October 2020 arXiv papers — page 30

Mark Pankov

Let $H$ be a complex Hilbert space of dimension not less than $3$ and let ${\mathcal C}$ be a conjugacy class of compact self-adjoint operators on $H$. Suppose that the dimension of the kernels of operators from ${\mathcal C}$ not less than the dimension of their ranges. In the case when ${\mathcal C}$ is formed by operators of finite rank $k$ and $\dim H=2k

Szymon Peszat, Dariusz Zawisza

We consider a consumption-investment problem (both on finite and infinite time horizon) in which the investor has an access to the bond market. In our approach prices of bonds with different maturities are described by the general HJM factor model. We assume that the bond market consists of entire family of rolling bonds and the investment strategy is a gene

Tomasz Danel, Marek Śmieja, Łukasz Struski, Przemysław Spurek

We investigate the problem of training neural networks from incomplete images without replacing missing values. For this purpose, we first represent an image as a graph, in which missing pixels are entirely ignored. The graph image representation is processed using a spatial graph convolutional network (SGCN) -- a type of graph convolutional networks, which

Jianwei Huang, Rong Yu, Zhijun Xu, Jian-Xin Zhu

Electronic correlation is of fundamental importance to high temperature superconductivity. Iron-based superconductors are believed to possess moderate correlation strength, which combined with their multi-orbital nature makes them a fascinating platform for the emergence of exotic phenomena. A particularly striking form is the emergence of an orbital selecti

Chien-Sheng Wu, Caiming Xiong

This paper investigates pre-trained language models to find out which model intrinsically carries the most informative representation for task-oriented dialogue tasks. We approach the problem from two aspects: supervised classifier probe and unsupervised mutual information probe. We fine-tune a feed-forward layer as the classifier probe on top of a fixed pre

Castaly Fan

This is a brief technical note of analyzing the $\nu_\mu$ disappearance in SBN detector. We here provide a kind of method of plotting the histograms and the heat map plot. We will explore the properties via ROOT framework supported by CERN. The main language we used is C++.

Marco Cattaneo, Gabriele De Chiara, Sabrina Maniscalco, Roberta Zambrini

We introduce the multipartite collision model, defined in terms of elementary interactions between subsystems and ancillae, and show that it can simulate the Markovian dynamics of any multipartite open quantum system. We develop a method to estimate an analytical error bound for any repeated interactions model, and we use it to prove that the error of our sc

Koh Takahashi, Norbert Langer

While magnetic fields have long been considered to be important for the evolution of magnetic non-degenerate stars and compact stars, it has become clear in recent years that actually all of the stars are deeply affected. This is particularly true regarding their internal angular momentum distribution, but magnetic fields may also influence internal mixing p

Bonggun Shin, Sungsoo Park, JinYeong Bak, Joyce C. Ho

Generating a novel and optimized molecule with desired chemical properties is an essential part of the drug discovery process. Failure to meet one of the required properties can frequently lead to failure in a clinical test which is costly. In addition, optimizing these multiple properties is a challenging task because the optimization of one property is pro

Domonkos Varga

Objective image quality assessment deals with the prediction of digital images' perceptual quality. No-reference image quality assessment predicts the quality of a given input image without any knowledge or information about its pristine (distortion free) counterpart. Machine learning algorithms are heavily used in no-reference image quality assessment becau

David M. Hernandez, Matthew J. Holman

We present EnckeHH, a new, highly accurate code for orbital dynamics of perturbed Keplerian systems such as planetary systems or galactic centre systems. It solves Encke's equations of motion, which assume perturbed Keplerian orbits. By incorporating numerical techniques, we have made the code follow optimal roundoff error growth. In a $10^ {12}$ day integra

Rodolfo Sánchez, Angela Braeuning-Demian, Jan Glorius, Anton Kalinin

The atomic physic collaboration SPARC is a part of the APPA pillar at the future Facility for Antiproton and Ion Research. It aims for atomic-physics research across virtually the full range of atomic matter. A research area of the atomic physics experiments is the study of the collision dynamics in strong electro-magnetic fields as well as the fundamental i

Jonathan Labadie-Bartz, Alex C. Carciofi, Tajan Henrique de Amorim, Amanda Rubio

TESS photometry is analyzed for 432 classical Be stars observed in the first year of the mission. The often complex and diverse variability of each object in this sample is classified to obtain an understanding of the behavior of this class as a population. 98\% of the systems are variable above the noise level, with timescales spanning nearly the entire ran

Hebatalla Eldakiky, David Hung-Chang Du, Eman Ramadan

The power and flexibility of software-defined networks lead to a programmable network infrastructure in which in-network computation can help accelerating the performance of applications. This can be achieved by offloading some computational tasks to the network. However, what kind of computational tasks should be delegated to the network to accelerate appli

Muxuan Liang, Menggang Yu

When there are resource constraints, it is important to rank or estimate treatment benefits according to patient characteristics. This facilitates prioritization of assigning different treatments. Most existing literature on individualized treatment rules targets absolute conditional treatment effect differences as the metric for benefits. However, there can

Denghui Zhang, Yanchi Liu, Wei Cheng, Bo Zong

Accurate air turbulence forecasting can help airlines avoid hazardous turbulence, guide the routes that keep passengers safe, maximize efficiency, and reduce costs. Traditional turbulence forecasting approaches heavily rely on painstakingly customized turbulence indexes, which are less effective in dynamic and complex weather conditions. The recent availabil

Louise Hanna, David Barr, Helen Hou, Shauna McGill

A study was performed with 33 Modern Foreign Language (MFL) teachers to afford insight into how classroom practitioners interact with Computer Assisted Language Learning (CALL) in Second Language (L2) pedagogy. A questionnaire with CALL specific statements was completed by MFL teachers who were recruited via UK based Facebook groups. Significantly, participa

Shashikant Kumar, David Codony, Irene Arias, Phanish Suryanarayana

We calculate transversal flexoelectric coefficients along the principal directions for fifty select atomic monolayers using ab initio Density Functional Theory (DFT). Specifically, considering representative materials from each of Groups IV, III-V, V monolayers, transition metal dichalcogenides (TMDs), Group III monochalcogenides, Group IV monochalcogenides,

Jinghang Lin, Xiaoran Tong, Chenxi Li, Qing Lu

The genetic etiologies of common diseases are highly complex and heterogeneous. Classic statistical methods, such as linear regression, have successfully identified numerous genetic variants associated with complex diseases. Nonetheless, for most complex diseases, the identified variants only account for a small proportion of heritability. Challenges remain

Jan Rozendaal

We prove mapping properties of pseudodifferential operators with rough symbols on Hardy spaces for Fourier integral operators. The symbols $a(x,\eta)$ are elements of $C^{r}_{*}S^{m}_{1,\delta}$ classes that have limited regularity in the $x$ variable. We show that the associated pseudodifferential operator $a(x,D)$ maps between Sobolev spaces $\mathcal{H}^{

Felicity F. Dear, Paraskevas Kontis, Baptiste Gault, Jan Ilavsky

Nucleation and growth of Ti$_3$Al \textalpha{}$_2$ ordered domains in \textalpha{}-Ti--Al--X alloys were characterised using a combination of transmission electron microscopy, atom probe tomography and small angle X-ray scattering. Model alloys based on Ti--7Al~(wt.\%) and containing O, V and Mo were aged at \SI{550}{\celsius} for times up to \SI{120}{\day}

Ion Necoara, Daniela Lupu

Majorization-minimization algorithms consist of successively minimizing a sequence of upper bounds of the objective function so that along the iterations the objective function decreases. Such a simple principle allows to solve a large class of optimization problems, even nonconvex and nonsmooth. We propose a general higher-order majorization-minimization al

Eman Abdullah AlOmar, Anthony Peruma, Mohamed Wiem Mkaouer, Christian Newman

Refactoring is the art of improving the design of a system without altering its external behavior. Refactoring has become a well established and disciplined software engineering practice that has attracted a significant amount of research presuming that refactoring is primarily motivated by the need to improve system structures. However, recent studies have

Eduardo Camps Moreno, Craig Kohne, Eliseo Sarmiento, Adam Van Tuyl

Fix a poset $Q$ on $\{x_1,\ldots,x_n\}$. A $Q$-Borel monomial ideal $I \subseteq \mathbb{K}[x_1,\ldots,x_n]$ is a monomial ideal whose monomials are closed under the Borel-like moves induced by $Q$. A monomial ideal $I$ is a principal $Q$-Borel ideal, denoted $I=Q(m)$, if there is a monomial $m$ such that all the minimal generators of $I$ can be obtained via

Jan van den Brand

Many algorithms use data structures that maintain properties of matrices undergoing some changes. The applications are wide-ranging and include for example matchings, shortest paths, linear programming, semi-definite programming, convex hull and volume computation. Given the wide range of applications, the exact property these data structures must maintain v

Fei Jia, Somshubra Majumdar, Boris Ginsburg

We present MarbleNet, an end-to-end neural network for Voice Activity Detection (VAD). MarbleNet is a deep residual network composed from blocks of 1D time-channel separable convolution, batch-normalization, ReLU and dropout layers. When compared to a state-of-the-art VAD model, MarbleNet is able to achieve similar performance with roughly 1/10-th the parame

Xinting Yu, Sarah Horst, Chao He, Patricia McGuiggan

The photochemical haze produced in the upper atmosphere of Titan plays a key role in various atmospheric and surface processes on Titan. The surface energy, one important physical properties of the haze, is crucial for understanding the growth of the haze particles and can be used to predict their wetting behavior with solid and liquid species on Titan. We p

Andrew Fowlie, Will Handley, Liangliang Su

It was recently emphasised by Riley (2019); Schittenhelm & Wacker (2020) that that in the presence of plateaus in the likelihood function nested sampling (NS) produces faulty estimates of the evidence and posterior densities. After informally explaining the cause of the problem, we present a modified version of NS that handles plateaus and can be applied ret

Ximena C. Abrevaya

Astrobiology or exobiology is a relatively new area of science that investigates the possibilities of finding life in other places in the universe. This not only includes the exploration of planets near or distant to Earth, but also the exploration of our own planet in the study of the origin and evolution of life. Given the complexity of the questions this

Eric A. Carlen, Ian Jauslin, Elliott H. Lieb

In a recent paper we studied an equation (called the "simple equation") introduced by one of us in 1963 for an approximate correlation function associated to the ground state of an interacting Bose gas. Solving the equation yields a relation between the density $\rho$ of the gas and the energy per particle. Our construction of solutions gave a well-defined f

John M. Gray, Jason Bossert, Yomay Shyur, Ben Saarel

Vacuum ultraviolet (VUV) light at 118 nm has been shown to be a powerful tool to ionize molecules for various gas-phase chemical studies. A convenient table top source of 118 nm light can be produced by frequency tripling 355 nm light from a Nd:YAG laser in xenon gas. This process has a low efficiency, typically producing only nJ/pulse of VUV light. Simple m

Laurens Devos, Wannes Meert, Jesse Davis

Machine learned models often must abide by certain requirements (e.g., fairness or legal). This has spurred interested in developing approaches that can provably verify whether a model satisfies certain properties. This paper introduces a generic algorithm called Veritas that enables tackling multiple different verification tasks for tree ensemble models lik

Mahshid Alamdar, Thomas Leonard, Can Cui, Bishweshwor P. Rimal

There are pressing problems with traditional computing, especially for accomplishing data-intensive and real-time tasks, that motivate the development of in-memory computing devices to both store information and perform computation. Magnetic tunnel junction (MTJ) memory elements can be used for computation by manipulating a domain wall (DW), a transition reg

Suyoun Kim, Yuan Shangguan, Jay Mahadeokar, Antoine Bruguier

Recurrent Neural Network Transducer (RNN-T), like most end-to-end speech recognition model architectures, has an implicit neural network language model (NNLM) and cannot easily leverage unpaired text data during training. Previous work has proposed various fusion methods to incorporate external NNLMs into end-to-end ASR to address this weakness. In this pape

Natasha Kang, Vadim Marmer

Recurrent boom-and-bust cycles are a salient feature of economic and financial history. Cycles found in the data are stochastic, often highly persistent, and span substantial fractions of the sample size. We refer to such cycles as "long". In this paper, we develop a novel approach to modeling cyclical behavior specifically designed to capture long cycles. W

David S. Lipham

We determine the exact Borel class of the points whose iterates under $\exp(z)+a$ tend to infinity. We also prove that the sets of non-escaping Julia points for many of these functions are topologically equivalent.

Yitong Shi, Sudha Joseph, Edward A. Saunders, Rebecca S. Sandala

The mechanism of AgCl-induced stress corrosion cracking of Ti-6246 was examined at \SI{500}{\mega\pascal} and \SI{380}{\celsius} for \SI{24}{\hour} exposures. SEM and STEM-EDX examination of a FIB-sectioned blister and crack showed that metallic Ag was formed and migrated along the crack. TEM analysis also revealed the presence of \ce{SnO2} and \ce{Al2O3} co

Yu Gu, Christopher Henderson

We consider the long time behavior of solutions to a nonlocal reaction diffusion equation that arises in the study of directed polymers. The model is characterized by convolution with a kernel $R$ and an $L^2$ inner product. In one spatial dimension, we extend a previous result of the authors [arXiv:2002.02799], where only the case $R =\delta$ was considered

Woo-Ram Lee, Karen Michaeli, Georg Schwiete

The Lorenz ratio serves as a measure to compare thermal and electric conductivities of metals. Recent experiments observed small Lorenz ratios in the compensated metal WP$_2$, indicating that charge flow is strongly favored over heat conduction. Motivated by these findings, we study transport properties of compensated metals in the presence of electron-elect

Kamil Adamczewski, Frederik Harder, Mijung Park

We introduce a simple and intuitive framework that provides quantitative explanations of statistical models through the probabilistic assessment of input feature importance. The core idea comes from utilizing the Dirichlet distribution to define the importance of input features and learning it via approximate Bayesian inference. The learned importance has pr

Simon Mattsson, Eric J. Michaud, Erik Hoel

Deep Neural Networks (DNNs) are often examined at the level of their response to input, such as analyzing the mutual information between nodes and data sets. Yet DNNs can also be examined at the level of causation, exploring "what does what" within the layers of the network itself. Historically, analyzing the causal structure of DNNs has received less attent

Charles Yu, Ryan Sie, Nico Tedeschi, Leon Bergen

Neural language models learn, to varying degrees of accuracy, the grammatical properties of natural languages. In this work, we investigate whether there are systematic sources of variation in the language models' accuracy. Focusing on subject-verb agreement and reflexive anaphora, we find that certain nouns are systematically understood better than others,

Samyobrata Mukherjee, Jordi Gomis-Bresco, David Artigas, Lluis Torner

Bound states in the continuum (BICs) exist in a variety of physical systems where they appear as lossless propagating states surrounded by radiating modes. However, in the case of open systems, they coexist with continuous families of guided states, which may be modes or other BICs, located in different regions of the frequency-momentum parameter space. Here

Richard Savery, Gil Weinberg

Composing for a film requires developing an understanding of the film, its characters and the film aesthetic choices made by the director. We propose using existing visual analysis systems as a core technology for film music generation. We extract film features including main characters and their emotions to develop a computer understanding of the film's nar

Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Mehmet Akçakaya

Physics-guided deep learning (PG-DL) via algorithm unrolling has received significant interest for improved image reconstruction, including MRI applications. These methods unroll an iterative optimization algorithm into a series of regularizer and data consistency units. The unrolled networks are typically trained end-to-end using a supervised approach. Curr

F. H. Maldonado-Villamizar, C. A. González-Gutiérrez, L. Villanueva-Vergara, B. M. Rodríguez-Lara

We propose a generalized Jaynes-Cummings model that includes but is not limited to an extensive collection of experimental and theoretical proposals from the literature. It covers nonlinear boson terms, nonlinear dispersive and multi-boson exchange interaction. Our model features an underlying Lie graded algebra symmetry reminiscent to supersymmetric quantum

Kacper Grzelakowski

We study type III contractions of Calabi-Yau threefolds containing a ruled surface over a smooth curve. We discuss the conditions necessary for the image threefold to by smoothable. We describe the change in Hodge numbers caused by this contraction and smoothing deformation. A generalization of a fomula for calculating Hodge numbers of hypersurfaces in $\mat

Yuichi Itto, Christian Beck

A recent experiment [Sadoon AA, Wang Y. 2018 Phys. Rev. E 98, 042411] has revealed that nucleoid associated proteins (i.e., DNA-binding proteins) exhibit highly heterogeneous diffusion processes in bacteria where not only the diffusion constant but also the anomalous diffusion exponent fluctuates for the various proteins. The distribution of displacements of

Kenneth Sharman, Faezeh Kimiaee Asadi, Stephen C Wein, Christoph Simon

Inspired by recent developments in the control and manipulation of quantum dot nuclear spins, which allow for the transfer of an electron spin state to the surrounding nuclear-spin ensemble for storage, we propose a quantum repeater scheme that combines individual quantum dot electron spins and nuclear-spin ensembles, which serve as spin-photon interfaces an

Shang Ren, Ivo Souza, David Vanderbilt

The modern theory of polarization allows for the determination of the macroscopic end charge of a truncated one-dimensional insulator, modulo the charge quantum $e$, from a knowledge of bulk properties alone. A more subtle problem is the determination of the corner charge of a two-dimensional insulator, modulo $e$, from a knowledge of bulk and edge propertie

Luis Sequeira, Juan Luis de la Cruz, Jose Ruiz-Mas, Jose Saldana

In this letter the development and testing of an open enterprise Wi-Fi solution based on virtual APs, managed by a central WLAN controller is presented. It allows seamless handovers between APs in different channels, maintaining the QoS of real-time services. The potential scalability issues associated to the beacon generation and channel assignment have bee

Sam Ganzfried

Many important real-world settings contain multiple players interacting over an unknown duration with probabilistic state transitions, and are naturally modeled as stochastic games. Prior research on algorithms for stochastic games has focused on two-player zero-sum games, games with perfect information, and games with imperfect-information that is local and

Eshed Ram, Yuval Cassuto

A new approach for designing bilayer and multi-layer LDPC codes is proposed and studied in the asymptotic regime. The ensembles are defined through individual uni-variate degree distributions, one for each layer. We present a construction that: 1) enables low-complexity decoding for high-SNR channel instances, 2) provably approaches capacity for low-SNR inst

Alicia B. Magann, Gerard McCaul, Herschel A. Rabitz, Denys I. Bondar

The characterization of mixtures of non-interacting, spectroscopically similar quantum components has important applications in chemistry, biology, and materials science. We introduce an approach based on quantum tracking control that allows for determining the relative concentrations of constituents in a quantum mixture, using a single pulse which enhances

Ivan De Oliveira Nunes, Xuhua Ding, Gene Tsudik

Root of Trust Identification (RTI) refers to determining whether a given security service or task is being performed by the particular root of trust (e.g., a TEE) within a specific physical device. Despite its importance, this problem has been mostly overlooked. We formalize the RTI problem and argue that security of RTI protocols is especially challenging d

S. J. Nakoneczny, M. Bilicki, A. Pollo, M. Asgari

We present a catalog of quasars and corresponding redshifts in the Kilo-Degree Survey (KiDS) Data Release 4. We trained machine learning (ML) models, using optical ugri and near-infrared ZYJHK_s bands, on objects known from Sloan Digital Sky Survey (SDSS) spectroscopy. We define inference subsets from the 45 million objects of the KiDS photometric data limit

Ciprian Chelba, Junpei Zhou, Yuezhang, Li

The paper investigates the feasibility of confidence estimation for neural machine translation models operating at the high end of the performance spectrum. As a side product of the data annotation process necessary for building such models we propose sentence level accuracy $SACC$ as a simple, self-explanatory evaluation metric for quality of translation. E

Pavol Matlovič, Julia de Leon, Hissa Medeiros, Marcel Popescu

Most of the currently known basaltic (V-type) asteroids are believed to be past or present members of the Vesta dynamical family. The rising discoveries of V-type asteroids that are not dynamically linked to the Vesta family suggest that a number of major basaltic bodies may have been present during the early stages of the solar system. In this work, we aim

Rajat Desikan, Amit Behera, Prabal K. Maiti, K. Ganapathy Ayappa

Pore forming toxins (PFTs) are virulent proteins released by several species, including many strains of bacteria, to attack and kill host cells. In this article, we focus on the utility of molecular dynamics (MD) simulations and the molecular insights gleaned from these techniques on the pore forming pathways of PFTs. In addition to all-atom simulations whic

Jonathan Conrad

I introduce an energy constrained approximate twirling operation that can be used to diagonalize effective logical channels in GKP quantum error correction, project states into the GKP code space and construct a dynamical decoupling sequence with fast displacements pulses to distill the GKP stabilizer Hamiltonians from a suitable substrate-Hamiltonian. The l

Jeffrey M. Epstein, K. Birgitta Whaley, Joshua Combes

Nonlinear amplifiers such as the transistor are ubiquitous in classical technology, but their quantum analogues are not well understood. We introduce a class of nonlinear amplifiers that amplify any normal operator and add only a half-quantum of vacuum noise at the output. In the large-gain limit, when used in conjunction with a noisy linear detector, these

Alexander W Olson, Andreea Cucu, Tom Bock

Zero-Shot Learning (ZSL) is an extreme form of transfer learning, where no labelled examples of the data to be classified are provided during the training stage. Instead, ZSL uses additional information learned about the domain, and relies upon transfer learning algorithms to infer knowledge about the missing instances. ZSL approaches are an attractive solut

Daniel Sebastia-Saez, Faiza Benaouda, Charlie Lim, Guoping Lian

Suction cups are widely used in applications such as in measurement of mechanical properties of skin in vivo, in drug delivery devices or in acupuncture treatment. Understanding the mechanical response of skin under hypobaric pressure are of great importance for users of suction cups. The aims of this work are to assess the capability of linear elasticity (Y

Mangqing Guo, M. Cenk Gursoy

Large number of antennas and radio frequency (RF) chains at the base stations (BSs) lead to high energy consumption in massive MIMO systems. Thus, how to improve the energy efficiency (EE) with a computationally efficient approach is a significant challenge in the design of massive MIMO systems. With this motivation, a learning-based stochastic gradient desc

Andreas Kretschmer

We propose an explicit conjectural lift of the Neron-Severi Lie algebra of a hyperk\"ahler variety $X$ of $K3^{[2]}$-type to the Chow ring of correspondences ${\rm CH}^\ast(X \times X)$ in terms of a canonical lift of the Beauville-Bogomolov class obtained by Markman. We give evidence for this conjecture in the case of the Hilbert scheme of two points of a $

Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie, Ioannis Mitliagkas

Adversarial formulations such as generative adversarial networks (GANs) have rekindled interest in two-player min-max games. A central obstacle in the optimization of such games is the rotational dynamics that hinder their convergence. In this paper, we show that game optimization shares dynamic properties with particle systems subject to multiple forces, an

Kai Hoffmann, Clotilde Laigle, Nora Elisa Chisari, Pau Tallada

The high abundance of disc galaxies without a large central bulge challenges predictions of current hydrodynamic simulations of galaxy formation. We aim to shed light on the formation of these objects by studying the redshift and mass dependence of their intrinsic 3D shape distributions in the COSMOS galaxy survey below redshift $z=1.0$. This distribution is

Jarrett Moon

This thesis describes an analysis developed for the MicroBooNE experiment to investigate an anomalous excess of electron-like events observed in the MiniBooNE detector. The hypothesis investigated here is that the MiniBooNE anomaly represents appearance of electron neutrinos. Using an amalgam of novel Deep Learning and standard algorithmic techniques this an

Tarik Ayaou, Azeddine Beghdadi, Karim Afdel, Abdellah Amghar

Road signs detection and recognition in natural scenes is one of the most important tasksin the design of Intelligent Transport Systems (ITS). However, illumination changes remain a major problem. In this paper, an efficient ap-proach of road signs segmentation based on photometric invariants is proposed. This method is based on color in-formation using a hy

Kristoffer Andersson, Cornelis W. Oosterlee

In this paper, we propose a neural network-based method for CVA computations of a portfolio of derivatives. In particular, we focus on portfolios consisting of a combination of derivatives, with and without true optionality, \textit{e.g.,} a portfolio of a mix of European- and Bermudan-type derivatives. CVA is computed, with and without netting, for differen

Alexandre Lourdeaux

The paper deals with the cohomological invariants of smooth and connected linear algebraic groups over an arbitrary field. More precisely, we study degree $2$ invariants with coefficients $\mathbb{Q}/\mathbb{Z}(1)$, that is invariants taking values in the Brauer group. Our main tool is the \'etale cohomology of sheaves on simplicial schemes. We get a descrip

Leon L. Xu, Hannes L. Röst

Liquid Chromatography coupled to Mass Spectrometry (LC-MS) based methods are commonly used for high-throughput, quantitative measurements of the proteome (i.e. the set of all proteins in a sample at a given time). Targeted LC-MS produces data in the form of a two-dimensional time series spectrum, with the mass to charge ratio of analytes (m/z) on one axis, a

Cica Gustiani, David P. DiVincenzo

In the standard oracle model, an oracle efficiently evaluates an unknown classical function independent of the quantum algorithm itself. Quantum algorithms have a complex interrelationship to their oracles; for example the possibility of quantum speedup is affected by the manner by which oracles are implemented. Therefore, it is physically meaningful to sepa

Thomas Carta, Subhajit Chaudhury, Kartik Talamadupula, Michiaki Tatsubori

We present VisualHints, a novel environment for multimodal reinforcement learning (RL) involving text-based interactions along with visual hints (obtained from the environment). Real-life problems often demand that agents interact with the environment using both natural language information and visual perception towards solving a goal. However, most traditio

Celia Escamilla-Rivera

In this work we present a brief discussion about modified and extended cosmological models using current observational tests. We show that according to these astrophysical samples based in late universe measurements, theories like $f(R)$ and $f(T,B)$ can provide useful interpretation to a dynamical dark energy. At this stage, precision cosmostatistics has al

M V Kubrikov, I A Paulin, M V Saramud, A S Kubrikova

The article describes the application of the Hough transform to a honeycomb block image. The problem of cutting a mold from a honeycomb block is described. A number of image transformations are considered to increase the efficiency of the Hough algorithm. A method for obtaining a binary image using a simple threshold, a method for obtaining a binary image us

Lawrence H. Kim, Rahul Goel, Jia Liang, Mert Pilanci

Prior work demonstrated the potential of using the Linear Predictive Coding (LPC) filter to approximate muscle stiffness and damping from computer mouse movements to predict acute stress levels of users. Theoretically, muscle stiffness and damping in the arm can be estimated using a mass-spring-damper (MSD) biomechanical model. However, the damping frequency

Luis A. Zapata, Paul T. P. Ho, Manuel Fernández-López, Estrella Guzmán Ccolque

The explosive molecular outflow detected decades ago in the Orion BN/KL region of massive star formation was considered to be a bizarre event. This belief was strengthened by the non detection of similar cases over the years with the only exception of the marginal case of DR21. Here, we confim a similar explosive outflow associated with the UCH$_{\rm II}$ re

Jiayang Li, Jing Yu, Yu Marco Nie, Zhaoran Wang

In a social system, the self-interest of agents can be detrimental to the collective good, sometimes leading to social dilemmas. To resolve such a conflict, a central designer may intervene by either redesigning the system or incentivizing the agents to change their behaviors. To be effective, the designer must anticipate how the agents react to the interven

Sebastiano Stramaglia, Tomas Scagliarini, Yuri Antonacci, Luca Faes

Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. For Gaussian variables it is equivalent to transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes. We exploit such equivalence and calculate exactly the 'local Granger causality', i

Bertrand Evrard, An Qu, Jean Dalibard, Fabrice Gerbier

The dynamics of a many-body system can take many forms, from a purely reversible evolution to fast thermalization. Here we show experimentally and numerically that an assembly of spin 1 atoms all in the same spatial mode allows one to explore this wide variety of behaviors. When the system can be described by a Bogoliubov analysis, the relevant energy spectr

Keren Censor-Hillel, Dean Leitersdorf, Volodymyr Polosukhin

The Hybrid network model was introduced in [Augustine et al., SODA '20] for laying down a theoretical foundation for networks which combine two possible modes of communication: One mode allows high-bandwidth communication with neighboring nodes, and the other allows low-bandwidth communication over few long-range connections at a time. This fundamentally abs

Shelly Bagchi, Jason R. Wilson, Muneeb I. Ahmad, Christian Dondrup

The Artificial Intelligence (AI) for Human-Robot Interaction (HRI) Symposium has been a successful venue of discussion and collaboration since 2014. In that time, the related topic of trust in robotics has been rapidly growing, with major research efforts at universities and laboratories across the world. Indeed, many of the past participants in AI-HRI have

Amirali Aghazadeh, Vipul Gupta, Alex DeWeese, O. Ozan Koyluoglu

We consider feature selection for applications in machine learning where the dimensionality of the data is so large that it exceeds the working memory of the (local) computing machine. Unfortunately, current large-scale sketching algorithms show poor memory-accuracy trade-off due to the irreversible collision and accumulation of the stochastic gradient noise

Nithin Abraham, Krishna Murali, Kenji Watanabe, Takashi Taniguchi

Van der Waals (vdW) tunnel junctions are attractive due to their atomically sharp interface, gate tunablity, and robustness against lattice mismatch between the successive layers. However, the negative differential resistance (NDR) demonstrated in this class of tunnel diodes often exhibits noisy behaviour with low peak current density, and lacks robustness a

Charles Arnal

In this article, we describe a recursive method for constructing a family of real projective algebraic hypersurfaces in ambient dimension $n$ from families of such hypersurfaces in ambient dimensions $k=1,\ldots,n-1$. The asymptotic Betti numbers of real parts of the resulting family can then be described in terms of the asymptotic Betti numbers of the real

Matteo Ronchetti, Davide Bacciu

We propose an end-to-end differentiable architecture for tomography reconstruction that directly maps a noisy sinogram into a denoised reconstruction. Compared to existing approaches our end-to-end architecture produces more accurate reconstructions while using less parameters and time. We also propose a generative model that, given a noisy sinogram, can sam

Cheng-I Lai, Yung-Sung Chuang, Hung-Yi Lee, Shang-Wen Li

Much recent work on Spoken Language Understanding (SLU) is limited in at least one of three ways: models were trained on oracle text input and neglected ASR errors, models were trained to predict only intents without the slot values, or models were trained on a large amount of in-house data. In this paper, we propose a clean and general framework to learn se

Mattia Di Mauro, Fiorenza Donato, Silvia Manconi

The latest AMS-02 data on cosmic ray electrons show a break in the energy spectrum around 40 GeV, with a change in the slope of about 0.1. We perform a combined fit to the newest AMS-02 positron and electron flux data above 10 GeV using a semi-analytical diffusion model where sources includes production of pairs from pulsar wind nebulae (PWNe), electrons fro

Marvin Edelmann, Yi Hua, Kemal Şafak, Franz X. Kärtner

In this work, we investigate the steady-states of a fiber lasers mode-locked with a nonlinear amplifying loop-mirror that has an inherent amplitude noise-suppression mechanism. Due to the interaction of the sinusoidal transmission function with the fluctuating intracavity pulse amplitude we show that this mechanism may lead to a detectable difference in rela

Haolin Liu, Ye Han, Daniel Emerson, Houriyeh Majditehran

Imaging modalities provide clinicians with real-time visualization of anatomical regions of interest (ROI) for the purpose of minimally invasive surgery. During the procedure, low-resolution image data are acquired and registered with high-resolution preoperative 3D reconstruction to guide the execution of surgical preplan. Unfortunately, due to the potentia

V. Yu. Tertychny-Dauri

The following offers a new axiomatic basis of mechanics and physics in their most important dynamics domain, i. e. an axiom (principle) of completeness intended to generalize Newton's second law of motion for the case of a non-stationary variable-mass point (system) that varies with time. This generalization leads to hyperdynamic dependencies describing such

S. Sajjad, A. Falvard

In gamma-ray astronomy through Imaging Atmospheric Cherenkov Telescopes (IACT), the atmosphere is used as a calorimeter. Incident gamma-rays in the GeV-TeV energy range are observed through the electromagnetic showers they produce in the atmosphere and the Cherenkov light emitted by them. We aim to obtain a parameterisation of the longitudinal profiles of el

Jason J. Yu, Konstantinos G. Derpanis, Marcus A. Brubaker

Normalizing flows are a class of probabilistic generative models which allow for both fast density computation and efficient sampling and are effective at modelling complex distributions like images. A drawback among current methods is their significant training cost, sometimes requiring months of GPU training time to achieve state-of-the-art results. This p

Ciro A. Guido, M. Rosa, R. Cammi, S. Corni

The problem of a solute described by Quantum Chemistry within a solvent represented as a polarizable continuum model (PCM) is here reformulated in terms of the open quantum systems (OQS) theory. Using its stochastic Schr\"{o}dinger Equation formulation, we are able to provide a more comprehensive picture of the electronic energies and of the coupling between

Arunima Singh, Manjari Jain, Saswata Bhattacharya

Two-dimensional (2D) materials viz. transition metal dichalcogenides (TMD) and transition metal oxides (TMO) offer a platform that allows creation of heterostructures with a variety of properties. The optoelectronic industry has observed an upheaval in the research arena of MoS$_2$ based van der Waals (vdW) heterostructures (HTSs) and Janus structures. There

Zi-Wen Liu, Andreas Winter

Magic (non-stabilizerness) is a necessary but "expensive" kind of "fuel" to drive universal fault-tolerant quantum computation. To properly study and characterize the origin of quantum "complexity" in computation as well as physics, it is crucial to develop a rigorous understanding of the quantification of magic. Previous studies of magic mostly focused on s

Xinyao Ma, Maarten Sap, Hannah Rashkin, Yejin Choi

Unconscious biases continue to be prevalent in modern text and media, calling for algorithms that can assist writers with bias correction. For example, a female character in a story is often portrayed as passive and powerless ("She daydreams about being a doctor") while a man is portrayed as more proactive and powerful ("He pursues his dream of being a docto

Edward Bierstone, Jean-Baptiste Campesato, Pierre D. Milman

We address the question of whether geometric conditions on the given data can be preserved by a solution in (1) the Whitney extension problem, and (2) the Brenner-Fefferman-Hochster-Koll\'ar problem, both for $\mathcal C^m$ functions. Our results involve a certain loss of differentiability. Problem (2) concerns the solution of a system of linear equations $A

Hadeel Saadany, Constantin Orasan

Since the advent of Neural Machine Translation (NMT) approaches there has been a tremendous improvement in the quality of automatic translation. However, NMT output still lacks accuracy in some low-resource languages and sometimes makes major errors that need extensive post-editing. This is particularly noticeable with texts that do not follow common lexico-