arXiv papers from July 2020

Shivam Barwey, Venkat Raman

A method which casts the chemical source term computation into an artificial neural network (ANN)-inspired form is presented. This approach is well-suited for use on emerging supercomputing platforms that rely on graphical processing units (GPUs). The resulting equations allow for a GPU-friendly matrix-multiplication based source term estimation where the le

Jinghao Sun, Luk Van Baelen, Els Plettinckx, Forrest W. Crawford

Capture-recapture (CRC) surveys are used to estimate the size of a population whose members cannot be enumerated directly. CRC surveys have been used to estimate the number of Covid-19 infections, people who use drugs, sex workers, conflict casualties, and trafficking victims. When $k$ capture samples are obtained, counts of unit captures in subsets of sampl

Jacques Demongeot, Hervé Seligmann

(1) Background: RNA viruses and especially coronaviruses could act inside host cells not only by building their own proteins, but also by perturbing the cell metabolism. We show the possibility of miRNA-like inhibitions by the SARS-CoV-2 concerning for example the hemoglobin and type I interferons syntheses, hence highly perturbing oxygen distribution in vit

Siddhartha Verma, Manhar Dhanak, John Frankenfield

Several places across the world are experiencing a steep surge in COVID-19 infections. Face masks have become increasingly accepted as one of the most effective means for combating the spread of the disease, when used in combination with social-distancing and frequent hand-washing. However, there is an increasing trend of people substituting regular cloth or

Qi Guo, Bruno Remillard, Anatoliy Swishchuk

In this paper, we focus on a new generalization of multivariate general compound Hawkes process (MGCHP), which we referred to as the multivariate general compound point process (MGCPP). Namely, we applied a multivariate point process to model the order flow instead of the Hawkes process. Law of large numbers (LLN) and two functional central limit theorems (F

N. Benjamin Erichson, Dane Taylor, Qixuan Wu, Michael W. Mahoney

The ubiquity of deep neural networks (DNNs), cloud-based training, and transfer learning is giving rise to a new cybersecurity frontier in which unsecure DNNs have `structural malware' (i.e., compromised weights and activation pathways). In particular, DNNs can be designed to have backdoors that allow an adversary to easily and reliably fool an image classif

Neha S. Wadia, Ryan V. Zarcone, Michael R. DeWeese

Considerable progress has recently been made with geometrical approaches to understanding and controlling small out-of-equilibrium systems, but a mathematically rigorous foundation for these methods has been lacking. Towards this end, we develop a perturbative solution to the Fokker-Planck equation for one-dimensional driven Brownian motion in the overdamped

Grigorios P. Zouros, Georgios D. Kolezas, Evangelos Almpanis, Kosmas L. Tsakmakidis

We report that the fundamental three-dimensional (3-D) scattering single-channel limit can be overcome in magneto-optical assisted systems by inducing nondegenerate magnetoplasmonic modes. In addition, we propose a 3-D active (magnetically assisted) forward-superscattering to invisibility switch, functioning at the same operational wavelength. Our structure

Lasse Blaauwbroek, Josef Urban, Herman Geuvers

We present Tactician, a tactic learner and prover for the Coq Proof Assistant. Tactician helps users make tactical proof decisions while they retain control over the general proof strategy. To this end, Tactician learns from previously written tactic scripts and gives users either suggestions about the next tactic to be executed or altogether takes over the

Indrani Bhattacharya, Arun Seetharaman, Wei Shao, Rewa Sood

Magnetic Resonance Imaging (MRI) is widely used for screening and staging prostate cancer. However, many prostate cancers have subtle features which are not easily identifiable on MRI, resulting in missed diagnoses and alarming variability in radiologist interpretation. Machine learning models have been developed in an effort to improve cancer identification

James Stokes, Javier Robledo Moreno, Eftychios A. Pnevmatikakis, Giuseppe Carleo

First-quantized deep neural network techniques are developed for analyzing strongly coupled fermionic systems on the lattice. Using a Slater-Jastrow inspired ansatz which exploits deep residual networks with convolutional residual blocks, we approximately determine the ground state of spinless fermions on a square lattice with nearest-neighbor interactions.

David Collins, Justin Endicott

We consider the issue of validating the relationship between electric fields and optical intensity as proposed by the classical theory of electromagnetism. We describe an interference scenario in which this can be checked using only intensity measurements and without any other information regarding the details of the arrangement of the associated fields. We

Alessio Fiscella

In this paper, we deal with the following double phase problem $$ \left\{\begin{array}{ll} -\mbox{div}\left(|\nabla u|^{p-2}\nabla u+a(x)|\nabla u|^{q-2}\nabla u\right)= \gamma\left(\displaystyle\frac{|u|^{p-2}u}{|x|^p}+a(x)\displaystyle\frac{|u|^{q-2}u}{|x|^q}\right)+f(x,u) & \mbox{in } \Omega,\\ u=0 & \mbox{in } \partial\Omega, \end{array} \right. $$ where

Nathan P. M. Holt, Ralf Rapp

Thermal radiation of photons and dileptons from hadronic matter plays an essential role in understanding electromagnetic emission spectra in high-energy heavy-ion collisions. In particular, baryons and anti-baryons have been found to be strong catalysts for electromagnetic radiation, even at collider energies where the baryon chemical potential is small. Her

Ankit Ramchandani, Chao Fan, Ali Mostafavi

In this paper, we propose a deep learning model to forecast the range of increase in COVID-19 infected cases in future days and we present a novel method to compute equidimensional representations of multivariate time series and multivariate spatial time series data. Using this novel method, the proposed model can both take in a large number of heterogeneous

Alessio Fiscella, Andrea Pinamonti

In this paper, we study two classes of Kirchhoff type problems set on a double phase framework. That is, the functional space where finding solutions coincides with the Musielak-Orlicz-Sobolev space $W^{1,\mathcal H}_0(\Omega)$, with modular function $\mathcal H$ related to the so called double phase operator. Via a variational approach, we provide existence

Shakila Khan Rumi, Kyle K. Qin, Flora D. Salim

A well-crafted police patrol route design is vital in providing community safety and security in the society. Previous works have largely focused on predicting crime events with historical crime data. The usage of large-scale mobility data collected from Location-Based Social Network, or check-ins, and Point of Interests (POI) data for designing an effective

Shashank Sripad, Daniel Korff, Steven C. DeCaluwe, Venkatasubramanian Viswanathan

Electrodeposition and stripping are fundamental electrochemical processes for metals and have gained importance in rechargeable Li-ion batteries due to lithium metal electrodes. The electrode kinetics associated with lithium metal electrodeposition and stripping is crucial in determining performance at fast discharge and charge which is important for electri

I. Filikhin, R. Ya. Kezerashvili, V. M. Suslov, Sh. M. Tsiklauri

The three-body $KK\bar K$ model for the $K(1460)$ resonance is developed on the basis of the Faddeev equations in configuration space. A single-channel approach is using with taking into account the difference of masses of neutral and charged kaons. It is demonstrated that a splitting the mass of the $K(1460)$ resonance takes a place around 1460 MeV accordin

Hu Hu, Sabato Marco Siniscalchi, Yannan Wang, Chin-Hui Lee

In this paper, we propose a domain adaptation framework to address the device mismatch issue in acoustic scene classification leveraging upon neural label embedding (NLE) and relational teacher student learning (RTSL). Taking into account the structural relationships between acoustic scene classes, our proposed framework captures such relationships which are

Mahdieh Nejati Javaremi, Brenna D. Argall

Assistive robotic devices can increase the independence of individuals with motor impairments. However, each person is unique in their level of injury, preferences, and skills, which moreover can change over time. Further, the amount of assistance required can vary throughout the day due to pain or fatigue, or over longer periods due to rehabilitation, debil

Shashank Kanade

Let $L_{l}=L(\mathfrak{sl}_{2l+1},-l-\frac{1}{2})$ be the simple vertex operator algebra based on the affine Lie algebra $\widehat{\mathfrak{sl}}_{2l+1}$ at boundary admissible level $-l-\frac{1}{2}$. We consider a lift $\nu$ of the Dynkin diagram involution of $A_{2l}=\mathfrak{sl}_{2l+1}$ to an involution of $L_{l}$. The $\nu$-twisted $L_l$-modules are $A_

Hu Hu, Sabato Marco Siniscalchi, Yannan Wang, Xue Bai

In this paper, we propose a sub-utterance unit selection framework to remove acoustic segments in audio recordings that carry little information for acoustic scene classification (ASC). Our approach is built upon a universal set of acoustic segment units covering the overall acoustic scene space. First, those units are modeled with acoustic segment models (A

Feiyan Hu, Venkatesh G M, Noel E. O'Connor, Alan F. Smeaton

Advanced Driver-Assistance Systems (ADAS) have been attracting attention from many researchers. Vision-based sensors are the closest way to emulate human driver visual behavior while driving. In this paper, we explore possible ways to use visual attention (saliency) for object detection and tracking. We investigate: 1) How a visual attention map such as a \e

I. Cabrera-Munguia

This paper is dedicated to derive and study binary systems of identical corotating dyonic black holes separated by a massless strut -- two 5-parametric corotating binary black hole models endowed with both electric and magnetic charges-- where the dyonic black holes carrying equal/opposite electromagnetic charges in the first/second model satisfy the extende

Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky

Most recommender systems (RS) research assumes that a user's utility can be maximized independently of the utility of the other agents (e.g., other users, content providers). In realistic settings, this is often not true---the dynamics of an RS ecosystem couple the long-term utility of all agents. In this work, we explore settings in which content providers

David J. Hand, Peter Christen, Nishadi Kirielle

The F-measure, also known as the F1-score, is widely used to assess the performance of classification algorithms. However, some researchers find it lacking in intuitive interpretation, questioning the appropriateness of combining two aspects of performance as conceptually distinct as precision and recall, and also questioning whether the harmonic mean is the

Xurong Chen, Feng-Kun Guo, Craig D. Roberts, Rong Wang

An electron ion collider has been proposed in China (EicC). It is anticipated that the facility would provide polarised electrons, protons and ion beams, in collisions with large centre-of-mass energy. This discussion highlights its potential to address issues that are central to understanding the emergence of mass within the Standard Model, using examples t

Liyiming Ke, Ajinkya Kamat, Jingqiang Wang, Tapomayukh Bhattacharjee

Chopsticks constitute a simple yet versatile tool that humans have used for thousands of years to perform a variety of challenging tasks ranging from food manipulation to surgery. Applying such a simple tool in a diverse repertoire of scenarios requires significant adaptability. Towards developing autonomous manipulators with comparable adaptability to human

Emily Clark, Angelie Vincent, J. Nathan Kutz, Steven L. Brunton

Brackets are an essential component in aircraft manufacture and design, joining parts together, supporting weight, holding wires, and strengthening joints. Hundreds or thousands of unique brackets are used in every aircraft, but manufacturing a large number of distinct brackets is inefficient and expensive. Fortunately, many so-called "different" brackets ar

Rasmus Larsen, Stefan Meinel, Swagato Mukherjee, Peter Petreczky

Based on lattice non-relativistic QCD (NRQCD) studies we present results for Bethe-Salpeter amplitudes for $\Upsilon(1S)$, $\Upsilon(2S)$ and $\Upsilon(3S)$ in vacuum as well as in quark-gluon plasma. Our study is based on 2+1 flavor $48^3 \times 12$ lattices generated using the Highly Improved Staggered Quark (HISQ) action and with a pion mass of $161$ MeV.

T Canavesi

Considering the GAIA data for {$\approx 10^6$} stars around the {barycenter,} we estimate the fractal dimension for different regions in the Milky Way. Then we use those fractal dimensions to calculate the gravitational potential considering the medium as a continuous fractal. Finally, {we use the gravitational potential to infer} the circular velocity {and

Antonio Montalbán, Rodrigo M. Corder, M. Gabriela M. Gomes

We study a SEIR model considered by Gomes et al. \cite{Gomes2020} and Aguas et al. \cite{Aguas2020} where different individuals are assumed to have different levels of susceptibility or exposure to infection. Under this heterogeneity assumption, epidemic growth is effectively suppressed when the percentage of population having acquired immunity surpasses a c

Karen Leung, Nikos Aréchiga, Marco Pavone

This paper presents a technique, named STLCG, to compute the quantitative semantics of Signal Temporal Logic (STL) formulas using computation graphs. STLCG provides a platform which enables the incorporation of logical specifications into robotics problems that benefit from gradient-based solutions. Specifically, STL is a powerful and expressive formal langu

Audrey Richard, Ian Cherabier, Martin R. Oswald, Marc Pollefeys

We present a novel 3D shape completion method that operates directly on unstructured point clouds, thus avoiding resource-intensive data structures like voxel grids. To this end, we introduce KAPLAN, a 3D point descriptor that aggregates local shape information via a series of 2D convolutions. The key idea is to project the points in a local neighborhood ont

Bryan Donyanavard, Amir M. Rahmani, Axel Jantsch, Onur Mutlu

Runtime resource management for many-core systems is increasingly complex. The complexity can be due to diverse workload characteristics with conflicting demands, or limited shared resources such as memory bandwidth and power. Resource management strategies for many-core systems must distribute shared resource(s) appropriately across workloads, while coordin

Edgar Knobloch, Arik Yochelis

An activator-inhibitor-substrate model of side-branching used in the context of pulmonary vascular and lung development is considered on the supposition that spatially localized concentrations of the activator trigger local side-branching. The model consists of four coupled reaction-diffusion equations and its steady localized solutions therefore obey an eig

Ezra Miller

Over any partially ordered abelian group whose positive cone is closed in an appropriate sense and has finitely many faces, modules that satisfy a weak finiteness condition admit finite primary decompositions. This conclusion rests on the introduction of basic notions in the relevant generality, such as closedness of partially ordered abelian groups, faces a

Kourosh Sartipi, Tien Do, Tong Ke, Khiem Vuong

This paper addresses the problem of learning to complete a scene's depth from sparse depth points and images of indoor scenes. Specifically, we study the case in which the sparse depth is computed from a visual-inertial simultaneous localization and mapping (VI-SLAM) system. The resulting point cloud has low density, it is noisy, and has non-uniform spatial

Ezra Miller

Interpreting the syzygy theorem for tame modules over posets in the setting of derived categories of subanalytically constructible sheaves proves two conjectures due to Kashiwara and Schapira concerning the existence of stratifications of real vector spaces that play well with sheaves having microsupport in a given cone or, equivalently, sheaves in the corre

Olav Nygaard, José Rodríguez

Let $X$ be a Banach space, $\Sigma$ be a $\sigma$-algebra, and $m:\Sigma\to X$ be a (countably additive) vector measure. It is a well known consequence of the Davis-Figiel-Johnson-Pelcz\'{y}nski factorization procedure that there exist a reflexive Banach space $Y$, a vector measure $\tilde{m}:\Sigma \to Y$ and an injective operator $J:Y \to X$ such that $m$

Kai-Mei C. Fu, Geoffrey Z. Iwata, Arne Wickenbrock, Dmitry Budker

State-of-the-art magnetic field measurements performed in shielded environments with carefully controlled conditions rarely reflect the realities of those applications envisioned in the introductions of peer-reviewed publications. Nevertheless, significant advances in magnetometer sensitivity have been accompanied by serious attempts to bring these magnetome

E. E. Giorgi, G. R. Solivella, A. Cruzado, R. A. Vazquez

Embedded clusters are groups of stars which have not dispersed yet the residual of the parental cloud where they were born so getting precise distances and properties of these groups turns out to be an essential task. We present results for five embedded clusters: [DBS2003]5, [DBS2003]60, [DBS2003]98, [DBS2003]116 and [DBS2003]117. Results come from a combin

Gordon Slade

We use the lace expansion to study the long-distance decay of the two-point function of weakly self-avoiding walk on the integer lattice $\mathbb{Z}^d$ in dimensions $d>4$, in the vicinity of the critical point, and prove an upper bound $|x|^{-(d-2)}\exp[-c|x|/\xi]$, where the correlation length $\xi$ has a square root divergence at the critical point. As an

Andrea Schirato, Margherita Maiuri, Andrea Toma, Silvio Fugattini

Ultrafast nanophotonics is an emerging research field aimed at the development of nanodevices capable of light modulation with unprecedented speed. A promising approach exploits the optical nonlinearity of nanostructured materials (either metallic or dielectric) to modulate their effective permittivity via interaction with intense ultrashort laser pulses. Wh

Minghan Li, Xialei Liu, Joost van de Weijer, Bogdan Raducanu

Active learning emerged as an alternative to alleviate the effort to label huge amount of data for data hungry applications (such as image/video indexing and retrieval, autonomous driving, etc.). The goal of active learning is to automatically select a number of unlabeled samples for annotation (according to a budget), based on an acquisition function, which

Matheus Nunes, Gisele L. Pappa

Performing analytical tasks over graph data has become increasingly interesting due to the ubiquity and large availability of relational information. However, unlike images or sentences, there is no notion of sequence in networks. Nodes (and edges) follow no absolute order, and it is hard for traditional machine learning (ML) algorithms to recognize a patter

Jacinto Davila

This is an attempt to formalize the conditions of possibility for free, libre, open access to scientific knowledge within a game. The challenge is to enunciate the terms under which agents participating in the Grand conversation of science would be willing to open share, exchange, negotiate or surrender their contributions, considering their corresponding in

Paul Z. Hanakata, Ekin D. Cubuk, David K. Campbell, Harold S. Park

Machine learning (ML) methods have recently been used as forward solvers to predict the mechanical properties of composite materials. Here, we use a supervised-autoencoder (sAE) to perform inverse design of graphene kirigami, where predicting the ultimate stress or strain under tensile loading is known to be difficult due to nonlinear effects arising from th

Max Kanovich, Stepan Kuznetsov, Andre Scedrov

We give a proof-theoretic and algorithmic complexity analysis for systems introduced by Morrill to serve as the core of the CatLog categorial grammar parser. We consider two recent versions of Morrill's calculi, and focus on their fragments including multiplicative (Lambek) connectives, additive conjunction and disjunction, brackets and bracket modalities, a

Ashot Gevorkyan

The article formulates the classical three-body problem in conformal-Euclidean space (Riemannian manifold), and its equivalence to the Newton three-body problem is mathematically rigorously proved. It is shown that a curved space with a local coordinate system allows us to detect new hidden symmetries of the internal motion of a dynamical system, which allow

Md Rafiqul Islam Rabin, Nghi D. Q. Bui, Ke Wang, Yijun Yu

With the prevalence of publicly available source code repositories to train deep neural network models, neural program models can do well in source code analysis tasks such as predicting method names in given programs that cannot be easily done by traditional program analysis techniques. Although such neural program models have been tested on various existin

Joonas Ilmavirta

These are lecture notes for the course "MATS4120 Geometry of geodesics" given at the University of Jyv\"askyl\"a in Spring 2020. Basic differential geometry or Riemannian geometry is useful background but is not strictly necessary. Exercise problems are included, and problems marked important should be solved as you read to ensure that you are able to follow

Jonathan Vincent, Mathieu Labbé, Jean-Samuel Lauzon, François Grondin

In dynamic environments, performance of visual SLAM techniques can be impaired by visual features taken from moving objects. One solution is to identify those objects so that their visual features can be removed for localization and mapping. This paper presents a simple and fast pipeline that uses deep neural networks, extended Kalman filters and visual SLAM

Rui Chen, Jinhua Cao, Stephen Gee, Yin Liu

Two-dimensional (2D) layered materials hosting dislocations have attracted considerable research attention in recent years. In particular, screw dislocations can result in a spiral topology and an interlayer twist in the layered materials, significantly impacting the stacking order and symmetry of the layers. Moreover, the dislocations with large strain and

Max Kanovich, Stepan Kuznetsov, Andre Scedrov

We investigate language interpretations of two extensions of the Lambek calculus: with additive conjunction and disjunction and with additive conjunction and the unit constant. For extensions with additive connectives, we show that conjunction and disjunction behave differently. Adding both of them leads to incompleteness due to the distributivity law. We sh

Juan Martínez-Sykora, Mikolaj Szydlarski, Viggo H. Hansteen, Bart De Pontieu

The solar atmosphere is composed of many species which are populated at different ionization and excitation levels. The upper chromosphere, transition region, and corona are nearly collisionless. Consequently, slippage between, for instance, ions and neutral particles, or interactions between separate species, may play important roles. We have developed a 3D

L. A. Pastur, V. V. Slavin, A. V. Yanovsky

Spin valves based on materials in which the spin-flip is suppressed by the spatial separation of charge carriers, while maintaining electric neutrality in the valve volume, are considered. The possibility of using these valves as electric batteries is discussed. It is shown that if the potential difference across the valve is controlled, incommensurability e

Xinrui Wang, Karen Leung, Marco Pavone

Within a robot autonomy stack, the planner and controller are typically designed separately, and serve different purposes. As such, there is often a diffusion of responsibilities when it comes to ensuring safety for the robot. We propose that a planner and controller should share the same interpretation of safety but apply this knowledge in a different yet c

Vasily A. Dolgushev, Khanh Q. Le, Aidan A. Lorenz

Let $B_4$ (resp. $PB_4$) be the braid group (resp. the pure braid group) on 4 strands and $NFI_{PB_4}(B_4)$ be the poset whose objects are finite index normal subgroups of $B_4$ that are contained in $PB_4$. In this paper, we introduce GT-shadows which may be thought of as "approximations" to elements of the profinite version $\widehat{GT}$ of the Grothendie

S. L. Todaro, V. B. Verma, K. C. McCormick, D. T. C. Allcock

We report high-fidelity state readout of a trapped ion qubit using a trap-integrated photon detector. We determine the hyperfine qubit state of a single $^9$Be$^+$ ion held in a surface-electrode rf ion trap by counting state-dependent ion fluorescence photons with a superconducting nanowire single-photon detector (SNSPD) fabricated into the trap structure.

S. M. Caballero-Nieves, D. R. Gies, E. K. Baines, A. H. Bouchez

We present results of a high angular resolution survey of massive OB stars in the Cygnus OB2 association that we conducted with the NIRI camera and ALTAIR adaptive optics system of the Gemini North telescope. We observed 74 O- and early B-type stars in Cyg OB2 in the $JHK$ infrared bands in order to detect binary and multiple companions. The observations are

Ezra Miller

Homological algebra of modules over posets is developed, as closely parallel as possible to that of finitely generated modules over noetherian commutative rings, in the direction of finite presentations and resolutions. Centrally at issue is how to define finiteness to replace the noetherian hypothesis which fails. The tameness condition introduced for this

Marie Nguyen, Nathan Serafin, James C. Hoe

FPGA designers have traditionally shared a similar design methodology with ASIC designers. Most notably, at design time, FPGA designers commit to a fixed allocation of logic resources to modules in a design. At runtime, some of the occupied resources could be left idle or under-utilized due to hard-to-avoid sources of inefficiencies (e.g., operation dependen

Omar Pedraza, L. A. López, R. Arceo, I. Cabrera-Munguia

Basing on the ideas used by Kiselev, we study the Hayward black hole surrounded by quintessence. By setting for the quintessence state parameter at the special case of $\omega=-\frac{2}{3}$, using the metric of the black hole surrounded by quintessence and the definition of the effective potential, we analyzed in detail the null geodesics for different energ

Joseph Cecil, Neelav Dutta, Christopher Manon, Benjamin Riley

An ideal $I$ is said to be "well-poised" if all of the initial ideals obtained from points in the tropical variety $Trop(I)$ are prime. This condition was first defined by Nathan Ilten and the third author. We classify all well-poised hypersurfaces over an algebraically closed field. We also study the tropical varieties and associated Newton-Okounkov bodies

Andrey Lazarev, Yunhe Sheng, Rong Tang

We describe $L_\infty$-algebras governing homotopy relative Rota-Baxter Lie algebras and triangular $L_\infty$-bialgebras, and establish a map between them. Our formulas are based on a functorial approach to Voronov's higher derived brackets construction which is of independent interest.

Alireza Karduni, Doug Markant, Ryan Wesslen, Wenwen Dou

Understanding correlation judgement is important to designing effective visualizations of bivariate data. Prior work on correlation perception has not considered how factors including prior beliefs and uncertainty representation impact such judgements. The present work focuses on the impact of uncertainty communication when judging bivariate visualizations.

S. Sharma, A. E. Kovalev, D. J. Rebar, D. Mann

Using the experimental capability of the novel X-ray diffraction instrument available at the 25 Tesla Florida Split Coil Magnet at the NHMFL, Tallahassee we present an extensive investigation on the magnetostriction of polycrystalline AlFe2B2. The magnetostriction was measured near the ferromagnetic transition temperature (Curie temperature TC = 280 K, deter

Sergey Lototsky, Apoorva Shah

The objective of the paper is to characterize the Gaussian free field as a stationary solution of the heat equation with additive space-time white noise. In the case of whole space, the investigation leads to other types of Gaussian fields, as well as interesting phenomena in dimensions one and two.

Randal E. Bryant, Randy H. Katz, Chase Hensel, Erwin P. Gianchandani

Our nation's infrastructure for generating, transmitting, and distributing electricity - "The Grid" - is a relic based in many respects on century-old technology. It consists of expensive, centralized generation via large plants, and a massive transmission and distribution system. It strives to deliver high-quality power to all subscribers simultaneously - n

Akhil Goel, Akshay Agarwal, Mayank Vatsa, Richa Singh

Blockchain has emerged as a leading technology that ensures security in a distributed framework. Recently, it has been shown that blockchain can be used to convert traditional blocks of any deep learning models into secure systems. In this research, we model a trained biometric recognition system in an architecture which leverages the blockchain technology t

Jacob Adamczyk

This report discusses the application of neural networks (NNs) as small segments of the brain. The networks representing the biological connectome are altered both spatially and temporally. The degradation techniques applied here are "weight degradation", "weight scrambling", and variable activation function. These methods aim to shine light on the study of

Nadejda Drenska, Jeff Calder

We study the problem of prediction of binary sequences with expert advice in the online setting, which is a classic example of online machine learning. We interpret the binary sequence as the price history of a stock, and view the predictor as an investor, which converts the problem into a stock prediction problem. In this framework, an investor, who predict

Ahmad Ajalloeian, Sebastian U. Stich

We analyze the complexity of biased stochastic gradient methods (SGD), where individual updates are corrupted by deterministic, i.e. biased error terms. We derive convergence results for smooth (non-convex) functions and give improved rates under the Polyak-Lojasiewicz condition. We quantify how the magnitude of the bias impacts the attainable accuracy and t

Florin P. Boca, Maria Siskaki

This paper investigates the periodic points of the Gauss type shifts associated to the even continued fraction (Schweiger) and to the backward continued fraction (R\'enyi). We show that they coincide exactly with two sets of quadratic irrationals that we call $E$-reduced, and respectively $B$-reduced. We prove that these numbers are equidistributed with resp

Qi Yang, Khizar Qureshi, Tauhid Zaman

Online social networks create echo-chambers where people are infrequently exposed to opposing opinions. Even if such exposure occurs, the persuasive effect may be minimal or nonexistent. Recent studies have shown that exposure to opposing opinions causes a backfire effect, where people become more steadfast in their original beliefs. We conducted a longitudi

Guojun Gan, Emiliano A. Valdez

The healthcare sector in the U.S. is complex and is also a large sector that generates about 20% of the country's gross domestic product. Healthcare analytics has been used by researchers and practitioners to better understand the industry. In this paper, we examine and demonstrate the use of Beta regression models to study the utilization of brand name drug

Bingyin Zhao, Yingjie Lao

Poisoning attacks on machine learning systems compromise the model performance by deliberately injecting malicious samples in the training dataset to influence the training process. Prior works focus on either availability attacks (i.e., lowering the overall model accuracy) or integrity attacks (i.e., enabling specific instance-based backdoor). In this paper

Pablo D. Bergamasco, Gabriel G. Carlo, Alejandro M. F. Rivas

The out-of-time order correlator (OTOC) has recently become relevant in different areas where it has been linked to scrambling of quantum information and entanglement. It has also been proposed as a good indicator of quantum complexity. In this sense, the OTOC-RE theorem relates the OTOCs summed over a complete base of operators to the second Renyi entropy.

Eric Horvitz, Tom Mitchell

A confluence of advances in the computer and mathematical sciences has unleashed unprecedented capabilities for enabling true evidence-based decision making. These capabilities are making possible the large-scale capture of data and the transformation of that data into insights and recommendations in support of decisions about challenging problems in science

Lily Li, Aleksandar Nikolov

Many problems in computer science and applied mathematics require rounding a vector $\mathbf{w}$ of fractional values lying in the interval $[0,1]$ to a binary vector $\mathbf{x}$ so that, for a given matrix $\mathbf{A}$, $\mathbf{A}\mathbf{x}$ is as close to $\mathbf{A}\mathbf{w}$ as possible. For example, this problem arises in LP rounding algorithms used

Jane Ivy Coons, Joseph Cummings, Benjamin Hollering, Aida Maraj

Marginal polytopes are important geometric objects that arise in statistics as the polytopes underlying hierarchical log-linear models. These polytopes can be used to answer geometric questions about these models, such as determining the existence of maximum likelihood estimates or the normality of the associated semigroup. Cut polytopes of graphs have been

William G. Newton, Gabriel Crocombe

We present an inference of the nuclear symmetry energy magnitude $J$, the slope $L$ and the curvature $K_{\rm sym}$ by combining neutron skin data on Ca, Pb and Sn isotopes and our best theoretical information about pure neutron matter (PNM). A Bayesian framework is used to consistently incorporate prior knowledge of the PNM equation of state from chiral eff

Gavin Hester, T. N. DeLazzer, D. R. Yahne, C. L. Sarkis

Ising-like spin-1/2 magnetic materials are of interest for their ready connection to theory, particularly in the context of quantum critical behavior. In this work we report detailed studies of the magnetic properties of a member of the rare earth pyrosilicate family, D-Er$_{2}$Si$_{2}$O$_{7}$, which is known to display a highly anisotropic Ising-like g-tens

Ashot Gevorkyan

The evolution of the joint system (JS) - ``quantum system (QS)+thermal bath (TB)" is considered in the framework of a complex probabilistic processes that satisfies the stochastic differential equation of the Langevin-Schr\"{o}dinger type. Two linearly coupled oscillators that randomly interact with the environment and with each other are selected as QS. In

Antonio M. García-García, Jie Ping Zheng, Vaios Ziogas

We study the thermodynamic properties of a two-site coupled complex Sachdev-Ye-Kitaev (SYK) model in the large $N$ limit by solving the saddle-point Schwinger-Dyson (SD) equations. We find that its phase diagram is richer than in the Majorana case. In the grand canonical ensemble, we identify a region of small chemical potential, and weak coupling between th

Ryosuke Itoh, Yousuke Utsumi, Yoshiyuki Inoue, Kouji Ohta

Utilizing the latest and the most sensitive radio and optical catalogs, we completed a new blazar candidate catalog, Blazar Radio and Optical Survey (BROS), which includes 88,211 sources located at declination $\delta > -40^{\circ}$ and outside the galactic plane ($|b| > 10^{\circ}$). We list compact flat-spectrum radio sources of $\alpha > -0.6$ ($\alpha$ i

Sabina Tomkins, Peng Liao, Predrag Klasnja, Susan Murphy

In mobile health (mHealth) smart devices deliver behavioral treatments repeatedly over time to a user with the goal of helping the user adopt and maintain healthy behaviors. Reinforcement learning appears ideal for learning how to optimally make these sequential treatment decisions. However, significant challenges must be overcome before reinforcement learni

Canavesi Tobias, Hurtado Santiago

Several two-dimensional studies in spiral galaxies show that HII star formation regions have a fractal distribution, with a fractal dimension of approximately 2.3. In this work, the fractal dimension is calculated through the box-counting method implemented in an R code. The innovation of the work lies in calculating the fractal dimension directly in 3 dimen

Tiziano Fagni, Fabrizio Falchi, Margherita Gambini, Antonio Martella

The recent advances in language modeling significantly improved the generative capabilities of deep neural models: in 2019 OpenAI released GPT-2, a pre-trained language model that can autonomously generate coherent, non-trivial and human-like text samples. Since then, ever more powerful text generative models have been developed. Adversaries can exploit thes

R. M. Albuquerque, S. Narison, A. Rabemananjara, D. Rabetiarivony

Alerted by the recent LHCb discovery of exotic hadrons in the range (6.2 -- 6.9) GeV, we present new results for the doubly-hidden scalar heavy $(\bar QQ) (Q\bar Q)$ charm and beauty molecules using the inverse Laplace transform sum rule (LSR) within stability criteria and including the Next-to-Leading Order (NLO) factorized perturbative and $\langle G^3\ran

M. Affolter, K. A. Gilmore, J. E. Jordan, J. J. Bollinger

Trapped ions are sensitive detectors of weak forces and electric fields that excite ion motion. Here measurements of the center-of-mass motion of a trapped-ion crystal that are phase-coherent with an applied weak external force are reported. These experiments are conducted far from the trap motional frequency on a two-dimensional trapped-ion crystal of appro

Sathyan Sandeep, Théo Thréard, Elton De Lima Savi, Nikolay Chigarev

Time-domain Brillouin scattering uses ultrashort laser pulses to generate coherent acoustic pulses of picoseconds duration in a solid sample and to follow their propagation in order to image material inhomogeneities with sub-optical depth resolution. The width of the acoustic pulse limits the spatial resolution of the technique along the direction of the pul

Vincenzo Denisi, Alessandro Papa, Marco Rossi

We speculate on Dyson series for the $S$-matrix when the interaction depends on derivatives of the fields. We stick on two particular examples: the scalar electrodynamics and the renormalised $\phi ^4$ theory. We eventually give evidence that Lorentz invariance is satisfied and that usual Feynman rules can be applied to the interaction Lagrangian.

Elisa Alòs, Maria Elvira Mancino, Raúl Merino, Simona Sanfelici

We provide a probabilistic SIRD model for the COVID-19 pandemic in Italy, where we allow the infection, recovery and death rates to be random. In particular, the underlying random factor is driven by a fractional Brownian motion. Our model is simple and needs only some few parameters to be calibrated.

Cristina Zuheros, Eugenio Martínez-Cámara, Enrique Herrera-Viedma, Francisco Herrera

Decision making models are constrained by taking the expert evaluations with pre-defined numerical or linguistic terms. We claim that the use of sentiment analysis will allow decision making models to consider expert evaluations in natural language. Accordingly, we propose the Sentiment Analysis based Multi-person Multi-criteria Decision Making (SA-MpMcDM) m

Joshua P. Ebenezer, Zaixi Shang, Yongjun Wu, Hai Wei

We propose a new prototype model for no-reference video quality assessment (VQA) based on the natural statistics of space-time chips of videos. Space-time chips (ST-chips) are a new, quality-aware feature space which we define as space-time localized cuts of video data in directions that are determined by the local motion flow. We use parametrized distributi

Ben Adlam, Jasper Snoek, Samuel L. Smith

Recent work has observed that one can outperform exact inference in Bayesian neural networks by tuning the "temperature" of the posterior on a validation set (the "cold posterior" effect). To help interpret this phenomenon, we argue that commonly used priors in Bayesian neural networks can significantly overestimate the aleatoric uncertainty in the labels on

Svetozar Zarko Valtchev, Jianhong Wu

Expansion and reduction of a neural network's width has well known properties in terms of the entropy of the propagating information. When carefully stacked on top of one another, an encoder network and a decoder network produce an autoencoder, often used in compression. Using this architecture, we develop an efficient method of encoding and decoding 4D Ligh