November 2018 arXiv papers — page 30

Heba Aly, Ashok Agrawala

In this paper, we present Hapi, a novel system that uses off-the-shelf standard WiFi to provide pseudo-3D indoor localization. It estimates the user's floor and her 2D location on that floor. Hapi is calibration-free, only requiring the building's floorplans and its WiFi APs' installation location for deployment. Our analysis shows that while a user can hear

Alexander Amini, Guy Rosman, Sertac Karaman, Daniela Rus

Deep learning has revolutionized the ability to learn "end-to-end" autonomous vehicle control directly from raw sensory data. While there have been recent extensions to handle forms of navigation instruction, these works are unable to capture the full distribution of possible actions that could be taken and to reason about localization of the robot within th

Angelos Koutsianas

In this paper, we study the generalized Lebesgue-Nagell equation \[ x^2+7^{2k+1}=y^n. \] This is the last case of equations of the form $x^2+q^{2k+1}=y^n$ with $k\geq0$ and $q>0$ where $\mathbb{Q}(\sqrt{-q})$ has class number one. Our proof is based on the modular method and the symplectic argument.

Valeri V. Makarov, Ciprian T. Berghea, Julien Frouard, Alan Fey

We investigate a sample of 3412 {\it International Celestial Reference Frame} (ICRF3) extragalactic radio-loud sources with accurate positions determined by VLBI in the S/X band, mostly active galactic nuclei (AGN) and quasars, which are cross-matched with optical sources in the second Gaia data release (Gaia DR2). The main goal of this study is to determine

Marcos Cardinot, Colm O'Riordan, Josephine Griffith, Matjaž Perc

Agent-based modeling and network science have been used extensively to advance our understanding of emergent collective behavior in systems that are composed of a large number of simple interacting individuals or agents. With the increasing availability of high computational power in affordable personal computers, dedicated efforts to develop multi-threaded,

Lam Si Tung Ho, Hayden Schaeffer, Giang Tran, Rachel Ward

Learning non-linear systems from noisy, limited, and/or dependent data is an important task across various scientific fields including statistics, engineering, computer science, mathematics, and many more. In general, this learning task is ill-posed; however, additional information about the data's structure or on the behavior of the unknown function can mak

Marcos Cardinot, Josephine Griffith, Colm O'Riordan, Matjaz Perc

Research has shown that the addition of abstention as an option transforms social dilemmas to rock-paper-scissor type games, where defectors dominate cooperators, cooperators dominate abstainers (loners), and abstainers (loners), in turn, dominate defectors. In this way, abstention can sustain cooperation even under adverse conditions, although defection als

A. David-Uraz, C. Erba, V. Petit, A. W. Fullerton

In this paper, we present high-resolution HST/COS observations of the extreme magnetic O star NGC 1624-2. These represent the first ultraviolet spectra of this archetypal object. We examine the variability of its wind-sensitive resonance lines, comparing it to that of other known magnetic O stars. In particular, the observed variations in the profiles of the

Rémi Besson, Erwan Le Pennec, Stéphanie Allassonnière, Julien Stirnemann

In this work, we present our various contributions to the objective of building a decision support tool for the diagnosis of rare diseases. Our goal is to achieve a state of knowledge where the uncertainty about the patient's disease is below a predetermined threshold. We aim to reach such states while minimizing the average number of medical tests to perfor

Cherif Mamadou Moctar Traoré, Moumouni Diallo, Gane Samb Lo, Mouhamad Ahsanullah

The new Sine Skewed Cardioid (ssc) distribution been just introduced and characterized by Ahsanullah (2018). Here, we study the asymptotic properties of its tails by determining its extreme value domain, the characteristic function, the moments and likelihood estimators of the two parameters, the asymptotic normality of the moments estimators and the random

Abhay Koushik, Judith Amores, Pattie Maes

We present the first real-time sleep staging system that uses deep learning without the need for servers in a smartphone application for a wearable EEG. We employ real-time adaptation of a single channel Electroencephalography (EEG) to infer from a Time-Distributed 1-D Deep Convolutional Neural Network. Polysomnography (PSG)-the gold standard for sleep stagi

Lanpeng Ji

Consider a multi-dimensional Brownian motion which models the surplus processes of multiple lines of business of an insurance company. Our main result gives exact asymptotics for the cumulative Parisian ruin probability as the initial capital tends to infinity. An asymptotic distribution for the conditional cumulative Parisian ruin time is also derived. The

Jiahua Xu, Benjamin Livshits

While pump-and-dump schemes have attracted the attention of cryptocurrency observers and regulators alike, this paper represents the first detailed empirical query of pump-and-dump activities in cryptocurrency markets. We present a case study of a recent pump-and-dump event, investigate 412 pump-and-dump activities organized in Telegram channels from June 17

Shu-Lin Cheng, Wolung Lee, Kin-Wang Ng

We study the growth of superhorizon modes in the curvature perturbation during an ultra-slow-roll or a large-$\eta$ phase in single-field inflation. In a simple toy model, we derive the two-point correlation function of the curvature perturbation and show that the requirement for causality restricts the growth rate and hence puts a lower limit on the value o

Alberto S. Cattaneo, Ivan Contreras

A Lagrangian subspace $L$ of a weak symplectic vector space is called \emph{split Lagrangian} if it has an isotropic (hence Lagrangian) complement. When the symplectic structure is strong, it is sufficient for $L$ to have a closed complement, which can then be moved to become isotropic. The purpose of this note is to develop the theory of compositions and re

Guy Bresler, Sung Min Park, Madalina Persu

Sparse Principal Component Analysis (SPCA) and Sparse Linear Regression (SLR) have a wide range of applications and have attracted a tremendous amount of attention in the last two decades as canonical examples of statistical problems in high dimension. A variety of algorithms have been proposed for both SPCA and SLR, but an explicit connection between the tw

Lam M. Nguyen, Katya Scheinberg, Martin Takáč

We develop and analyze a variant of the SARAH algorithm, which does not require computation of the exact gradient. Thus this new method can be applied to general expectation minimization problems rather than only finite sum problems. While the original SARAH algorithm, as well as its predecessor, SVRG, require an exact gradient computation on each outer iter

Ben Hutchinson, Margaret Mitchell

Quantitative definitions of what is unfair and what is fair have been introduced in multiple disciplines for well over 50 years, including in education, hiring, and machine learning. We trace how the notion of fairness has been defined within the testing communities of education and hiring over the past half century, exploring the cultural and social context

Johanna Hansen, Sandeep Manjanna, Alberto Quattrini Li, Ioannis Rekleitis

We present a transportable system for ocean observations in which a small autonomous surface vehicle (ASV) adaptively collects spatially diverse samples with aid from a team of inexpensive, passive floating sensors known as drifters. Drifters can provide an increase in spatial coverage at little cost as they are propelled about the survey area by the ambient

Chenyang Shen, Yesenia Gonzalez, Peter Klages, Nan Qin

Inverse treatment planning in radiation therapy is formulated as optimization problems. The objective function and constraints consist of multiple terms designed for different clinical and practical considerations. Weighting factors of these terms are needed to define the optimization problem. While a treatment planning system can solve the optimization prob

Mehdi Mirzakhanloo, Mohammad-Reza Alam

Here we show that micro-swimmers can form a concealed swarm through synergistic cooperation in suppressing one another's disturbing flows. We then demonstrate how such a concealed swarm can actively gather around a favorite spot, point toward a target, or track a desired trajectory in space, while minimally disturbing the ambient fluid. Our findings provide

Yichun Shi, Debayan Deb, Anil K. Jain

We propose, WarpGAN, a fully automatic network that can generate caricatures given an input face photo. Besides transferring rich texture styles, WarpGAN learns to automatically predict a set of control points that can warp the photo into a caricature, while preserving identity. We introduce an identity-preserving adversarial loss that aids the discriminator

S. V. Andreev, O. I. Utesov

We consider a two-component Bose-condensed mixture characterized by positive s-wave scattering lengths. We assume equal densities and intra-species interactions. By doing the Bogoliubov transformation of an effective Hamiltonian we obtain the lower energy magnon dispersion incorporating the superfluid entrainment between the components. We argue that p-wave

Arnulf Stein, Daniela Rolf, Christian Lotze, Constantin Czekelius

Surface-bound porphyrins are promising candidates for molecular switches, electronics and spintronics. Here, we studied the structural and the electronic properties of Fe-tetra-pyridil-porphyrin adsorbed on Au(111) in the monolayer regime. We combined scanning tunneling microscopy/spectroscopy, ultraviolet photoemission, and two-photon photoemission to deter

Johanna Hansen, Kyle Kastner, Aaron Courville, Gregory Dudek

We demonstrate the use of conditional autoregressive generative models (van den Oord et al., 2016a) over a discrete latent space (van den Oord et al., 2017b) for forward planning with MCTS. In order to test this method, we introduce a new environment featuring varying difficulty levels, along with moving goals and obstacles. The combination of high-quality f

Paul D. Mitchener, Behnam Norouzizadeh, Thomas Schick

In this note on coarse geometry we revisit coarse homotopy. We prove that coarse homotopy indeed is an equivalence relation, and this in the most general context of abstract coarse structures. We introduce (in a geometric way) coarse homotopy groups. The main result is that the coarse homotopy groups of cone of a compact simplicial complex coincide with the

James Dibble

Each Abelian subgroup of the fundamental group of a compact and locally simply connected $d$-dimensional length space with no conjugate points is isomorphic to $\mathbb{Z}^k$ for some $0 \leq k \leq d$. It follows from this and previously known results that each solvable subgroup of the fundamental group is a Bieberbach group. In the Riemannian setting, this

Rakesh Chaturvedi, Sneihil Gopal, Sanjit Krishnan Kaul

Consumers of Internet content typically pay an Internet Service Provider (ISP) to connect to the Internet. A content provider (CP) may charge consumers for its content or may earn via advertising revenue. In such settings, a matter of continuing debate, under the umbrella of net neutrality regulations, is whether an ISP serving a consumer may in addition cha

Roman Vetter, Jürgen O. Schumacher

Numerical modeling of proton exchange membrane fuel cells is at the verge of becoming predictive. A crucial requisite for this, though, is that material properties of the membrane-electrode assembly and their functional dependence on the conditions of operation are known with high precision. In this bipartite paper series we determine the most critical trans

Xin Wang, Qiuyuan Huang, Asli Celikyilmaz, Jianfeng Gao

Vision-language navigation (VLN) is the task of navigating an embodied agent to carry out natural language instructions inside real 3D environments. In this paper, we study how to address three critical challenges for this task: the cross-modal grounding, the ill-posed feedback, and the generalization problems. First, we propose a novel Reinforced Cross-Moda

Roman Vetter, Jürgen O. Schumacher

Ever since modeling has become a mature part of proton exchange membrane fuel cell (PEMFC) research and development, it has been plagued by significant uncertainty lying in the detailed knowledge of material properties required. Experimental data published on several transport coefficients are scattered over orders of magnitude, even for the most extensively

Makrand Sinha, Ronald de Wolf

Chattopadhyay, Mande and Sherif (ECCC 2018) recently exhibited a total Boolean function, the sink function, that has polynomial approximate rank and polynomial randomized communication complexity. This gives an exponential separation between randomized communication complexity and logarithm of the approximate rank, refuting the log-approximate-rank conjectur

Hany Ibrahim

We introduce a new bivariate polynomial which we call the defensive alliance polynomial and denote it by da(G; x, y). It is a generalization of the alliance polynomial [Carballosa et al., 2014] and the strong alliance polynomial [Carballosa et al., 2016]. We show the relation between da(G; x, y) and the alliance, the strong alliance and the induced connected

József Zsolt Bernád, Claudio Sanavio, André Xuereb

This paper is devoted to the study of the Bayesian-inference approach in the context of estimating the dipole coupling strength in matter-field interactions. In particular, we consider the simplest model of a two-level system interacting with a single mode of the radiation field. Our estimation strategy is based on the emerging state of the two-level system,

Anwar Irmatov

Let $ E=\{ (1, b_1, \ldots , b_n)\in R^{n+1} \mid \; b_i= \pm 1 ,\; i=1, \ldots, n \}$, $E^{\times n}_{\ne 0} := \{ W=(w_{i_1}, \ldots , w_{i_n}) \mid w_{i_k}\in E, \, k=1, \ldots, n, \, dim \, span(w_{i_1}, \ldots , w_{i_n}) = n \},$ and $q^W_l := |span(w_{i_{n-l+1}}, \ldots , w_{i_n}) \cap E|.$ Then for any weights $p=(p_1, \ldots, p_{2^n})$, $p_i\in R$, $

Irene I. Bouw, Ozlem Ejder, Valentijn Karemaker

We consider a large class of so-called dynamical Belyi maps and study the Galois groups of iterates of such maps. From the combinatorial invariants of the maps, we construct a useful presentation of their Galois groups as subgroups of automorphism groups of regular trees, in terms of iterated wreath products. This allows us to study the behavior of the monod

John Preskill

Forthcoming exascale digital computers will further advance our knowledge of quantum chromodynamics, but formidable challenges will remain. In particular, Euclidean Monte Carlo methods are not well suited for studying real-time evolution in hadronic collisions, or the properties of hadronic matter at nonzero temperature and chemical potential. Digital comput

Raymond G. Carlberg

Simulations are run with and without a normal cold dark matter sub-halo population below 4x10^8 M_sun to examine the role of the lower mass sub-halos in the creation of density variations, "gaps", within thin tidal star streams. Dense star clusters composed of stellar mass particles are started within a redshift 3 sub-galactic dark matter halo distribution w

Lakhan Shiva Kamireddy

This paper is a survey of extensions to finite automata theory to model real-time systems as well as systems exhibiting mixed discrete-continuous behavior. Real-time systems maintain a continuous and timely interaction with the environment, often adhering to some timing constraints. Therefore, the finite automata theory is extended to measure real-time value

Fu Liu, Odysseas Tsilipakos, Alexandros Pitilakis, Anna C. Tasolamprou

Electromagnetic metasurfaces can be characterized as intelligent if they are able to perform multiple tunable functions, with the desired response being controlled by a computer influencing the individual electromagnetic properties of each metasurface inclusion. In this paper, we present an example of an intelligent metasurface which operates in the reflecti

M. Silarski

Positronium is a unique laboratory to study fundamental symmetries in the Standard Model, reflection in space ($\mathcal{P}$), reversal in time ($\mathcal{T}$), charge conjugation ($\mathcal{C}$) and their combinations. The experimental limits on the $\mathcal{C}$, $\mathcal{CP}$ and $\mathcal{CPT}$ symmetries violation in the decays of positronium are still

Keren Ye, Mingda Zhang, Wei Li, Danfeng Qin

To alleviate the cost of obtaining accurate bounding boxes for training today's state-of-the-art object detection models, recent weakly supervised detection work has proposed techniques to learn from image-level labels. However, requiring discrete image-level labels is both restrictive and suboptimal. Real-world "supervision" usually consists of more unstruc

Tze-Yang Tung, Deniz Gündüz

A hybrid digital-analog wireless image transmission scheme, called SparseCast, is introduced, which provides graceful degradation with channel quality. SparseCast achieves improved end-to-end reconstruction quality while reducing the bandwidth requirement by exploiting frequency domain sparsity through compressed sensing. The proposed algorithm produces a li

Massimiliano Alvioli, Mark Strikman

We extend our Monte Carlo generator of global configurations in nuclei to include different spatial distributions of protons and neutrons in heavy nuclei taking into account the difference of spatial correlations between two protons, two neutrons and proton-neutron pairs. These configurations are used for building an event generator for proton-heavy nucleus

Nir Shlezinger, Yonina C. Eldar, Miguel R. D. Rodrigues

Quantizers take part in nearly every digital signal processing system which operates on physical signals. They are commonly designed to accurately represent the underlying signal, regardless of the specific task to be performed on the quantized data. In systems working with high-dimensional signals, such as massive multiple-input multiple-output (MIMO) syste

Anatoly Svidzinsky, Robert Hilborn

In a recent paper "Tests of general relativity with GW170817" (arXiv:1811.00364 [gr-qc]) the authors claimed overwhelming evidence in favor of tensor gravitational wave (GW) polarization over vector by analyzing GW signals measured by the LIGO-Virgo network. Here we show that the measured LIGO-Livingston signal is substantially reduced at certain frequency i

Rana Jafari, Rick Trebino

Frequency-resolved optical gating (FROG) is widely used to measure ultrashort laser pulses, also providing an excellent indication of pulse-shape instabilities by disagreement between measured and retrieved FROG traces. FROG, however, requires -- but currently lacks -- an extremely reliable pulse-retrieval algorithm. So, this work provides one. It uses a sim

Cheng Shang, H. Z. Shen, X. X. Yi

In the few-photon regime, we theoretically propose a feasible scheme to realize strong coupling optomechanical cycle in a three-mode optomechanical circulatory system (OMCS) comprising of cross-Kerr (CK) type and linear coupling between the corresponding two bosonic modes, meanwhile, where one of the bosonic modes is strongly coherently driven and the rest a

Martin Djukanović

We compute all the "special" cases of (3,3)-split Jacobians and we parametrize the Igusa-Clebsch invariants of curves of genus two whose Jacobian is (3,3)-isogenous to a product of two elliptic curves from the Hesse pencil.

Roman Snytsar, Yatish Turakhia

Sliding window sums are widely used in bioinformatics applications, including sequence assembly, k-mer generation, hashing and compression. New vector algorithms which utilize the advanced vector extension (AVX) instructions available on modern processors, or the parallel compute units on GPUs and FPGAs, would provide a significant performance boost for the

Revathy Venkataramanan, Dipesh Kadariya, Hong Yung Yip, Utkarshani Jamini

Objective: Asthma is a chronic pulmonary disease with multiple triggers manifesting as symptoms with various intensities. This paper evaluates the suitability of long-term monitoring of pediatric asthma using diverse data to qualify and quantify triggers that contribute to the asthma symptoms and control to enable a personalized management plan. Materials an

Nicolas Brosse, Alain Durmus, Eric Moulines

Stochastic Gradient Langevin Dynamics (SGLD) has emerged as a key MCMC algorithm for Bayesian learning from large scale datasets. While SGLD with decreasing step sizes converges weakly to the posterior distribution, the algorithm is often used with a constant step size in practice and has demonstrated successes in machine learning tasks. The current practice

Amichai Painsky, Saharon Rosset, Meir Feder

Typically, real-world stochastic processes are not easy to analyze. In this work we study the representation of any stochastic process as a memoryless innovation process triggering a dynamic system. We show that such a representation is always feasible for innovation processes taking values over a continuous set. However, the problem becomes more challenging

Daisuke Shiga, Makoto Minohara, Miho Kitamura, Ryu Yukawa

In order to study the origin of metallization of VO$_2$ induced by electron injection, we deposit K atoms onto the surface of VO$_2$ films grown on TiO$_2$ (001) substrates, and we investigate the change in the electronic and crystal structures using ${in~situ}$ photoemission spectroscopy and x-ray absorption spectroscopy (XAS). The deposition of K atoms ont

Andrew Conner, Peter Goetz

Let $\mathbb{k}$ be an algebraically closed field. We classify all of the quadratic twisted tensor products $A \otimes_{\tau} B$ in the cases where $(A, B) = (\mathbb{k}[x], \mathbb{k}[y])$ and $(A, B) = (\mathbb{k}[x, y], \mathbb{k}[z])$. We determine when a quadratic twisted tensor product of this form is Koszul, and when it is Artin-Schelter regular.

Andrey Kuehlkamp, Allan Pinto, Anderson Rocha, Kevin Bowyer

The adoption of large-scale iris recognition systems around the world has brought to light the importance of detecting presentation attack images (textured contact lenses and printouts). This work presents a new approach in iris Presentation Attack Detection (PAD), by exploring combinations of Convolutional Neural Networks (CNNs) and transformed input spaces

Antonio Pich

We review the current status of the determination of the strong coupling from tau decay. Using the most recent release of the ALEPH data, a very comprehensive phenomenological analysis has been performed, exploring all strategies previously considered in the literature and several complementary approaches. Once their actual uncertainties are properly assesse

Andrey Kuehlkamp, Kevin Bowyer

Predicting gender from iris images has been reported by several researchers as an application of machine learning in biometrics. Recent works on this topic have suggested that the preponderance of the gender cues is located in the periocular region rather than in the iris texture itself. This paper focuses on teasing out whether the information for gender pr

I Chien, Huozhi Zhou, Pan Li

We propose a hypergraph-based active learning scheme which we term $HS^2$, $HS^2$ generalizes the previously reported algorithm $S^2$ originally proposed for graph-based active learning with pointwise queries [Dasarathy et al., COLT 2015]. Our $HS^2$ method can accommodate hypergraph structures and allows one to ask both pointwise queries and pairwise querie

Hui Wang, M. P. Blencowe, C. M. Wilson, A. J. Rimberg

We consider a model for an oscillatory, relativistic accelerating photodetector inside a cavity and show that the entangled photon pair production from the vacuum (Unruh effect) can be accurately described in the steady state by a non-degenerate parametric amplifier (NDPA), with the detector's accelerating center of mass serving as the parametric drive (pump

Fabio Bagarello, Francesco G. Russo

We have recently shown that pseudo-bosonic operators realize concrete examples of finite dimensional nilpotent Lie algebras over the complex field. It has been the first time that such operators were analyzed in terms of nilpotent Lie algebras (under prescribed conditions of physical character). On the other hand, the general classification of a finite dimen

Oliver Schulz, Nicolas Noiray

This numerical study investigates the combustion modes in the second stage of a sequential combustor at atmospheric and high pressure. The sequential burner (SB) features a mixing section with fuel injection into a hot vitiated crossflow. Depending on the dominant combustion mode, a recirculation zone assists flame anchoring in the combustion chamber. The fl

Victor Magron, Mohab Safey El Din

We consider the problem of computing exact sums of squares (SOS) decompositions for certain classes of non-negative multivariate polynomials, relying on semidefinite programming (SDP) solvers. We provide a hybrid numeric-symbolic algorithm computing exact rational SOS decompositions with rational coefficients for polynomials lying in the interior of the SOS

G. Dimitriadis, R. J. Foley, A. Rest, D. Kasen

We present an exquisite, 30-min cadence Kepler (K2) light curve of the Type Ia supernova (SN Ia) 2018oh (ASASSN-18bt), starting weeks before explosion, covering the moment of explosion and the subsequent rise, and continuing past peak brightness. These data are supplemented by multi-color Pan-STARRS1 and CTIO 4-m DECam observations obtained within hours of e

Chenhe Zhang, Peiyuan Sun

The authors propose a parametric model called the arena model for prediction in paired competitions, i.e. paired comparisons with eliminations and bifurcations. The arena model has a number of appealing advantages. First, it predicts the results of competitions without rating many individuals. Second, it takes full advantage of the structure of competitions.

François Baccelli, Mir-Omid Haji-Mirsadeghi, James T. Murphy

This paper is centered on the random graph generated by a Doeblin-type coupling of discrete time processes on a countable state space whereby when two paths meet, they merge. This random graph is studied through a novel subgraph, called a bridge graph, generated by paths started in a fixed state at any time. The bridge graph is made into a unimodular network

Bogdan Raiţă

We show that the inequality $$ \|D^{k-1}(u-\pi u)\|_{\mathrm{L}^{n/(n-1)}(\mathbb{R}^n)}\leq c\|\mathbb{B}(D) u\|_{\mathrm{L}^1(\mathbb{R}^n)} $$ holds for vector fields $u\in\mathrm{C}^\infty_c$ if and only if $\mathbb{B}$ is canceling. Here $\pi$ denotes the $\mathrm{L}^2$-orthogonal projection onto the kernel of the $k$-homogeneous differential operator $

W. Li, X. Wang, J. Vinkó, J. Mo

Supernova (SN) 2018oh (ASASSN-18bt) is the first spectroscopically-confirmed type Ia supernova (SN Ia) observed in the $Kepler$ field. The $Kepler$ data revealed an excess emission in its early light curve, allowing to place interesting constraints on its progenitor system (Dimitriadis et al. 2018, Shappee et al. 2018b). Here, we present extensive optical, u

Himani Sinhmar, Sukumar Srikant

This paper addresses the problem of distributed coordination control of spacecraft formation. It is assumed that the agents measure relative positions of each other with a non-zero, unknown constant sensor bias. The translational dynamics of the spacecraft is expressed in Euler-Lagrangian form. We propose a novel distributed, model independent control law fo

Keisuke Isogai, Taichi Kato, Akira Imada, Tomohito Ohshima

ASASSN-14dx showed an extraordinary outburst whose features are the small outburst amplitude (~ 2.3 mag) and long duration (> 4 years). Because we found a long observational gap of 123 d before the outburst detection, we propose that the main outburst plateau was missed and that this outburst is just a "fading tail" often seen after the WZ Sge-type superoutb

Avner Kiro, Alon Nishry

In this note we consider a certain class of Gaussian entire functions, characterized by some asymptotic properties of their covariance kernels, which we call admissible (as defined by Hayman). A notable example is the Gaussian Entire Function, whose zero set is well-known to be invariant with respect to the isometries of the complex plane. We explore the rig

Alexander Selvikvåg Lundervold, Arvid Lundervold

What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when so-called deep artificial neural networks began outperforming other established models on a number of important benchma

Jae Dong Noh, Eiki Iyoda, Takahiro Sagawa

We investigate the Joule expansion of an interacting quantum gas in an energy eigenstate. The Joule expansion occurs when two subsystems of different particle density are allowed to exchange particles. We demonstrate numerically that the subsystems in their energy eigenstates evolves unitarily into the global equilibrium state in accordance with the eigensta

Daegeon Kim, Huy Kang Kim

The objectives of cyberattacks are becoming sophisticated, and attackers are concealing their identity by masquerading as other attackers. Cyber threat intelligence (CTI) is gaining attention as a way to collect meaningful knowledge to better understand the intention of an attacker and eventually predict future attacks. A systemic threat analysis based on da

Oleg Shishanin

A techniques, describing electron dynamics for magnetic models closed to cyclical accelerators, is developed and applied to the analysis of electromagnetic radiation emitted by charged particles. Formulas for the angular characteristics of synchrotron emission, which take into account the electron vibrations in the lattices of accelerators and storage rings

Antoine Fond, Marie-Odile Berger, Gilles Simon

This paper presents an efficient approach for solving jointly facade registration and semantic segmentation. Progress in facade detection and recognition enable good initialization for the registration of a reference facade to a newly acquired target image. We propose here to rely on semantic segmentation to improve the accuracy of that initial registration.

J. Fry, R. Alarcon, S. Baessler, S. Balascuta

Neutron beta decay is one of the most fundamental processes in nuclear physics and provides sensitive means to uncover the details of the weak interaction. Neutron beta decay can evaluate the ratio of axial-vector to vector coupling constants in the standard model, $\lambda = g_A / g_V$, through multiple decay correlations. The Nab experiment will carry out

Yuhan Ye, Manting Gui, Jun-Wei Luo

The performance of strained silicon as the channel material for transistors has plateaued. Motivated by increasing charge-carrier mobility within the device channel to improve transistor performance, germanium (Ge) is considered as an attractive option as a silicon replacement due to its highest p-type mobility in all of the known semiconductor materials and

Matteo Barigozzi, Marc Hallin

Volatilities, in high-dimensional panels of economic time series with a dynamic factor structure on the levels or returns, typically also admit a dynamic factor decomposition. We consider a two-stage dynamic factor model method recovering the common and idiosyncratic components of both levels and log-volatilities. Specifically, in a first estimation step, we

M. L. Nekrasov

The coherent meson scattering off heavy nuclei with the production of two particles in the final state is investigated. We obtain the form factors for the direct production of the final state and through intermediate particles, unstable ones that can decay inside the nucleus and virtual ones. The cases of scattering both in the Coulomb and in the strong fiel

Konstantin Ilin, Andrey Morgulis

We study the stability of the Couette-Taylor flow between porous cylinders with radial throughflow. It had been shown earlier that this flow can be unstable with respect to non-axisymmetric (azimuthal or helical) waves provided that the radial Reynolds number, $R$ (constructed using the radial velocity at the inner cylinder and its radius), is high. In this

Weiyuan Qiu, Fei Yang

For Cantor circle Julia sets of hyperbolic rational maps, we prove that they are quasisymmetrically equivalent to standard Cantor circles (i.e., connected components are round circles). This gives a quasisymmetric uniformization of all Cantor circle Julia sets of hyperbolic rational maps. By analyzing the combinatorial information of the rational maps whose

Zihao Zhang, Stefan Zohren, Stephen Roberts

We showcase how dropout variational inference can be applied to a large-scale deep learning model that predicts price movements from limit order books (LOBs), the canonical data source representing trading and pricing movements. We demonstrate that uncertainty information derived from posterior predictive distributions can be utilised for position sizing, av

Adam M. Meier

Randomized benchmarking is an experimental procedure intended to demonstrate control of quantum systems. The procedure extracts the average error introduced by a set of control operations. When the target set of operations is intended to be the set of Clifford operators, the randomized benchmarking algorithm is particularly easy to perform and its results ha

Jens Hemelaer

Lindenhovius has studied Grothendieck topologies on posets and has given a complete classification in the case that the poset is Artinian. We extend his approach to more general posets, by translating known results in locale and domain theory to the study of Grothendieck topologies. In particular, explicit descriptions are given for the family of Grothendiec

Andronikos Paliathanasis, Genly Leon, Supriya Pan

In multi-scalar field cosmologies new dynamical degrees of freedom are introduced which can explain the observational phenomena. Unlike the usual scalar field theory where a single scalar field is considered, the multi-scalar field cosmologies allow more than one scalar field and exhibits interetsing consequences, such as quintom, hybrid inflation etc. The c

Christian Kuehn, Alexandra Neamtu

Since the breakthrough in rough paths theory for stochastic ordinary differential equations (SDEs), there has been a strong interest in investigating the rough differential equation (RDE) approach and its numerous applications. Rough path techniques can stay closer to deterministic analytical methods and have the potential to transfer many pathwise ordinary

O. Rogla, N. Pelechano, G. Patow

Authoring realistic behaviors to populate a large virtual city can be a cumbersome, time-consuming and error-prone task. Believable crowds require the effort of storytellers and programming experts working together for long periods of time. In this work, we present a new framework to allow users to generate populated environments in an easier and faster way,

Sayantan Choudhury, Arkaprava Mukherjee

In this article, we study quantum randomness of stochastic cosmological particle production scenario using quantum corrected higher order Fokker Planck equation. Using the one to one correspondence between particle production in presence of scatterers and electron transport in conduction wire with impurities we compute the quantum corrections of Fokker Planc

Viorel Nitica

Let $b$ be a numeration base. A $b$-additive Ramanujan-Hardy number $N$ is an integer for which there exists at least an integer $M$, called additive multiplier, such that the product of $M$ and the sum of base $b$ digits of $N$, added to the reversal of the product, gives $N$. We show that for any $b$ there exists an infinity of $b$-additive Ramanujan-Hardy

Luka Leskovec, Constantia Alexandrou, Stefan Meinel, John W. Negele

We present the results of our lattice QCD study of the $\pi\gamma\to\pi\pi$ process, where the $\rho$ resonance appears as an enhancement in the transition amplitude. We use $N_f=2+1$ clover fermions on a lattice of $L=3.6$ fm and a pion mass of $320$ MeV. Using a combination of forward, stochastic, and sequential propagators, we calculate the two-point and

James Stovold, Simon O'Keefe, Jon Timmis

Homeostasis keeps animals alive; it is a fundamental process that allows animals to adapt quickly to their environment. Artificial homeostasis can be used to help robots adapt to changing environments. Previous attempts at developing artificial homeostasis for robots were driven by mimicry of the biochemical machinery that drives homeostasis in humans. By co

Chenqi Mou, Yang Bai, Jiahua Lai

In this paper, we first prove that when the associated graph of a polynomial set is chordal, a particular triangular set computed by a general algorithm in top-down style for computing the triangular decomposition of this polynomial set has an associated graph as a subgraph of this chordal graph. Then for Wang's method and a subresultant-based algorithm for

Naween Kumar, Dinesh Dash

In energy-constrained wireless sensor networks (WSNs), maximizing the data collection using mobile sink(s) with minimum energy consumption is one of the practical challenging issues. In this article, we consider the problem of efficient data collection along with a pre-specified path using a mobile sink with constant speed. We refer the problem as a Maximizi

Xige Yang, Dapeng Li

In this paper, we introduce a novel approach to study reaction-diffusion systems -- dynamic transition theory approach developed in Ma and Wang 2015. This approach generalizes Turing's classical result (linear stability analysis) on pattern formation and cast some new insights into Turing's systems. Specifically, we studied the Turing's instability and dynam

Aru Beri, Biswajit Paul, J S Yadav, H M Antia

We present results from an observation of the Low Mass X-ray Binary 4U 1636-536 obtained with the LAXPC instrument aboard AstroSat. The observations of 4U 1636-536 made during the performance verification phase of AstroSat showed seven thermonuclear X-ray bursts in a total exposure of ~ 65 ks over a period of about two consecutive days. Moreover, the light c

K. Murali, Sudeshna Sinha, Vivek Kohar, Behnam Kia

Certain nonlinear systems can switch between dynamical attractors occupying different regions of phase space, under variation of parameters or initial states. In this work we exploit this feature to obtain reliable logic operations. With logic output 0 or 1 mapped to dynamical attractors bounded in distinct regions of phase space, and logic inputs encoded by

S. Nakata, M. Horio, K. Koshiishi, K. Hagiwara

The nature of the pseudogap and its relationship with superconductivity are one of the central issues of cuprate superconductors. Recently, a possible scenario has been proposed that the pseudogap state is a distinct phase characterized by spontaneous rotational symmetry breaking called "nematicity" based on transport and magnetic susceptibility measurements

Charalampos Saitis, Kyriaki Kalimeri

In this study, we aim to better understand the cognitive-emotional experience of visually impaired people when navigating in unfamiliar urban environments, both outdoor and indoor. We propose a multimodal framework based on random forest classifiers, which predict the actual environment among predefined generic classes of urban settings, inferring on real-ti

Yaochen Li, Ying Liu, Rui Sun, Rui Guo

Multi-view point cloud registration is a hot topic in the communities of multimedia technology and artificial intelligence (AI). In this paper, we propose a framework to reconstruct the 3D models by the multi-view point cloud registration algorithm with adaptive convergence threshold, and subsequently apply it to 3D model retrieval. The iterative closest poi