December 2020 arXiv papers — page 134

Pascal Auscher, Moritz Egert

For elliptic systems with block structure in the upper half-space and t-independent coefficients, we settle the study of boundary value problems by proving compatible well-posedness of Dirichlet, regularity and Neumann problems in optimal ranges of exponents. Prior to this work, only the two-dimensional situation was fully understood. In higher dimensions, p

Shoaib Akhtar

Phase Transition is associated with a drastic change in some observable (ordered parameter) of the system when the controlled parameter is tuned smoothly. Lee-Yang theory of phase transition is discussed which is related to the accumulation of singularities of free energy, equivalently complex roots of Grand Partition function (Partition function) at points

Yiou Lin, Hang Lei, Yu Deng

In early 2020, the Corona Virus Disease 2019 (COVID-19) pandemic swept the world.In China, COVID-19 has caused severe consequences. Moreover, online rumors during the COVID-19 pandemic increased people's panic about public health and social stability. At present, understanding and curbing the spread of online rumors is an urgent task. Therefore, we analy

Annika Betken, Herold Dehling, Nüßgen, Alexander Schnurr

In this article, we show that the recently introduced ordinal pattern dependence fits into the axiomatic framework of general multivariate dependence measures, i.e., measures of dependence between two multivariate random objects. Furthermore, we consider multivariate generalizations of established univariate dependence measures like Kendall's $τ$, Spearm

Marc Arnaudon, Koléhè Coulibaly-Pasquier, Laurent Miclo

The purpose of this paper is to construct a Brownian motion $X := (X_t)_{t\geq 0}$ taking values in a Riemannian manifold $M$, together with a compact valued process $D:= (D_t)_{t\geq 0}$ such that, at least for small enough ${\mathscr F}^D$-stopping time $\tau> 0$ and conditioned by ${\mathscr F}_\tau^D$, the law of $X_\tau$ is the normalized Lebesgue measu

Yuye Feng, Qingbiao Wu

This paper introduces and analyzes a preconditioned modified of the Hermitian and skew-Hermitian splitting (PMHSS). The large sparse continuous Sylvester equations are solved by PMHSS iterative algorithm based on nonHermitian, complex, positive definite/semidefinite, and symmetric matrices. We prove that the PMHSS is converged under suitable conditions. In a

S. L. Cherkas, V. L. Kalashnikov

Effects of the quantum gravity under Minkowski space-time background are considered. It is shown that despite the absence of the complete theory of quantum gravity, some concrete predictions could be made for the influence of the quantum gravitational fluctuations on the propagation of the massive particles. We demonstrate that although the gravitational pot

Erol Vatansever, Zeynep Demir Vatansever, Panagiotis E. Theodorakis, Nikolaos G. Fytas

Using high-precision Monte-Carlo simulations based on a parallel version of the Wang-Landau algorithm and finite-size scaling techniques we study the effect of quenched disorder in the crystal-field coupling of the Blume-Capel model on the square lattice. We mainly focus on the part of the phase diagram where the pure model undergoes a continuous transition,

Xiangyi Cui, Zhou Wang, Yonglin Ju, Xiuli Wang

An online cryogenic distillation system for the removal of krypton and radon from xenon was designed and constructed for PandaX-4T, a highly sensitive dark matter detection experiment. The krypton content in a commercial xenon product is expected to be reduced by 7 orders of magnitude with 99% xenon collection efficiency at a flow rate of 10 kg/h by design.

Marthe Bonamy, Nicolas Bousquet, Louis Esperet, Carla Groenland

The asymptotic dimension is an invariant of metric spaces introduced by Gromov in the context of geometric group theory. In this paper, we study the asymptotic dimension of metric spaces generated by graphs and their shortest path metric and show their applications to some continuous spaces. The asymptotic dimension of such graph metrics can be seen as a lar

Danylo Lykov, Roman Schutski, Alexey Galda, Valerii Vinokur

In this work, we present a new large-scale quantum circuit simulator. It is based on the tensor network contraction technique to represent quantum circuits. We propose a novel parallelization algorithm based on \stepslice . In this paper, we push the requirement on the size of a quantum computer that will be needed to demonstrate the advantage of quantum com

Jeremy Levick, Mizanur Rahaman

We initiate a study of linear maps on $M_n(\mathbb{C})$ that have the property that they factor through a tracial von Neumann algebra $(\mathcal{A,τ})$ via operators $Z\in M_n(\mathcal{A})$ whose entries consist of positive elements from the von-Neumann algebra. These maps often arise in the context of non-local games, especially in the synchronous case. We

Thomas H. Geisser, Baptiste Morin

Let $\mathcal X$ be a regular scheme, flat and proper over the ring of integers of a $p$-adic field, with generic fiber $X$ and special fiber $\mathcal X_s$. We study the left kernel $Br(\mathcal X)$ of the Brauer-Manin pairing $Br(X)\times CH_0(X)\to \mathbb Q/\mathbb Z$. Our main result is that the kernel of the reduction map $Br(\mathcal X)\to Br(\mathcal

Haixiang Zhang, Zeyu Zheng, Javad Lavaei

We develop and analyze a set of new sequential simulation-optimization algorithms for large-scale multi-dimensional discrete optimization via simulation problems with a convexity structure. The "large-scale" notion refers to that the decision variable has a large number of values to choose from on each dimension. The proposed algorithms are targeted to ident

Matthew J. Holland

In this work, we study a new class of risks defined in terms of the location and deviation of the loss distribution, generalizing far beyond classical mean-variance risk functions. The class is easily implemented as a wrapper around any smooth loss, it admits finite-sample stationarity guarantees for stochastic gradient methods, it is straightforward to inte

Mohamadreza Ahmadi, Ugo Rosolia, Michel D. Ingham, Richard M. Murray

We consider the problem of designing policies for Markov decision processes (MDPs) with dynamic coherent risk objectives and constraints. We begin by formulating the problem in a Lagrangian framework. Under the assumption that the risk objectives and constraints can be represented by a Markov risk transition mapping, we propose an optimization-based method t

Na Kang, Wenhui Wan, Yanfeng Ge, Yong Liu

In this paper, we systematically investigated the structural and magnetic properties of CrTe by combining particle swarm optimization algorithm and first-principles calculations. With the electronic correlation effect considered, we predicted the ground-state structure of CrTe to be NiAs-type (space group P63/mmc) structure at ambient pressure, consistent wi

Simon C. -C. Ho, Tomotsugu Goto, Nagisa Oi, Seong Jin Kim

The $AKARI$ space infrared telescope has performed near- to mid-infrared (MIR) observations on the North Ecliptic Pole Wide (NEPW) field (5.4 deg$^2$) for about one year. $AKARI$ took advantage of its continuous nine photometric bands, compared with NASA's $Spitzer$ and WISE space telescopes, which had only four filters with a wide gap in the MIR. The $A

Junyu Luo, Zifei Zheng, Hanzhong Ye, Muchao Ye

Patients with low health literacy usually have difficulty understanding medical jargon and the complex structure of professional medical language. Although some studies are proposed to automatically translate expert language into layperson-understandable language, only a few of them focus on both accuracy and readability aspects simultaneously in the clinica

Abdul Zalloum

In \cite{QR19}, Qing, Rafi and Tiozzo introduced the sublinearly contracting boundary for CAT(0) spaces. Every point of this boundary is uniquely represented by a sublinearly contracting geodesic ray: a geodesic ray $b$ where every disjoint ball projects to a subset whose diameter is bounded by a sublinear function in terms of the ball's distance to the orig

Anh Nguyen, Quang Tran

Autonomous navigation is a long-standing field of robotics research, which provides an essential capability for mobile robots to execute a series of tasks on the same environments performed by human everyday. In this chapter, we present a set of algorithms to train and deploy deep networks for autonomous navigation of mobile robots using the Robot Operation

Philipp Scharpf, Moritz Schubotz, Andre Greiner-Petter, Malte Ostendorff

The zbMATH database contains more than 4 million bibliographic entries. We aim to provide easy access to these entries. Therefore, we maintain different index structures, including a formula index. To optimize the findability of the entries in our database, we continuously investigate new approaches to satisfy the information needs of our users. We believe t

Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett

We study the training of finite-width two-layer smoothed ReLU networks for binary classification using the logistic loss. We show that gradient descent drives the training loss to zero if the initial loss is small enough. When the data satisfies certain cluster and separation conditions and the network is wide enough, we show that one step of gradient descen

Cheng Peng, Haofu Liao, Gina Wong, Jiebo Luo

A radiograph visualizes the internal anatomy of a patient through the use of X-ray, which projects 3D information onto a 2D plane. Hence, radiograph analysis naturally requires physicians to relate the prior about 3D human anatomy to 2D radiographs. Synthesizing novel radiographic views in a small range can assist physicians in interpreting anatomy more reli

Houwang Tu, Yongxian Wang, Xian Ma, Xunjiang Zhu

Solving an acoustic wave equation using a parabolic approximation is a popular approach for many existing ocean acoustic models. Commonly used parabolic equation (PE) model programs, such as the range-dependent acoustic model (RAM), are discretized by the finite difference method (FDM). Considering the idea and theory of the wide-angle rational approximation

Hiroshi Shimahara

We examine the Fermi-surface effect called the nesting effect for the FFLO state in strongly Pauli-limited Q2D superconductors, focusing on the effect of 3D factors, such as interlayer electron transfer, interlayer pairing, and off-plane magnetic fields including those perpendicular to the most conductive layers. We examine the systems with a large Maki para

Hemian Yi, Zengle Huang, Wujun Shi, Lujin Min

(TaSe4)2I, a quasi-one-dimensional (1D) crystal, shows a characteristic temperature-driven metal-insulator phase transition. Above the charge density wave (CDW) temperature Tc, (TaSe4)2I has been predicted to harbor a Weyl semimetal phase. Below Tc, it becomes an axion insulator. Here, we performed angle-resolved photoemission spectroscopy (ARPES) measuremen

Anton Izosimov

Consider the map $S$ which sends a planar polygon $P$ to a new polygon $S(P)$ whose vertices are the intersection points of second nearest sides of $P$. This map is the inverse of the famous pentagram map. In this paper we investigate the dynamics of the map $S$. Namely, we address the question of whether a convex polygon stays convex under iterations of $S$

Benjamin A. Burton, Alexander He

A key result in computational 3-manifold topology is that any two triangulations of the same 3-manifold are connected by a finite sequence of bistellar flips, also known as Pachner moves. One limitation of this result is that little is known about the structure of this sequence; knowing more about the structure could help both proofs and algorithms. Motivate

Daniel Calderón

We prove that it is relatively consistent with $\mathrm{ZFC}$ that every strong measure zero subset of the real line is meager-additive while there are uncountable strong measure zero sets (i.e., Borel's conjecture fails). This answers a long-standing question due to Bartoszyński and Judah.

Kasumi Okazaki, Junsik Han, Makoto Tsubota

We numerically study the dynamics of Faraday waves in a pancake-shaped Bose--Einstein condensate (BEC) subject to periodic modulation of the interaction. After the modulation starts, Faraday waves appear and, thereafter, the BEC enters the "nonlinear regime", in which several collective modes are excited. By maintaining the modulation without dissipa

Philip Marx

A fundamental question underlying the literature on partial identification is: what can we learn about parameters that are relevant for policy but not necessarily point-identified by the exogenous variation we observe? This paper provides an answer in terms of sharp, analytic characterizations and bounds for an important class of policy-relevant treatment ef

Saugata Purkayastha, Sukannya Purkayastha

In this work, we study an optimizer, Grad-Avg to optimize error functions. We establish the convergence of the sequence of iterates of Grad-Avg mathematically to a minimizer (under boundedness assumption). We apply Grad-Avg along with some of the popular optimizers on regression as well as classification tasks. In regression tasks, it is observed that the be

Dongfen Bian, Xueke Pu

In this paper, we consider the stability threshold for the shear flows of the Boussinesq system in a domain $\mathbb{T} \times \mathbb{R}$. The main goal is to prove the nonlinear stability of the shear flow $(U^S,\Theta^S)=((e^{\nu t\partial_{yy}}U(y),0)^{\top},\alpha y)$ with $U(y)$ close to $y$ and $\alpha\geq0$. We separate two cases: one is $\alpha\geq

Hien Duy Nguyen, TrungTin Nguyen, Faicel Chamroukhi, Geoffrey McLachlan

Mixture of experts (MoE) models are widely applied for conditional probability density estimation problems. We demonstrate the richness of the class of MoE models by proving denseness results in Lebesgue spaces, when inputs and outputs variables are both compactly supported. We further prove an almost uniform convergence result when the input is univariate.

Yunhan Huang, Zehui Xiong, Quanyan Zhu

This work establishes a game-theoretic framework to study cross-layer coordinated attacks on cyber-physical systems (CPSs). The attacker can interfere with the physical process and launch jamming attacks on the communication channels simultaneously. At the same time, the defender can dodge the jamming by dispensing with observations. The generic framework ca

Ke Yan, Jinzheng Cai, Dakai Jin, Shun Miao

Radiological images such as computed tomography (CT) and X-rays render anatomy with intrinsic structures. Being able to reliably locate the same anatomical structure across varying images is a fundamental task in medical image analysis. In principle it is possible to use landmark detection or semantic segmentation for this task, but to work well these requir

Huali Zhang, Kun Zhao

Cauchy problem for 3D incompressible Hall-magnetohydrodynamics (Hall-MHD) system with fractional Laplacians is studied. First, global well-posedness of small-energy solutions with general initial data in $H^s$, $s>\frac{5}{2}$, is proved. Second, a special class of large-energy initial data is constructed, with which the Cauchy problem is globally well-posed

Zhong-Yi Li, Ju-Jun Xie

Based on the recently measurements of the $e^{+} e^{-} \to Σ^{+} \barΣ^{-}$ and $e^{+} e^{-} \to Σ^{-} \barΣ^{+}$ processes, the electromagnetic form factors of the hyperon $Σ^+$ and $Σ^-$ in the timelike region are investigate by using the vector meson dominance model. We have included the contributions from the $ρ$, $ω$ and $ϕ$ mesons. The model parameters

Armin Khamoshi, Guo P. Chen, Thomas M. Henderson, Gustavo E. Scuseria

Single-reference methods such as Hartree-Fock-based coupled cluster theory are well known for their accuracy and efficiency for weakly correlated systems. For strongly correlated systems, more sophisticated methods are needed. Recent studies have revealed the potential of the antisymmetrized geminal power (AGP) as an excellent initial reference for the stron

Haoan Wang, Levent Guvenc

This paper presents a multi-objective digital PID controller design method using the parameter space approach of robust control. Absolute stability is treated first by finding the digital PID controller gain parameter space corresponding to closed loop poles being inside the unit circle. Phase margin, gain margin and a mixed sensitivity bound are treated as

Rohit Ram, Quyu Kong, Marian-Andrei Rizoiu

The impact of online social media on societal events and institutions is profound; and with the rapid increases in user uptake, we are just starting to understand its ramifications. Social scientists and practitioners who model online discourse as a proxy for real-world behavior, often curate large social media datasets. A lack of available tooling aimed at

Dongfang Liu, Yiming Cui, Liqi Yan, Christos Mousas

In this work, we introduce a Denser Feature Network (DenserNet) for visual localization. Our work provides three principal contributions. First, we develop a convolutional neural network (CNN) architecture which aggregates feature maps at different semantic levels for image representations. Using denser feature maps, our method can produce more keypoint feat

Nestor Guillen, Inwon Kim, Antoine Mellet

We study the incompressible limit of the porous medium equation with a right hand side representing either a source or a sink term, and an injection boundary condition. This model can be seen as a simplified description of non-monotone motions in tumor growth and crowd motion, generalizing the congestion-only motions studied in recent literature (\cite{AKY},

Tharindu Fernando, Harshala Gammulle, Simon Denman, Sridha Sridharan

Machine learning-based medical anomaly detection is an important problem that has been extensively studied. Numerous approaches have been proposed across various medical application domains and we observe several similarities across these distinct applications. Despite this comparability, we observe a lack of structured organisation of these diverse research

Jianer Chen, Qin Huang, Iyad Kanj, Ge Xia

We study fundamental point-line covering problems in computational geometry, in which the input is a set $S$ of points in the plane. The first is the Rich Lines problem, which asks for the set of all lines that each covers at least $λ$ points from $S$, for a given integer parameter $λ\geq 2$; this problem subsumes the 3-Points-on-Line problem and the Exact F

Jing Qin

Due to researchers'aim to study personalized recommendations for different business fields, the summary of recommendation methods in specific fields is of practical significance. News recommendation systems were the earliest research field regarding recommendation systems, and were also the earliest recommendation field to apply the collaborative filteri

Salvatore Torquato, Jaeuk Kim, Michael A. Klatt

The local number variance associated with a spherical sampling window of radius $R$ enables a classification of many-particle systems in $d$-dimensional Euclidean space according to the degree to which large-scale density fluctuations are suppressed, resulting in a demarcation between hyperuniform and nonhyperuniform phyla. To better characterize density flu

Nava Gaddam, Nico Groenenboom, Gerard 't Hooft

We study scattering on the black hole horizon in a partial wave basis, with an impact parameter of the order of the Schwarzschild radius or less. This resembles the strong gravity regime where quantum gravitational effects appear. The scattering is governed by an infinite number of virtual gravitons exchanged on the horizon. Remarkably, they can all be summe

Pratyay Banerjee, Tejas Gokhale, Yezhou Yang, Chitta Baral

Methodologies for training visual question answering (VQA) models assume the availability of datasets with human-annotated \textit{Image-Question-Answer} (I-Q-A) triplets. This has led to heavy reliance on datasets and a lack of generalization to new types of questions and scenes. Linguistic priors along with biases and errors due to annotator subjectivity h

Nava Gaddam, Nico Groenenboom

We show that there is a remarkable phase in quantum gravity where gravitational scattering amplitudes mediated by virtual gravitons can be calculated explicitly in effective field theory, when the impact parameter $b$ satisfies $L_{Pl}\ll b \lesssim R_S$, with $R_S$ being the Schwarzschild radius. This phase captures collisions with energies satisfying $\sqr

David Gomez-Ullate, Yves Grandati, Robert Milson

In this paper we revisit exceptional Hermite polynomials from the point of view of spectral theory, following the work initiated by Lance Littlejohn. Adapting a result of Deift, we provide an alternative proof of the completeness of these polynomial families. In addition, using equivalence of Hermite Wronskians we characterize the possible gap sets for the c

Xin Cong, Shiyao Cui, Bowen Yu, Tingwen Liu

Event detection tends to struggle when it needs to recognize novel event types with a few samples. The previous work attempts to solve this problem in the identify-then-classify manner but ignores the trigger discrepancy between event types, thus suffering from the error propagation. In this paper, we present a novel unified model which converts the task to

Sridhar Majety, Victoria A. Norman, Liang Li, Miranda Bell

Silicon carbide is evolving as a prominent solid-state platform for the realization of quantum information processing hardware. Angle-etched nanodevices are emerging as a solution to photonic integration in bulk substrates where color centers are best defined. We model triangular cross-section waveguides and photonic crystal cavities using Finite-Difference

Renato G. Bettiol, Emilio A. Lauret, Paolo Piccione

We use Lie-theoretic methods to explicitly compute the full spectrum of the Laplace--Beltrami operator on homogeneous spheres which occur as geodesic distance spheres in (compact or noncompact) symmetric spaces of rank one, and provide a single unified formula for all cases. As an application, we find all resonant radii for distance spheres in the compact ca

Joshua Foo, Michael R. R. Good, Robert B. Mann

We derive a correspondence between the Hawking radiation spectra emitted from general classes of Taub-NUT black holes with that induced by the relativistic motion of an accelerated Dirichlet boundary condition (i.e.\ a perfectly reflecting mirror) in (1+1)-dimensional flat spacetime. We demonstrate that the particle and energy spectra is thermal at late-time

Hiroyasu Ejiri

Neutrinoless double beta-decay(DBD) is of current interest in high-sensitivity frontiers of particle physics. The decay is very sensitive to Majorana neutrinos masses, neutrino CP phases, right-handed weak interactions and others, which are beyond the standard electro-weal model. DBDs are actually ultra-rare events, and thus DBD experiments with ultra-high s

Takumi Kimura, Takashi Matsubara, Kuniaki Uehara

A point cloud serves as a representation of the surface of a three-dimensional (3D) shape. Deep generative models have been adapted to model their variations typically using a map from a ball-like set of latent variables. However, previous approaches did not pay much attention to the topological structure of a point cloud, despite that a continuous map canno

Vassillen Chizhov, Iliyan Georgiev, Karol Myszkowski, Gurprit Singh

Synthesizing realistic images involves computing high-dimensional light-transport integrals. In practice, these integrals are numerically estimated via Monte Carlo integration. The error of this estimation manifests itself as conspicuous aliasing or noise. To ameliorate such artifacts and improve image fidelity, we propose a perception-oriented framework to

Wen-Lei Zhao, Yue Hu, Zhi Li, Qian Wang

Out-of-time-ordered correlators (OTOCs) are an effective tool in characterizing black hole chaos, many-body thermalization and quantum dynamics instability. Previous research findings have shown that the OTOCs' exponential growth (EG) marks the limit for quantum systems. However, we report in this letter a periodically-modulated nonlinear Schrödinger sys

Aniket Shirsat, Spring Berman

We consider a scenario in which a group of quadrotors is tasked at tracking multiple stationary targets in an unknown, bounded environment. The quadrotors search for targets along a spatial grid overlaid on the environment while performing a random walk on this grid modeled by a discrete-time discrete-state (DTDS) Markov chain. The quadrotors can transmit th

Edwin G. Ng, Bo Pang, Piyush Sharma, Radu Soricut

Image captioning models generally lack the capability to take into account user interest, and usually default to global descriptions that try to balance readability, informativeness, and information overload. On the other hand, VQA models generally lack the ability to provide long descriptive answers, while expecting the textual question to be quite precise.

Hadi A. Khorshidi, Michael Kirley, Uwe Aickelin

Machine learning techniques have been developed to learn from complete data. When missing values exist in a dataset, the incomplete data should be preprocessed separately by removing data points with missing values or imputation. In this paper, we propose an online approach to handle missing values while a classification model is learnt. To reach this goal,

M. L. L. Dantas, E. Cameron, Rafael S. de Souza, A. R. da Silva

The recent paper by AlShebli et al. (2020) investigates the impact of mentorship in young scientists. Among their conclusions, they state that female protégés benefit more from male than female mentorship. We herein expose a critical flaw in their methodological design that is a common issue in Astronomy, namely "selection biases". An effect that if

Danial A. Muhammed, Tarik A. Rashid, Abeer Alsadoon, Nebojsa Bacanin

This paper works on one of the most recent pedestrian crowd evacuation models, i.e., "a simulation model for pedestrian crowd evacuation based on various AI techniques", developed in late 2019. This study adds a new feature to the developed model by proposing a new method and integrating it with the model. This method enables the developed model to f

Jessica M. Lundin, Michael Sollami, Brian Lonsdorf, Alan Ross

The placement of text over an image is an important part of producing high-quality visual designs. Automating this work by determining appropriate position, orientation, and style for textual elements requires understanding the contents of the background image. We refer to the search for aesthetic parameters of text rendered over images as "copyspace det

Zhihong Pang, Fan Feng, Zheng O'Neill

This study investigated the impacts of the COVID-19 pandemic on the electricity consumption of a university dormitory building in the southern U.S. The historical electricity consumption data of this university dormitory building and weather data of an on-campus weather station, which were collected from January 1st, 2017 to July 31st, 2020, were used for an

Evan Hubinger

This paper analyzes and compares 11 different proposals for building safe advanced AI under the current machine learning paradigm, including major contenders such as iterated amplification, AI safety via debate, and recursive reward modeling. Each proposal is evaluated on the four components of outer alignment, inner alignment, training competitiveness, and

J Liu, R Bai, Z Lu, P Ge

In medical fields, text classification is one of the most important tasks that can significantly reduce human workload through structured information digitization and intelligent decision support. Despite the popularity of learning-based text classification techniques, it is hard for human to understand or manually fine-tune the classification results for be

Andrew Simon Johnson, William Winlow

Here we provide evidence that the fundamental basis of nervous communication is derived from a pressure pulse/soliton capable of computation with sufficient temporal precision to overcome any processing errors. Signalling and computing within the nervous system are complex and different phenomena. Action potentials are plastic and this makes the action poten

Simon Gottschalk, Elena Demidova

Research on notable accomplishments and important events in the life of people of public interest usually requires close reading of long encyclopedic or biographical sources, which is a tedious and time-consuming task. Whereas semantic reference sources, such as the EventKG knowledge graph, provide structured representations of relevant facts, they often inc

Chulhong Min, Akhil Mathur, Alessandro Montanari, Utku Gunay Acer

The emergence of multiple sensory devices on or near a human body is uncovering new dynamics of extreme edge computing. In this, a powerful and resource-rich edge device such as a smartphone or a Wi-Fi gateway is transformed into a personal edge, collaborating with multiple devices to offer remarkable sensory al eapplications, while harnessing the power of l

Clifford M. Krowne

It is shown here that the usual operating frequencies for RF limiters, in the nominal 5, 11 or 15 GHz center frequencies, can be lifted up into the much higher frequencies of the 40 to 60 GHz range by a new formula developed from fundamental spin wave electromagnetic interactions in magnetic material characterized by a magnetization M.

Manfred Bucher

Independent investigations of nuclear quadrupole resonance (NQR) and of stripes in high-$T_c$ cuprates find a small deviation of doped-hole density $h$ from the doping level of $La_{2-x}Sr_xCuO_4$. The value observed with NQR, $ x - h \approx 0.02$, agrees closely with the density of itinerant holes, $\tilde{p}$, responsible for suppression of 3D-AFM, as obt

L. Gordeev, E. H. Haeusler

The subject logic in computer science should entail proof theoretic applications. So the question arises whether open problems in computational complexity can be solved by advanced proof theoretic techniques. In particular, consider the complexity classes NP, coNP and PSPACE. It is well-known that NP and coNP are contained in PSPACE, but till recently precis

Yawen Zhang, Seth Spielman, Qi Liu, Si Shen

Human mobility plays a critical role in urban planning and policy-making. However, at certain spatial and temporal resolutions, it is very challenging to track, for example, job and housing mobility. In this study, we explore the usage of a new modality of dataset, online food delivery data, to detect job and housing mobility. By leveraging millions of meal

Mostafa Behtouei, Bruno Spataro, Franco Di Paolo, Alberto Leggieri

Self consistent analytic and numeric design for a set of electron guns with a high beams quality to be used in high power Ka-band klystrons are presented in this paper. The set of electron guns can be used in the high power Ka-band klystrons in order to feed linear accelerating structures at 36 GHz with an estimated 20 MW input power by achieving an effectiv

Raymond Puzio, Paola Ricaurte, Charles Jeffrey Danoff, Charlotte Pierce

Patterns embody repeating phenomena, and, as such, they are partly but not fully detachable from their context. 'Design patterns' and 'pattern languages' are established methods for working with patterns. They have been applied in architecture, software engineering, and other design fields, but have so far seen little application in the field

Justin Kane Gunn, Hadi Akbarzadeh Khorshidi, Uwe Aickelin

This paper presents a method to compute the degree of similarity between two aggregated fuzzy numbers from intervals using the Interval Agreement Approach (IAA). The similarity measure proposed within this study contains several features and attributes, of which are novel to aggregated fuzzy numbers. The attributes completely redefined or modified within thi

Rosalba Garcia-Millan, Gunnar Pruessner

Run-and-tumble motion is an example of active motility where particles move at constant speed and change direction at random times. In this work we study run-and-tumble motion with diffusion in a harmonic potential in one dimension via a path integral approach. We derive a Doi-Peliti field theory and use it to calculate the entropy production and other obser

Reza Maalek, Derek Lichti

This manuscript provides a new framework for calibration of optical instruments, in particular mobile cameras, using large-scale circular black and white target fields. New methods were introduced for (i) matching targets between images; (ii) adjusting the systematic eccentricity error of target centers; and (iii) iteratively improving the calibration soluti

Isaac Lage, Finale Doshi-Velez

Machine learning models that first learn a representation of a domain in terms of human-understandable concepts, then use it to make predictions, have been proposed to facilitate interpretation and interaction with models trained on high-dimensional data. However these methods have important limitations: the way they define concepts are not inherently interp

Utkarsh Mall, Kavita Bala, Tamara Berg, Kristen Grauman

The fashion sense -- meaning the clothing styles people wear -- in a geographical region can reveal information about that region. For example, it can reflect the kind of activities people do there, or the type of crowds that frequently visit the region (e.g., tourist hot spot, student neighborhood, business center). We propose a method to automatically crea

Ankit Goel, Juan Augusto Paredes, Harshil Dadhaniya, Syed Aseem Ul Islam

This paper develops an adaptive digital autopilot for quadcopters and presents experimental results. The adaptive digital autopilot is constructed by augmenting the PX4 autopilot control system architecture with adaptive digital control laws based on retrospective cost adaptive control (RCAC). In order to investigate the performance of the adaptive digital a

Suchuan Dong, Zongwei Li

We present a neural network-based method for solving linear and nonlinear partial differential equations, by combining the ideas of extreme learning machines (ELM), domain decomposition and local neural networks. The field solution on each sub-domain is represented by a local feed-forward neural network, and $C^k$ continuity is imposed on the sub-domain boun

Xabier Feal, Carlos Pajares, Ricardo Vazquez

We analyze the transverse momentum distributions of pp, pPb, XeXe and PbPb collisions at different RHIC and LHC energies and centralities as well as the corresponding distributions for Higgs production decaying into $γγ$ and 4l. A simple linear relation is found between the effective thermal temperature and the hard scale, approximately valid for all process

Moshe Babaioff, Richard Cole, Jason Hartline, Nicole Immorlica

Mechanisms with money are commonly designed under the assumption that agents are quasi-linear, meaning they have linear disutility for spending money. We study the implications when agents with non-linear (specifically, convex) disutility for payments participate in mechanisms designed for quasi-linear agents. We first show that any mechanism that is truthfu

Mayra Macas, Chunming Wu

As the number of cyber-attacks is increasing, cybersecurity is evolving to a key concern for any business. Artificial Intelligence (AI) and Machine Learning (ML) (in particular Deep Learning - DL) can be leveraged as key enabling technologies for cyber-defense, since they can contribute in threat detection and can even provide recommended actions to cyber an

Alan Gatherer, Ashish Shrivastava, Hao Luan, Asheesh Kashyap

Wireless cellular System on Chip (SoC) are experiencing unprecedented demands on data rate, latency use case variety. 5G wireless technologies require a massive number of antennas and complex signal processing to improve bandwidth and spectral efficiency. The Internet of Things is causing a proliferation in the number of connected devices, and service catego

Mohammad Majidzadeh, Jarkko Kaleva, Nuutti Tervo, Harri Pennanen

To satisfy the capacity requirements of future mobile systems, under-utilized millimeter wave frequencies can be efficiently exploited by employing massive MIMO technology with highly directive beamforming. Hybrid analog-digital beamforming has been recognised as a promising approach for large-scale MIMO implementations with a reduced number of costly and po

Abhishek Singh, Ramesh Raskar

In the current pandemic, testing continues to be the most important tool for monitoring and curbing the disease spread and early identification of the disease to perform health-related interventions like quarantine, contact tracing and etc. Therefore, the ability to verify the testing status is pertinent as public places prepare to safely open. Recent advanc

Daniel Kalmbach

We describe the branching of Lie algebras of classical type over $A_{n-1}$ using an inductive approach, which was motivated by the work of Gornitskii. This allows us to label the highest weight vectors of the modules occurring in the decomposition of the restriction of a finite-dimensional simple module to $A_{n-1}$ by lattice points of a string or a Lusztig

Luis Núñez-Betancourt, Yuriko Pitones, Rafael H. Villarreal

Let $I$ be a homogeneous ideal in a polynomial ring $S$. In this paper, we extend the study of the asymptotic behavior of the minimum distance function $δ_I$ of $I$ and give bounds for its stabilization point, $r_I$, when $I$ is an $F$-pure or a square-free monomial ideal. These bounds are related with the dimension and the Castelnuovo--Mumford regularity of

Yuxuan Yuan, Kaveh Dehghanpour, Zhaoyu Wang, Fankun Bu

Due to increasing penetration of volatile distributed photovoltaic (PV) resources, real-time monitoring of customers at the grid-edge has become a critical task. However, this requires solving the distribution system state estimation (DSSE) jointly for both primary and secondary levels of distribution grids, which is computationally complex and lacks scalabi

Matthew Ko, Elliot Padgett, Venkata Yarlagadda, Anusorn Kongkanand

Achieving high power performance and durability with low Pt loadings are critical challenges for proton exchange membrane fuel cells. PtCo catalysts developed on new carbon black supports show promise by simultaneously providing good oxygen reduction kinetics and local oxygen transport. We investigate the role of nanoscale morphology in the performance of th

Hyojeong Kim, Lothar Schimmele, S. Dietrich

A partially miscible binary liquid mixture, composed of A and B particles, is considered theoretically under conditions for which a stable A-rich liquid phase is in thermal equilibrium with the vapor phase. The B-rich liquid is metastable. The liquids and the thermodynamic conditions are chosen such, that the interface between the A-rich liquid and the vapor

Daniel Vial, Sanjay Shakkottai, R. Srikant

We consider a variant of the traditional multi-armed bandit problem in which each arm is only able to provide one-bit feedback during each pull based on its past history of rewards. Our main result is the following: given an upper confidence bound policy which uses full-reward feedback, there exists a coding scheme for generating one-bit feedback, and a corr

Shangmin Guo, Yi Ren, Agnieszka Słowik, Kory Mathewson

Referential games and reconstruction games are the most common game types for studying emergent languages. We investigate how the type of the language game affects the emergent language in terms of: i) language compositionality and ii) transfer of an emergent language to a task different from its origin, which we refer to as language expressivity. With empir

Corbin Klett, Matthew Abate, Samuel Coogan, Eric Feron

Stability margins for linear time-varying (LTV) and switched-linear systems are traditionally computed via quadratic Lyapunov functions, and these functions certify the stability of the system under study. In this work, we show how the more general class of homogeneous polynomial Lyapunov functions is used to compute stability margins with reduced conservati

L. J. Stanley, Hsun-Jen Chuang, Zhixian Zhou, M. Koehler

We report the fabrication of hexagonal-boron-nitride (hBN) encapsulated multi-terminal WSe$_2$ Hall bars with 2D/2D low-temperature Ohmic contacts as a platform for investigating the two-dimensional (2D) metal-insulator transition. We demonstrate that the WSe$_2$ devices exhibit Ohmic behavior down to 0.25 K and at low enough excitation voltages to avoid cur