-periodic boundary condition. The conical spacetime could be either a disclination or a cosmic string. In this context, we consider a phonon field representing quantum excitations of the liqu

Markus Allgaier, Matthew G. Cooper, Anders E. Carlson, Sarah W. Cooley

The production of meltwater from glacier ice, which is exposed at the margins of land ice during the summer, is responsible for a large proportion of glacier mass loss. The rate of meltwater production from glacier ice is especially sensitive to its physical structure and chemical composition which combine to determine the albedo of glacier ice. However, the

Ezekiel Barnett, Olga Kaiser, Jonathan Masci, Ernst Wit

We introduce a new periodicity detection algorithm for binary time series of event onsets, the Gaussian Mixture Periodicity Detection Algorithm (GMPDA). The algorithm approaches the periodicity detection problem to infer the parameters of a generative model. We specified two models - the Clock and Random Walk - which describe two different periodic phenomena

C. Adolphsen, D. Angal-Kalinin, T. Arndt, M. Arnold

The 2020 update of the European Strategy for Particle Physics emphasised the importance of an intensified and well-coordinated programme of accelerator R&D, supporting the design and delivery of future particle accelerators in a timely, affordable and sustainable way. This report sets out a roadmap for European accelerator R&D for the next five to ten years,

Touqeer Ahmad, Mohsen Jafarzadeh, Akshay Raj Dhamija, Ryan Rabinowitz

There exists a distribution discrepancy between training and testing, in the way images are fed to modern CNNs. Recent work tried to bridge this gap either by fine-tuning or re-training the network at different resolutions. However re-training a network is rarely cheap and not always viable. To this end, we propose a simple solution to address the train-test

Koji Kudo, Yasuhiro Hatsugai

By using the extended Hubbard model of anyons, we numerically demonstrate the adiabatic deformation of the spinful quantum Hall (QH) states by transmutation of statistical fluxes. While the ground state is always spin-polarized in a series of $\nu=1$ integer QH system, the adiabatic continuity between the singlet QH states at $\nu=2$ and $\nu=2/5$ is confirm

Ramin Abolfath, Alexander Baikalov, Stefan Bartzsch, Niayesh Afshordi

We present a microscopic mechanism that accounts for the outward burst of "cold" ion species (IS) in a high-energy particle track due to coupling with ''hot" non-ion species (NIS). IS refers to radiolysis products of ionized molecules, whereas NIS refers to non-ionized excitations of molecules in a medium. The interaction is mediated by a quantized field of

Andrew Keane, Alexandre Pohl, Henk A. Dijkstra, Andy Ridgwell

The global ocean circulation plays a pivotal role in the regulation of the Earth's climate. The specific pattern and strength of circulation also determines how carbon and nutrients are cycled and via the resulting distribution of dissolved oxygen, where habitats suitable for marine animals occur. However, evidence from both geological data and models sugges

Carlos A. Cadavid, Paulina Hoyos, Jay Jorgenson, Lejla Smajlović

In this article we develop a general method by which one can explicitly evaluate certain sums of $n$-th powers of products of $d\geq 1$ elementary trigonometric functions evaluated at $\mathbf{m}=(m_1,\ldots,m_d)$-th roots of unity. Our approach is to first identify the individual terms in the expression under consideration as eigenvalues of a discrete Lapla

Zhiyu Zhang, Ashok Cutkosky, Ioannis Paschalidis

Unconstrained Online Linear Optimization (OLO) is a practical problem setting to study the training of machine learning models. Existing works proposed a number of potential-based algorithms, but in general the design of these potential functions relies heavily on guessing. To streamline this workflow, we present a framework that generates new potential func

Kusha Sridhar, Carlos Busso

The prediction of valence from speech is an important, but challenging problem. The externalization of valence in speech has speaker-dependent cues, which contribute to performances that are often significantly lower than the prediction of other emotional attributes such as arousal and dominance. A practical approach to improve valence prediction from speech

Jinfei Wang, Yi Ma, Na Yi, Rahim Tafazolli

In vehicle-to-infrastructure (V2I) networks, a cluster of multi-antenna access points (APs) can collaboratively conduct transmitter beamforming to provide data services (e.g., eMBB or URLLC). The collaboration between APs effectively forms a networked linear antenna-array with extra-large aperture (i.e., network-ELAA), where the wireless channel exhibits spa

Caroline Svahn, Mattias Villani

Missing values in covariates due to censoring by signal interference or lack of sensitivity in the measuring devices are common in industrial problems. We propose a full Bayesian solution to the prediction problem with an efficient Markov Chain Monte Carlo (MCMC) algorithm that updates all the censored covariate values jointly in a random scan Gibbs sampler.

Peter Czajka, Tong Gao, Max Hirschberger, Paula Lampen-Kelley

We report detailed measurements of the Onsager-like planar thermal Hall conductivity $\kappa_{xy}$ in $\alpha$-RuCl$_3$, a spin-liquid candidate of topical interest. With the thermal current ${\bf J}_{\rm Q}$ and magnetic field $\bf B\parallel a$ (zigzag axis), the observed $\kappa_{xy}/T$ varies strongly with temperature $T$ (1-10 K). The results are well-d

Osama Muhammad Raisuddin, Suvranu De

The solution of physical problems discretized using the finite element methods using quantum computers remains relatively unexplored. Here, we present a unified formulation (FEqa) to solve such problems using quantum annealers. FEqa is a hybrid technique in which the finite element problem is formulated on a classical computer, and the residual is minimized

Hui Hu, Xia-Ji Liu

We present a systematic study of a mobile impurity immersed in a three-dimensional Fermi sea of fermions at finite temperature, by using the standard non-self-consistent many-body $T$-matrix theory that is equivalent to a finite-temperature variational approach with the inclusion of one-particle-hole excitation. The impurity spectral function is determined i

Chi Zhang, Chaoqun Zhang, Lan Cheng, Timothy C. Steimle

The YbF molecule is a sensitive system for measuring the electron's electric dipole moment. The precision of this measurement can be improved by direct laser cooling of the molecules to ultracold temperature. However, low-lying electronic states arising from excitation of a 4f electron may hinder laser cooling. One set of these "4f hole" states lies below th

Lei Chang, Fei Gao, Craig D. Roberts

An algebraic Ansatz for the proton's Poincar\'e-covariant wave function, which includes both scalar and pseudovector diquark correlations, is used to calculate proton valence, sea, and glue distribution functions (DFs). Regarding contemporary data, a material pseudovector diquark component in the proton is necessary for an explanation of the neutron-proton s

The CHIME Collaboration, Mandana Amiri, Kevin Bandura, Anja Boskovic

The Canadian Hydrogen Intensity Mapping Experiment (CHIME) is a drift scan radio telescope operating across the 400-800 MHz band. CHIME is located at the Dominion Radio Astrophysical Observatory near Penticton, BC Canada. The instrument is designed to map neutral hydrogen over the redshift range 0.8 to 2.5 to constrain the expansion history of the Universe.

Robert L. Benedetto, Vefa Goksel

We study the dynamics of the unicritical polynomial family $f_{d,c}(z)=z^d+c\in \mathbb{C}[z]$. The $c$-values for which $f_{d,c}$ has a strictly preperiodic postcritical orbit are called Misiurewicz parameters, and they are the roots of Misiurewicz polynomials. The arithmetic properties of these special parameters have found applications in both arithmetic

Philipp Kellmeyer, Roland Berkemeier, Tonio Ball

In the past three decades, neuroimaging has provided important insights into structure-function relationships in the human brain. Recently, however, the methods for analyzing functional magnetic resonance imaging (fMRI) data have come under scrutiny, with studies questioning cross-software comparability, the validity of statistical inference and interpretati

Julia E. Huddy, Youxiong Ye, William J. Scheideler

Perovskite solar cells have potential to deliver terawatt-scale power via low-cost manufacturing. However, scaling is limited by slow, high-temperature annealing of the inorganic transport layers and the lack of reliable, large-area methods for depositing thin (< 30 nm) charge transport layers (CTLs). We present a method for scaling ultrathin NiOx hole trans

Natalia Queiroz de Oliveira, Vânia Borges, Henrique F. Rodrigues, Maria Luiza Machado Campos

Since their proposal in 2016, the FAIR principles have been largely discussed by different communities and initiatives involved in the development of infrastructures to enhance support for data findability, accessibility, interoperability, and reuse. One of the challenges in implementing these principles lies in defining a well-delimited process with organiz

Abdul Jalal, Ravi Kant, Arjun Kumar, V. Kumar

This paper presents the plan of an in-pipe climbing robot that works utilizing a novel Three-Output Open Differential(3-OOD) component to navigate complex organizations of lines. Customary wheeled/followed in-pipe climbing robots are inclined to slip and haul while navigating in pipe twists. The 3-OOD component helps in accomplishing the original aftereffect

Jean Rabault, Takehiko Nose, Gaute Hope, Malte Muller

There is a wide consensus within the polar science, meteorology, and oceanography communities that more in-situ observations of the ocean, atmosphere, and sea ice, are required to further improve operational forecasting model skills. Traditionally, the volume of such measurements has been limited by the high cost of commercially available instruments. An inc

M. Renzo, D. D. Hendriks, L. A. C. van Son, R. Farmer

Population synthesis relies on semi-analytic formulae to determine masses of compact objects from the (helium or carbon-oxygen) cores of collapsing stars. Such formulae are combined across mass ranges that span different explosion mechanisms, potentially introducing artificial features in the compact object mass distribution. Such artifacts impair the interp

M. L. Graham, T. D. Kennedy, S. Kumar, R. C. Amaro

The observed diversity in Type Ia supernovae (SNe Ia) -- the thermonuclear explosions of carbon-oxygen white dwarf stars used as cosmological standard candles -- is currently met with a variety of explosion models and progenitor scenarios. To help improve our understanding of whether and how often different models contribute to the occurrence of SNe Ia and t

Andrew R. Willis, Kevin Brink, Kathleen Dipple

This article describes a software package called ROS georegistration intended for use with the Robot Operating System (ROS) and the Gazebo 3D simulation environment. ROSgeoregistration provides tools for the simulation, test and deployment of aerial georegistration algorithms and is made available with a link provided in the paper. A model creation package i

Shimaa Naser, Lina Bariah, Sami Muhaidat, Mahmoud Al-Qutayri

We propose an enhanced spatial modulation (SM)-based scheme for indoor visible light communication systems. This scheme enhances the achievable throughput of conventional SM schemes by transmitting higher order complex modulation symbol, which is decomposed into three different parts. These parts carry the amplitude, phase, and quadrant components of the com