March 2020 arXiv papers — page 34

Hirokazu Shimobe

In this paper, we consider a class of balanced manifolds and provide a proof of a problem proposed by Silva-that compact complex manifolds that are Kahler outside an analytic subset are balanced. Next, as a special case of this theorem, we prove that compact complex manifolds which are Kahler outside a Kahler submanifold are class C. Finally, we prove that a

The Anh Bui, Ji Li, Fu Ken Ly

We study weighted Besov and Triebel--Lizorkin spaces associated with Hermite expansions and obtain (i) frame decompositions, and (ii) characterizations of continuous Sobolev-type embeddings. The weights we consider generalize the Muckhenhoupt weights.

Mikael Sørensen, Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos

Generalized Canonical Correlation Analysis (GCCA) is an important tool that finds numerous applications in data mining, machine learning, and artificial intelligence. It aims at finding `common' random variables that are strongly correlated across multiple feature representations (views) of the same set of entities. CCA and to a lesser extent GCCA have been

Pieter Tibboel

Let $q_{1}$,...,$q_{n}$ be the position vectors of the point masses of the curved $n$-body problem. Consider any positive elliptic-elliptic rotopulsator solution $q_{i}^{T}=(r\cos{(\theta+\alpha_{i})},r\sin{(\theta+\alpha_{i})},\rho\cos{(\phi+\beta_{i})},\rho\sin{(\phi+\beta_{i})})$, $i\in\{1,...,n\}$, where $\alpha_{1},...,\alpha_{n},\beta_{1},...,\beta_{n}

Hao Yu

The moduli spaces of compact and connected Riemann surfaces has been a central topic in modern mathematics in recent years. Thus their homological dimensions become important invariants. Motivated by the emergence mathematical counterparts of open-closed string theory, we give an estimate of rational homological dimension of Riemann suraces with possible bou

Xavier-Lewis Palmer, Lucas Potter, Saltuk Karahan

Biocybersecurity is a novel space for the 21st century that meets our innovations in biotechnology and computing head on. Within this space, many considerations are open for and demand consideration as groups endeavor to develop products and policies that adequately ensure asset management and protection. Herein, simplified and brief exploration is given fol

Z. Yousaf, Kazuharu Bamba, M. Z. Bhatti, K. Hassan

The aim of this paper is to present the definition of complexity for static self-gravitating anisotropic matter proposed in $f(G,T)$ theory, where $G$ is the Gauss-Bonnet term and $T$ is the trace of energy momentum tensor. We evaluate field equations, Tolman-Oppenheimer-Volkoff equation, mass functions and structure scalars. Among the calculated modified sc

Ryan Alweiss

We prove that given a constant $k \ge 2$ and a large set system $\mathcal{F}$ of sets of size at most $w$, a typical $k$-tuple of sets $(S_1, \cdots, S_k)$ from $\mathcal{F}$ can be ``blown up" in the following sense: for each $1 \le i \le k$, we can find a large subfamily $\mathcal{F}_i$ containing $S_i$ so that for $i \neq j$, if $T_i \in \mathcal{F}_i$ an

Zongjian Fan, Krishna Yaddanapudi, Ryan Bunk, Subhash Mahajan

Comprehensive investigations on ZnSe/GaAs and GaAs/ZnSe interfaces were carried out by photoluminescence (PL) and transmission electron microscopy (TEM), as a part of realizing high quality ZnSe-GaAs (100) hetero-valent structures (HS). The nature of ZnSe/GaAs interface under different surface terminations of GaAs was examined. The ZnSe/Ga-terminated GaAs wa

Nikolay Bogachev

We establish some geometric constraints on compact Coxeter polytopes in hyperbolic spaces and show that these constraints can be a very useful tool for the classification problem of reflective anisotropic Lorentzian lattices and cocompact arithmetic hyperbolic reflection groups.

Ren-Tong Guo, Yu Wang, Rashid Shaisultanov, Feng Wan

Stochasticity effects in the spin (de)polarization of an ultrarelativistic electron beam during photon emissions in a counterpropoagating ultrastrong focused laser pulse in the quantum radiation reaction regime are investigated. We employ a Monte Carlo method to describe the electron dynamics semiclassically, and photon emissions as well as the electron radi

Tomoshige Miyaguchi, Takamasa Miki, Ryota Hamada

The Bonabeau model of self-organized hierarchy formation is studied by using a piecewise linear approximation to the sigmoid function. Simulations of the piecewise-linear agent model show that there exist two-level and three-level hierarchical solutions, and that each agent exhibits a transition from non-ergodic to ergodic behaviors. Furthermore, by using a

Jean Carlo Guella

We present a characterization for a positive definite operator valued kernel to be universal or $C_{0}$-universal, and apply these characterizations to a family of operator valued kernels that are shown to be well behaved. Later, we obtain a characterization for an operator valued differentiable kernel to be $C^{q}$-universal and $C_{0}^{q}$-universal. In or

Xiongfeng Guo, Tianhao Wu, Lin Zhang

Platooning is considered one of the most representative 5G use cases. Due to the small spacing within the platoon, the platoon needs more reliable transmission to guarantee driving safety while improving fuel and driving efficiency. However, efficient resource allocation between platoons has been a challenge, especially considering that the channel and power

Hoda Shajari, Anand Rangarajan

We propose a novel integrated formulation for multiclass and multilabel support vector machines (SVMs). A number of approaches have been proposed to extend the original binary SVM to an all-in-one multiclass SVM. However, its direct extension to a unified multilabel SVM has not been widely investigated. We propose a straightforward extension to the SVM to co

Xi Chen, Qiang Liu, Xin T. Tong

One classical canon of statistics is that large models are prone to overfitting, and model selection procedures are necessary for high dimensional data. However, many overparameterized models, such as neural networks, perform very well in practice, although they are often trained with simple online methods and regularization. The empirical success of overpar

Xingbo Lu, Weiwei Yang, Xinrong Guan, Qingqing Wu

In this letter, we investigate the robust and secure beamforming (RSBF) in an intelligent reflecting surface (IRS) aided millimeter wave (mmWave) multiple input single output (MISO) system, where multiple single antenna eavesdroppers (Eves) are arbitrarily distributed nearby the legitimate receiver. Considering the channel state information (CSI) of Eves' ch

Donald Ebeigbe, Tyrus Berry, Steven J. Schiff, Timothy Sauer

An optimal filter for Poisson observations is developed as a variant of the traditional Kalman filter. Poisson distributions are characteristic of infectious diseases, which model the number of patients recorded as presenting each day to a health care system. We develop both a linear and nonlinear (extended) filter. The methods are applied to a case study of

Xue-Feng Zhang, Je-Ho Shim, Xiao-Ping Ma, Cheng Song

In this letter, an asymmetric spin wave scattering behaviors caused by vortex chirality are investigated in cross-shaped ferromagnetic system. In the system, four scattering behaviors are found, 1) asymmetric skew scattering, depending on the polarity of vortex core, 2) back scattering (reflection), depending on the vortex core stiffness, 3) side deflection

Ankit Vora, Siddharth Agarwal, Gaurav Pandey, James McBride

This paper presents a localization technique using aerial imagery maps and LIDAR based ground reflectivity for autonomous vehicles in urban environments. Traditional localization techniques using LIDAR reflectivity rely on high definition reflectivity maps generated from a mapping vehicle. The cost and effort required to maintain such prior maps are generall

Pengli Lu, Yulong Xue

The graph entropy describes the structural information of graph. Motivated by the definition of graph entropy in general graphs, the graph entropy of hypergraphs based on Laplacian degree are defined. Some results on graph entropy of simple graphs are extended to k-uniform hypergraphs. Using an edge-moving operation, the maximum and minimum graph entropy bas

Siqi Lu, Lin Xie, Kang Lai, Runkun Chen

Versatile quantum modes emerge for plasmon describing the collective oscillations of free electrons in metallic nanoparticles when the particle sizes are greatly reduced. Rather than traditional nanoscale study, the understanding of quantum plasmon desires extremal atomic control of the nanoparticles, calling for size dependent plasmon measurement over a ser

Gamal Mograby, Maxim Derevyagin, Gerald V. Dunne, Alexander Teplyaev

In this paper we study the spectral features, on fractal-like graphs, of Hamiltonians which exhibit the special property of perfect quantum state transfer: the transmission of quantum states without dissipation. The essential goal is to develop the theoretical framework for understanding the interplay between perfect quantum state transfer, spectral properti

Kangkang Zhang, Cong Wang, Minhao Zhang, Zhanbin Bai

Single molecular electrets exhibiting single molecule electric polarization switching have been long desired as a platform for extremely small non-volatile storage devices, although it is controversial because of the poor stability of single molecular electric dipoles. Here we study the single molecular device of GdC82, where the encapsulated Gd atom forms a

Valentin Patilea, Hamdi Raïssi

In this paper the orthogonal impulse response functions (OIRF) are studied in the non-standard, though quite common, case where the covariance of the error vector is not constant in time. The usual approach for taking into account such behavior of the covariance consists in applying the standard tools to sub-periods of the whole sample. We underline that suc

Jonathan D. Smith, Kamyar Azizzadenesheli, Zachary E. Ross

The recent deep learning revolution has created an enormous opportunity for accelerating compute capabilities in the context of physics-based simulations. Here, we propose EikoNet, a deep learning approach to solving the Eikonal equation, which characterizes the first-arrival-time field in heterogeneous 3D velocity structures. Our grid-free approach allows f

Uğur Odabaşı

The complete symmetric directed graph of order $v$, denoted $K_{v}^*$, is the directed graph on $v$ vertices that contains both arcs $(x,y)$ and $(y,x)$ for each pair of distinct vertices $x$ and $y$. For a given directed graph, $D$, the set of all $v$ for which $K_{v}^*$ admits a $D$-decomposition is called the spectrum of $D$. There are 10 non-isomorphic o

Takanobu Hara, Adisak Seesanea

We study the existence of positive solutions to quasilinear elliptic equations of the type \[ -\Delta_{p} u = \sigma u^{q} + \mu \quad \text{in} \ \mathbb{R}^{n}, \] in the sub-natural growth case $0 < q < p - 1$, where $\Delta_{p}u = \nabla \cdot ( |\nabla u|^{p - 2} \nabla u )$ is the $p$-Laplacian with $1 < p < n$, and $\sigma$ and $\mu$ are nonnegative R

Hao Tung, Chao Zheng, Xinsheng Mao, Dahong Qian

Objective: A novel structure based on channel-wise attention mechanism is presented in this paper. Embedding with the proposed structure, an efficient classification model that accepts multi-lead electrocardiogram (ECG) as input is constructed. Methods: One-dimensional convolutional neural networks (CNN) have proven to be effective in pervasive classificatio

Hongjie Dong, Seick Kim

We construct the Green function for second-order elliptic equations in non-divergence form when the mean oscillations of the coefficients satisfy the Dini condition. We show that the Green's function is BMO in the domain and establish logarithmic pointwise bounds. We also obtain pointwise bounds for first and second derivatives of the Green's function.

Haiyang Xu, Junwen Chen, Kun Han, Xiangang Li

Multi-class text classification is one of the key problems in machine learning and natural language processing. Emerging neural networks deal with the problem using a multi-output softmax layer and achieve substantial progress, but they do not explicitly learn the correlation among classes. In this paper, we use a multi-task framework to address multi-class

Naoya Arakawa

This article surveys engineering and neuroscientific models of planning as a cognitive function, which is regarded as a typical function of fluid intelligence in the discussion of general intelligence. It aims to present existing planning models as references for realizing the planning function in brain-inspired AI or artificial general intelligence (AGI). I

Jian Cao, Marc G. Genton, David E. Keyes, George M. Turkiyyah

We present a preconditioned Monte Carlo method for computing high-dimensional multivariate normal and Student-$t$ probabilities arising in spatial statistics. The approach combines a tile-low-rank representation of covariance matrices with a block-reordering scheme for efficient Quasi-Monte Carlo simulation. The tile-low-rank representation decomposes the hi

Jeff Moore, Linda Spilker, Morgan Cable, Scott Edgington

The outer solar system has a diverse range of objects, holding important clues about the formation and evolution of our solar system, the emergence and current distribution of life, and the physical processes controlling both our own and exoplanetary systems. This White Paper summarizes the Outer Planets Analysis Group's (OPAG's) priorities in the Decadal Su

Rui Duan, C. Jason Liang, Pamela Shaw, Cheng Yong Tang

Practical problems with missing data are common, and statistical methods have been developed concerning the validity and/or efficiency of statistical procedures. On a central focus, there have been longstanding interests on the mechanism governing data missingness, and correctly deciding the appropriate mechanism is crucially relevant for conducting proper p

Brice Loustau

This textbook is an introductory course on hyperbolic geometry, intended for students at the advanced undergraduate (Bachelor) or early graduate (Master) level.

Giulio Biroli, Patrick Charbonneau, Eric I. Corwin, Yi Hu

The random Lorentz gas (RLG) is a minimal model of transport in heterogeneous media. It also models the dynamics of a tracer in a glassy system. These two perspectives, however, are fundamentally inconsistent. Arrest in the former is related to percolation, and hence continuous, while glass-like arrest is discontinuous. In order to clarify the interplay betw

Pritish Narayanan, Charles E. Cox, Alexis Asseman, Nicolas Antoine

The IBM Neural Computer (INC) is a highly flexible, re-configurable parallel processing system that is intended as a research and development platform for emerging machine intelligence algorithms and computational neuroscience. It consists of hundreds of programmable nodes, primarily based on Xilinx's Field Programmable Gate Array (FPGA) technology. The node

Saeed Izadi, Ghassan Hamarneh

Confocal microscopy is essential for histopathologic cell visualization and quantification. Despite its significant role in biology, fluorescence confocal microscopy suffers from the presence of inherent noise during image acquisition. Non-local patch-wise Bayesian mean filtering (NLB) was until recently the state-of-the-art denoising approach. However, clas

Aunas Manzoor, S. M. Ahsan Kazmi, Shashi Raj Pandey, Choong Seon Hong

Recently, the coexistence of ultra-reliable and low-latency communication (URLLC) and enhanced mobile broadband (eMBB) services on the same licensed spectrum has gained a lot of attention from both academia and industry. However, the coexistence of these services is not trivial due to the diverse multiple access protocols, contrasting frame distributions in

Hai-Ming Zhang, Zhen-Jie Wang, Jin Zhang, Ting-Feng Yi

Violent multi-wavelength variabilities are observed in gamma-ray-selected blazars. We present an analysis of long-term light curves for eight bright blazars to explore the co-variation pattern in the gamma-ray and radio bands. We extract their gamma-ray light curves and spectra with data observed by the Fermi/LAT since 2008. We find diverse co-variation patt

Teruo Nagase, Akiko Shima

Let $\Gamma$ be a chart, and we denote by $\Gamma_m$ the union of all the edges of label $m$. A chart $\Gamma$ is of type $(m;2,3,2)$ if $w(\Gamma)=7$, $w(\Gamma_m\cap\Gamma_{m+1})=2$, $w(\Gamma_{m+1}\cap\Gamma_{m+2})=3$, and $w(\Gamma_{m+2}\cap\Gamma_{m+3})=2$ where $w(G)$ is the number of white vertices in $G$. In this paper, we prove that if there is a mi

Ward Whitt, Wei You

We develop a robust queueing network analyzer algorithm to approximate the steady-state performance of a single-class open queueing network of single-server queues with Markovian routing. The algorithm allows non-renewal external arrival processes, general service-time distributions and customer feedback. We focus on the customer flows, defined as the contin

Lorenzo Rocutto, Claudio Destri, Enrico Prati

Boltzmann Machines constitute a class of neural networks with applications to image reconstruction, pattern classification and unsupervised learning in general. Their most common variants, called Restricted Boltzmann Machines (RBMs) exhibit a good trade-off between computability on existing silicon-based hardware and generality of possible applications. Stil

Haiyang Xu, Yahao He, Kun Han, Junwen Chen

Text summarization aims to generate a headline or a short summary consisting of the major information of the source text. Recent studies employ the sequence-to-sequence framework to encode the input with a neural network and generate abstractive summary. However, most studies feed the encoder with the semantic word embedding but ignore the syntactic informat

Yiwen Hua, Puneet Kohli, Pritish Uplavikar, Anand Ravi

With the mass-market adoption of dual-camera mobile phones, leveraging stereo information in computer vision has become increasingly important. Current state-of-the-art methods utilize learning-based algorithms, where the amount and quality of training samples heavily influence results. Existing stereo image datasets are limited either in size or subject var

Navid Saneie, Varun Kulkarni, Kamel Fezzaa, Neelesh Patankar

Manipulating surface topography is one of the most promising strategies for increasing the efficiency of numerous industrial processes involving droplet contact with superheated surfaces. In such scenarios, the droplets may immediately boil upon contact, splash and boil, or could levitate on their own vapor in the Leidenfrost state. In this work, we report t

Nirav Ajmeri, Shubham Goyal, Munindar P. Singh

Many cybersecurity breaches occur due to users not following good cybersecurity practices, chief among them being regulations for applying software patches to operating systems, updating applications, and maintaining strong passwords. We capture cybersecurity expectations on users as norms. We empirically investigate sanctioning mechanisms in promoting compl

Nikolaos E. Mavromatos

In this talk, I review briefly a scenario for the evolution of a string-inspired cosmological model, in which condensates of primordial gravitational waves (GW), formed at the very early eras after the Big Bang, are considered responsible for inducing inflation and then a smooth exit to a radiation dominated epoch. Primordial axion fields, that exist in the

Ricardo Puebla, Obinna Abah, Mauro Paternostro

We propose two measurement-based schemes to cool a nonlinear mechanical resonator down to energies close to that of its ground state. The protocols rely on projective measurements of a spin degree of freedom, which interacts with the resonator through a Jaynes-Cummings interaction. We show the performance of these cooling schemes, that can be either concaten

Xin Zhang, Kevin Makles, Léo Colombier, Dominik Metten

Graphene and related two-dimensional (2D) materials associate remarkable mechanical, electronic, optical and phononic properties. As such, 2D materials are promising for hybrid systems that couple their elementary excitations (excitons, phonons) to their macroscopic mechanical modes. These built-in systems may yield enhanced strain-mediated coupling compared

R. M. Causey

We use the repeated averages hierarchy to prove a Ramsey theorem regarding uniform upper estimates of convex block sequences of weakly null sequences. The base case of the theorem recovers a result of Freeman.

Jack West, Neil Kingensmith, George K. Thiruvathukal

We present FLIC, a distributed software data caching framework for fogs that reduces network traffic and latency. FLICis targeted toward city-scale deployments of cooperative IoT devices in which each node gathers and shares data with surrounding devices. As machine learning and other data processing techniques that require large volumes of training data are

Francesco Lin, Michael Lipnowski

We show that the Seifert-Weber dodecahedral space $\mathsf{SW}$ is an $L$-space. The proof builds on our work relating Floer homology and spectral geometry of hyperbolic three-manifolds. A direct application of our previous techniques runs into difficulties arising from the computational complexity of the problem. We overcome this by exploiting the large sym

Jeremy Kepner, Simon Alford, Vijay Gadepally, Michael Jones

The MIT/IEEE/Amazon GraphChallenge.org encourages community approaches to developing new solutions for analyzing graphs and sparse data. Sparse AI analytics present unique scalability difficulties. The Sparse Deep Neural Network (DNN) Challenge draws upon prior challenges from machine learning, high performance computing, and visual analytics to create a cha

Jiale Zhi, Rui Wang, Jeff Clune, Kenneth O. Stanley

Recent advances in machine learning are consistently enabled by increasing amounts of computation. Reinforcement learning (RL) and population-based methods in particular pose unique challenges for efficiency and flexibility to the underlying distributed computing frameworks. These challenges include frequent interaction with simulations, the need for dynamic

Zhe Zhang, Chunyu Wang, Wenhu Qin, Wenjun Zeng

We propose to estimate 3D human pose from multi-view images and a few IMUs attached at person's limbs. It operates by firstly detecting 2D poses from the two signals, and then lifting them to the 3D space. We present a geometric approach to reinforce the visual features of each pair of joints based on the IMUs. This notably improves 2D pose estimation accura

Takuya Nomoto, Takashi Koretsune, Ryotaro Arita

To estimate the Curie temperature of metallic magnets from first principles, we develop a local force method for the tight-binding model having spin-dependent hopping derived from spin density functional theory. While spin-dependent hopping is crucial for the self-consistent mapping to the effective spin model, the numerical cost to treat such non-local term

Takami Tohyama, Shigetoshi Sota, Seiji Yunoki

The ground state of a hole-doped t-t'-J ladder with four legs favors a striped charge distribution. Spin excitation from the striped ground state is known to exhibit incommensurate spin excitation near q=(pi,pi) along the leg direction (qx direction). However, an outward dispersion from the incommensurate position toward q=(0,pi) is strong in intensity, inco

Mario Ullrich

It was recently shown in [4] that, for $L_2$-approximation of functions from a Hilbert space, function values are almost as powerful as arbitrary linear information, if the approximation numbers are square-summable. That is, we showed that \[ e_n \,\lesssim\, \sqrt{\frac{1}{k_n} \sum_{j\geq k_n} a_j^2} \qquad \text{ with }\quad k_n \asymp \frac{n}{\ln(n)}, \

Ali Eghbali

We generalize the formulation of Poisson-Lie (PL) T-plurality proposed by R. von Unge [JHEP 07 (2002) 014] from Lie groups to Lie supergroups. By taking a convenient ansatz for metric of the $\sigma$-model in terms of the left-invariant one-forms of the isometry Lie supergroups $(C^3 +A)$ and $GL(1|1)$ we construct cosmological string backgrounds, including

Josimar E. Chire Saire, Roberto C. Navarro

During the last months, there is an increasing alarm about a new mutation of coronavirus, covid-19 coined by World Health Organization(WHO) with an impact in many areas: economy, health, politics and others. This situation was declared a pandemic by WHO, because of the fast expansion over many countries. At the same time, people is using Social Networks to e

M. Rodriguez-Vega, Ze-Xun Lin, A. Leonardo, A. Ernst

In bilayer CrI3, experimental and theoretical studies suggest that the magnetic order is closely related to the layer staking configuration. In this work, we study the effect of dynamical lattice distortions, induced by non-linear phonon coupling, in the magnetic order of the bilayer system. We use density functional theory to determine the phonon properties

Anthony Aguirre, Gaia Dempsey, Harry Surden, Peter B. Reiner

When we consult with a doctor, lawyer, or financial advisor, we generally assume that they are acting in our best interests. But what should we assume when it is an artificial intelligence (AI) system that is acting on our behalf? Early examples of AI assistants like Alexa, Siri, Google, and Cortana already serve as a key interface between consumers and info

Christina Frederick, Soledad Villar, Zoi-Heleni Michalopoulou

In this work model-based methods are employed along with machine learning techniques to classify sediments in oceanic environments based on the geoacoustic properties of a two-layer seabed. Two different scenarios are investigated. First, a simple low-frequency case is set up, where the acoustic field is modeled with normal modes. Four different hypotheses a

Alexander Scheinker, Simon Hirlaende, Francesco Maria Velotti, Spencer Gessner

Multi-objective optimization is important for particle accelerators where various competing objectives must be satisfied routinely such as, for example, transverse emittance vs bunch length. We develop and demonstrate an online multi-time scale multi-objective optimization algorithm that performs real time feedback on particle accelerators. We demonstrate th

Saeed Anwar, Nick Barnes, Lars Petersson

To make the best use of the underlying minute and subtle differences, fine-grained classifiers collect information about inter-class variations. The task is very challenging due to the small differences between the colors, viewpoint, and structure in the same class entities. The classification becomes more difficult due to the similarities between the differ

Amir Saberi, Farhad Farokhi, Girish N. Nair

We investigate state estimation of linear systems over channels having a finite state not known by the transmitter or receiver. We show that similar to memoryless channels, zero-error capacity is the right figure of merit for achieving bounded estimation errors. We then consider finite-state, worst-case versions of the common erasure and additive noise chann

James P. Crutchfield

Short-term survival and an exuberant plunge into building our future are generating a new kind of unintended consequence -- hidden fragility. This is a direct effect of the sophistication and structural complexity of the socio-technical systems humans create. It is inevitable. And so the challenge is, How much can we understand and predict about these system

Nazar Emirov, Cheng Cheng, Junzheng Jiang, Qiyu Sun

Polynomial graph filters and their inverses play important roles in graph signal processing. An advantage of polynomial graph filters is that they can be implemented in a distributed manner, which involves data transmission between adjacent vertices only. The challenge arisen in the inverse filtering is that a direct implementation may suffer from high compu

Heng Fan, Jiayang Chen, Zitong Zhao, Jianming Wen

Parity-time (PT) symmetry in non-Hermitian optical systems promises distinct optical effects and applications not found in conservative optics. Its counterpart, anti-PT symmetry, subscribes another class of intriguing optical phenomena and implies complementary techniques for exotic light manipulation. Despite exciting progress, so far anti-PT symmetry has o

Anca Radulescu, Cassandra Williams, Kieran Cavanagh

The 2019 Novel Corona virus infection (COVID 19) is an ongoing public health emergency of international focus. Significant gaps persist in our knowledge of COVID 19 epidemiology, transmission dynamics, investigation tools and management, despite (or possibly because of) the fact that the outbreak is an unprecedented global threat. On the positive side, enoug

Apiano F. Morais

In this investigation I used the Logistic Model to fit the COVID-19 pandemic data for some countries. The data modeled is the death numbers per day in China, Iran, Italy, South Korea, Spain and United States. Considering the current growth rate of the pandemic, it was possible to show that the death toll should be between 3,277-3,327 deaths in China, 2,035-2

Kaisa Liimatainen, Leena Latonen, Masi Valkonen, Kimmo Kartasalo

Virtual reality (VR) enables data visualization in an immersive and engaging manner, and it can be used for creating ways to explore scientific data. Here, we use VR for visualization of 3D histology data, creating a novel interface for digital pathology. Our contribution includes 3D modeling of a whole organ and embedded objects of interest, fusing the mode

Alexis Tricot, Igor M. Sokolov, David Holcman

The distribution of voltage in sub-micron cellular domains remains poorly understood. In neurons, the voltage results from the difference in ionic concentrations which are continuously maintained by pumps and exchangers. However, it not clear how electro-neutrality could be maintained by an excess of fast moving positive ions that should be counter balanced

Jens Schulenborg, Maarten R. Wegewijs, Janine Splettstoesser

We study the linear and nonlinear thermovoltage of a quantum dot with effective attractive electron-electron interaction and weak, energy-dependent tunnel-coupling to electronic contacts. Remarkably, we find that the thermovoltage shows signatures of repulsive interaction which can be rationalized. These thermovoltage characteristics are robust against large

Dinh-Luan Nguyen, Sunpreet S. Arora, Yuhang Wu, Hao Yang

Deep learning-based systems have been shown to be vulnerable to adversarial attacks in both digital and physical domains. While feasible, digital attacks have limited applicability in attacking deployed systems, including face recognition systems, where an adversary typically has access to the input and not the transmission channel. In such setting, physical

David H. Wolpert

All previously derived thermodynamic fluctuation theorems (FTs) that concern multiple co-evolving systems have required that each system can only change its state during an associated pre-fixed, limited set of time intervals. However, in many real-world cases the times when systems change their states are randomly determined, e.g., in almost all biological e

Jonathan Crussell, David Fritz, Vince Urias

Sandia has an extensive background in cybersecurity research and is currently extending its state-of-the-art modeling via emulation capability. However, a key part of Sandia's modeling methodology is the discovery and specification of the information-system under study, and the ability to recreate that specification with the highest fidelity possible in orde

Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender

Neural architecture search (NAS) has shown promising results discovering models that are both accurate and fast. For NAS, training a one-shot model has become a popular strategy to rank the relative quality of different architectures (child models) using a single set of shared weights. However, while one-shot model weights can effectively rank different netw

D. S. Akerib, S. Alsum, H. M. Araújo, X. Bai

The Large Underground Xenon (LUX) dark matter search was a 250-kg active mass dual-phase time projection chamber that operated by detecting light and ionization signals from particles incident on a xenon target. In December 2015, LUX reported a minimum 90% upper C.L. of 6e-46 cm^2 on the spin-independent WIMP-nucleon elastic scattering cross section based on

Krzysztof P. Wójcik, Ireneusz Weymann, Johann Kroha

We analyze theoretically the phase diagram of a triangular triple quantum dot with strong onsite repulsion coupled to ferromagnetic leads. This model includes the competition of magnetic ordering of local or itinerant magnetic moments, geometric frustration and Kondo screening. We identify all the phases resulting from this competition. We find that three Ko

Ji Eun Kim, Milena Tsvetkova

Antisocial behavior can be contagious, spreading from individual to individual and rippling through social networks. Moreover, it can spread not only through third-party influence from observation, just like innovations or individual behavior do, but also through direct experience, via "pay-it-forward" retaliation. Here, we distinguish between the effects of

Mark J. Kuiack, Ralph A. M. J. Wijers, Aleksandar Shulevski, Antonia Rowlinson

We report the discovery of bright, fast, radio flashes lasting tens of seconds with the AARTFAAC high-cadence all-sky survey at 60 MHz. The vast majority of these coincide with known, bright radio sources that brighten by factors of up to 100 during such an event. We attribute them to magnification events induced by plasma near the Earth, most likely in the

Julius de Rojas, Alberto Quintana, Aitor Lopeandía, Joaquín Salguero

So far, magneto-ionics, understood as voltage-driven ion transport in magnetic materials, has largely relied on controlled migration of oxygen ion/vacancy and, to a lesser extent, lithium and hydrogen. Here, we demonstrate efficient, room-temperature, voltage-driven nitrogen transport (i.e., nitrogen magneto-ionics) by electrolyte-gating of a single CoN film

Dung Nguyen, Sridha Sridharan, Duc Thanh Nguyen, Simon Denman

Deep learning has been applied to achieve significant progress in emotion recognition. Despite such substantial progress, existing approaches are still hindered by insufficient training data, and the resulting models do not generalize well under mismatched conditions. To address this challenge, we propose a learning strategy which jointly transfers the knowl

Victoria Norman, Sridhar Majety, Zhipan Wang, William H. Casey

Color centers are versatile systems that generate quantum light, sense magnetic fields and produce spin-photon entanglement. We review how these properties have pushed the limits of fundamental knowledge in a variety of scientific disciplines, from rejecting local-realistic theories to sensing superconducting phase transitions. In the light of recent progres

Chunming Zhu, Jiong Qiu, Paulett Liewer, Angelos Vourlidas

Theoretically, CME kinematics are related to magnetic reconnection processes in the solar corona. However, the current quantitative understanding of this relationship is based on the analysis of only a handful of events. Here we report a statistical study of 60 CME-flare events from August 2010 to December 2013. We investigate kinematic properties of CMEs an

Tiago Novello, Vinicius da Silva, Luiz Velho

This paper presents a path tracer algorithm to compute the global illumination of non-Euclidean manifolds. We use the 3D torus as an example.

Thibaut Vidal, Toni Pacheco, Maximilian Schiffer

The use of machine learning algorithms in finance, medicine, and criminal justice can deeply impact human lives. As a consequence, research into interpretable machine learning has rapidly grown in an attempt to better control and fix possible sources of mistakes and biases. Tree ensembles offer a good prediction quality in various domains, but the concurrent

Gordon W. Semenoff

This essay is a tribute to Professor Roman Jackiw on the occasion of his eightieth year. It discusses some ideas about Fermion zero modes and fractional charges and quantum entanglement.

Chandra M. Varma

The conjecture made recently by the group at Sherbrooke, that their observed anomalous thermal Hall effect in the pseudo-gap phase in the cuprates is due to phonons, is supported on the basis of an earlier result that the observed loop-current order in this phase must induce lattice distortions which are linear in the order parameter and an applied magnetic

Sean Howe

Following a suggestion of Peter Scholze, we construct an action of $\hat{\mathbb{G}}_m$ on the Katz moduli problem, a profinite-\'{e}tale cover of the ordinary locus of the $p$-adic modular curve whose ring of functions is Serre's space of $p$-adic modular functions. This action is a local, $p$-adic analog of a global, archimedean action of the circle group

Alexander Saffer, Kent Yagi

Recent observations of gravitational waves from binary black holes and neutron stars allow us to probe the strong and dynamical field regime of gravity. On the other hand, a collective signal from many individual, unresolved sources results in what is known as a stochastic background. We here consider probing gravity with such a background from stellar-mass

Marcelo Aguiar

Loday's dendriform algebras and its siblings pre-Lie and zinbiel have received attention over the past two decades. In recent literature, there has been interest in a generalization of these types of algebra in which each individual operation is replaced by a family of operations indexed by a fixed semigroup $S$. The purpose of this note is twofold. First, w

Michal Svrček

A megascopic revalidation is offered providing responses and resolutions of current inconsistencies and existing contradictions in present-day quantum theory. As the core of this study we present an independent proof of the Goldstone theorem for a quantum field formulation of molecules and solids. Along with phonons two types of new quasiparticles appear: ro

Ali Mousavi, Lihong Li, Qiang Liu, Denny Zhou

Off-policy estimation for long-horizon problems is important in many real-life applications such as healthcare and robotics, where high-fidelity simulators may not be available and on-policy evaluation is expensive or impossible. Recently, \cite{liu18breaking} proposed an approach that avoids the \emph{curse of horizon} suffered by typical importance-samplin

Martino Borello, Abdelillah Jamous

Dihedral codes, particular cases of quasi-cyclic codes, have a nice algebraic structure which allows to store them efficiently. In this paper, we investigate it and prove some lower bounds on their dimension and minimum distance, in analogy with the theory of BCH codes. This allows us to construct dihedral codes with prescribed minimum distance. In the binar

Piero Giacomelli

In this paper we will describe a new approach on the well-known suffix-array algorithm using Big Table Data Technology. We will demonstrate how it is possible to refactor a well-known algorithm coupled by taking advantage of an high-performance distributed datastore, to illustrate the advantages of using datastore cloud related technology for storing large t

Bruno Leonardo Macedo Ferreira, Bruno Tadeu Costa

Let A and A' be two Cstar-algebras with identities I_A and I_A', respectively, and P_1 and P_2 = I_A - P_1 nontrivial projections in A. In this paper we study the characterization of multiplicative star-Lie-Jordan-type maps, where the notion of these maps arise here. In particular, if M_A is a von Neumann algebra relative Cstar-algebra A without central summ