November 2018 arXiv papers — page 8

Stefan Haar, Juraj Kolčák, Loïc Paulevé

Parametric models abstract part of the specification of dynamical models by integral parameters. They are for example used in computational systems biology, notably with parametric regulatory networks, which specify the global architecture (interactions) of the networks, while parameterising the precise rules for drawing the possible temporal evolutions of t

Daisuke Kadoh, Yoshinobu Kuramashi, Yoshifumi Nakamura, Ryo Sakai

We make a detailed analysis of the spontaneous $Z_{2}$-symmetry breaking in the two dimensional real $\phi^{4}$ theory with the tensor renormalization group approach, which allows us to take the thermodynamic limit easily and determine the physical observables without statistical uncertainties. We determine the critical coupling in the continuum limit employ

Ronnie Rodgers

We compute the holographic entanglement entropy contribution from planar two-dimensional defects in six-dimensional $\mathcal{N}=(2,0)$ superconformal field theory, holographically dual to probe M2- and M5-branes in $AdS_7 \times S^4$. In particular, we test the viability of the universal contribution of the defect to entanglement entropy as a candidate $C$-

John T. Stocke, Brian A. Keeney, Charles W. Danforth, Benjamin D. Oppenheimer

A small survey of the UV-absorbing gas in 12 low-$z$ galaxy groups has been conducted using the Cosmic Origins Spectrograph (COS) on-board the Hubble Space Telescope (HST). Targets were selected from a large, homogeneously-selected sample of groups found in the Sloan Digital Sky Survey (SDSS). A critical selection criterion excluded sight lines that pass clo

Ke Li, Tianhao Zhang, Jitendra Malik

Most existing methods for conditional image synthesis are only able to generate a single plausible image for any given input, or at best a fixed number of plausible images. In this paper, we focus on the problem of generating images from semantic segmentation maps and present a simple new method that can generate an arbitrary number of images with diverse ap

Eric Neiva, Michele Chiumenti, Miguel Cervera, Emilio Salsi

Among metal additive manufacturing technologies, powder-bed fusion features very thin layers and rapid solidification rates, leading to long build jobs and a highly localized process. Many efforts are being devoted to accelerate simulation times for practical industrial applications. The new approach suggested here, the virtual domain approximation, is a phy

Tomohiro Fujita, Ryo Namba, Ippei Obata

We study scalar-tensor-tensor cross correlation $\langle \zeta hh \rangle$ generated by the dynamics of interacting axion and SU(2) gauge fields during inflation. We quantize the quadratic action and solve the linear equations by taking into account mixing terms in a non-perturbative manner. Combining that with the in-in formalism, we compute contributions f

Ioann Vasilyev

Local boundary smoothness of an analytic function f on the unit ball of C^n is compared to the smoothness of its modulus. We prove that different conditions imposed on the zeros of f imply different drops of the smoothness. We also show that some of the drops are the best possible.

Johannes Bund, Christoph Lenzen, Moti Medina

Ikenmeyer et al. (JACM'19) proved an unconditional exponential separation between the hazard-free complexity and (standard) circuit complexity of explicit functions. This raises the question: which classes of functions permit efficient hazard-free circuits? In this work, we prove that circuit implementations of transducers with small state space are such a c

Raphaël Cerf, Wei Zhou

We consider the Bernoulli bond percolation model in a box $\Lambda$ (not necessarily parallel to the directions of the lattice) in the regime where the percolation parameter is close to $1$. We condition the configuration on the event that two opposite faces of the box are disconnected. We couple this configuration with an unconstrained percolation configura

Arash Arabi Ardehali, Finn Larsen, James T. Liu, Phillip Szepietowski

We study the Casimir energy of bulk fields in AdS$_3$ and its relation to subleading terms in the central charge of the dual CFT$_2$. Computing both sides of the standard CFT$_2$ relation $E=-c/12$ independently we show that this relation is not necessarily satisfied at the level of individual bulk supergravity states, but in theories with sufficient supersy

Sophia Borowka, Claude Duhr, Fabio Maltoni, Davide Pagani

We present a sensitivity study on the cubic and quartic self couplings in double Higgs production via gluon fusion at hadron colliders. Considering the relevant operators in the Standard Model Effective Field Theory up to dimension eight, we calculate the dominant contributions up to two-loop level, where the first dependence on the quartic interaction appea

Peter T. Breuer, Jonathan P. Bowen

This paper first describes an `obfuscating' compiler technology developed for encrypted computing, then examines if the trivial case without encryption produces much-sought indistinguishability obfuscation.

Steven M. Flores, Eveliina Peltola

We investigate a subalgebra of the Temperley-Lieb algebra called the Jones-Wenzl algebra, which is obtained by action of certain Jones-Wenzl projectors. This algebra arises naturally in applications to conformal field theory and statistical physics. It is also the commutant (centralizer) algebra of the Hopf algebra $U_q(\mathfrak{sl}_2)$ on its type-one modu

A. Foley, S. Verret, A. -M. S. Tremblay, D. Sénéchal

Antiferromagnetism and $d$-wave superconductivity are the most important competing ground-state phases of cuprate superconductors. Using cellular dynamical mean-field theory (CDMFT) for the Hubbard model, we revisit the question of the coexistence and competition of these phases in the one-band Hubbard model with realistic band parameters and interaction str

Simyung Chang, SeongUk Park, John Yang, Nojun Kwak

Recent advances in image-to-image translation have led to some ways to generate multiple domain images through a single network. However, there is still a limit in creating an image of a target domain without a dataset on it. We propose a method that expands the concept of `multi-domain' from data to the loss area and learns the combined characteristics of e

Aditya Bhaskara, Aidao Chen, Aidan Perreault, Aravindan Vijayaraghavan

Smoothed analysis is a powerful paradigm in overcoming worst-case intractability in unsupervised learning and high-dimensional data analysis. While polynomial time smoothed analysis guarantees have been obtained for worst-case intractable problems like tensor decompositions and learning mixtures of Gaussians, such guarantees have been hard to obtain for seve

Manoel Campêlo, Daniel Severín

A sequence of vertices in a graph is called a \emph{(total) legal dominating sequence} if every vertex in the sequence (total) dominates at least one vertex not dominated by those ones that precede it, and at the end all vertices of the graph are (totally) dominated. The \emph{Grundy (total) domination number} of a graph is the size of the largest (total) le

Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch

The key idea behind the unsupervised learning of disentangled representations is that real-world data is generated by a few explanatory factors of variation which can be recovered by unsupervised learning algorithms. In this paper, we provide a sober look at recent progress in the field and challenge some common assumptions. We first theoretically show that

M. A. L. Capri, R. C. Terin, H. C. Toledo

In this work we present an algebraic proof of the renormazibility of the super-Yang-Mills action quantized in a generalized supersymmetric version of the maximal Abelian gauge. The main point stated here is that the generalized gauge depends on a set of infinity gauge parameters in order to take into account all possible composite operators emerging from the

David Lafontaine

We prove Strichartz estimates without loss for the Schr\"odinger equation and the wave equation outside finitely many strictly convex obstacles verifying Ikawa's condition, extending the approach we introduced previously for the two convex case.

Sean Ledger, Andreas Sojmark

We present a simple uniqueness argument for a collection of McKean-Vlasov problems that have seen recent interest. Our first result shows that, in the weak feedback regime, there is global uniqueness for a very general class of random drivers. By weak feedback we mean the case where the contagion parameters are small enough to prevent blow-ups in solutions.

Joe G Greener, Shaun M Kandathil, David T Jones

The inapplicability of amino acid covariation methods to small protein families has limited their use for structural annotation of whole genomes. Recently, deep learning has shown promise in allowing accurate residue-residue contact prediction even for shallow sequence alignments. Here we introduce DMPfold, which uses deep learning to predict inter-atomic di

Howard Chen, Alane Suhr, Dipendra Misra, Noah Snavely

We study the problem of jointly reasoning about language and vision through a navigation and spatial reasoning task. We introduce the Touchdown task and dataset, where an agent must first follow navigation instructions in a real-life visual urban environment, and then identify a location described in natural language to find a hidden object at the goal posit

Miguel Berasategui, Daniel Carando

We show that, for $1<p \le 2$, the space $L_p(\mathbb{R}^d)$ does not admit unconditional Schauder frames $\left\lbrace f_i,f_i'\right\rbrace_{i\in\mathbb{N}}$ where $\left\lbrace f_i\right\rbrace$ is a sequence of translates of finitely many functions and $\left\lbrace f_i'\right\rbrace$ is seminormalized. In fact, the only subspaces of $L_p(\mathbb{R}^d)$

Shahab Mirjalili, Wai Hong Ronald Chan, Ali Mani

Micro-bubbles are of significant interest due to the long-living signature they leave behind naval ships. In order to numerically model and predict these bubbles in naval applications, subgrid-scale models are required because of the extreme separation of length- and time-scales between the macroscopic geometries and the physical processes leading to the for

Nils Mönning, Suresh Manandhar

Complex-valued neural networks are not a new concept, however, the use of real-valued models has often been favoured over complex-valued models due to difficulties in training and performance. When comparing real-valued versus complex-valued neural networks, existing literature often ignores the number of parameters, resulting in comparisons of neural networ

Tomáš Husek

We briefly summarize current experimental and theoretical results on the two important processes of the low-energy hadron physics involving neutral pions, the rare decay $\pi^0\to e^+e^-$ and the Dalitz decay of $\pi^0$, and provide a new value for the ratio $R={\Gamma(\pi^0\to e^+e^-\gamma(\gamma))}/{\Gamma(\pi^0\to\gamma\gamma)}=11.978(6)\times10^{-3}$, wh

Sina Mohseni, Eric Ragan

Nowadays, artificial intelligence algorithms are used for targeted and personalized content distribution in the large scale as part of the intense competition for attention in the digital media environment. Unfortunately, targeted information dissemination may result in intellectual isolation and discrimination. Further, as demonstrated in recent political e

Xiaoqing Zhou, D. C. Peets, Benjamin Morgan, W. A. Huttema

In cuprate superconductors, high magnetic fields have been used extensively to suppress superconductivity and expose the underlying normal state. Early measurements revealed insulating-like behavior in underdoped material versus temperature $T$, in which resistivity increases on cooling with a puzzling $\log(1/T)$ form. We instead use microwave measurements

Rohan Ghanta

We consider a Fr\"ohlich polaron bound in a symmetric Mexican hat-type potential. The ground state is unique and therefore invariant under rotations. However, we show that the minimizers of the corresponding Pekar problem are nonradial. Assuming these nonradial minimizers are unique up to rotation, we prove in the strong-coupling limit that the ground-state

Xi-Lin Li

We study a multiclass multiple instance learning (MIL) problem where the labels only suggest whether any instance of a class exists or does not exist in a training sample or example. No further information, e.g., the number of instances of each class, relative locations or orders of all instances in a training sample, is exploited. Such a weak supervision le

Jia Chen, Gang Wang, Georgios B. Giannakis

Multiview canonical correlation analysis (MCCA) seeks latent low-dimensional representations encountered with multiview data of shared entities (a.k.a. common sources). However, existing MCCA approaches do not exploit the geometry of the common sources, which may be available \emph{a priori}, or can be constructed using certain domain knowledge. This prior i

Caelan Wang, Karen Yeats

We generalize Schwenk's result that almost all trees contain any given limb to trees with positive integer vertex weights. The concept of characteristic polynomial is extended to such weighted trees and we prove that the proportion of $n$-vertex weighted trees that is weighted cospectral to another $n$-vertex weighted tree approaches $1$ as $n$ approaches in

Andy Hardt, Jared Marx-Kuo, Vaughan McDonald, John M. O'Brien

This paper gives a general algorithm for computing the character table of any Renner monoid Hecke algebra, by adapting and generalizing techniques of Solomon used to study the rook monoid. The character table of the Hecke algebra of the rook monoid (i.e., the Cartan type $A$ Renner monoid) was computed earlier by Dieng, Halverson, and Poladian using differen

Tony C. Dorlas, Alexei L. Rebenko, Baptiste Savoie

In this article, we investigate partially truncated correlation functions (PTCF) of infinite continuous systems of classical point particles with pair interaction. We derive Kirkwood-Salsburg-type equations for the PTCF and write the solutions of these equations as a sum of contributions labelled by certain forests graphs, the connected components of which a

Neil J. Gunther, Mohit Chawla

The need for Linux system administrators to do performance management has returned with a vengeance. Why? The cloud. Resource consumption in the cloud is all about pay-as-you-go. This article shows you how performance models can find the most cost-effective deployment of an application on Amazon's cloud.

Gui-Jun Ding, Stephen F. King, Cai-Chang Li

We perform an exhaustive analysis of all possible breaking patterns arising from $S_4\rtimes H_{CP}$ in a new {\it tri-direct CP approach} to the minimal seesaw model with two right-handed neutrinos, and construct a realistic flavour model along these lines. According to this approach, separate residual flavour and CP symmetries persist in the charged lepton

Célia Borlido, Mai Gehrke

Boolean spaces with internal semigroups generalize profinite semigroups and are pertinent for the recognition of not-necessarily regular languages. Via recognition, the study of existential quantification in logic on words amounts to the study of certain spans of Boolean spaces with internal semigroups. In turn, these can be understood as the superposition o

Philip Andreasson, Joel Johansson, Simon Liljestrand, Mats Granath

We implement a quantum error correction algorithm for bit-flip errors on the topological toric code using deep reinforcement learning. An action-value Q-function encodes the discounted value of moving a defect to a neighboring site on the square grid (the action) depending on the full set of defects on the torus (the syndrome or state). The Q-function is rep

Freweyni K. Teklehaymanot, Michael Muma, Abdelhak M. Zoubir

A major challenge in cluster analysis is that the number of data clusters is mostly unknown and it must be estimated prior to clustering the observed data. In real-world applications, the observed data is often subject to heavy tailed noise and outliers which obscure the true underlying structure of the data. Consequently, estimating the number of clusters b

Fei Wang

Extraordinary gauge mediation extension of deflected AMSB scenarios can be interesting because it can accommodate together the deflection in the Kahler potential and the superpotential. We revisit the EGM scenario and derive the analytical expressions for soft SUSY breaking parameters in EGM and EGM extension of deflected AMSB scenarios with wavefunction ren

Artur Bekasov, Iain Murray

Modern deep neural network models suffer from adversarial examples, i.e. confidently misclassified points in the input space. It has been shown that Bayesian neural networks are a promising approach for detecting adversarial points, but careful analysis is problematic due to the complexity of these models. Recently Gilmer et al. (2018) introduced adversarial

W. Zhu, Benedikt Fauseweh, Alexis Chacon, Jian-Xin Zhu

Ultrafast laser pulse has provided a systematic way to inspect the dynamics of electrons in condensed matter systems. In this paper, by means of time-dependent density matrix renormalization group, we study an ultrafast laser driven Kondo lattice model, in which conduction electrons are strongly coupled with magnetically local moments. The single-particle sp

Didier Ferrere, Yves Bandi, Frank Cadoux, Dean Forshaw

The TT-PET collaboration is developing an MRI-compatible small animal PET scanner in which the sensitive element is a monolithic silicon pixel ASIC targeting 30 ps RMS time resolution. The photon-detection technique is based on a stack of alternating layers of high-Z photon converter and 100 $\mathrm{\mu m}$ silicon sensors, to produce a scanner with 0.5 $\m

Evgeny D. Skvortsov

We propose a new approach to solve conformal field theories and apply it to Chern-Simons Matter theories and three-dimensional bosonization duality. All three-point correlation functions of single-trace operators are obtained in the large-$N$ as a simple application. The idea is to construct, as an effective weakly-coupled theory, a nonlinear realization of

Kubra Yeter-Aydeniz, Eugene F. Dumitrescu, Alex J. McCaskey, Ryan S. Bennink

Quantum field theory (QFT) simulations are a potentially important application for noisy intermediate scale quantum (NISQ) computers. The ability of a quantum computer to emulate a QFT, therefore, constitutes a natural application-centric benchmark. Foundational quantum algorithms to simulate QFT processes rely on fault-tolerant computational resources, but

Maxime M. C. Tortora, Garima Mishra, Domen Presern, Jonathan P. K. Doye

Lyotropic cholesteric liquid crystal phases are ubiquitously observed in biological and synthetic polymer solutions, characterized by a complex interplay between thermal fluctuations, entropic and enthalpic forces. The elucidation of the link between microscopic features and macroscopic chiral structure, and of the relative roles of these competing contribut

Pedro H. D. B. Hokama, Mário C. San Felice, Evandro C. Bracht, Fábio L. Usberti

Resource allocation problems are a family of problems in which resources must be selected to satisfy given demands. This paper focuses on the two-stage stochastic generalization of resource allocation problems where future demands are expressed in a finite number of possible scenarios. The goal is to select cost effective resources to be acquired in the pres

Francesco Bei

Let $(M,\omega,J,g)$ be a non-compact almost K\"ahler manifold. In this paper we provide various criteria that assure that $\omega^k$ induces a non trivial class in the reduced $L^p$ maximal/minimal cohomology of $(M,g)$. Furthermore in the last part we explore some topological applications of our results.

Benjamin Morris, Ludovico Lami, Gerardo Adesso

We study the process of assisted work distillation. This scenario arises when two parties share a bipartite quantum state $\rho_{AB}$ and their task is to locally distil the optimal amount of work when one party is restricted to thermal operations whereas the other can perform general quantum operations and they are allowed to communicate classically. We dem

Ye Yu, William A. P. Smith

We show how to train a fully convolutional neural network to perform inverse rendering from a single, uncontrolled image. The network takes an RGB image as input, regresses albedo and normal maps from which we compute lighting coefficients. Our network is trained using large uncontrolled image collections without ground truth. By incorporating a differentiab

T. Arrufat, M. Crialesi-Esposito, D. Fuster, Y. Ling

The computation of flows with large density contrasts is notoriously difficult. To alleviate the difficulty we consider a discretization of the Navier-Stokes equation that advects mass and momentum in a consistent manner. Incompressible flow with capillary forces is modeled and the discretization is performed on a staggered grid of Marker and Cell type. The

R. Srikanth

An operational concept of locality whose quantum violation is indicated independently of any other assumption(s) seems to be lacking in the quantum foundations literature so far. Bell's theorem only shows that quantum correlations violate the conjunction of the ontological assumptions of localism and determinism. Taking a cue from computational complexity th

Mohsen Joneidi, Alireza Zaeemzadeh, Nazanin Rahnavard, Mubarak Shah

The goal of data selection is to capture the most structural information from a set of data. This paper presents a fast and accurate data selection method, in which the selected samples are optimized to span the subspace of all data. We propose a new selection algorithm, referred to as iterative projection and matching (IPM), with linear complexity w.r.t. th

Rohan Ghanta

The ground-state electron density of a polaron bound to a Coulomb potential in a homogeneous magnetic field--the transverse coordinates integrated out--converges pointwise and weakly in the strong magnetic field limit to the square of a hyperbolic secant function.

Francesco Renga, Gianluca Cavoto, Angela Papa, Emanuele Ripiccini

The search for the Lepton Flavor Violating decay $\mu \to e \gamma$ exploits the most intense continuous muon beams, which can currently deliver $\sim 10^8$ muons per second. In the next decade, accelerator upgrades are expected in various facilities, making it feasible to have continuous beams with an intensity of $10^9$ or even $10^{10}$ muons per second.

Cédric Beaulac, Jeffrey S. Rosenthal, David Hodgson

In the following short article we adapt a new and popular machine learning model for inference on medical data sets. Our method is based on the Variational AutoEncoder (VAE) framework that we adapt to survival analysis on small data sets with missing values. In our model, the true health status appears as a set of latent variables that affects the observed c

Dian Mo, Marco F. Duarte

Wideband communication is often expected to deal with a very wide spectrum, which in many environments of interest includes strong interferers. Thus receivers for the wideband communication systems often need to mitigate interferers to reduce the distortion caused by the amplifier nonlinearity and noise. Recently, a new architecture for communication receive

J. Delavoipiére, B. Herteufeu, J. Teissiere, A. Chateauminois

Hydrogel coatings absorb water vapor - or other solvents - and, as such, are good candidates for antifog applications. In the present study, the transfer of vapor from the atmosphere to hydrogel thin films is measured in a situation where water vapor flows alongside the coating which is set to a temperature lower that the ambient temperature. The effect of t

Danilo Morales Teixeira, Erico Luiz Rempel

Space and astrophysical plasmas are frequently found in the regime of differential rotation, where the presence of a magnetic field can result in the magnetorotational instability, directly responsible for important phenomena such as turbulent angular momentum transport in accretion disks. In the absence of an imposed magnetic field, a nonlinear dynamo is ne

S. Hosseinzadeh, L. Jamilpanah, J. Shoa e Gharehbagh, M. Behboudnia

Proximity-induced magnetism (PIM) in graphene (Gr) adjacent to magnetic specimen has raised great fundamental interests. The subject is under debate and yet no application is proposed and granted. In this paper, toward accomplishment of fundamental facts, we first explore the effect of particle size and clustering in the PIM in Gr nanoplates (GNPs)/yttrium i

Francois Delduc, Sylvain Lacroix, Marc Magro, Benoit Vicedo

A systematic procedure for constructing classical integrable field theories with arbitrarily many free parameters is outlined. It is based on the recent interpretation of integrable field theories as realisations of affine Gaudin models. In this language, one can associate integrable field theories with affine Gaudin models having arbitrarily many sites. We

Patrick Godon

Observations of semi-detached interacting binaries reveal orbital modulation indicating the presence of absorbing material obscuring the disk and accreting primary star at specific orbital phases consistent with L1 stream material overflowing the disk edge. We simulate the L1 stream interaction with the disk using tests particles within the context of the Ro

Stefano Anselmi, Pier-Stefano Corasaniti, Ariel G. Sanchez, Glenn D. Starkman

Leveraging the Baryon Acoustic Oscillations (BAO) feature present in clustering 2-point statistics, we aim to measure cosmological distances independently of the underlying background cosmological model. However this inference is complicated by late-time non-linearities that introduce model and tracer dependencies in the clustering correlation function and p

Arun Pandey, Debrup Mukherjee, M. Bandyopadhyay, Dipshikha Borah

HELicon Experiment for Negative ion source (HELEN-I) with single driver is developed with a focus on the production of negative hydrogen ions. In the Helicon wave heated plasmas, very high plasma densities ($\sim10^{19} m^{-3}$) can be attained with electron temperatures as low as $\sim$1 eV in the downstream region. These conditions favor the production of

Kyle D. Bednar, Ian C. Cloët, Peter C. Tandy

The leading-twist parton distribution functions of the pion and kaon are calculated for the first time using a rainbow-ladder truncation of QCD's Dyson-Schwinger equations (DSEs) that self-consistently sums all planar diagrams. The non-perturbative gluon dressing of the quarks is thereby correctly accounted for, which in practice means solving the inhomogene

Andrew Wuensche, Edward Coxon

The cellular automaton (CA) pulsing model (arXiv:1806.06416) described the surprising phenomenon of spontaneous, sustained and robust rhythmic oscillations, pulsing dynamics, when random wiring is applied to a 2D `glider' rule running in a 3-value totalistic CA. Case studies, pulsing measures, possible mechanisms, and implications for oscillatory networks in

Alessandro Gaggero, Francesco Martini, Francesco Mattioli, Fabio Chiarello

The realization of large-scale photonic circuit for quantum optics experiments at telecom wavelengths requires an increasing number of integrated detectors. Superconductive nanowire single photon detectors (SNSPDs) can be easily integrated on chip and they can efficiently detect the light propagating inside waveguides. The thermal budget of cryostats poses a

Rex C. Y. Cheung, Alexander Aue, Seungyong Hwang, Thomas C. M. Lee

In many complex systems, networks and graphs arise in a natural manner. Often, time evolving behavior can be easily found and modeled using time-series methodology. Amongst others, two common research problems in network analysis are community detection and change-point detection. Community detection aims at finding specific sub-structures within the network

Wenjing Wu, David Cameron, Qing Di

Grid computing typically provides most of the data processing resources for large High Energy Physics experiments. However typical grid sites are not fully utilized by regular workloads. In order to increase the CPU utilization of these grid sites, the ATLAS@Home volunteer computing framework can be used as a backfilling mechanism. Results show an extra 15%

Andrea Arfé, Stefano Peluso, Pietro Muliere

In this paper we introduce the subdistribution beta-Stacy process, a novel Bayesian nonparametric process prior for subdistribution functions useful for the analysis of competing risks data. In particular, we i) characterize this process from a predictive perspective by means of an urn model with reinforcement, ii) show that it is conjugate with respect to r

Julien Ducoulombier, Victor Turchin, Thomas Willwacher

It is known that the bimodule derived mapping spaces between two operads have a delooping in terms of the operadic mapping space. We show a relative version of that statement. The result has applications to the spaces of disc embeddings fixed near the boundary and framed disc embeddings.

A. Huamán, Gonzalo Usaj

We study the transport properties of a monolayer transition metal dichalcogenide (TMDC) ribbon subject to a time periodic circularly polarized laser field. First, we calculate the quasienergy spectrum within the framework of the Floquet theory and analyze the nontrivial topology of the Floquet bulk gaps. The later is revealed by the presence of chiral edge s

Alexander Haber, Andreas Schmitt

Color-flavor locked quark matter can be described as a three-component superconductor and thus shows unconventional behavior in the transition regime from type-I to type-II superconductivity. We discuss this behavior by studying magnetic line defects in a Ginzburg-Landau approach, taking into account all possible values of the three winding numbers. After a

Clare Burrage, Edmund J. Copeland, Christian Käding, Peter Millington

Scalar fields coupled to gravity through the Ricci scalar have been considered both as dark matter candidates and as a possible modified gravity explanation for galactic dynamics. It has recently been demonstrated that the dynamics of baryonic matter in disk galaxies may be explained, in the absence of particle dark matter, by a symmetron scalar field that m

Victor Arnaiz

An exact semiclassical version of the classical KAM theorem about small perturbations of vector fields on the torus is given. Moreover, a renormalization theorem based on counterterms for some semiclassical systems that are close to being completely integrable is obtained. We apply these results to characterize the sets of semiclassical measures and quantum

Michael Zacharias, Markus Böttcher, Felix Jankowsky, Jean-Philippe Lenain

The flat spectrum radio quasar CTA 102 (redshift 1.037) exhibited a tremendously bright 4-months long outburst from late 2016 to early 2017. In a previous paper, we interpreted the event as the ablation of a gas cloud by the relativistic jet. The multiwavelength data have been reproduced very well within this model using a leptonic emission scenario. Here we

Mark Shoemaker

These expository notes are based on a series of lectures given at the May 2018 Snowbird workshop, Crossing the Walls in Enumerative Geometry. We give an introductory treatment of the notion of a virtual fundamental class in algebraic geometry, and describe a new construction of the virtual fundamental class for Gromov-Witten theory of a hypersurface. The res

Benjamin Planche, Xuejian Rong, Ziyan Wu, Srikrishna Karanam

We present a method to incrementally generate complete 2D or 3D scenes with the following properties: (a) it is globally consistent at each step according to a learned scene prior, (b) real observations of a scene can be incorporated while observing global consistency, (c) unobserved regions can be hallucinated locally in consistence with previous observatio

Thibaut Issenhuth, Vinkle Srivastav, Afshin Gangi, Nicolas Padoy

Purpose: Face detection is a needed component for the automatic analysis and assistance of human activities during surgical procedures. Efficient face detection algorithms can indeed help to detect and identify the persons present in the room, and also be used to automatically anonymize the data. However, current algorithms trained on natural images do not g

Adolfo Quiroz, Simón Ramírez-Amaya, Álvaro Riascos

High quality risk adjustment in health insurance markets weakens insurer incentives to engage in inefficient behavior to attract lower-cost enrollees. We propose a novel methodology based on Markov Chain Monte Carlo methods to improve risk adjustment by clustering diagnostic codes into risk groups optimal for health expenditure prediction. We test the perfor

Thorsten Wißmann, Jérémy Dubut, Shin-ya Katsumata, Ichiro Hasuo

There are different categorical approaches to variations of transition systems and their bisimulations. One is coalgebra for a functor G, where a bisimulation is defined as a span of G-coalgebra homomorphism. Another one is in terms of path categories and open morphisms, where a bisimulation is defined as a span of open morphisms. This similarity is no coinc

Warren P. Johnson

We compute the nth derivative of a function given parametrically, and of one given implicitly, and some history for both problems. I am posting this version of the paper at the request of Shaul Zemel, whose forthcoming paper The Combinatorics of Higher Derivatives of Implicit Functions refers to it.

Filipp Rukhovich

The existence of an aperiodic orbit for an outer billiard outside a regular octagon is proved. Additionally, almost all orbits of such an outer billiard are proved to be periodic. All possible periods are explicitly listed.

Paulo Luz, Filipe C. Mena, Amir Hadi Ziaie

The evolution of inhomogeneous space-times composed of uncharged fermions is studied for Szekeres metrics which have no Killing vectors, in general. Using the Einstein-Cartan theory to include the effects of (intrinsic) matter spin in General Relativity, the dynamics of a perfect fluid with non-null spin degrees of freedom is considered. It is shown that, if

Aswin Doekhie, Rajeev Dattani, Yun-Chu Chen, Yi Yang

Ensilication is a technology we developed that can physically stabilise proteins in silica without use of a pre-formed particle matrix. Stabilisation is done by tailor fitting individual proteins with a silica coat using a modified sol-gel process. Biopharmaceuticals, for example, liquid-formulated vaccines with adjuvants, have poor thermal stability. Heatin

Li Wan, Prashant Sridhar, Yang Yu, Quan Wang

In many scenarios of a language identification task, the user will specify a small set of languages which he/she can speak instead of a large set of all possible languages. We want to model such prior knowledge into the way we train our neural networks, by replacing the commonly used softmax loss function with a novel loss function named tuplemax loss. As a

Jonas Linzen, Maxim V. Polyakov, Kirill M. Semenov-Tian-Shansky, Nika S. Sokolova

A method of exact all-order summation of leading infrared logarithms in two dimensional massless $\Phi^4$-type non-renormalizable effective field theories (EFTs) is developed. The method is applied to the ${\rm O}(N)$-symmetric EFT, which is a two-dimensional sibling of the four dimensional ${\rm O}(N+1)/{\rm O}(N)$ sigma-model. For the first time the exact

Oem Trivedi

In this paper, we present a formulation of Schwinger's Method for non relativistic propogators in momentum space. While the aforementioned method has been used heavily in some papers to deduce various non relativistic propogators in position space, we show that a variation of method in momentum space works well. We also show how to extract the Propogator for

Giovanni Piredda, Sandra Stroj, Dorian Ziss, Julian Stangl

Lead-magnesium niobate lead-titanate (PMN-PT) has been proven as an excellent material for sensing and actuating applications. The fabrication of advanced ultra-small PMN-PT-based devices relies on the availability of sophisticated procedures for the micro-machining of PMN-PT thin films or bulk substrates. Approaches reported up to date include chemical etch

David Martinez-Delgado

Mergers and tidal interactions between massive galaxies and their dwarf satellites are a fundamental prediction of the Lambda-Cold Dark Matter cosmology. These events are thought to influence galaxy evolution throughout cosmic history and to provide important observational diagnostics of structure formation. Stellar streams in the Local Group are spectacular

Colin S. Gordon

Sequential effect systems are a class of effect system that exploits information about program order, rather than discarding it as traditional commutative effect systems do. This extra expressive power allows effect systems to reason about behavior over time, capturing properties such as atomicity, unstructured lock ownership, or even general safety properti

Ihusan Adam, Duccio Fanelli, Timoteo Carletti, Giacomo Innocenti

A procedure is developed and tested to recover the distribution of connectivity of an a priori unknown network, by sampling the dynamics of an ensemble made of reactive walkers. The relative weight between reaction and relocation is gauged by a scalar control parameter, which can be adjusted at will. Different equilibria are attained by the system, following

Ram Brustein, A. J. M. Medved, K. Yagi

Black hole (BH) thermodynamics was established by Bekenstein and Hawking, who made abstract theoretical arguments about the second law of thermodynamics and quantum theory in curved spacetime respectively. Testing these ideas experimentally has, so far, been impractical because the putative flux of Hawking radiation from astrophysical BHs is too small to be

Sergey Denisov, Tetyana Laptyeva, Wojciech Tarnowski, Dariusz Chruściński

To understand typical dynamics of an open quantum system in continuous time, we introduce an ensemble of random Lindblad operators, which generate Markovian completely positive evolution in the space of density matrices. Spectral properties of these operators, including the shape of the spectrum in the complex plane, are evaluated by using methods of free pr

Yuxuan Xia, Karl Granström, Lennart Svensson, Ángel F. García-Fernández

This paper proposes an efficient implementation of the Poisson multi-Bernoulli mixture (PMBM) trajectory filter. The proposed implementation performs track-oriented N-scan pruning to limit complexity, and uses dual decomposition to solve the involved multi-frame assignment problem. In contrast to the existing PMBM filter for sets of targets, the PMBM traject

Nate Veldt, Christine Klymko, David Gleich

Flow-based methods for local graph clustering have received significant recent attention for their theoretical cut improvement and runtime guarantees. In this work we present two improvements for using flow-based methods in real-world semi-supervised clustering problems. Our first contribution is a generalized objective function that allows practitioners to

Taylor Brysiewicz

We present our implementation of an algorithm which functions as a numerical oracle for the Newton polytope of a hypersurface in the Macaulay2 package NumericalNP.m2. We propose a tropical membership test, relying on this algorithm, for higher codimension varieties based on ideas from Hept and Theobald. To showcase this software, we investigate the Newton po

Finn Olav Bjørnson, Torgeir Dingsøyr

Software engineering is knowledge-intensive work, and how to manage software engineering knowledge has received much attention. This systematic review identifies empirical studies of knowledge management initiatives in software engineering, and discusses the concepts studied, the major findings, and the research methods used. Seven hundred and sixty-two arti