December 2020 arXiv papers — page 151

Benjamin Smith

Deep learning ship detection in satellite optical imagery suffers from false positive occurrences with clouds, landmasses, and man-made objects that interfere with correct classification of ships, typically limiting class accuracy scores to 88\%. This work explores the tensions between customization strategies, class accuracy rates, training times, and costs

Chaolun Lu, Yongqiang Li, Zijun Feng, Zhongsheng Hou

This paper presents new results that allow one to address the discrete-time general nonlinear robust control problem. The uncertain system is described by a general nonlinear function set characterized by the nominal model and the corresponding modeling error bound. Traditional synthesis methods design parameters of a structured robust controller. The key ai

Chen Wang, Yuan Ren

We apply the CP to CAVs for the first time experimentally. Firstly, we introduce the propagation properties of a CAV with the LOCP in the process of measuring TCs, and measure the TCs of CAVs in the self-focusing areas experimentally. Secondly, we shape the CAVs via the HOCP and discuss the manipulaiton of singularities.

Nikolai V. Ivanov

The paper is devoted to an approach to the bounded cohomology theory based on the theories of simplicial sets and Postnikov systems. In particular, the main results of the bounded cohomology theory of topological spaces are extended to arbitrary Kan (fibrant) simplicial sets.

Michele Peruzzi, David B. Dunson

High resolution geospatial data are challenging because standard geostatistical models based on Gaussian processes are known to not scale to large data sizes. While progress has been made towards methods that can be computed more efficiently, considerably less attention has been devoted to big data methods that allow the description of complex relationships

Patrick McGlynn, Cedric Simenel

Background: Quantum tunneling in many-body systems is the subject of many experimental and theoretical studies in fields ranging from cold atoms to nuclear physics. However, theoretical description of quantum tunneling with strongly interacting particles, such as nucleons in atomic nuclei, remains a major challenge in quantum physics. Purpose: An initial-val

Karthik Boyareddygari

Category theory provides a means through which many far-ranging fields of mathematics can be related by their similar structure. In a paper by Robinson [2], this interconnectivity afforded by categorical perspectives allowed for the realization of torsion products as the homotopy groups of a topological space, which is itself constructed for this express pur

D. Shcherbakov, P. Stepanov, S. Memaran, Y. Wang

Spin-orbit coupling (SOC) is a relativistic effect, where an electron moving in an electric field experiences an effective magnetic field in its rest frame. In crystals without inversion symmetry, it lifts the spin degeneracy and leads to many magnetic, spintronic and topological phenomena and applications. In bulk materials, SOC strength is a constant that

J. Yang, K. Wang, S. Che, Z. J. Tuchfeld

We realize p-p'-p junctions in few-layer black phosphorus (BP) devices, and use magneto-transport measurements to study the equilibration and transmission of edge states at the interfaces of regions with different charge densities. We observe both full equilibration, where all edge channels equilibrate and are equally partitioned at the interfaces, and p

Kelvin Say, Michele John

With Australia's significant capacity of household PV, decreasing battery costs may lead to widespread use of household PV-battery systems. As the adoption of these systems are heavily influenced by retail tariffs, this paper analyses the effects of flat retail tariffs with households free to invest in PV battery systems. Using Perth, Australia for conte

Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang

The label noise transition matrix $T$, reflecting the probabilities that true labels flip into noisy ones, is of vital importance to model label noise and design statistically consistent classifiers. The traditional transition matrix is limited to model closed-set label noise, where noisy training data has true class labels within the noisy label set. It is

Hana Gil, Chang Ho Hyun

Equation of state of dense nuclear matter is explored in the KIDS density functional theory. Parameters of the equation of state which are coefficients of the energy density expanded in powers of $(ρ- ρ_0)/3ρ_0$ where $ρ$ is the nuclear matter density and $ρ_0$ is its density at saturation are constrained by using both nuclear data and the mass-radius relati

Benjamin Dodson, Cristian Gavrus

In this paper we prove instability of the soliton for the focusing, mass-critical generalized KdV equation. We prove that the solution to the generalized KdV equation for any initial data with mass smaller than the mass of the soliton and close to the soliton in $L^{2}$ norm must eventually move away from the soliton.

Sertac Karaman, Levent Guvenc

Different hardware platforms and their associated real time operating systems that can be used in an educational laboratory for illustrating engine electronic control unit hardware in the loop testing are presented and compared in this paper. A Matlab graphical user interface prepared for generating synthetic crank and camshaft angular position sensor signal

Lauren Hayes

Live music making can be understood as an enactive process, whereby musical experiences are created through human action. This suggests that musical worlds coevolve with their agents through repeated sensorimotor interactions with the environment (where the music is being created), and at the same time cannot be separated from their sociocultural contexts. T

Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng

Deep learning with noisy labels is a challenging task. Recent prominent methods that build on a specific sample selection (SS) strategy and a specific semi-supervised learning (SSL) model achieved state-of-the-art performance. Intuitively, better performance could be achieved if stronger SS strategies and SSL models are employed. Following this intuition, on

Lauren Hayes, Adnan Marquez-Borbon

Nearly two decades after its inception as a workshop at the ACM Conference on Human Factors in Computing Systems, NIME exists as an established international conference significantly distinct from its precursor. While this origin story is often noted, the implications of NIME's history as emerging from a field predominantly dealing with human-computer in

Gabriella Isaac, Lauren Hayes, Todd Ingalls

This paper explores the idea of using virtual textural terrains as a means of generating haptic profiles for force-feedback controllers. This approach breaks from the para-digm established within audio-haptic research over the last few decades where physical models within virtual environments are designed to transduce gesture into sonic output. We outline a

Dandan Cheng, Qian Hao, Zhiming Li

In this paper we introduce the notion of scale pressure and measure theoretic scale pressure for amenable group actions. A variational principle for amenable group actions is presented. We also describe these quantities by pseudo-orbits. Moreover, we prove that if $G$ is a finitely generated countable discrete amenable group, then the scale pressure of $G$ c

Francesco Noseda, Ilir Snopce

Let $p$ be a prime. We say that a pro-$p$ group is self-similar of index $p^k$ if it admits a faithful self-similar action on a $p^k$-ary regular rooted tree such that the action is transitive on the first level. The self-similarity index of a self-similar pro-$p$ group $G$ is defined to be the least power of $p$, say $p^k$, such that $G$ is self-similar of

Serge B. Dieterich, Andrew Simler, Todd J. Henry, Wei-Chun Jao

We use HST/STIS optical spectroscopy of ten M dwarfs in five closely separated binary systems to test models of M dwarf structure and evolution. Individual dynamical masses ranging from 0.083 to 0.405 Mo for all stars are known from previous work. We first derive temperature, radius, luminosity, surface gravity, and metallicity by fitting the BT-Settl atmosp

Kellie Corona, Katie Osterdahl, Roderic Collins, Anthony Hoogs

We present the Multiview Extended Video with Activities (MEVA) dataset, a new and very-large-scale dataset for human activity recognition. Existing security datasets either focus on activity counts by aggregating public video disseminated due to its content, which typically excludes same-scene background video, or they achieve persistence by observing public

Shuxiong Zhang

Given a branching random walk$\{Z_n\}_{n\geq0}$ on $\mathbb{R}$, let $Z_n([y,\infty))$ be the number of particles located in $[y,\infty)$ at generation $n$. It is known from \cite{Biggins1977} that under some mild conditions, $n^{-1}\log Z_n([θx^* n,\infty))$ converges a.s. to $\log m-I(θx^*)$, where $\log m-I(θx^*)$ is a positive constant. In this work, we

A. A. Coker, A. Saxena, J. T. Haraldsen

This study examines the effect of distorted triangular magnetic interactions in the Kagome lattice. Using a Holstein-Primakoff expansion, we determine the analytical solutions for classical energies and the spin-wave modes for various magnetic configurations. By understanding the magnetic phase diagram, we characterize the changes in the spin waves and exami

Richard G. Forbes

This Comment suggests that technological field electron emission (FE) papers, such as the paper under discussion [P. Serbun et al.,, Rev. Sci. Instrum. 91, 083906 (2020)], should use FE theory based on the 1956 work of Murphy and Good (MG), rather than a simplified version of FE theory based on the original 1928 work of Fowler and Nordheim (FN). Use of the 1

Andrew Matas, Joseph D. Romano

Sufficient statistics are combinations of data in terms of which the likelihood function can be rewritten without loss of information. Depending on the data volume reduction, the use of sufficient statistics as a preliminary step in a Bayesian analysis can lead to significant increases in efficiency when sampling from posterior distributions of model paramet

Atsushi Nishimura, Kazuki Tokuda, Ryohei Harada, Yutaka Hasegawa

We report the current status of the 1.85-m mm-submm telescope installed at the Nobeyama Radio Observatory (altitude 1400 m) and the future plan. The scientific goal is to reveal the physical/chemical properties of molecular clouds in the Galaxy by obtaining large-scale distributions of molecular gas with an angular resolution of several arcminutes. A semi-au

Yang Zhao, Chunyuan Li, Ping Yu, Changyou Chen

Few-shot learning features the capability of generalizing from a few examples. In this paper, we first identify that a discriminative feature space, namely a rectified metric space, that is learned to maintain the metric consistency from training to testing, is an essential component to the success of metric-based few-shot learning. Numerous analyses indicat

Behrouz Bokharaeian, Alberto Diaz

Genome-wide association (GWA) constitutes a prominent portion of studies which have been conducted on personalized medicine and pharmacogenomics. Recently, very few methods have been developed for extracting mutation-diseases associations. However, there is no available method for extracting the association of SNP-phenotype from text which considers degree o

Jinggang Zhuo, Ling Fan, Harry Jiannan Wang

With the advancement of deep learning, artificial intelligence (AI) has made many breakthroughs in recent years and achieved superhuman performance in various tasks such as object detection, reading comprehension, and video games. Generative Modeling, such as various Generative Adversarial Networks (GAN) models, has been applied to generate paintings and mus

Marco Coraggio, Pietro DeLellis, Mario di Bernardo

Complex networks are a successful framework to describe collective behaviour in many applications, but a notable gap remains in the current literature, that of proving asymptotic convergence in networks of piecewise-smooth systems. Indeed, a wide variety of physical systems display discontinuous dynamics that change abruptly, including dry friction mechanica

Takeshi Kobayashi, Rajeev Kumar Jain

Primordial electromagnetic fields can strongly affect the cosmic evolution of axions, and vice versa. We show that if helical electromagnetic fields are coherently produced in the early universe, their remnants source a field velocity to the coupled axions and enhance the relic abundance of axion dark matter. We discuss the implications for the QCD axion and

Filip Krizek, Sonka Reimers, Zdeněk Kašpar, Alberto Marmodoro

The interest in understanding scaling limits of magnetic textures such as domain walls spans the entire field of magnetism from its relativistic quantum fundamentals to applications in information technologies. The traditional focus of the field on ferromagnets has recently started to shift towards antiferromagnets which offer a rich materials landscape and

Danish Pruthi, Rachit Bansal, Bhuwan Dhingra, Livio Baldini Soares

While many methods purport to explain predictions by highlighting salient features, what aims these explanations serve and how they ought to be evaluated often go unstated. In this work, we introduce a framework to quantify the value of explanations via the accuracy gains that they confer on a student model trained to simulate a teacher model. Crucially, the

David Andersson, Sigrid Bratsberg, Andrew K. Ringsmuth, Astrid S. de Wijn

A pressing challenge for coming decades is sustainable and just management of large-scale common-pool resources including the atmosphere, biodiversity and public services. This poses a difficult collective action problem because such resources may not show signs that usage restraint is needed until tragedy is almost inevitable. To solve this problem, a suffi

Javier Flores, Sergi Nadal, Oscar Romero

We study the problem of discovering joinable datasets at scale. This is, how to automatically discover pairs of attributes in a massive collection of independent, heterogeneous datasets that can be joined. Exact (e.g., based on distinct values) and hash-based (e.g., based on locality-sensitive hashing) techniques require indexing the entire dataset, which is

Aaron J. Snoswell, Surya P. N. Singh, Nan Ye

We provide new perspectives and inference algorithms for Maximum Entropy (MaxEnt) Inverse Reinforcement Learning (IRL), which provides a principled method to find a most non-committal reward function consistent with given expert demonstrations, among many consistent reward functions. We first present a generalized MaxEnt formulation based on minimizing a KL-

Nicholas Sharp, Souhaib Attaiki, Keenan Crane, Maks Ovsjanikov

We introduce a new general-purpose approach to deep learning on 3D surfaces, based on the insight that a simple diffusion layer is highly effective for spatial communication. The resulting networks are automatically robust to changes in resolution and sampling of a surface -- a basic property which is crucial for practical applications. Our networks can be d

Stuart F Knowles, Nicole E Weckman, Vincent J Lim, Douwe J Bonthuis

Modification of surface properties by polymer adsorption is a widely used technique to tune interactions in molecular experiments such as nanopore sensing. Here, we investigate how the ionic current noise through solid-state nanopores reflects the adsorption of short, neutral polymers to the pore surface. The power spectral density of the noise shows a chara

Tianhong Wang, Vladimir Khudik, Jihoon Kim, Gennady Shvets

We introduce a quasi-static particle-in-cell (PIC) code -- WAND-PIC -- which does not suffer from some of the common limitations of many quasi-static PICs, such as the need for a predictor-corrector method in solving electromagnetic fields. We derive the field equations under quasi-static (QS) approximation and find the explicit form of the "time" de

Weisheng Si, Balume Mburano, Wei Xing Zheng, Tie Qiu

Infrastructure networks such as the Internet backbone and power grids are essential for our everyday lives. With the prevalence of cyber-attacks on them, measuring their robustness has become an important issue. To date, many robustness metrics have been proposed. It is desirable for a robustness metric to possess the following three properties: considering

S. K. Adhikari

We demonstrate exotic stable quasi-two-dimensional solitons in a Rashba or a Dresselhaus spin-orbit (SO) coupled hyperfine spin-1 ($F=1$) trap-less antiferromagnetic Bose-Einstein condensate using the mean-field Gross-Pitaevskii equation. For weak SO coupling, the solitons are of the $(-1,0,+1)$ or $(+1,0,-1)$ type with intrinsic vorticity, for Rashba or Dre

Michelle Daher

We show that for any $n\geq6$, for any $m$, we can find $m$ non-homeomorphic $n$-manifolds that can be mapped by cell-like maps onto the same space $X$.

Lukas Kölsch, Björn Kriepke, Gohar M. Kyureghyan

We consider image sets of differentially $d$-uniform maps of finite fields. We present a lower bound on the image size of such maps and study their preimage distribution, by extending methods used for planar maps. We apply the results to study $d$-uniform Dembowski-Ostrom polynomials. Further, we focus on a particularly interesting case of APN maps on binary

Matt Landreman

A new paradigm for rapid stellarator configuration design has been recently demonstrated, in which the shapes of quasisymmetric or omnigenous flux surfaces are computed directly using an expansion in small distance from the magnetic axis. To further develop this approach, here we derive several other quantities of interest that can be rapidly computed from t

Jeremy Hahn, Dylan Wilson

We equip $\mathrm{BP} \langle n \rangle$ with an $\mathbb{E}_3$-$\mathrm{BP}$-algebra structure, for each prime $p$ and height $n$. The algebraic $K$-theory of this ring is of chromatic height exactly $n+1$, and the map $\mathrm{K}(\mathrm{BP}\langle n \rangle)_{(p)} \to \mathrm{L}_{n+1}^{f} \mathrm{K}(\mathrm{BP}\langle n\rangle)_{(p)}$ has bounded above fi

Yuchen Wang, Matthieu Chan Chee, Ziyad Edher, Minh Duc Hoang

Black Sigatoka disease severely decreases global banana production, and climate change aggravates the problem by altering fungal species distributions. Due to the heavy financial burden of managing this infectious disease, farmers in developing countries face significant banana crop losses. Though scientists have produced mathematical models of infectious di

Liliana Borcea, Vladimir Druskin, Jörn Zimmerling

We introduce a reduced order model (ROM) methodology for inverse electromagnetic wave scattering in layered lossy media, using data gathered by an antenna which generates a probing wave and measures the time resolved reflected wave. We recast the wave propagation problem as a passive infinite-dimensional dynamical system, whose transfer function is expressed

Siyu Heng, Wendy P. O'Meara, Ryan A. Simmons, Dylan S. Small

Although interventional studies demonstrate that preventing malaria during pregnancy can reduce the low birth weight (i.e., child&#39;s birth weight $<$ 2,500 grams) rate, it remains unknown whether natural changes in parasite transmission and malaria burden can improve birth outcomes. We conduct an observational study of the effect of changing malaria burde

Yikang Shen, Yi Tay, Che Zheng, Dara Bahri

There are two major classes of natural language grammar -- the dependency grammar that models one-to-one correspondences between words and the constituency grammar that models the assembly of one or several corresponded words. While previous unsupervised parsing methods mostly focus on only inducing one class of grammars, we introduce a novel model, StructFo

Matt Luckcuck

Formal Methods are mathematically-based techniques for software design and engineering, which enable the unambiguous description of and reasoning about a system&#39;s behaviour. Autonomous systems use software to make decisions without human control, are often embedded in a robotic system, are often safety-critical, and are increasingly being introduced into

Axel Osmond

Diers developed a general theory of right multi-adjoint functors leading to a purely categorical, point-set construction of spectra. Situations of multiversal properties return sets of canonical solutions rather than a unique one. In the case of a right multi-adjoint, each object deploys a canonical cone of local units jointly assuming the role of the unit o

Céline Comte

The problem of appropriately matching items subject to compatibility constraints arises in a number of important applications. While most of the literature on matching theory focuses on a static setting with a fixed number of items, several recent works incorporated time by considering a stochastic model in which items of different classes arrive according t

Ivan Zhivkov Stefanov

The paper studies the uniqueness and the monotonicity of the mass-spin relation of black holes the X-ray power density spectra of which contain twin high-frequency quasi-periodic oscillations in 3:2 ratio. It is found that for geodesic models the properties of the mass-spin relation are independent of the observed frequencies, i.e. they are independent of th

Marie-Anne Bizouard, Patricio Maturana-Russel, Alejandro Torres-Forné, Martin Obergaulinger

The eventual detection of gravitational waves from core-collapse supernovae (CCSN) will help improve our current understanding of the explosion mechanism of massive stars. The stochastic nature of the late post-bounce gravitational wave signal due to the non-linear dynamics of the matter involved and the large number of degrees of freedom of the phenomenon m

Hugo Barbosa, Surendra Hazarie, Brian Dickinson, Aleix Bassolas

Given the rapid recent trend of urbanization, a better understanding of how urban infrastructure mediates socioeconomic interactions and economic systems is of vital importance. While the accessibility of location-enabled devices as well as large-scale datasets of human activities, has fueled significant advances in our understanding, there is little agreeme

A. A. Dontsov, A. P. Dmitriev

In this paper, we consider analytically the density evolution of a spinless Fermi liquid with a nonlinear dispersion relation into which one particle is injected. The interaction is point-like and the temperature is zero. We obtain a formula for the evolution of the density and discuss the picture it gives as well as the physics behind it. Compared to the ca

Ihar Lobach, Sergei Nagaitsev, Valeri Lebedev, Aleksandr Romanov

Generally, turn-to-turn power fluctuations of incoherent spontaneous synchrotron radiation in a storage ring depend on the 6D phase-space distribution of the electron bunch. In some cases, if only one parameter of the distribution is unknown, this parameter can be determined from the measured magnitude of these power fluctuations. In this Letter, we report a

Daniel Bultrini, Max Hunter Gordon, Esperanza López, Germȧn Sierra

We report the observation and characterisation of a systematic error in the implementation of $U_3$ gates in the IBM quantum computers. The error appears as a consistent shift in one of the angles of the gate, whose magnitude does not correlate with IBM&#39;s cited errors calculated using Clifford randomized benchmarking. We propose a simple mitigation proce

Sean Colin-Ellerin, Xi Dong, Donald Marolf, Mukund Rangamani

This work is the first step in a two-part investigation of real-time replica wormholes. Here we study the associated real-time gravitational path integral and construct the variational principle that will define its saddle-points. We also describe the general structure of the resulting real-time replica wormhole saddles, setting the stage for construction of

Rihuan Ke, Angelica Aviles-Rivero, Saurabh Pandey, Saikumar Reddy

Semantic segmentation has been widely investigated in the community, in which the state of the art techniques are based on supervised models. Those models have reported unprecedented performance at the cost of requiring a large set of high quality segmentation masks. To obtain such annotations is highly expensive and time consuming, in particular, in semanti

Elvis Rojas, Albert Njoroge Kahira, Esteban Meneses, Leonardo Bautista Gomez

Deep learning (DL) applications are increasingly being deployed on HPC systems, to leverage the massive parallelism and computing power of those systems for DL model training. While significant effort has been put to facilitate distributed training by DL frameworks, fault tolerance has been largely ignored. In this work, we evaluate checkpoint-restart, a com

Haozheng Luo, Ruiyang Qin, Chenwei Xu, Guo Ye

In this paper, we introduce a robotic agent specifically designed to analyze external environments and address participants' questions. The primary focus of this agent is to assist individuals using language-based interactions within video-based scenes. Our proposed method integrates video recognition technology and natural language processing models within

Tiziano Peraro, Lorenzo Tancredi

In this paper, we elaborate on a method to decompose multiloop multileg scattering amplitudes into Lorentz-invariant form factors, which exploits the simplifications that arise from considering four-dimensional external states. We propose a simple and general approach that applies to both fermionic and bosonic amplitudes and allows us to identify a minimal n

Revan MacQueen, Natalie Bombardieri, James R. Wright, Karim Ali

Malware attacks are costly. To mitigate against such attacks, organizations deploy malware detection tools that help them detect and eventually resolve those threats. While running only the best available tool does not provide enough coverage of the potential attacks, running all available tools is prohibitively expensive in terms of financial cost and compu

Alin Bostan, Manuel Kauers, Thibaut Verron

Beaton, Owczarek and Xu (2019) studied generating functions of Kreweras walks and of reverse Kreweras walks in the quarter plane, with interacting boundaries. They proved that for the reverse Kreweras step set, the generating function is always algebraic, and for the Kreweras step set, the generating function is always D-finite. However, apart from the parti

A. E. Derbyshev, A. M. Povolotsky

We study the model of the totally asymmetric exclusion process with generalized update, which compared to the usual totally asymmetric exclusion process, has an additional parameter enhancing clustering of particles. We derive the exact multiparticle distributions of distances travelled by particles on the infinite lattice for two types of initial conditions

Geoffrey Chinot, Matthias Löffler, Sara van de Geer

This article develops a general theory for minimum norm interpolating estimators and regularized empirical risk minimizers (RERM) in linear models in the presence of additive, potentially adversarial, errors. In particular, no conditions on the errors are imposed. A quantitative bound for the prediction error is given, relating it to the Rademacher complexit

Ferenc Bencs, Péter Csikvári, Guus Regts

We use Wagner&#39;s weighted subgraph counting polynomial to prove that the partition function of the anti-ferromagnetic Ising model on line graphs is real rooted and to prove that roots of the edge cover polynomial have length at most $4$. We moreover discuss how our results relate to efficient algorithms for approximately computing evaluations of these pol

Dulce M. Morales, Marcel Risch

Discovery of electrocatalytic materials for high-performance energy conversion and storage applications relies on the adequate characterization of their intrinsic activity, which is currently hindered by the dearth of a protocol for consistent and precise determination of double layer capacitance (CDL). Herein, we propose a seven-step method that aims to det

Luca Di Persio, Matteo Garbelli, Lucian Maticiuc, Adrian Zălinescu

We prove the existence and uniqueness of the solution of a BSDE with time-delayed generators in the small delay setting (or equivalently small Lipschitz constant), which employs the Stieltjes integral with respect to an increasing continuous stochastic process. Moreover, we obtain a result of continuity of the solution with regard to the increasing process,

Lei Miao, Dingde Jiang

Wireless secret sharing is crucial to information security in the era of Internet of Things. One method is to utilize the effect of the randomness of the wireless channel in the data link layer to generate the common secret between two legitimate users Alice and Bob. This paper studies this secret sharing mechanism from the perspective of game theory. In par

Edward F. Redish

When students are learning to use math in physics, one of the most important ideas they need to learn is that equations are not just calculational tools; they represent relationships between physical variables that change together (covary). How much a change in one variable or parameter is associated with a change in another depends on how they appear in the

Jonathan Freundlich, Dan Maoz

The delay time distribution (DTD) of Type-Ia supernovae (SNe Ia) is important for understanding chemical evolution, SN Ia progenitors, and SN Ia physics. Past estimates of the DTD in galaxy clusters have been deduced from SN Ia rates measured in cluster samples observed at various redshifts, corresponding to different time intervals after a presumed initial

Sarah Oscroft, Adam M. Sykulski, Jeffrey J. Early

Drifters deployed in close proximity collectively provide a unique observational data set with which to separate mesoscale and submesoscale flows. In this paper we provide a principled approach for doing so by fitting observed velocities to a local Taylor expansion of the velocity flow field. We demonstrate how to estimate mesoscale and submesoscale quantiti

Mustafa Abdallah, Sayan Mitra, Shreyas Sundaram, Saurabh Bagchi

We consider a security setting in which the Cyber-Physical System (CPS) is composed of subnetworks where each subnetwork is under ownership of one defender. Such CPS can be represented by an attack graph where the defenders are required to invest (subject to a budget constraint) on the graph&#39;s edges in order to protect their critical assets (where each d

Andrzej Chlebicki, Pawel Jakubczyk

We employ the functional renormalization group framework at the second order in the derivative expansion to study the $O(N)$ models continuously varying the number of field components $N$ and the spatial dimensionality $d$. We in particular address the Cardy-Hamber prediction concerning nonanalytical behavior of the critical exponents $ν$ and $η$ across a li

Abdul Fatir Ansari, Ming Liang Ang, Harold Soh

Deep generative modeling has seen impressive advances in recent years, to the point where it is now commonplace to see simulated samples (e.g., images) that closely resemble real-world data. However, generation quality is generally inconsistent for any given model and can vary dramatically between samples. We introduce Discriminator Gradient flow (DGflow), a

Mingjian Zhu, Kai Han, Changbin Yu, Yunhe Wang

Feature pyramid network (FPN) is a critical component in modern object detection frameworks. The performance gain in most of the existing FPN variants is mainly attributed to the increase of computational burden. An attempt to enhance the FPN is enriching the spatial information by expanding the receptive fields, which is promising to largely improve the det

Michael Sonner, Alessio Lerose, Dmitry A. Abanin

Many-body localized (MBL) phases of disordered quantum many-particle systems have a number of unique properties, including failure to act as a thermal bath and protection of quantum coherence. Studying MBL is complicated by the effects of rare ergodic regions, necessitating large system sizes and averaging over many disorder configurations. Here, building on

Colin DeGraf, Debora Sijacki, Tiziana Di Matteo, Kelly Holley-Bockelmann

With projects such as Laser Interferometer Space Antenna (LISA) and Pulsar Timing Arrays expected to detect gravitational waves from supermassive black hole mergers in the near future, it is key that we understand what we expect those detections to be, and maximize what we can learn from them. To address this, we study the mergers of supermassive black holes

Li Huang, Samuel D. Lane, Ian M. Lewis, Zhen Liu

The LHC is exploring electroweak (EW) physics at the scale EW symmetry is broken. As the LHC and new high energy colliders push our understanding of the Standard Model to ever-higher energies, it will be possible to probe not only the breaking of but also the restoration of EW symmetry. We propose to observe EW restoration in double EW boson production via t

Ian Low, Nausheen R. Shah, Xiao-Ping Wang

Null results from searches for new physics at the Large Hadron Collider (LHC) tend to enforce the belief that new particles must be much heavier than the weak scale. We undertake a systematic study of the interplay between Higgs alignment and $CP$-violation in complex two-Higgs-doublet models, which enables us to construct a $CP$-violating scenario where new

José Luis Bernal, Andrea Caputo, Marc Kamionkowski

The nature of dark matter is a longstanding mystery in cosmology, which can be studied with laboratory or collider experiments, as well as astrophysical and cosmological observations. In this work, we propose realistic and efficient strategies to detect radiative products from dark-matter decays with line-intensity mapping (LIM) experiments. This radiation w

Seung-Joo Lee, Wolfgang Lerche, Guglielmo Lockhart, Timo Weigand

We investigate holomorphic anomalies of partition functions underlying string compactifications on Calabi-Yau fourfolds with background fluxes. For elliptic fourfolds the partition functions have an alternative interpretation as elliptic genera of N=1 supersymmetric string theories in four dimensions, or as generating functions for relative Gromov-Witten inv

Erik E. Aldape, Tessa Cookmeyer, Aavishkar A. Patel, Ehud Altman

We introduce an effective theory for quantum critical points (QCPs) in heavy fermion systems, involving a change in carrier density without symmetry breaking. Our new theory captures a strongly coupled metallic QCP, leading to robust marginal Fermi liquid transport phenomenology, and associated linear in temperature ($T$) &#34;strange metal&#34; resistivity,

Jasmin Graf, Sanchar Sharma, Hans Huebl, Silvia Viola Kusminskiy

We put forward the concept of an optomagnonic crystal: a periodically patterned structure at the microscale based on a magnetic dielectric, which can co-localize magnon and photon modes. The co-localization in small volumes can result in large values of the photon-magnon coupling at the single quanta level, which opens perspectives for quantum information pr

Huiyu Wang, Yukun Zhu, Hartwig Adam, Alan Yuille

We present MaX-DeepLab, the first end-to-end model for panoptic segmentation. Our approach simplifies the current pipeline that depends heavily on surrogate sub-tasks and hand-designed components, such as box detection, non-maximum suppression, thing-stuff merging, etc. Although these sub-tasks are tackled by area experts, they fail to comprehensively solve

Chaim Even-Zohar, Tsviqa Lakrec, Ran J. Tessler

Given a random text over a finite alphabet, we study the frequencies at which fixed-length words occur as subsequences. As the data size grows, the joint distribution of word counts exhibits a rich asymptotic structure. We investigate all linear combinations of subword statistics, and fully characterize their different orders of magnitude using diverse algeb

Daniel Ranard, Michael Walter, Freek Witteveen

Unitary dynamics with a strict causal cone (or &#34;light cone&#34;) have been studied extensively, under the name of quantum cellular automata (QCAs). In particular, QCAs in one dimension have been completely classified by an index theory. Physical systems often exhibit only approximate causal cones; Hamiltonian evolutions on the lattice satisfy Lieb-Robins

Simina Brânzei, Dimitris Paparas, Nicholas Recker

We study searching and sorting in rounds motivated by a fair division question: given a cake cutting problem with $n$ players, compute a fair allocation in at most $k$ rounds of interaction with the players. Rounds interpolate between the simultaneous and the fully adaptive settings, also capturing parallel complexity. We find that proportional cake cutting

Jan D. Burger, Jorge Peñarrubia, Jesús Zavala

In slowly evolving spherical potentials, $Φ(r,t)$, radial actions are typically assumed to remain constant. Here, we construct dynamical invariants that allow us to derive the evolution of radial actions in spherical central potentials with an arbitrary time dependence. We show that to linear order, radial actions oscillate around a constant value with an am

Martina Gschwendtner, Andreas Winter

A universal programmable quantum processor uses program quantum states to apply an arbitrary quantum channel to an input state. We generalize the concept of a finite-dimensional programmable quantum processor to infinite dimension assuming an energy constraint on the input and output of the target quantum channels. By proving reductions to and from finite-di

Alim Sukhtayev, Kevin Zumbrun

Extending work of Carty, we show that $H^1$ solutions of a simplified 1D BGK model decay exponentially in $L^2$ to a subclass of the class of grossly determined solutions as defined by Truesdell and Muncaster. In the process, we determine the spectrum and generalized eigenfunctions of the associated non-selfadjoint linearized operator and derive the associat

Hasret Turkeri, Xinyu Zhao, Metin Muradgolu

The LES/PDF methodology is applied to the Cambridge/Sandia turbulent stratified flame series under swirling conditions. The methane/air chemistry is represented by a 16-species reduced ARM1 mechanism, and the in situ adaptive tabulation method is adopted to accelerate the chemistry calculation. Effects of differential diffusion and heat loss through the bluf

Noel Brady, Robert Kropholler, Ignat Soroko

We prove foundational results for homological Dehn functions of groups of type $FP_2$ such as superadditivity and the invariance under quasi-isometry. We then study the homological Dehn functions of Leary&#39;s groups $G_L(S)$ providing methods to obtain uncountably many groups with a given homological Dehn function. This allows us to show that there exist g

Mike Ludkovski

We introduce mlOSP, a computational template for Machine Learning for Optimal Stopping Problems. The template is implemented in the R statistical environment and publicly available via a GitHub repository. mlOSP presents a unified numerical implementation of Regression Monte Carlo (RMC) approaches to optimal stopping, providing a state-of-the-art, open-sourc

Mohit Mayank

Recent word embeddings techniques represent words in a continuous vector space, moving away from the atomic and sparse representations of the past. Each such technique can further create multiple varieties of embeddings based on different settings of hyper-parameters like embedding dimension size, context window size and training method. One additional varie

Zachary Teed, Jia Deng

We address the problem of scene flow: given a pair of stereo or RGB-D video frames, estimate pixelwise 3D motion. We introduce RAFT-3D, a new deep architecture for scene flow. RAFT-3D is based on the RAFT model developed for optical flow but iteratively updates a dense field of pixelwise SE3 motion instead of 2D motion. A key innovation of RAFT-3D is rigid-m

Tamás Szabados

The aim of this paper is to give a simpler, more usable sufficient condition to the regularity of generic weakly stationary time series. Also, this condition is used to show how regular processes satisfying these sufficient conditions can be approximated by a lower rank \emph{regular} process. The relevance of these issues is shown by the ever increasing pre