May 2020 arXiv papers — page 41

D. Kaganovich, B. Hafizi, L. A. Johnson, D. F. Gordon

Experimental studies of the optical properties of compressible, viscous and rapidly-rotating gas flows (vortices) are presented. Gas vortices can function as optical elements such as lenses or waveguides. The optical properties are determined from direct interferometric phase measurements and beam propagation analysis. Output beams are analyzed in terms of Z

Zonghe Chua, Allison M. Okamura, Darrel R. Deo

Individuals living with paralysis or amputation can operate robotic prostheses using input signals based on their intent or attempt to move. Because sensory function is lost or diminished in these individuals, haptic feedback must be non-collocated. The intracortical brain computer interface (iBCI) has enabled a variety of neural prostheses for people with p

Colin S. Gordon

Capabilities (whether object or reference capabilities) are fundamentally tools to restrict effects. Thus static capabilities (object or reference) and effect systems take different technical machinery to the same core problem of statically restricting or reasoning about effects in programs. Any time two approaches can in principle address the same sets of p

Nicolas Castaño, Seth Cordts, Myra Kurosu Jalil, Kevin Zhang

Contaminated objects or surfaces, referred to as fomites, play a critical role in the spread of viruses, including SARS-CoV-2, the virus responsible for the COVID-19 pandemic. The long persistence of viruses (hours to days) on surfaces calls for an urgent need for surface disinfection strategies to intercept virus transmission and the spread of the disease.

Abbas Kazerouni, Qi Zhao, Jing Xie, Sandeep Tata

Consider a sequential active learning problem where, at each round, an agent selects a batch of unlabeled data points, queries their labels and updates a binary classifier. While there exists a rich body of work on active learning in this general form, in this paper, we focus on problems with two distinguishing characteristics: severe class imbalance (skew)

Shun-Jen Cheng, Kevin Coulembier

We study a semisimple extension of a Takiff superalgebra which turns out to have a remarkably rich representation theory. We determine the blocks in both the finite-dimensional and BGG module categories and also classify the Borel subalgebras. We further compute all extension groups between two finite-dimensional simple objects and prove that all non-princip

Valdivino V. Junior, Pablo M. Rodriguez, Adalto Speroto

In this paper we study the Maki-Thompson rumor model on infinite Cayley trees. The basic version of the model is defined by assuming that a population represented by a graph is subdivided into three classes of individuals: ignorants, spreaders and stiflers. A spreader tells the rumor to any of its (nearest) ignorant neighbors at rate one. At the same rate, a

E. V. Tsiper

A design principle is suggested to overcome obstacles that prevent positive net energy output in nuclear fusion devices based on electrostatically accelerated ions. Since Coulomb scattering cross-section dwarfs that of nuclear fusion, the focus is on re-capturing energy of elastically scattered ions before the energy is lost to heat. Device configuration to

Y. H. Gong, X. Jiang, B. X. Shang

In this paper, we study how to quickly compute the <-minimal monomial interpolating basis for a multivariate polynomial interpolation problem. We address the notion of "reverse" reduced basis of linearly independent polynomials and design an algorithm for it. Based on the notion, for any monomial ordering we present a new method to read off the <-minimal mon

Chuan-Ju Wang, Yu-Neng Chuang, Chih-Ming Chen, Ming-Feng Tsai

In this paper, we propose a novel optimization criterion that leverages features of the skew normal distribution to better model the problem of personalized recommendation. Specifically, the developed criterion borrows the concept and the flexibility of the skew normal distribution, based on which three hyperparameters are attached to the optimization criter

Yingxun Zhang, Ning Wang, Qingfeng Li, Li Ou

In this review article, we first briefly introduce the transport theory and quantum molecular dynamics model applied in the study of the heavy ion collisions from low to intermediate energies. The developments of improved quantum molecular dynamics model (ImQMD) and ultra-relativistic quantum molecular dynamics model (UrQMD), are reviewed. The reaction mecha

Xu Zhang, Marcos M. Vasconcelos, Wei Cui, Urbashi Mitra

The emergence of the Internet-of-Things and cyber-physical systems necessitates the coordination of access to limited communication resources in an autonomous and distributed fashion. Herein, the optimal design of a wireless sensing system with n sensors communicating with a fusion center via a collision channel of limited capacity k (k < n) is considered. I

Teruhisa Sugimoto

In this study, various rotationally symmetric tilings that can be formed using pentagons that are related to rhombus are discussed. The pentagons can be convex or concave and can be degenerated into a trapezoid. If the pentagons are convex, they belong to the Type 2 family. Because the properties of pentagons correspond to those of rhombuses, the study also

Yizhe Zhu, Martin Renqiang Min, Asim Kadav, Hans Peter Graf

We propose a sequential variational autoencoder to learn disentangled representations of sequential data (e.g., videos and audios) under self-supervision. Specifically, we exploit the benefits of some readily accessible supervisory signals from input data itself or some off-the-shelf functional models and accordingly design auxiliary tasks for our model to u

Amit Agarwal, James Bartusek, Vipul Goyal, Dakshita Khurana

We initiate the study of multi-party computation for classical functionalities (in the plain model) with security against malicious polynomial-time quantum adversaries. We observe that existing techniques readily give a polynomial-round protocol, but our main result is a construction of *constant-round* post-quantum multi-party computation. We assume mildly

Debarchan Das, K. Kobayashi, M. P. Smylie, C. Mielke

Recently, the niobium (Nb)-doped topological insulator Bi_2Se_3, in which the finite magnetic moments of the Nb atoms are intercalated in the van der Waals gap between the Bi_2Se_3 layers, has been shown to exhibit both superconductivity with T_c = 3 K and topological surface states. Here we report on muon spin rotation experiments probing the temperature-de

Victor Klemm, Alessandro Morra, Ciro Salzmann, Florian Tschopp

Applications of mobile ground robots demand high speed and agility while navigating in complex indoor environments. These present an ongoing challenge in mobile robotics. A system with these specifications would be of great use for a wide range of indoor inspection tasks. This paper introduces Ascento, a compact wheeled bipedal robot that is able to move qui

Hanqing Zhao, Hong Zhao

The Stokes-Einstein (SE) relation has been widely applied to quantitatively describe the Brownian motion. Notwithstanding, here we show that even for a simple fluid, the SE relation may not be completely applicable. Namely, although the SE relation could be a good approximation for a large enough Brownian particle, we find that it induces significant error f

Antti Lankinen, Ismael Mullor Ruiz, Thomas E. Ouldridge

DNA strand displacement (DSD) reactions have been used to construct chemical reaction networks in which species act catalytically at the level of the overall stoichiometry of reactions. These effective catalytic reactions are typically realised through one or more of the following: many-stranded gate complexes to coordinate the catalysis, indirect interactio

S Anand, G Sangeethapriya

In this paper, a non-separable (NS), robust to noise, Two Dimensional (2D) isotropic Gaussian Modulated Hyperbolic Tangent (GMHPT) High Pass (HP) filter is designed to filter the high-frequency components present in a noisy image. The major drawbacks of conventional HP filters used for image analysis are noise influences (more sensitivity to noise) which lea

Victor Klemm, Alessandro Morra, Lionel Gulich, Dominik Mannhart

We present a hierarchical whole-body controller leveraging the full rigid body dynamics of the wheeled bipedal robot Ascento. We derive closed-form expressions for the dynamics of its kinematic loops in a way that readily generalizes to more complex systems. The rolling constraint is incorporated using a compact analytic solution based on rotation matrices.

Bruno Leonardo Macedo Ferreira, Bruno Tadeu Costa

Let $\mathfrak{A}$ and $\mathfrak{A}'$ be two $C^*$-algebras with identities $I_{\mathfrak{A}}$ and $I_{\mathfrak{A}'}$, respectively, and $P_1$ and $P_2 = I_{\mathfrak{A}} - P_1$ nontrivial projections in $\mathfrak{A}$. In this paper we study the characterization of multiplicative $*$-Jordan-type maps. In particular, if $\mathcal{M}$ is a factor von Neuman

Scott Eisele, Taha Eghtesad, Nicholas Troutman, Aron Laszka

As the number of personal computing and IoT devices grows rapidly, so does the amount of computational power that is available at the edge. Since many of these devices are often idle, there is a vast amount of computational power that is currently untapped, and which could be used for outsourcing computation. Existing solutions for harnessing this power, suc

Hashim A. Hashim, Lyndon J. Brown, Kenneth McIsaac

Two nonlinear stochastic complimentary filters are developed on SO(3). They guarantee that errors in the Rodriguez vector and estimates are semi-globally uniformly ultimately bounded in mean square, and they converge to a small neighborhood of the origin. Simulation results are presented to illustrate the effectiveness of the proposed filters considering hig

Russell Avdek

Let $\Lambda^{\pm} = \Lambda^{+} \cup \Lambda^{-} \subset (\mathbb{R}^{3}, \xi_{std})$ be a contact surgery diagram determining a closed, connected contact $3$-manifold $(S^{3}_{\Lambda^{\pm}}, \xi_{\Lambda^{\pm}})$ and an open contact manifold $(\mathbb{R}^{3}_{\Lambda^{\pm}}, \xi_{\Lambda^{\pm}})$. Following arXiv:0911.0026 and arXiv:1906.07228 we demonstr

Yang Zhang, Weili Jiang, Luning Sun, Jianxun Wang

This paper proposes a deep-learning based generalized reduced-order model (ROM) that can provide a fast and accurate prediction of the glottal flow during normal phonation. The approach is based on the assumption that the vibration of the vocal folds can be represented by a universal kinematics equation (UKE), which is used to generate a glottal shape librar

Jianfeng Wang, Xi Yin, Lijuan Wang, Lei Zhang

In this paper, we propose an algorithm, named hashing-based non-maximum suppression (HNMS) to efficiently suppress the non-maximum boxes for object detection. Non-maximum suppression (NMS) is an essential component to suppress the boxes at closely located locations with similar shapes. The time cost tends to be huge when the number of boxes becomes large, es

Shenshen Chen, Geng Li, Dennis Duan, Kerim Gokarslan

Achieving highly reliable networks is essential for network operators to ensure proper packet delivery in the event of software errors or hardware failures. Networks must ensure reachability and routing correctness, such as subnet isolation and waypoint traversal. Existing work in network verification relies on centralized computation at the cost of fault to

Xiangjue Dong, Changmao Li, Jinho D. Choi

We present a transformer-based sarcasm detection model that accounts for the context from the entire conversation thread for more robust predictions. Our model uses deep transformer layers to perform multi-head attentions among the target utterance and the relevant context in the thread. The context-aware models are evaluated on two datasets from social medi

Aviad Levis, Yoav Y. Schechner, Anthony B. Davis, Jesse Loveridge

Tomography aims to recover a three-dimensional (3D) density map of a medium or an object. In medical imaging, it is extensively used for diagnostics via X-ray computed tomography (CT). Optical diffusion tomography is an alternative to X-ray CT that uses multiply scattered light to deliver coarse density maps for soft tissues. We define and derive tomography

Mengdi Wang, Hung Chau, Khushboo Thaker, Peter Brusilovsky

With the increased popularity of electronic textbooks, there is a growing interests in developing a new generation of "intelligent textbooks", which have the ability to guide the readers according to their learning goals and current knowledge. The intelligent textbooks extend regular textbooks by integrating machine-manipulatable knowledge such as a knowledg

Maxim Emelin

We study the possibility of realizing scale-separated type IIB Anti-de Sitter and de Sitter compactifications within a controlled effective field theory regime defined by low-energy and large (but scale-separated) compactification volume. The approach we use views effective theories as truncations of the full quantum equations of motion expanded in a trans-s

Suzete Afonso, Juarez Azevedo, Mariana Pinheiro

We shall apply a generalized SEIR model to study the outbreak of COVID-19 in Brazil. In particular, we would like to explain the projections of the increase in the level of infection over a long period of time, overlapping large local outbreaks in the most populous states in the country. A time-dependent dynamic SEIR model inspired in a model previously used

Nima Arkani-Hamed, Song He, Thomas Lam

For each Dynkin diagram $D$, we define a ''cluster configuration space'' ${\mathcal{M}}_D$ and a partial compactification ${\widetilde {\mathcal{M}}}_D$. For $D = A_{n-3}$, we have ${\mathcal{M}}_{A_{n-3}} = {\mathcal{M}}_{0,n}$, the configuration space of $n$ points on ${\mathbb P}^1$, and the partial compactification ${\widetilde {\mathcal{M}}}_{A_{n-3}}$

Xinwei Zhang, Mingyi Hong, Sairaj Dhople, Wotao Yin

Federated Learning (FL) has become a popular paradigm for learning from distributed data. To effectively utilize data at different devices without moving them to the cloud, algorithms such as the Federated Averaging (FedAvg) have adopted a "computation then aggregation" (CTA) model, in which multiple local updates are performed using local data, before sendi

Rishabh Malhotra, Dhron Joshi, Ku Young Shin

Malaria is a deadly disease which claims the lives of hundreds of thousands of people every year. Computational methods have been proven to be useful in the medical industry by providing effective means of classification of diagnostic imaging and disease identification. This paper examines different machine learning methods in the context of classifying the

Hugh Lawson-Tancred, Henry C. W. Price, Alessandro Provetti

We respond to a recent short paper by de Motjoye et el. on privacy issues with Covid-19 tracking. Their paper, which we discuss here, is structured around three "toy protocols" for the design of an app which can maximise the utility of contact tracing information while minimising the more general risk to privacy. On this basis, the paper proceeds to introduc

Antonio Lanteri, Raquel Mallavibarrena

Polarized rational surfaces $(X, \mathcal L)$ of sectional genus two ruled in conics are studied. When they are not minimal, they are described as the blow-up of $\mathbb F_1$ at some points lying on distinct fibers. Ampleness and very ampleness of $\mathcal L$ are studied in terms of their location. When $\mathcal L$ is very ample and there is a line contai

Larissa Romualdo-Suzuki, Anthony Finkelstein

The systems that operate the infrastructure of cities have evolved in a fragmented fashion across several generations of technology, causing city utilities and services to operate sub-optimally and limiting the creation of new value-added services and restrict opportunities for cost-saving. The integration of cross-domain city data offers a new wave of oppor

Sikender Gul, Muhammad Faisal Siddiqui, Naveed Ur Rehman

Multivariate or multichannel data have become ubiquitous in many modern scientific and engineering applications, e.g., biomedical engineering, owing to recent advances in sensor and computing technology. Processing these data sets is challenging owing to: i) their large size and multidimensional nature, thus requiring specialized algorithms and efficient har

Beyza Dabak, Ahmed Hareedy, Robert Calderbank

The two-dimensional magnetic recording (TDMR) technology promises storage densities of $10$ terabits per square inch. However, when tracks are squeezed together, a bit stored in the two-dimensional (TD) grid suffers inter-symbol interference (ISI) from adjacent bits in the same track, and inter-track interference (ITI) from nearby bits in the adjacent tracks

Arkady L. Kholodenko

Recently,a noticeable progress had been achieved in the area of high temperature superconductors. The maximum temperature of 250K for LaH(10) and 288K for CSH(8) were reported at the megabar pressures. The highest possible temperatures were achieved by employing hydrides of chemical elements. Empirically, many of these are made of Madelung-exceptional atoms.

Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright

Many statistical estimators are defined as the fixed point of a data-dependent operator, with estimators based on minimizing a cost function being an important special case. The limiting performance of such estimators depends on the properties of the population-level operator in the idealized limit of infinitely many samples. We develop a general framework t

Naoyuki Kanda, Yusuke Nakanishi, Dan Liu, Zheng Liu

Atomically thin one dimensional (1D) van der Waals wires of transition metal monochalocogenides (TMMs) have been anticipated as promising building blocks for integrated nanoelectronics. While reliable production of TMM nanowires has eluded scientists over the past few decades, we finally demonstrated a bottom up fabrication of MoTe nanowires inside carbon na

Driss Lhaimer, Khalid Bouras, Mohammed Moussa

In this paper, we introduce and study new concepts of order L-weakly and order M-weakly compact operators. As consequences, we obtain some characterizations of Banach lattices with order continuous norms or whose topological duals have order continuous norms. It is proved that if $T : E \longrightarrow F$ is an operator between two Banach lattices, then T is

Junzhe Zhu, Mark Hasegawa-Johnson, Leda Sari

In scenarios where multiple speakers talk at the same time, it is important to be able to identify the talkers accurately. This paper presents an end-to-end system that integrates speech source extraction and speaker identification, and proposes a new way to jointly optimize these two parts by max-pooling the speaker predictions along the channel dimension.

Abdessamad Belfakir, Yassine Hassouni

We introduce a generalization structure of the su(1,1) algebra which depends on a function of one generator of the algebra, f(H). Following the same ideas developed to the generalized Heisenberg algebra (GHA) and to the generalized su(2), we show that a symmetry is present in the sequence of eigenvalues of one generator of the algebra. Then, we construct the

Yuhang Song, Wenbo Li, Lei Zhang, Jianwei Yang

We study in this paper the problem of novel human-object interaction (HOI) detection, aiming at improving the generalization ability of the model to unseen scenarios. The challenge mainly stems from the large compositional space of objects and predicates, which leads to the lack of sufficient training data for all the object-predicate combinations. As a resu

Nat Roth, Justin Wagle

To perform well, most deep learning based image classification systems require large amounts of data and computing resources. These constraints make it difficult to quickly personalize to individual users or train models outside of fairly powerful machines. To deal with these problems, there has been a large body of research into teaching machines to learn t

Pedro Cisneros-Velarde, Francesco Bullo

This paper analyzes a Susceptible-Infected-Susceptible (SIS) model of epidemic propagation over hypergraphs and, motivated by an important special case, we refer to the model as to the simplicial SIS model. Classically, the multi-group SIS model has assumed pairwise interactions of contagion across groups and thus has been vastly studied in the literature. I

E. Bempong-Manful, M. J. Hardcastle, M. Birkinshaw, R. A. Laing

We present new high-resolution and high-sensitivity studies of the jets in the WAT source 3C 465, using deep transverse-resolved radio observations from e-MERLIN, and with complementary observations from the VLA. We derive a lower limit $\beta_{\rm j}$ = ($\nu_{\rm j}$/$c$) $\gtrsim$ 0.5 for the jet speed, and an upper limit $\theta_{\rm j}$ $\lesssim$ 61$^{

Krzysztof Malarz, Maciej Wołoszyn, Krzysztof Kułakowski

The state of structural balance (termed also `Heider balance') of a social network is often discussed in social psychology and sociophysics. In this state, actors at network nodes classify other individuals as enemies or friends. Hence, the network contains two kinds of links: positive and negative. Here a new cellular automaton is designed and investigated,

Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni

Large pre-trained language models have been shown to store factual knowledge in their parameters, and achieve state-of-the-art results when fine-tuned on downstream NLP tasks. However, their ability to access and precisely manipulate knowledge is still limited, and hence on knowledge-intensive tasks, their performance lags behind task-specific architectures.

Dimitry Yankelev, Chen Avinadav, Nir Davidson, Ofer Firstenberg

The periodicity inherent to any interferometric signal entails a fundamental trade-off between sensitivity and dynamic range of interferometry-based sensors. Here we develop a methodology for significantly extending the dynamic range of such sensors without compromising their sensitivity, scale-factor, and bandwidth. The scheme is based on operating two simu

Laurens Arp, Dyon van Vreumingen, Daniela Gawehns, Mitra Baratchi

How can urban movement data be exploited in order to improve the flow of traffic within a city? Movement data provides valuable information about routes and specific roads that people are likely to drive on. This allows us to pinpoint roads that occur in many routes and are thus sensitive to congestion. Redistributing some of the traffic to avoid unnecessary

Narayan Mohanta, Andrew D. Christianson, Satoshi Okamoto, Elbio Dagotto

Understanding the spin-wave excitations of chiral magnetic order, such as the skyrmion crystal (SkX), is of fundamental interest to confirm such exotic magnetic order. The SkX is realized by competing Dzyaloshinskii-Moriya and ferromagnetic-exchange interactions with a magnetic field or anisotropy. Here we compute the dynamical spin structure factor, using M

Ziheng Sun

Due to the complexities of virus genotypes and the stochastic contacts in human society, it is a big challenge to estimate the potential risks of getting exposed to a widely spreading virus. To allow the public to be aware of the exposure risks in their daily activities, we proposed a birthday-paradox-based probability model and implement it into a web-based

M. Mohammadi, R. Dehghani

We borrow the form of potential of the well-known kink-bearing $\varphi^4$ system in the range between its two vacua and paste it repeatedly into the other ranges to introduce the periodic $\varphi^4$ system. The paper is devoted to providing a comparative numerical study of the properties of the two systems. Although the two systems are quite similar for a

R. Aly

In the High Luminosity Large Hadron Collider (HL-LHC) program, during the next years, the instantaneous luminosity will increase up to 5 $\times$ 10$^{34}$ cm$^{-2}$ s$^{-1}$ which means a factor five higher than the nominal LHC. In that period, the present CMS Resistive Plate Chambers (RPC) system will be subjected to background rates higher than those for

Priyanka Kumari

During Phase-2 of the LHC, known as the High Luminosity LHC (HL-LHC), the accelerator will increase its instantaneous luminosity to 5 $\times$ 10$^{34}$ cm$^{-2}$ s$^{-1}$, delivering an integrated luminosity of 3000 fb$^{-1}$ over 10 years of operation starting from 2027. In view of the HL-LHC, the CMS muon system will be upgraded to sustain efficient muon

Arran Fernandez, Jean-Daniel Djida

Starting from a recent result expressing the Lerch zeta function as a fractional derivative, we consider further fractional derivatives of the Lerch zeta function with respect to different variables. We establish a partial differential equation, involving an infinite series of fractional derivatives, which is satisfied by the Lerch zeta function.

Sandeep Singh Sandha, Mohit Aggarwal, Igor Fedorov, Mani Srivastava

Tuning hyperparameters for machine learning algorithms is a tedious task, one that is typically done manually. To enable automated hyperparameter tuning, recent works have started to use techniques based on Bayesian optimization. However, to practically enable automated tuning for large scale machine learning training pipelines, significant gaps remain in ex

Gerd Wagner, Matthew W. Guthrie

This paper expands on previous work to derive and motivate the Lagrangian formulation of field theories. In the process, we take three deliberate steps. First, we give the definition of the action and derive Euler-Lagrange equations for field theories. Second, we prove the Euler-Lagrange equations are independent under arbitrary coordinate transformations an

Vladimir Rovenski, Sergey Stepanov, Irina Tsyganok

In the paper, we study evolution equations of the scalar and Ricci curvatures under the Hamilton's Ricci flow on a closed manifold and on a complete noncompact manifold. In particular, we study conditions when the Ricci flow is trivial and the Ricci soliton is Ricci flat or Einstein.

Sofia Sanz, Pedro Brandimarte, Géza Giedke, Daniel Sánchez-Portal

We analyze theoretically 4-terminal electronic devices composed of two crossed graphene nanoribbons (GNRs) and show that they can function as beam splitters or mirrors. These features are identified for electrons in the low-energy region where a single valence or conduction band is present. Our modeling is based on $p_z$ orbital tight-binding with Slater--Ko

Pascale Hibon, Francis Tang, Romain Thomas

Context. Searching for high-redshift galaxies is a field of intense activity in modern observational cosmology that will continue to grow with future ground-based and sky observatories. Over the last few years, a lot has been learned about the high-z Universe. Aims. Despite extensive Ly-alpha Blobs (LAB) surveys from low to high redshifts, giant LABs over 10

Gioacchino Antonelli, Daniela Di Donato, Sebastiano Don, Enrico Le Donne

In arbitrary Carnot groups we study intrinsic graphs of maps with horizontal target. These graphs are $C^1_H$ regular exactly when the map is uniformly intrinsically differentiable. Our first main result characterizes the uniformly intrinsic differentiability by means of H\"older properties along the projections of left-invariant vector fields on the graph.

Keiichiro Furuya, Nima Lashkari, Shoy Ouseph

The entanglement theory in quantum systems with internal symmetries is rich due to the spontaneous creation of entangled pairs of charge/anti-charge particles at the entangling surface. We call these pair creation operators the bi-local intertwiners because of the role they play in the representation theory of the symmetry group. We define a generalized meas

Nail Khusnutdinov

On a particle moving with variable acceleration in the flat space-time affects the self-force due to outgoing radiation. The gravitational fields bring an additional contribution to self-force due to scattering waves on the curved backgrounds. This force is not zero even for a particle at rest. A review of the self-interaction in the gravitational field is p

Crystel Bujold

In this paper, we prove a lower bound for $\underset{\chi \neq \chi_0}{\max}\bigg|\sum_{n\leq x} \chi(n)\bigg|$, when $x= \frac{q}{(\log q)^B}$. This improves on a result of Granville and Soundararajan for large character sums when the range of summation is wide. When $B$ goes to zero, our lower bound recovers the expected maximal value of character sums for

Daniel G. Suárez-Forero, Fabrizio Riminucci, Vincenzo Ardizzone, Nicholas Karpowicz

Exciton-polaritons are hybrid light-matter excitations arising from the non-perturbative coupling of a photonic mode and an excitonic resonance. Behaving as interacting photons, they show optical third-order nonlinearities providing effects such as optical parametric oscillation or amplification. It has been suggested that polariton-polariton interactions ca

Yingying Zhu, Daniel C. Elton, Sungwon Lee, Perry J. Pickhardt

Calcified plaque in the aorta and pelvic arteries is associated with coronary artery calcification and is a strong predictor of heart attack. Current calcified plaque detection models show poor generalizability to different domains (ie. pre-contrast vs. post-contrast CT scans). Many recent works have shown how cross domain object detection can be improved us

Marc Fabert, Maria Săpânţan, Katarzyna Krupa, Alessandro Tonello

A low intensity light beam emerges from a graded-index, highly multimode optical fibre with a speckled shape, while at higher intensity the Kerr nonlinearity may induce a spontaneous spatial self-cleaning of the beam [1,2]. Here, we reveal that we can generate two self-cleaned beams with a mutual coherence large enough to produce a clear stable fringe patter

Nail A. Gumerov, Ross N. Adelman, Ramani Duraiswami

A novel boundary element formulation for solving problems involving eddy currents in the thin skin depth approximation is developed. It is assumed that the time-harmonic magnetic field outside the scatterers can be described using the quasistatic approximation. A two-term asymptotic expansion with respect to a small parameter characterizing the skin depth is

Ravi Raghunathan

We will introduce two new classes of Dirichlet series which are monoids under multiplication. The first class $\mathfrak{A}^{\#}$ contains both the extended Selberg class $\mathscr{S}^{\#}$ of Kaczorowski and Perelli as well as many $L$-functions attached to automorphic representations of ${\rm GL}_n({\mathbb A}_K)$, where ${\mathbb A}_K$ denotes the ad\`ele

Minglang Yin, Xiaoning Zheng, Jay D. Humphrey, George Em Karniadakis

We employ physics-informed neural networks (PINNs) to infer properties of biological materials using synthetic data. In particular, we successfully apply PINNs on inferring the thrombus permeability and visco-elastic modulus from thrombus deformation data, which can be described by the fourth-order Cahn-Hilliard and Navier-Stokes Equations. In PINNs, the par

Anuj P. Lara, Samudra Roy

We theoretically and numerically investigate the evolution of discrete soliton in a 1D linearly chirped nonlinear waveguide array (WA). The discrete soliton is self-accelerated inside the transversely chirped WA and emits a \textit{dynamic diffractive resonant radiation} (DifRR). The radiation appears when soliton wave-number matched with linear radiation wa

Youssouph Cissokho, Rafal Kulik

Cluster indices describe extremal behaviour of stationary time series. We consider their sliding blocks estimators. Using a modern theory of multivariate, regularly varying time series, we obtain central limit theorems under conditions that can be easily verified for a large class of models. In particular, we show that in the Peak over Threshold framework, s

Huta R. Banjade, Jinbo Pan, Qimin Yan

Discovery and design of two-dimensional (2D) materials with suitable band gaps and high carrier mobility is of vital importance for photonics, optoelectronics, and high-speed electronics. In this work, based on first principles calculations using density functional theory (DFT) with PBE and HSE functionals, we introduce a family of monolayer isostructural se

Ryan F. Johnson, Andrew D. Kercher

We present a detailed description and verification of a discontinuous Galerkin finite element method (DG) for the multi-component chemically reacting compressible Navier-Stokes equations that retains the desirable properties of DG, namely discrete conservation and high-order accuracy in smooth regions of the flow. Pressure equilibrium between adjacent elemen

Yifan Chen, Houman Owhadi, Andrew M. Stuart

Gaussian process regression has proven very powerful in statistics, machine learning and inverse problems. A crucial aspect of the success of this methodology, in a wide range of applications to complex and real-world problems, is hierarchical modeling and learning of hyperparameters. The purpose of this paper is to study two paradigms of learning hierarchic

Ignatios Antoniadis, Jean-Pierre Derendinger, Hongliang Jiang, Gabriele Tartaglino-Mazzucchelli

A necessary condition for partial breaking of N=2 global supersymmetry is the presence of nonlinear deformations of the field transformations which cannot be generated by background values of auxiliary fields. This work studies the simplest of these deformations which already occurs in N=1 global supersymmetry, and its coupling to supergravity. It can be vie

Giovanni Lo Faro, Antoinette Tripodi

Let $G$ be a simple finite graph and $G'$ be a subgraph of $G$. A $G'$-design $(X,\cal B)$ of order $n$ is said to be embedded into a $G$-design $(X\cup U,\cal C)$ of order $n+u$, if there is an injective function $f:\cal B\rightarrow \cal C$ such that $B$ is a subgraph of $f(B)$ for every $B\in\cal B$. The function $f$ is called an embedding of $(X,\cal B)$

Karla. Z. Arellano-Córdova, César Esteban, Jorge García-Rojas, J. Eduardo Méndez-Delgado

We present a reassessment of the radial abundance gradients of C, N, O, Ne, S, Cl and Ar in the Milky Way using deep spectra of 33 H II regions gathered from the literature, covering Galactocentric distances from 6 to 17 kpc. The distances of the objects have been revised using Gaia parallaxes. We recalculate the physical conditions and ionic abundances in a

Jixuan Wang, Xiong Xiao, Jian Wu, Ranjani Ramamurthy

Deep speaker embedding models have been commonly used as a building block for speaker diarization systems; however, the speaker embedding model is usually trained according to a global loss defined on the training data, which could be sub-optimal for distinguishing speakers locally in a specific meeting session. In this work we present the first use of graph

Victoria Grushkovskaya, Alexander Zuyev

In this paper, a class of nonlinear driftless control-affine systems satisfying the bracket generating condition is considered. A gradient-free optimization algorithm is developed for the minimization of a cost function along the trajectories of the controlled system. The algorithm comprises an approximation scheme with fast oscillating controls for the nonh

Eric MSP Veith, Jawad Kazmi, Stephan Balduin

Power grids are transitioning from an infrastructure model based on reactive electronics towards a smart grid that features complex software stacks with intelligent, pro-active and decentralized control. As the power grid infrastructure becomes a platform for software, so does the need for a reliable roll-out of software updates on a large scale. In order to

Amartya Kalapahar, Julio Silva-Rodríguez, Adrián Colomer, Fernando López-Mir

Worldwide, prostate cancer is one of the main cancers affecting men. The final diagnosis of prostate cancer is based on the visual detection of Gleason patterns in prostate biopsy by pathologists. Computer-aided-diagnosis systems allow to delineate and classify the cancerous patterns in the tissue via computer-vision algorithms in order to support the physic

Andrew Harder

We study the cohomology rings of snc log symplectic pairs $(X,Y)$ which have log symplectic forms of pure weight. We show that under a certain natural condition, the cohomology ring of $X \setminus Y$ exhibits the curious hard Lefschetz property. Analogous results are shown to hold for limit mixed Hodge structures associated to good degenerations of projecti

Fernando Macías, Adrian Rutle, Volker Stolz, Torben Scheffel

Within Model-Driven Software Engineering, Domain-Specific Modelling has proven to be a powerful technique to specify systems and systems' behaviour in a formal, yet understandable way. Runtime verification (RV) has been successfully used to verify the correctness of such behaviour. Specifying behaviour requires managing various levels of abstractions, making

Junjie Liu, Dvira Segal

We unravel the critical role of vibrational mode softening in single-molecule electronic devices at high bias. Our theoretical analysis is carried out with a minimal model for molecular junctions, with mode softening arising due to quadratic electron-vibration couplings, and by developing a mean-field approach. We discover that the negative sign of the quadr

Chen Qu, Liu Yang, Cen Chen, Minghui Qiu

Conversational search is one of the ultimate goals of information retrieval. Recent research approaches conversational search by simplified settings of response ranking and conversational question answering, where an answer is either selected from a given candidate set or extracted from a given passage. These simplifications neglect the fundamental role of r

S. Yashiro, N. Gopalswamy, S. Akiyama, P. A. Mäkelä

We report on a statistical study of prominence eruptions (PEs) using a catalog of these events routinely imaged by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) in the 304 \r{A} pass band. Using an algorithm developed as part of an LWS project, we have detected PEs in 304 \r{A} synoptic images with 2-min cadence since M

Drew Linsley, Alekh Karkada Ashok, Lakshmi Narasimhan Govindarajan, Rex Liu

Primate vision depends on recurrent processing for reliable perception. A growing body of literature also suggests that recurrent connections improve the learning efficiency and generalization of vision models on classic computer vision challenges. Why then, are current large-scale challenges dominated by feedforward networks? We posit that the effectiveness

Alireza Fali, Tianyi Zhang, Jason Patrick Terry, Ethan Kahn

Single-layer heterostructures exhibit striking quasiparticle properties and many-body interaction effects that hold promise for a range of applications. However, their properties can be altered by intrinsic and extrinsic defects, thus diminishing their applicability. Therefore, it is of paramount importance to identify defects and understand 2D materials' de

Andrii Khrabustovskyi

Let $\Gamma$ be an arbitrary $\mathbb{Z}^n$-periodic metric graph, which does not coincide with a line. We consider the Hamiltonian $\mathcal{H}_\varepsilon$ on $\Gamma$ with the action $-\varepsilon^{-1}{\mathrm{d}^2/\mathrm{d} x^2}$ on its edges; here $\varepsilon>0$ is a small parameter. Let $m\in\mathbb{N}$. We show that under a proper choice of vertex c

Lars Helge Heyen, Stefan Floerchinger

The existing transformation from a relativistic real scalar field to a complex non-relativistic scalar field by Namjoo, Guth, and Kaiser is generalized from Minkowski space to a more general background metric. In that case the transformation is not purely algebraic any more but determined by a differential equation. We apply the generalized transformation to

Kyle R. Myers, Wei Yang Tham, Yian Yin, Nina Cohodes

The COVID-19 pandemic has undoubtedly disrupted the scientific enterprise, but we lack empirical evidence on the nature and magnitude of these disruptions. Here we report the results of a survey of approximately 4,500 Principal Investigators (PIs) at U.S.- and Europe-based research institutions. Distributed in mid-April 2020, the survey solicited information

Xuan Guo, Robert Mullins

It has always been difficult to balance the accuracy and performance of ISSs. RTL simulators or systems such as gem5 are used to execute programs in a cycle-accurate manner but are often prohibitively slow. In contrast, functional simulators such as QEMU can run large benchmarks to completion in a reasonable time yet capture few performance metrics and fail

Z. E. Brubaker, J. S. Harvey, J. R. Badger, R. R. Ullah

We have performed an extensive pressure-dependent structural, spectroscopic, and electrical transport study of LaCrSb$_3$. The ferromagnetic phase (T$_C$ = 120 K at p = 0 GPa) is fully suppressed by p = 26.5 GPa and the Cr-moment decreases steadily with increasing pressure. The unit cell volume decreases smoothly up to p = 55 GPa. We find that the bulk modul