July 2019 arXiv papers — page 108

Xiang Meng

The portfolio optimisation problem, first raised by Harry Markowitz in 1952, has been a fundamental and central topic to understanding the stock market and making decisions. There has been plenty of works contributing to development of the mean-variance optimisation (MVO) so far. In this paper, one kind of them, namely, dynamic mean-variance optimisation (DM

Jingbo Lin, Weipeng Jing, Houbing Song

High-resolution aerial images have a wide range of applications, such as military exploration, and urban planning. Semantic segmentation is a fundamental method extensively used in the analysis of high-resolution aerial images. However, the ground objects in high-resolution aerial images have the characteristics of inconsistent scales, and this feature usual

Xiao-Bao Shu, Linxin Shu, Fei Xu

In this article, we consider mild solutions to a class of impulsive fractional evolution equations of order $0<α<1$. After analyzing analytic results reported in the literature using Mittag-Leffer function, $α$-resolvent operator theory, we propose a more appropriate new definition of mild solutions for impulsive fractional evolution equations by replacing t

Ankit Pensia, Varun Jog, Po-Ling Loh

We consider the problem of estimating the common mean of independently sampled data, where samples are drawn in a possibly non-identical manner from symmetric, unimodal distributions with a common mean. This generalizes the setting of Gaussian mixture modeling, since the number of distinct mixture components may diverge with the number of observations. We pr

Venkatramanan D, Vinod John

In this paper, a photovoltaic (PV) reconfigurable grid-tied inverter (RGTI) scheme is proposed. Unlike a conventional GTI that ceases operation during a power outage, the RGTI is designed to act as a regular GTI in the on-grid mode but it is reconfigured to function as a DC-DC charge-controller that continues operation during a grid outage. During this perio

J. H. Alvarenga Nogueira, D. Colasante, V. Gherardi, T. Frederico

The ladder Bethe-Salpeter Equation of a bound (1/2)+ system, composed by a fermion and a scalar boson, is solved in Minkowski space, for the first time. The formal tools are the same already successfully adopted for two-scalar and two-fermion systems, namely the Nakanishi integral representation of the Bethe-Salpeter amplitude and the light-front projection

Nicholas Zobrist, Byeong Ho Eom, Peter Day, Benjamin A. Mazin

The energy resolution of a single photon counting Microwave Kinetic Inductance Detector (MKID) can be degraded by noise coming from the primary low temperature amplifier in the detector&#39;s readout system. Until recently, quantum limited amplifiers have been incompatible with these detectors due to dynamic range, power, and bandwidth constraints. However,

Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han

In this work, we propose an introspection technique for deep neural networks that relies on a generative model to instigate salient editing of the input image for model interpretation. Such modification provides the fundamental interventional operation that allows us to obtain answers to counterfactual inquiries, i.e., what meaningful change can be made to t

Dwarikanath Mahapatra

We propose a method to predict severity of age related macular degeneration (AMD) from input optical coherence tomography (OCT) images. Although there is no standard clinical severity scale for AMD, we leverage deep learning (DL) based image registration and clustering methods to identify diseased cases and predict their severity. Experiments demonstrate our

Samira Sheykhi, Mahmoud Payami

In this work using the density functional theory (DFT), we have studied the structural, electronic and magnetic properties of uranium dioxide with antiferromagnetic 1k-, 2k-, and 3k-order structures. Ordinary approximations in DFT, such as the local density approximation (LDA) or generalized gradient approximation (GGA), usually predict incorrect metallic be

Sung Wook Han, Kim Myung-Whun

We measured photon absorption in dielectric media and proposed the photon-version Beer-Lambert&#39;s law to quantify the absorption. We used a Hong-Ou-Mandel interferometer and 810 nm twin-photons. We found that the depth ratio of the null point in the interference patterns of the interferometer agreed with the classical transmittance of the samples. We esta

Ming-Hsun Yang, Jwo-Yuh Wu, Tsang-Yi Wang, Robert G. Maunder

This paper proposes a fusion-based cooperative support identification scheme for distributed compressive sparse signal recovery via resource-constrained wireless sensor networks. The proposed support identification protocol involves: (i) local sparse sensing for economizing data gathering and storage, (ii) local binary decision making for partial support kno

Hsiang-En Cherng, Chia-Hui Chang

With the development of Natural Language Processing, Automatic question-answering system such as Waston, Siri, Alexa, has become one of the most important NLP applications. Nowadays, enterprises try to build automatic custom service chatbots to save human resources and provide a 24-hour customer service. Evaluation of chatbots currently relied greatly on hum

Xiu-Shen Wei, Jianxin Wu, Quan Cui

Computer vision (CV) is the process of using machines to understand and analyze imagery, which is an integral branch of artificial intelligence. Among various research areas of CV, fine-grained image analysis (FGIA) is a longstanding and fundamental problem, and has become ubiquitous in diverse real-world applications. The task of FGIA targets analyzing visu

Dmitry S. Kaparulin

We consider the issue of correspondence between symmetries and conserved quantities in the class of linear relativistic higher-derivative theories of derived type. In this class of models the wave operator is a polynomial in another formally self-adjoint operator, while each isometry of space-time gives rise to the series of symmetries of action functional.

D. S. Kaparulin, S. L. Lyakhovich, I. A. Retuntsev

We propose the model of massive spinning particle traveling in four-dimensional Minkowski space. The equations of motion of the particle follow from the fact that all the classical paths of the particle lie on a cylinder whose position in Minkowski space is determined by the particle&#39;s linear momentum and total angular momentum. All the paths on one and

D. S. Kaparulin, S. L. Lyakhovich, I. A. Retuntsev

We proceed from the fact that the classical paths of irreducible massive spinning particle lie on a circular cylinder with the time-like axis in Minkowski space. Assuming that all the classical paths on the cylinder are gauge-equivalent, we derive the equations of motion for the cylindrical curves. These equations are non-Lagrangian, but they admit interpret

Astik Biswas, Raghav Menon, Ewald van der Westhuizen, Thomas Niesler

We present improvements in automatic speech recognition (ASR) for Somali, a currently extremely under-resourced language. This forms part of a continuing United Nations (UN) effort to employ ASR-based keyword spotting systems to support humanitarian relief programmes in rural Africa. Using just 1.57 hours of annotated speech data as a seed corpus, we increas

Qing Lyu, Hongming Shan, Ge Wang

Magnetic resonance imaging (MRI) is a widely used medical imaging modality. However, due to the limitations in hardware, scan time, and throughput, it is often clinically challenging to obtain high-quality MR images. The super-resolution approach is potentially promising to improve MR image quality without any hardware upgrade. In this paper, we propose an e

Subekshya Bidari, Orit Peleg, Zachary P Kilpatrick

To effectively forage in natural environments, organisms must adapt to changes in the quality and yield of food sources across multiple timescales. Individuals foraging in groups act based on both their private observations and the opinions of their neighbors. How do these information sources interact in changing environments? We address this problem in the

Aizhan Imankulova, Raj Dabre, Atsushi Fujita, Kenji Imamura

This paper proposes a novel multilingual multistage fine-tuning approach for low-resource neural machine translation (NMT), taking a challenging Japanese--Russian pair for benchmarking. Although there are many solutions for low-resource scenarios, such as multilingual NMT and back-translation, we have empirically confirmed their limited success when restrict

Zheng Zhou, Yu Fang, Han Chen, Yipeng Wu

High energy electron radiography (HEER) is a promising tool for high energy density physics diagnostics, apart from other tools like X/γ ray shadowgraphy and high energy proton radiography. Impressive progresses have been made in development and application of HEER in past few years, and proved its potentials for high-resolution imaging of static opaque obje

Deyu Xu, Ahamed Bilal, Junming Zhao, Linhua Liu

Near-field radiative heat transfer (NFRHT) between rough surfaces, due to its widespread presence in engineering practice of near-field energy utilization, requires indepth studies, especially from the perspective of physical mechanism. In this paper, an effective multilayer model is built to approach the NFRHT between random rough surfaces of silicon carbid

Ruggero Lot, Franco Pellegrini, Yusuf Shaidu, Emine Kucukbenli

Prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package &#34;Properties from Artifi

Victoria Xu, Matt Jaffe, Cristian D. Panda, Sofus L. Kristensen

Atom interferometers are powerful tools for both measurements in fundamental physics and inertial sensing applications. Their performance, however, has been limited by the available interrogation time of freely falling atoms in a gravitational field. We realize an unprecedented interrogation time of 20 seconds by suspending the spatially-separated atomic wav

Yixuan Lin, Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang

This paper considers a distributed reinforcement learning problem in which a network of multiple agents aim to cooperatively maximize the globally averaged return through communication with only local neighbors. A randomized communication-efficient multi-agent actor-critic algorithm is proposed for possibly unidirectional communication relationships depicted

Soheil Khorram, Melvin G McInnis, Emily Mower Provost

Time-continuous dimensional descriptions of emotions (e.g., arousal, valence) allow researchers to characterize short-time changes and to capture long-term trends in emotion expression. However, continuous emotion labels are generally not synchronized with the input speech signal due to delays caused by reaction-time, which is inherent in human evaluations.

Yu-Siang Wang, Hung-Ting Su, Chen-Hsi Chang, Zhe-Yu Liu

We introduce a novel task, Video Question Generation (Video QG). A Video QG model automatically generates questions given a video clip and its corresponding dialogues. Video QG requires a range of skills -- sentence comprehension, temporal relation, the interplay between vision and language, and the ability to ask meaningful questions. To address this, we pr

Yingtong Dou, Weijian Li, Zhirong Liu, Zhenhua Dong

Download fraud is a prevalent threat in mobile App markets, where fraudsters manipulate the number of downloads of Apps via various cheating approaches. Purchased fake downloads can mislead recommendation and search algorithms and further lead to bad user experience in App markets. In this paper, we investigate download fraud problem based on a company&#39;s

Zongshen Wu, Chin-Ya Huang, Parameswaran Ramanathan

Millimeter wave (mmWave) access networks have the potential to meet the high-throughput and low-latency needs of immersive applications. However, due to the highly directional nature of the mmWave beams and their susceptibility to beam misalignment and blockage resulting from user movements and rotations, the associated mmWave links are vulnerable to large c

Michel Barbeau, Joaquin Garcia-Alfaro

We show that the Quantum Generative Adversarial Network (QGAN) paradigm can be employed by an adversary to learn generating data that deceives the monitoring of a Cyber-Physical System (CPS) and to perpetrate a covert attack. As a test case, the ideas are elaborated considering the navigation data of a Micro Aerial Vehicle (MAV). A concrete QGAN design is pr

Saurabh Sawlani, Junxing Wang

We give the first fully dynamic algorithm which maintains a $(1-ε)$-approximate densest subgraph in worst-case time $\text{poly}(\log n, ε^{-1})$ per update. Dense subgraph discovery is an important primitive for many real-world applications such as community detection, link spam detection, distance query indexing, and computational biology. We approach the

Eric R. Coughlin, C. J. Nixon

The tidal disruption of a star by a supermassive black hole, and the subsequent accretion of the disrupted debris by that black hole, offers a direct means to study the inner regions of otherwise-quiescent galaxies. These tidal disruption events (TDEs) are being discovered at an ever-increasing rate. We present a model for the evolution of the tidally-disrup

Shuxing Li, Alexander Pott

The concept of formal duality was proposed by Cohn, Kumar and Schürmann, which reflects a remarkable symmetry among energy-minimizing periodic configurations. This formal duality was later translated into a purely combinatorial property by Cohn, Kumar, Reiher and Schürmann, where the corresponding combinatorial objects were called formally dual pairs. So far

Akaki Tikaradze

A classical theorem of Veldkamp describes the center of an enveloping algebra of a Lie algebra of a semi-simple algebraic group in characteristic $p.$ We generalize this result to a class of Lie algebras with a property that they arise as the reduction modulo $p\gg 0$ from an algebraic Lie algebra $\mathfrak{g},$ such that $\mathfrak{g}$ has no nontrivial se

Majed El Helou, Sabine Süsstrunk

Blind and universal image denoising consists of using a unique model that denoises images with any level of noise. It is especially practical as noise levels do not need to be known when the model is developed or at test time. We propose a theoretically-grounded blind and universal deep learning image denoiser for additive Gaussian noise removal. Our network

Svetlana V. Butler

Topological measures and deficient topological measures are defined on open and closed subsets of a topological space, generalize regular Borel measures, and correspond to (non-linear in general) functionals that are linear on singly generated subalgebras or singly generated cones of functions. They lack subadditivity, and many standard techniques of measure

Jonas Iskander, Vanshika Jain, Victoria Talvola

The partition function $p(n)$ has been a testing ground for applications of analytic number theory to combinatorics. In particular, Hardy and Ramanujan invented the &#34;circle method&#34; to estimate the size of $p(n)$, which was later perfected by Rademacher who obtained an exact formula. Recently, Chan and Wang considered the fractional partition function

Piotr Pokarowski, Wojciech Rejchel, Agnieszka Soltys, Michal Frej

It is known that the Thresholded Lasso (TL), SCAD or MCP correct intrinsic estimation bias of the Lasso. In this paper we propose an alternative method of improving the Lasso for predictive models with general convex loss functions which encompass normal linear models, logistic regression, quantile regression or support vector machines. For a given penalty w

Ammar Alali, Francois Hamon, Bradley Mallison, Hamdi Tchelepi

In numerical simulations of multiphase flow and transport in fractured porous media, the estimation of the hydrocarbon recovery requires accurately predicting the capillary-driven imbibition rate of the wetting phase initially present in the fracture into the low-permeability matrix. In the fully implicit finite-volume scheme, this entails a robust methodolo

Darya E. Apushkinskaya, Alexander I. Nazarov, Dian K. Palagachev, Lubomira G. Softova

We study linear and quasilinear Venttsel boundary value problems involving elliptic operators with discontinuous coefficients. On the base of the a priori estimates obtained, maximal regularity and strong solvability in Sobolev spaces are proved.

Danielle R. Yahne, Liurukara D. Sanjeewa, Athena S. Sefat, Bradley S. Stadelman

Spin-1/2 antiferromagnetic triangular lattice models are paradigms of geometrical frustration, revealing very different ground states and quantum effects depending on the nature of anisotropies in the model. Due to strong spin orbit coupling and crystal field effects, rare-earth ions can form pseudo-spin-1/2 magnetic moments with anisotropic single-ion and e

Wolf-Patrick Düll

We consider the two-dimensional water wave problem in an infinitely long canal of finite depth both with and without surface tension. In order to describe the evolution of the envelopes of small oscillating wave packet-like solutions to this problem the Nonlinear Schrödinger equation can be derived as a formal approximation equation. In recent years, the val

Miguel Ballesteros, Dirk-André Deckert, Felix Hänle

In scattering experiments, physicists observe so-called resonances as peaks at certain energy values in the measured scattering cross sections per solid angle. These peaks are usually associate with certain scattering processes, e.g., emission, absorption, or excitation of certain particles and systems. On the other hand, mathematicians define resonances as

Marius Oltean, Richard J. Epp, Carlos F. Sopuerta, Alessandro D. A. M. Spallicci

An idealized &#34;test&#34; object in general relativity moves along a geodesic. However, if the object has a finite mass, this will create additional curvature in the spacetime, causing it to deviate from geodesic motion. If the mass is nonetheless sufficiently small, such an effect is usually treated perturbatively and is known as the gravitational self-fo

Laira Aggarwal, Sam Nelson, Patricia Rivera

We enhance the tribracket counting invariant with \textit{tribracket brackets}, skein invariants of tribracket-colored oriented knots and links analogously to biquandle brackets. This infinite family of invariants includes the classical quantum invariants and tribracket cocycle invariants as special cases, as well as new invariants. We provide explicit examp

Larry Goldstein

The Game of Poker Chips, Dominoes and Survival fosters team building and high level cooperation in large groups, and is a tool applied in management training exercises. Each player, initially given two colored poker chips, is allowed to make exchanges with the game coordinator according to two rules, and must secure a domino before time is called in order to

Jonas Richter, Niklas Casper, Wolfram Brenig, Robin Steinigeweg

We study spin transport in the one-dimensional anisotropic S = 1 Heisenberg model. Particular emphasis is given to dynamics at infinite temperature, where current autocorrelations and spatio-temporal correlation functions are obtained by means of an efficient pure-state approach based on the concept of typicality. Our comprehensive numerical analysis unveils

Abey López-García, Guillermo López Lagomasino

In this paper we continue the investigations initiated in \cite{LopLopstar} on ratio asymptotics of multiple orthogonal polynomials and functions of the second kind associated with Nikishin systems on star-like sets. We describe in detail the limiting functions found in \cite{LopLopstar}, expressing them in terms of certain conformal mappings defined on a co

Raphael Forien, Etienne Pardoux

This paper presents a new view of household epidemic models, where the interaction between the households is of mean field type. We thus obtain in the limit of infinitely many households a nonlinear Markov process solution of a McKean - Vlasov type Poisson driven SDE, and a propagation of chaos result. We also define a basic reproduction number R0, and show

Guochao Sun, Brandon S. Hensley, Tzu-Ching Chang, Olivier Doré

Line intensity mapping (LIM) is a promising approach to study star formation and the interstellar medium (ISM) in galaxies by measuring the aggregate line emission from the entire galaxy population. In this work, we develop a simple yet physically-motivated framework for modeling the line emission as would be observed in LIM experiments, which is done by bui

Srinivas Venkattaramanujam, Eric Crawford, Thang Doan, Doina Precup

Goal-conditioned policies are used in order to break down complex reinforcement learning (RL) problems by using subgoals, which can be defined either in state space or in a latent feature space. This can increase the efficiency of learning by using a curriculum, and also enables simultaneous learning and generalization across goals. A crucial requirement of

Hussein Alrubaye, Mohamed Wiem Mkaouer, Ali Ouni

In this paper we introduce, MigrationMiner, an automated tool that detects code migrations performed between Java third-party library. Given a list of open source projects, the tool detects potential library migration code changes and collects the specific code fragments in which the developer replaces methods from the retired library with methods from the n

C. Martínez-Lombilla, J. H. Knapen

We study the structure of thick discs in extraordinary depth by reaching a surface brightness limit of $μ_{r_{\rm deep}} \sim$28.5$-$29~mag arcsec$^{-2}$ with combined $g$,$r$,$i$ band images from the IAC Stripe 82 Legacy Project. We present the characterisation of the thick discs in a sample of five edge-on galaxies. A study of the radial and vertical surfa

Ruud JG van Sloun, Regev Cohen, Yonina C Eldar

We consider deep learning strategies in ultrasound systems, from the front-end to advanced applications. Our goal is to provide the reader with a broad understanding of the possible impact of deep learning methodologies on many aspects of ultrasound imaging. In particular, we discuss methods that lie at the interface of signal acquisition and machine learnin

Sheng Cheng, Nuno C. Martins

We propose a necessary and sufficient test to determine whether a solution for a general quadratic program with two quadratic constraints (QC2QP) can be computed from that of a specific convex semidefinite relaxation, in which case we say that there is no optimality gap. Originally intended to solve a nonconvex optimal control problem, we consider the case i

Thomas Roy, Tom B Jönsthövel, Christopher Lemon, Andrew J Wathen

For both isothermal and thermal petroleum reservoir simulation, the Constrained Pressure Residual (CPR) method is the industry-standard preconditioner. This method is a two-stage process involving the solution of a restricted pressure system. While initially designed for the isothermal case, CPR is also the standard for thermal cases. However, its treatment

Federico Landi, Lorenzo Baraldi, Massimiliano Corsini, Rita Cucchiara

In Vision-and-Language Navigation (VLN), an embodied agent needs to reach a target destination with the only guidance of a natural language instruction. To explore the environment and progress towards the target location, the agent must perform a series of low-level actions, such as rotate, before stepping ahead. In this paper, we propose to exploit dynamic

Sebastian Baader, Ryan Blair, Alexandra Kjuchukova

We prove the meridional rank conjecture for twisted links and arborescent links associated to bipartite trees with even weights. These links are substantial generalizations of pretzels and two-bridge links, respectively. Lower bounds on meridional rank are obtained via Coxeter quotients of the groups of link complements. Matching upper bounds on bridge numbe

Matteo Leo, Christian Arnold, Baojiu Li

Future 21 cm intensity mapping surveys such as SKA can provide precise information on the spatial distribution of the neutral hydrogen (HI) in the post-reionization epoch. This information will allow to test the standard LCDM paradigm and with that the nature of gravity. In this work, we employ the SHYBONE simulations, which model galaxy formation in f(R) mo

Christian Arnold, Baojiu Li

We present an analysis of the matter, halo and galaxy clustering in $f(R)$-gravity employing the SHYBONE full-physics hydrodynamical simulation suite. Our analysis focuses on the interplay between baryonic feedback and $f(R)$-gravity in the matter power spectrum, the matter and halo correlation functions, the halo and galaxy-host-halo mass function, the subh

Ethan D. Jahn, Laura V. Sales, Andrew Wetzel, Michael Boylan-Kolchin

Within $Λ$CDM, dwarf galaxies like the Large Magellanic Cloud (LMC) are expected to host numerous dark matter subhalos, several of which should host faint dwarf companions. Recent Gaia proper motions confirm new members of the LMC-system in addition to the previously known SMC, including two classical dwarf galaxies ($M_\ast$ > $10^5$ M$_{\odot}$; Carina and

Riley W. Chien, Sha Xue, Tarini S. Hardikar, Kanav Setia

In our recent work, we have examined various fermion to qubit mappings in the context of quantum simulation including the original Bravyi-Kitaev Superfast encoding (OSE) as well as a generalized version (GSE). We return to OSE and compare it against the Jordan-Wigner (JW) transform for quantum chemistry considering the number of qubits required, the Pauli we

José Fonseca, Jan-Albert Viljoen, Roy Maartens

The large-scale structure growth index $γ$ provides a consistency test of the standard cosmology and is a potential indicator of modified gravity. We investigate the constraints on $γ$ from next-generation spectroscopic surveys, using the power spectrum that is observed in redshift space, i.e., the angular power spectrum. The angular power spectrum avoids th

Natalia Porqueres, Jens Jasche, Guilhem Lavaux, Torsten Enßlin

One of the major science goals over the coming decade is to test fundamental physics with probes of the cosmic large-scale structure out to high redshift. Here we present a fully Bayesian approach to infer the three-dimensional cosmic matter distribution and its dynamics at $z>2$ from observations of the Lyman-$α$ forest. We demonstrate that the method recov

T. K. Daisy Leung, Andrea Pallottini, Andrea Ferrara, Mordecai-Mark Mac Low

We study the properties of molecular-forming gas clumps (MGCs) at the epoch of reionization using cosmological zoom-in simulations. We identify MGCs in a z=6 prototypical galaxy (&#34;Althaea&#34;) using an H2 density-based clump finder. We compare their mass, size, velocity dispersion, gas surface density, and virial parameter (alpha_vir) to observations. I

Georgios Billis, Frank J. Tackmann, Jim Talbert

We consider the higher-order resummation of Sudakov double logarithms in the presence of multiple coupled gauge interactions. The associated evolution equations depend on the coupled $β$ functions of two (or more) coupling constants $α_a$ and $α_b$, as well as anomalous dimensions that have joint perturbative series in $α_a$ and $α_b$. We discuss possible st

Joel Leja, Sandro Tacchella, Charlie Conroy

The UVJ color-color diagram is a popular and efficient method to distinguish between quiescent and star-forming galaxies through their rest-frame $U-V$ vs. $V-J$ colors. Here we explore the information content of this color-color space using the Bayesian inference machine Prospector. We fit the same physical model to two datasets: (i) UVJ fluxes alone, and (

Muhammad A. Latif, Sadegh Khochfar

The first galaxies forming a few hundred million years after the Big Bang are the key drivers of cosmic evolution and ideal laboratories to study theories of galaxy formation. We here study the role of UV radiation in suppressing star formation in primordial galaxies by destroying molecular hydrogen, the main coolant in primordial gas and provide estimates o

Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel

Adversarial examples raise questions about whether neural network models are sensitive to the same visual features as humans. In this paper, we first detect adversarial examples or otherwise corrupted images based on a class-conditional reconstruction of the input. To specifically attack our detection mechanism, we propose the Reconstructive Attack which see

José Matias, Marco Morandotti, David R. Owen, Elvira Zappale

We describe multiscale geometrical changes via structured deformations $(g,G)$ and the non-local energetic response at a point $x$ via a function $Ψ$ of the weighted averages of the jumps $[u_{n}](y)$ of microlevel deformations $u_{n}$ at points $y$ within a distance $r$ of $x$. The deformations $u_{n}$ are chosen so that $\lim_{n\to \infty }u_{n}=g$ and $\l

Micol Benetti, Leila Graef, Rudnei O. Ramos

By incorporating quantum aspects of gravity, Loop Quantum Cosmology (LQC) provides a self-consistent extension of the inflationary scenario, allowing for modifications in the primordial inflationary power spectrum with respect to the standard General Relativity one. We investigate such modifications and explore the constraints imposed by the Cosmic Microwave

Carlo Forestiere, Giovanni Miano, Mariano Pascale, Guglielmo Rubinacci

A small dielectric object with positive permittivity may resonate when the free-space wavelength is large in comparison with the object dimensions if the permittivity is sufficiently high. We show that these resonances are described by the magnetoquasistatic approximation of the Maxwell&#39;s equations in which the normal component of the displacement curren

Djordje Baralic, Pierre-Louis Curien, Marina Milicevic, Jovana Obradovic

A formal sequent system dealing with Menelaus&#39; configurations is introduced in this paper. The axiomatic sequents of the system stem from 2-cycles of Delta-complexes. The Euclidean and projective interpretations of the sequents are defined and a soundness result is proved. This system is decidable and its provable sequents deliver incidence results. A cy

Takeshi Fukuyama, Nobuchika Okada, Hieu Minh Tran

The alternative renormalizable minimal $SO(10)$ model is composed of the Yukawa couplings with $\textbf{10} \oplus \textbf{120}$ Higgs fields, whereas the right-handed (RH) neutrino Majorana masses are generated via the Witten mechanism. The gauge coupling unification is achieved together with a unique pattern of the fermion masses and mixing at the grand un

Jordi Gaset, Xavier Gràcia, Miguel C. Muñoz-Lecanda, Xavier Rivas

We provide new insights into the contact Hamiltonian and Lagrangian formulations of dissipative mechanical systems. In particular, we state a new form of the contact dynamical equations, and we review two recently presented Lagrangian formalisms, studying their equivalence. We define several kinds of symmetries for contact dynamical systems, as well as the n

Li Ding, Mohammad H. Bawany, Ajay E. Kuriyan, Rajeev S. Ramchandran

While recent advances in deep learning have significantly advanced the state of the art for vessel detection in color fundus (CF) images, the success for detecting vessels in fluorescein angiography (FA) has been stymied due to the lack of labeled ground truth datasets. We propose a novel pipeline to detect retinal vessels in FA images using deep neural netw

Paolo Abiuso, Martí Perarnau-Llobet

We consider the optimization of a finite-time Carnot engine characterized by small dissipations. We bound the power with a simple inequality and show that the optimal strategy is to perform small cycles around a given working point, which can be thus chosen optimally. Remarkably, this optimal point is independent of the figure of merit combining power and ef

Ivan V. Pechenezhskiy, Raymond A. Mencia, Long B. Nguyen, Yen-Hsiang Lin

The non-dissipative non-linearity of a Josephson junction converts macroscopic superconducting circuits into artificial atoms, enabling some of the best controlled quantum bits (qubits) today. Three fundamental types of superconducting qubits are known, each reflecting a distinct behavior of quantum fluctuations in a Cooper pair condensate: single charge tun

Vasiliki Liakoni, Alireza Modirshanechi, Wulfram Gerstner, Johanni Brea

Surprise-based learning allows agents to rapidly adapt to non-stationary stochastic environments characterized by sudden changes. We show that exact Bayesian inference in a hierarchical model gives rise to a surprise-modulated trade-off between forgetting old observations and integrating them with the new ones. The modulation depends on a probability ratio,

Suraj S. Hegde, Guang Yue, Yuxuan Wang, Erik Huemiller

As part of the intense effort towards identifying platforms in which Majorana bound states can be realized and manipulated to perform qubit operations, we propose a topological Josephson junction architecture that achieves these capabilities and which can be experimentally implemented. The platform uses conventional superconducting electrodes deposited on a

Andrea Araldo, Andrea Di Maria, Antonella Di Stefano, Giovanni Morana

Mobility on Demand (MoD) services, like Uber and Lyft, are revolutionizing the way people move in cities around the world and are often considered a convenient alternative to public transit, since they offer higher Quality of Service (QoS - less waiting time, door-to-door service) at a cheap price. In the next decades, these advantages are expected to be fur

M. Orieux, R. Roussarie

We study the singularities for minimum time control-affine problems in 4D with 2D controls. After regularization, the problem boils down to the study of a bifurcation around some nilpotent equilibrium in the singular locus. We show that the extremal flow - thus, the exponential map - is smooth on a stratification, and therefore piece-wise smooth.

Nicolas Boria, David B. Blumenthal, Sébastien Bougleux, Luc Brun

The graph edit distance (GED) measures the dissimilarity between two graphs as the minimal cost of a sequence of elementary operations transforming one graph into another. This measure is fundamental in many areas such as structural pattern recognition or classification. However, exactly computing GED is NP-hard. Among different classes of heuristic algorith

John D. Barrow, Spiros Cotsakis

We generalise Einstein&#39;s formulation of the traceless Einstein equations to $f(R)$ gravity theories. In the case of the vacuum traceless Einstein equations, we show that a non-constant Weyl tensor leads via a conformal transformation to a dimensionally homogeneous (`no-scale&#39;) theory in the conformal frame with a scalar field source that has an expon

Daniel Vial, Vijay Subramanian

Given a reversible Markov chain $P_n$ on $n$ states, and another chain $\tilde{P}_n$ obtained by perturbing each row of $P_n$ by at most $α_n$ in total variation, we study the total variation distance between the two stationary distributions, $\| π_n - \tildeπ_n \|$. We show that for chains with cutoff, $\| π_n - \tildeπ_n \|$ converges to $0$, $e^{-c}$, and

Katarzyna Grabowska, Janusz Grabowski

We present a local and constructive differential geometric description of finite-dimensional solvable and transitive Lie algebras of vector fields. We show that it implies a Lie&#39;s conjecture for such Lie algebras. Also infinite-dimensional analytical solvable and transitive Lie algebras of vector fields whose derivative ideal is nilpotent can be adapted

Gergely Kántor, Constantinos Papageorgakis, Paul Richmond

We generalise the work of 1810.11442 for the case of AdS$_7$/CFT$_6$. Starting from the 2-equivalent charge, 3-equivalent rotation non-extremal black-hole solution in 7D gauged supergravity, we consider the supersymmetric and then the extremal limit and evaluate the associated thermodynamic quantities. Away from extremality, the black-hole solution becomes c

Daniel Skodlerack

Given a quaternionic form G of a p-adic classical group (p odd) we classify all cuspidal irreducible representations of G with coefficients in an algebraically closed field of characteristic different from p. We prove two theorems: At first: Every irreducible cuspidal representation of G is induced from a cuspidal type, i.e. from a certain irreducible repres

Petr A. Golovach, Giannos Stamoulis, Dimitrios M. Thilikos

For a finite collection of graphs ${\cal F}$, the \textsc{${\cal F}$-TM-Deletion} problem has as input an $n$-vertex graph $G$ and an integer $k$ and asks whether there exists a set $S \subseteq V(G)$ with $|S| \leq k$ such that $G \setminus S$ does not contain any of the graphs in ${\cal F}$ as a topological minor. We prove that for every such ${\cal F}$, \

Milad Dehghani Filabadi, Houra Mahmoudzadeh

Robust optimization (RO) tackles data uncertainty by optimizing for the worst-case scenario of an uncertain parameter and, in its basic form, is sometimes criticized for producing overly-conservative solutions. To reduce the level of conservatism in RO, one can use the well-known budget-of-uncertainty approach which limits the amount of uncertainty to be con

Tomoyuki Yamakami

The state complexity of a finite(-state) automaton intuitively measures the size of the description of the automaton. Sakoda and Sipser [STOC 1972, pp. 275--286] were concerned with nonuniform families of finite automata and they discussed the behaviors of the nonuniform complexity classes defined by such families of finite automata having polynomial-size st

Michael Kural, Vaughan McDonald, Ashwin Sah

We generalize results of Alladi, Dawsey, and Sweeting and Woo for Chebotarev densities to general densities of sets of primes. We show that if $K$ is a number field and $S$ is any set of prime ideals with natural density $δ(S)$ within the primes, then \[ -\lim_{X \to \infty}\sum_{\substack{2 \le \operatorname{N}(\mathfrak{a})\le X\\ \mathfrak{a} \in D(K,S)}}

Pramod Kumar Das, Tarun Das

We introduce and study a new variant of shadowing namely mean ergodic shadowing. We establish relationship of this variant with several other variants of shadowing. We show that a minimal system with shadowing cannot have mean ergodic shadowing. We give a necessary and sufficient condition for an orbital limit function to have mean ergodic shadowing property

Kayvan Sadeghi

We study the independence structure of finitely exchangeable distributions over random vectors and random networks. In particular, we provide necessary and sufficient conditions for an exchangeable vector so that its elements are completely independent or completely dependent. We also provide a sufficient condition for an exchangeable vector so that its elem

Erin Scanlon, Zachary W. Taylor, Jacquelyn J. Chini

While there have been numerous calls to increase the participation of people with disabilities in STEM, many postsecondary institutions are not equipped to support students with disabilities. We examined the digital accessibility of 139 webpages from 73 postsecondary institutions that contained information about the undergraduate physics curriculum and gradu

Drasko Masovic

Modern physics is based on three major theories - general relativity, quantum field theory, and (quantum) thermodynamics. Classical acoustics in fluids is usually regarded and studied as a part of classical mechanics, more precisely fluid dynamics. This assumes velocities much below the speed of light and length scales much above the molecular scale. However

Leigh N. Fletcher, Imke de Pater, Glenn S. Orton, Mark D. Hofstadter

Atmospheric circulation patterns derived from multi-spectral remote sensing can serve as a guide for choosing a suitable entry site for a future in situ probe mission. Since the Voyager-2 flybys in the 1980s, three decades of observations from ground- and space-based observatories have generated a picture of Ice Giant circulation that is complex, perplexing,

Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, David Lopez-Paz

We introduce Invariant Risk Minimization (IRM), a learning paradigm to estimate invariant correlations across multiple training distributions. To achieve this goal, IRM learns a data representation such that the optimal classifier, on top of that data representation, matches for all training distributions. Through theory and experiments, we show how the inva

Frank Fuhlbrück, Johannes Köbler, Oleg Verbitsky

As it is well known, the isomorphism problem for vertex-colored graphs with color multiplicity at most 3 is solvable by the classical 2-dimensional Weisfeiler-Leman algorithm (2-WL). On the other hand, the prominent Cai-Fürer-Immerman construction shows that even the multidimensional version of the algorithm does not suffice for graphs with color multiplicit