November 2019 arXiv papers — page 4

Indranil SenGupta, William Nganje, Erik Hanson

A commonly used stochastic model for derivative and commodity market analysis is the Barndorff-Nielsen and Shephard (BN-S) model. Though this model is very efficient and analytically tractable, it suffers from the absence of long range dependence and many other issues. For this paper, the analysis is restricted to crude oil price dynamics. A simple way of im

Vivek Ramanujan, Mitchell Wortsman, Aniruddha Kembhavi, Ali Farhadi

Training a neural network is synonymous with learning the values of the weights. By contrast, we demonstrate that randomly weighted neural networks contain subnetworks which achieve impressive performance without ever training the weight values. Hidden in a randomly weighted Wide ResNet-50 we show that there is a subnetwork (with random weights) that is smal

Triparno Bandyopadhyay, Rinku Maji

We present a framework of dark- and visible-sector unification in the E6 embedding of the standard model. The demand for consistently getting the standard model leads to the existence of the dark-sector. We show that the hierarchy of vevs typifying unified models leads to multicomponent dark matter at the IR. The symmetry breaking itself categorises the matt

Alex Chandler, Radmila Sazdanovic, Salvatore Stella, Martha Yip

In this paper, we investigate the strength of chromatic symmetric homology as a graph invariant. Chromatic symmetric homology is a lift of the chromatic symmetric function for graphs to a homological setting, and its Frobenius characteristic is a q,t generalization of the chromatic symmetric function. We exhibit three pairs of graphs where each pair has the

N. C. Hara, F. Bouchy, M. Stalport, I. Boisse

Since 2011, the SOPHIE spectrograph has been used to search for Neptunes and super-Earths in the Northern Hemisphere. As part of this observational program, 290 radial velocity measurements of the 6.4 V magnitude star HD 158259 were obtained. Additionally, TESS photometric measurements of this target are available. We present an analysis of the SOPHIE data a

Richard Bowman, Boyko Vodenicharski, Joel Collins, Julian Stirling

The Raspberry Pi camera module is widely used in open source hardware projects as a low cost camera sensor. However, when the stock lens is removed and replaced with other custom optics the sensor will return a non-uniform background and colour response which hampers the use of this excellent and popular image sensor. This effect is found to be due to the se

Alkida Balliu, Sebastian Brandt, Yuval Efron, Juho Hirvonen

We present a complete classification of the deterministic distributed time complexity for a family of graph problems: binary labeling problems in trees. These are locally checkable problems that can be encoded with an alphabet of size two in the edge labeling formalism. Examples of binary labeling problems include sinkless orientation, sinkless and sourceles

E. G Charalampidis, N. Boullé, P. E. Farrell, P. G. Kevrekidis

Recently, a novel bifurcation technique known as the deflated continuation method (DCM) was applied to the single-component nonlinear Schr\"odinger (NLS) equation with a parabolic trap in two spatial dimensions. The bifurcation analysis carried out by a subset of the present authors shed light on the configuration space of solutions of this fundamental probl

Aniket Joglekar, Nirmal Raj, Philip Tanedo, Hai-Bo Yu

Dark matter can capture in neutron stars and heat them to observable luminosities. We study relativistic scattering of dark matter on highly degenerate electrons. We develop a Lorentz invariant formalism to calculate the capture probability of dark matter that accounts for the relativistic motion of the target particles and Pauli exclusion principle. We find

Maciej Skorski

Computing multivariate derivatives of matrix-like expressions in the compact, coordinate free fashion is very important for both theory and applied computations (e.g. optimization and machine learning). The critical components of such computations are \emph{chain and product rules} for derivatives. Although they are taught early in simple scenarios, practica

A. Korochkin, A. Neronov, D. Semikoz

Decaying axion-like particles (ALP) with masses in the eV range which might occupy dark matter halos of the Milky Way and other galaxies produce a characteristic "bump" feature in the spectrum of extragalactic background light (EBL). This feature leaves an imprint on the gamma-ray spectra of distant extragalactic sources. We derive constraints on the ALP cou

Patrick Dorey, Clare Dunning, Stefano Negro, Roberto Tateo

This review describes a link between Lax operators, embedded surfaces and Thermodynamic Bethe Ansatz equations for integrable quantum field theories. This surprising connection between classical and quantum models is undoubtedly one of the most striking discoveries that emerged from the off-critical generalisation of the ODE/IM correspondence, which initiall

Kathleen E. Hamilton, Raphael C. Pooser

Application-inspired benchmarks measure how well a quantum device performs meaningful calculations. In the case of parameterized circuit training, the computational task is the preparation of a target quantum state via optimization over a loss landscape. This is complicated by various sources of noise, fixed hardware connectivity, and for generative modeling

Omer Berat Sezer, Mehmet Ugur Gudelek, Ahmet Murat Ozbayoglu

Financial time series forecasting is, without a doubt, the top choice of computational intelligence for finance researchers from both academia and financial industry due to its broad implementation areas and substantial impact. Machine Learning (ML) researchers came up with various models and a vast number of studies have been published accordingly. As such,

Feihu Zhang, Xiaojuan Qi, Ruigang Yang, Victor Prisacariu

State-of-the-art stereo matching networks have difficulties in generalizing to new unseen environments due to significant domain differences, such as color, illumination, contrast, and texture. In this paper, we aim at designing a domain-invariant stereo matching network (DSMNet) that generalizes well to unseen scenes. To achieve this goal, we propose i) a n

Hans Jockers, Peter Mayr, Urmi Ninad, Alexander Tabler

We study the algebra of Wilson line operators in three-dimensional N=2 supersymmetric U(M) gauge theories with a Higgs phase related to a complex Grassmannian Gr(M,N), and its connection to K-theoretic Gromov-Witten invariants for Gr(M,N). For different Chern-Simons levels, the Wilson loop algebra realizes either the quantum cohomology of Gr(M,N), isomorphic

Bonnie Zaire, Laurene Jouve

Magnetic fields vary in complexity for different stars. The stability of dipolar magnetic fields is known to depend on different quantities, e.g., the stellar rotation, the stratification, and the intensity of convective motions. Here, we study the dipolar stability in a system with an inner stable zone. We present preliminary results of dynamo simulations u

Martin W. Liebeck, Aner Shalev, Pham Huu Tiep

Let $G$ be a finite group, and $\alpha$ a nontrivial character of $G$. The McKay graph ${\mathcal M}(G,\alpha)$ has the irreducible characters of $G$ as vertices, with an edge from $\chi_1$ to $\chi_2$ if $\chi_2$ is a constituent of $\alpha\chi_1$. We study the diameters of McKay graphs for simple groups $G$. For $G$ a group of Lie type, we show that for an

Atul Singh Arora, Jérémie Roland, Chrysoula Vlachou

Weak coin flipping (WCF) is a fundamental cryptographic primitive for two-party secure computation, where two distrustful parties need to remotely establish a shared random bit whilst having opposite preferred outcomes. It is the strongest known primitive with arbitrarily close to perfect security quantumly while classically, its security is completely compr

Lucien Hardy, Adam G. M. Lewis

We describe how one may go about performing quantum computation with arbitrary "quantum stuff", as long as it has some basic physical properties. Imagine a long strip of stuff, equipped with regularly spaced wires to provide input settings and to read off outcomes. After showing how the corresponding map from settings to outcomes can be construed as a quantu

Gia Dvali, Emmanouil Koutsangelas, Florian Kuhnel

We propose a novel class of compact dark matter objects in theories where the dark matter consists of multiple sectors. We call these objects $N$-MACHOs. In such theories neither the existence of dark matter species nor their extremely weak coupling to the observable sector represent additional hypotheses but instead are imposed by the solution to the Hierar

Edward Newell, Kian Kenyon-Dean, Jackie Chi Kit Cheung

Uncontextualized word embeddings are reliable feature representations of words used to obtain high quality results for various NLP applications. Given the historical success of word embeddings in NLP, we propose a retrospective on some of the most well-known word embedding algorithms. In this work, we deconstruct Word2vec, GloVe, and others, into a common fo

Saikat Chakraborty

Video abstraction has become one of the efficient approaches to grasp the content of a video without seeing it entirely. Key frame-based static video summarization falls under this category. In this paper, we propose a graph-based approach which summarizes the video with best user satisfaction. We treated each video frame as a node of the graph and assigned

Daniel L. Baker, Matthew Reynolds, Robin Masurel, Peter D. Olmsted

The glass transition is a long-standing unsolved problem in materials science. For polymers, our understanding of glass-formation is particularly poor due to the added complexity of chain connectivity and flexibility; structural relaxation of polymers thus involves a complex interplay between intra- and inter-molecular cooperativity. Here we study how the gl

Jun Qin, Lexing Ying

This note shows that the matrix forms of several one-parameter distribution families satisfy a hierarchical low-rank structure. Such families of distributions include binomial, Poisson, and $\chi^2$ distributions. The proof is based on a uniform relative bound of a related divergence function. Numerical results are provided to confirm the theoretical finding

Yuanjian Zheng, Hartmut Löwen

The ability to navigate in complex, inhomogeneous environments is fundamental to survival at all length scales, giving rise to the rapid development of various subfields in bio-locomotion such as the well established concept of chemotaxis. In this work, we extend this existing notion of taxis to rotating environments and introduce the idea of roto-taxis to b

David Fabian, Juanjo Rué, Christoph Spiegel

A set of integers $S \subset \mathbb{N}$ is an $\alpha$-strong Sidon set if the pairwise sums of its elements are far apart by a certain measure depending on $\alpha$, more specifically if $| (x+w) - (y+z) | \geq \max \{ x^{\alpha},y^{\alpha},z^{\alpha},w^\alpha \}$ for every $x,y,z,w \in S$ satisfying $\max \{x,w\} \neq \max \{y,z\}$. We obtain a new lower

Emilian M. Nica, Qimiao Si

Recent experiments in multiband Fe-based and heavy-fermion superconductors have challenged the long-held dichotomy between simple $s$- and $d$-wave spin-singlet pairing states. Here, we advance several time-reversal-invariant irreducible pairings that go beyond the standard singlet functions through a matrix structure in the band/orbital space, and elucidate

Alireza Mehrtash, William M. Wells, Clare M. Tempany, Purang Abolmaesumi

Fully convolutional neural networks (FCNs), and in particular U-Nets, have achieved state-of-the-art results in semantic segmentation for numerous medical imaging applications. Moreover, batch normalization and Dice loss have been used successfully to stabilize and accelerate training. However, these networks are poorly calibrated i.e. they tend to produce o

Hossein Khazaei, X. Andy Sun, Yue Zhao

With increasing renewable penetration in power systems, a prominent challenge in efficient and reliable power system operation is handling the uncertainties inherent in the renewable generation. In this paper, we propose a simple two-settlement market mechanism in which renewable power producers (RPPs) participate, so that a) the independent system operator

Christian Hennig

There are many distance-based methods for classification and clustering, and for data with a high number of dimensions and a lower number of observations, processing distances is computationally advantageous compared to the raw data matrix. Euclidean distances are used as a default for continuous multivariate data, but there are alternatives. Here the so-cal

Wonwoong Cho, Kangyeol Kim, Eungyeup Kim, Hyunwoo J. Kim

Disentangling content and style information of an image has played an important role in recent success in image translation. In this setting, how to inject given style into an input image containing its own content is an important issue, but existing methods followed relatively simple approaches, leaving room for improvement especially when incorporating sig

Hamid Farhadi

In this article we shall focus on the derivations on module extension of Banach algebras and determine the general structure of them. Then we obtain some results concerning the automatic continuity of these mappings.

Andrew Gambardella, Atılım Güneş Baydin, Philip H. S. Torr

It is well known that deep generative models have a rich latent space, and that it is possible to smoothly manipulate their outputs by traversing this latent space. Recently, architectures have emerged that allow for more complex manipulations, such as making an image look as though it were from a different class, or painted in a certain style. These methods

Michail Tarasiou, Stefanos Zafeiriou

Recent developments in computer vision and machine learning have made it possible to create realistic manipulated videos of human faces, raising the issue of ensuring adequate protection against the malevolent effects unlocked by such capabilities. In this paper we propose local image features that are shared across manipulated regions are the key element fo

Pranjal Awasthi, Vaggos Chatziafratis, Xue Chen, Aravindan Vijayaraghavan

Many machine learning systems are vulnerable to small perturbations made to inputs either at test time or at training time. This has received much recent interest on the empirical front due to applications where reliability and security are critical. However, theoretical understanding of algorithms that are robust to adversarial perturbations is limited. In

Manuel A. Buen-Abad, Raymond T. Co, Keisuke Harigaya

We consider a cosmological scenario where a relativistic particle and a stable massive particle are simultaneously produced from the decay of a late-decaying particle after Big-Bang Nucleosynthesis but before matter-radiation equality. The relativistic and massive particles behave as dark radiation and warm dark matter, respectively. Due to a common origin,

Shuowen Zhang, Rui Zhang

In this paper, we study the three-dimensional (3D) path planning for a cellular-connected unmanned aerial vehicle (UAV) to minimize its flying distance from given initial to final locations, while ensuring a target link quality in terms of the expected signal-to-interference-plus-noise ratio (SINR) at the UAV receiver with each of its associated ground base

George Ciprian Modoi

We study t-structures generated by sets of objects which satisfy a condition weaker than the compactness. We also study weight structures cogenerated by sets of objects satisfying the dual condition. Under some appropriate hypothesis, it turns out that the weight structure is right adjacent to the t-structure.

Shinya Kinoshita

This paper is concerned with the Cauchy problem of the modified Zakharov-Kuznetsov equation on $\mathbb{R}^d$. If $d=2$, we prove the sharp estimate which implies local in time well-posedness in the Sobolev space $H^s(\mathbb{R}^2)$ for $s \geq 1/4$. If $d \geq 3$, by employing $U^p$ and $V^p$ spaces, we establish the small data global well-posedness in the

Antonio Amariti, Andrea Marcassoli

The additional data necessary to univocally fix the gauge group for a given algebra are represented by the same charge lattices of mutually local Wilson and 't Hooft lines for both 4d $\mathcal{N}=4$ SYM and $\mathcal{N}=2$ elliptic models. Motivated by this equivalence in this paper we study the Lens space index of these $\mathcal{N}=2$ elliptic models. The

Maxim Dvornikov

We review the application of the relativistic quantum mechanics method for the description of neutrino oscillations for the studies of spin-flavor oscillations in background matter under the influence of a plane electromagnetic wave. Basing on the new exact solution of the Dirac-Pauli equation for a massive neutrino in the given external fields, we derive th

Saugata Basu, Antonio Lerario, Abhiram Natarajan

We study the expected behavior of the Betti numbers of arrangements of the zeros of random (distributed according to the Kostlan distribution) polynomials in $\mathbb{R}\mathrm{P}^n$. Using a random spectral sequence, we prove an asymptotically exact estimate on the expected number of connected components in the complement of $s$ such hypersurfaces in $\math

Jiangtong Li, Zhixin Ling, Li Niu, Liqing Zhang

The goal of Sketch-Based Image Retrieval (SBIR) is using free-hand sketches to retrieve images of the same category from a natural image gallery. However, SBIR requires all test categories to be seen during training, which cannot be guaranteed in real-world applications. So we investigate more challenging Zero-Shot SBIR (ZS-SBIR), in which test categories do

Alex Cameron, Jiasheng Yan

We say that a vertex-coloring of a graph is a proper k-distance domatic coloring if for each color, every vertex is within distance k from a vertex receiving that color. The maximum number of colors for which such a coloring exists is called the k-distance domatic number of the graph. The problem of determining the k-distance domatic number is motivated by q

Zihui Wu, Yu Sun, Alex Matlock, Jiaming Liu

Two features desired in a three-dimensional (3D) optical tomographic image reconstruction algorithm are the ability to reduce imaging artifacts and to do fast processing of large data volumes. Traditional iterative inversion algorithms are impractical in this context due to their heavy computational and memory requirements. We propose and experimentally vali

Jakob Hultgren, Erlend F. Wold

We provide unipotent factorizations of vector bundle automorphisms of real and complex vector bundles over smooth manifolds. This generalises work of Thurston-Wasserstein and Wasserstein for trivial vector bundles. We also address two symplectic cases and propose a complex geometric analog of the problem in the setting of holomorphic vector bundles over Stei

Oussama Ben Said, Jiahong Wu

This article examines the existence and uniqueness of weak solutions to the d-dimensional micropolar equations ($d=2$ or $d=3$) with general fractional dissipation $(-\Delta)^{\alpha}u$ and $(-\Delta)^{\beta}w$. The micropolar equations with standard Laplacian dissipation model fluids with microstructure. The generalization to include fractional dissipation

Timo Nolle, Alexander Seeliger, Nils Thoma, Max Mühlhäuser

In this paper, we propose DeepAlign, a novel approach to multi-perspective process anomaly correction, based on recurrent neural networks and bidirectional beam search. At the core of the DeepAlign algorithm are two recurrent neural networks trained to predict the next event. One is reading sequences of process executions from left to right, while the other

Alex Chandler, Radmila Sazdanovic

Using the tools of algebraic Morse theory, and the thin poset approach to constructing homology theories, we give a categorification of Whitney's broken circuit theorem for the chromatic polynomial, and for Stanley's chromatic symmetric function.

Shaohui Liu, Yinda Zhang, Songyou Peng, Boxin Shi

We propose a differentiable sphere tracing algorithm to bridge the gap between inverse graphics methods and the recently proposed deep learning based implicit signed distance function. Due to the nature of the implicit function, the rendering process requires tremendous function queries, which is particularly problematic when the function is represented as a

GiBaik Sim, Archana Mishra, Moon Jip Park, Yong Baek Kim

Topological superconductivity in multiband systems has received much attention due to a variety of possible exotic superconducting order parameters as well as non-trivial bulk and surface states. While the impact of coexisting magnetic order on superconductivity has been studied for many years, such as ferromagnetic superconductors, the implication of coexis

Ady Cambraia, Mostafa Salarinoghabi, Diego Trindade

For a pair of points in a smooth closed convex planar curve $\gamma$, its mid-line is the line containing its mid-point and the intersection point of the corresponding pair of tangent lines. It is well known that the envelope of the mid-lines ($EML$) is formed by the union of three affine invariants sets: Affine Envelope Symmetry Sets ($AESS$); Mid-Parallel

Konstantin Alkalaev, Xavier Bekaert

We aim at formulating a higher-spin gravity theory around AdS$_2$ relevant for holography. As a first step, we investigate its kinematics by identifying the low-dimensional cousins of the standard higher-dimensional structures in higher-spin gravity such as the singleton, the higher-spin symmetry algebra, the higher-rank gauge and matter fields, etc. In part

Adeline Fermanian

Sequential and temporal data arise in many fields of research, such as quantitative finance, medicine, or computer vision. A novel approach for sequential learning, called the signature method and rooted in rough path theory, is considered. Its basic principle is to represent multidimensional paths by a graded feature set of their iterated integrals, called

Hasanpour Tadi Saeed, Shokri Babak

Based on electromagnetic and acoustic transformation theory, a new strategy has been presented in this article to implement double invisibility cloaking, which has not been done yet. By applying a combination of four conventional cloaking methods, for cloaking an object by electromagnetic and acoustic waves, which are two essential methods for objects detect

M. Sedlmayr, N. Sedlmayr, J. Barnaś, V. K. Dugaev

In this article we consider the chiral Hall effect due to topologically protected kink states formed in topological insulators at boundaries between domains with differing topological invariants. Such systems include the surfaces of three dimensional topological insulators magnetically doped or in proximity with ferromagnets, as well as certain two dimension

CMS Collaboration

The cross section of top quark pair production is measured in the $\mathrm{t\bar{t}}$ $\to$ $(\ell\nu_{\ell})(\tau_\mathrm{h}\nu_{\tau})\mathrm{b\bar{b}}$ final state, where $\tau_\mathrm{h}$ refers to the hadronic decays of the $\tau$ lepton, and $\ell$ is either an electron or a muon. The data sample corresponds to an integrated luminosity of 35.9 fb$^{-1}

Denis Garoli, Giorgia Giovannini, Sandro Cattarin, Paolo Ponzellini

Plasmonics applications have been extending into the ultraviolet region of the electromagnetic spectrum. Unfortunately the commonly used noble metals have intrinsic optical properties that limit their use above 350 nm. Aluminum is probably the most suitable material for UV plasmonics and in this work we show that nanoporous aluminum can be prepared starting

Felix J. Meigel, Peter Cha, Michael P. Brenner, Karen Alim

Neuronal activity induces changes in blood flow by locally dilating vessels in the brain microvasculature. How can the local dilation of a single vessel increase flow-based metabolite supply, given that flows are globally coupled within microvasculature? Solving the supply dynamics for rat brain microvasculature, we find one parameter regime to dominate phys

Nicola Grittini

A group $G$ is said to be cut if, for every $g \in G$, each generator of $< \! g \! >$ is conjugated to either $g$ or $g^{-1}$. It is conjectured that a Sylow 3-subgroup $P$ of a cut group $G$ is cut. We prove that this is true if $|G|$ is odd.

N. Grittini

If a group $G$ is $\pi$-separable, where $\pi$ is a set of primes, the set of irreducible characters $\operatorname{B}_{\pi}(G) \cup \operatorname{B}_{\pi'}(G)$ can be defined. In this paper, we prove that there are variants of some classical theorems in character theory, namely the Theorem of Ito-Michler and Thompson theorem on character degrees, which invo

Eloise Hamilton

We study three instability stratifications of the stack of twisted Higgs bundle of a fixed rank and degree on a smooth complex projective curve. The first is the Harder-Narasimhan (HN) stratification, defined by the instability type of the Higgs bundle. The second is the bundle Harder-Narasimhan (bHN) stratification, defined by the instability type of the un

Julian Renner, Thomas Jerkovits, Hannes Bartz, Sven Puchinger

We address the problem of decoding Gabidulin codes beyond their unique error-correction radius. The complexity of this problem is of importance to assess the security of some rank-metric code-based cryptosystems. We propose an approach that introduces row or column erasures to decrease the rank of the error in order to use any proper polynomial-time Gabiduli

Nick Träger, Paweł Gruszecki, Filip Lisiecki, Felix Groß

The concept of Space-Time Crystals (STC), i.e. translational symmetry breaking in time and space, was recently proposed and experimentally demonstrated for quantum systems. Here, we transfer this concept to magnons and experimentally demonstrate a driven STC at room temperature. The STC is realized by strong homogeneous micro-wave pumping of a micron-sized p

Jehanne Dousse, Isaac Konan

In these two companion papers, we give infinite families of partition identities which generalise Primc's and Capparelli's identities, and study their consequences on the theory of crystal bases of the affine Lie algebra $A_{n-1}^{(1)}.$ In this first paper, we focus on combinatorial aspects. We give a $n^2$-coloured generalisation of Primc's identity by con

Weikaixin Kong, Xinyu Tu, Zhengwei Xie, Zhuo Huang

We used machine learning methods to predict NaV1.7 inhibitors and found the model RF-CDK that performed best on the imbalanced dataset. Using the RF-CDK model for screening drugs, we got effective compounds K1. We use the cell patch clamp method to verify K1. However, because the model evaluation method in this article is not comprehensive enough, there is s

Umut Şimşekli, Mert Gürbüzbalaban, Thanh Huy Nguyen, Gaël Richard

The gradient noise (GN) in the stochastic gradient descent (SGD) algorithm is often considered to be Gaussian in the large data regime by assuming that the \emph{classical} central limit theorem (CLT) kicks in. This assumption is often made for mathematical convenience, since it enables SGD to be analyzed as a stochastic differential equation (SDE) driven by

Hugo Ribeiro, Florian Marquardt

Recent advances illustrate the power of reservoir engineering in applications to many-body systems, such as quantum simulators based on superconducting circuits. We present a framework based on kinetic equations and noise spectra that can be used to understand both the transient and long-time behavior of many particles coupled to an engineered reservoir in a

Jehanne Dousse, Isaac Konan

In the first paper of this series, we gave infinite families of coloured partition identities which generalise Primc's and Capparelli's classical identities. In this second paper, we study the representation theoretic consequences of our combinatorial results. First, we show that the difference conditions we defined in our $n^2$-coloured generalisation of Pr

C. A. Wuensche, L. Reitano, M. W. Peel, I. W. A. Browne

The Baryon acoustic oscillations from Integrated Neutral Gas Observations (BINGO) telescope is a 40-m~class radio telescope under construction that has been designed to measure the large-angular-scale intensity of HI emission at 980--1260 MHz and hence to constrain dark energy parameters. A large focal plane array comprising of 1.7-metre diameter, 4.3-metre

John Fernley, Marcel Ortgiese

The voter model is a classical interacting particle system modelling how consensus is formed across a network. We analyse the time to consensus for the voter model when the underlying graph is a subcritical scale-free random graph. Moreover, we generalise the model to include a `temperature' parameter. The interplay between the temperature and the structure

Yang Su, Jianqiang Yang

In this paper we study smooth orientation-preserving free actions of the cyclic group $\mathbb Z/m$ on a class of $(n-1)$-connected $2n$-manifolds, $\sharp g (S^n \times S^n)\sharp \Sigma$, where $\Sigma$ is a homotopy $2n$-sphere. When $n=2$ we obtain a classification up to topological conjugation. When $n=3$ we obtain a classification up to smooth conjugat

L. Beilina, I. Gainova

The paper considers a time-adaptive method for determination of drug efficacy in a parameter identification problem (PIP) for system of ordinary differential equations (ODE) which describe dynamics of the primary HIV infection. Optimization approach to solve this problem is presented and a posteriori error estimates in the Tikhonov functional and Lagrangian

Jeremy Bleyer

Convex variational problems arise in many fields ranging from image processing to fluid and solid mechanics communities. Interesting applications usually involve non-smooth terms which require well-designed optimization algorithms for their resolution. The present manuscript presents the Python package called fenics_optim built on top of the FEniCS finite el

David Ziemkiewicz, Karol Karpiński, Sylwia Zielińska-Raczyńska, Gerard Czajkowski

We propose a scheme for calculation of optical functions of a semiconductor with Rydberg excitons, for a wide interval of dimensions. We start with 2-dimensional structure, then going to thin films and ending on 3-dimensional bulk crystals. The calculations including the polaritons are performed, the case of large number of polariton branches is discussed an

Haldun Özgür Bayındır

In this work, we study those differential graded algebras (DGAs) that arise from ring spectra through the extension of scalars functor. Namely, we study DGAs whose corresponding Eilenberg-Mac Lane ring spectrum is equivalent to $H\mathbb{Z} \wedge E$ for some ring spectrum $E$. We call these DGAs extension DGAs. We also define and study this notion for $E_\i

Liming Deng, Jie Wang, Hangming Liang, Hui Chen

Owing to its unique literal and aesthetical characteristics, automatic generation of Chinese poetry is still challenging in Artificial Intelligence, which can hardly be straightforwardly realized by end-to-end methods. In this paper, we propose a novel iterative polishing framework for highly qualified Chinese poetry generation. In the first stage, an encode

Cheonbok Park, Chunggi Lee, Hyojin Bahng, Yunwon Tae

Predicting road traffic speed is a challenging task due to different types of roads, abrupt speed change and spatial dependencies between roads; it requires the modeling of dynamically changing spatial dependencies among roads and temporal patterns over long input sequences. This paper proposes a novel spatio-temporal graph attention (ST-GRAT) that effective

Marcelo F. Ciappina, Maciej Lewenstein

Two emerging areas of research, attosecond and nanoscale physics, have recently started to merge. Attosecond physics deals with phenomena occurring when ultrashort laser pulses, with duration on the femto- and sub-femtosecond time scales, interact with atoms, molecules or solids. The laser-induced electron dynamics occurs natively on a timescale down to a fe

Eitan Levin, Tamir Bendory

The properties of gradient techniques for the phase retrieval problem have received a considerable attention in recent years. In almost all applications, however, the phase retrieval problem is solved using a family of algorithms that can be interpreted as variants of Douglas-Rachford splitting. In this work, we establish a connection between Douglas-Rachfor

Jesper Provoost, Luc Wismans, Sander Van der Drift, Andreas Kamilaris

Public road authorities and private mobility service providers need information derived from the current and predicted traffic states to act upon the daily urban system and its spatial and temporal dynamics. In this research, a real-time parking area state (occupancy, in- and outflux) prediction model (up to 60 minutes ahead) has been developed using publicl

Indranil Biswas, Sorin Dumitrescu

We investigate the holomorphic differential operators on a Riemann surface $M$. This is done by endowing $M$ with a projective structure. Let $\mathcal L$ be a theta characteristic on $M$. We explicitly describe the jet bundle $J^k(E\otimes {\mathcal L}^{\otimes n})$, where $E$ is a holomorphic vector bundle on $M$ equipped with a holomorphic connection, for

L. Banszerus, B. Frohn, T. Fabian, S. Somanchi

We report on measurements of quantized conductance in gate-defined quantum point contacts in bilayer graphene that allow the observation of subband splittings due to spin-orbit coupling. The size of this splitting can be tuned from 40 to 80 $\mu$eV by the displacement field. We assign this gate-tunable subband-splitting to a gap induced by spin-orbit couplin

Sean Moran, Steven McDonagh, Gregory Slabaugh

We present a novel approach to adjust global image properties such as colour, saturation, and luminance using human-interpretable image enhancement curves, inspired by the Photoshop curves tool. Our method, dubbed neural CURve Layers (CURL), is designed as a multi-colour space neural retouching block trained jointly in three different colour spaces (HSV, CIE

Geoffrey McGregor, Jean-Christophe Nave

In this paper we present a novel framework for obtaining high order numerical methods for 1-D scalar conservation laws with non-convex flux functions. When solving Riemann problems, the Oleinik entropy condition, [16], is satisfied when the resulting shocks and rarefactions correspond to correct portions of the appropriate (upper or lower) convex envelope of

Brendan Ruff, Taylor Beck, Joscha Bach

Deep convolutional neural networks are known to be unstable during training at high learning rate unless normalization techniques are employed. Normalizing weights or activations allows the use of higher learning rates, resulting in faster convergence and higher test accuracy. Batch normalization requires minibatch statistics that approximate the dataset sta

Mohammad Neinavaie, Mostafa Derakhtian, Sergiy A. Vorobyov

Minimum achievable complexity (MAC) for a maximum likelihood (ML) performance-achieving detection algorithm is derived. Using the derived MAC, we prove that the conventional sphere decoding (SD) algorithms suffer from an inherent weakness at low SNRs. To find a solution for the low SNR deficiency, we analyze the effect of zero-forcing (ZF) and minimum mean s

Fabio Grillo, Miguel-Angel Fernandez-Rodriguez, Maria-Nefeli Antonopoulou, Dominic Gerber

Self-assembled monolayers of microparticles encoding Archimedean and non-regular tessellations promise unprecedented structure-property relationships for a wide spectrum of applications in fields ranging from optoelectronics to surface technology. Yet, despite numerous computational studies predicting the emergence of exotic structures from simple interparti

Agnieszka Barbara Szczotka, Dzhoshkun Ismail Shakir, DanieleRavi, Matthew J. Clarkson

Purpose: Probe-based Confocal Laser Endomicroscopy (pCLE) enables performing an optical biopsy, providing real-time microscopic images, via a probe. pCLE probes consist of multiple optical fibres arranged in a bundle, which taken together generate signals in an irregularly sampled pattern. Current pCLE reconstruction is based on interpolating irregular signa

Sina Mohammadi, Mehrdad Noori, Ali Bahri, Sina Ghofrani Majelan

Beneficial from Fully Convolutional Neural Networks (FCNs), saliency detection methods have achieved promising results. However, it is still challenging to learn effective features for detecting salient objects in complicated scenarios, in which i) non-salient regions may have "salient-like" appearance; ii) the salient objects may have different-looking regi

Stefano Marchesani, Stefano Olla

We consider a chain of particles connected by an-harmonic springs, with a boundary force (tension) acting on the last particle, while the first particle is kept pinned at a point. The particles are in contact with stochastic heat baths, whose action on the dynamics conserves the volume and the momentum, while energy is exchanged with the heat baths in such w

Christopher D. Carone

We review some recent work by Carone, Erlich and Vaman on composite gravitons in metric-independent quantum field theories, with the aim of clarifying a number of basic issues. Focusing on a theory of scalar fields presented previously in the literature, we clarify the meaning of the tunings required to obtain a massless graviton. We argue that this formulat

O. Zenaiev, M. V. Garzelli, K. Lipka, S. -O. Moch

The impact of measurements of heavy-flavour production in deep inelastic $ep$ scattering and in $pp$ collisions on parton distribution functions is studied in a QCD analysis at next-to-leading order. Recent combined results of inclusive and heavy-flavour production cross sections in deep inelastic scattering at HERA are investigated together with heavy-flavo

Bjarke Frost Nielsen, Gaute Linga, Amalie Christensen, Joachim Mathiesen

Self-assembly of ordered nanometer-scale patterns is interesting in itself, but its practical value depends on the ability to predict and control pattern formation. In this paper we demonstrate theoretically and numerically that engineering of extrinsic as well as intrinsic substrate geometry may provide such a controllable ordering mechanism for block copol

Alexander Preuhs, Michael Manhart, Philipp Roser, Bernhard Stimpel

High quality reconstruction with interventional C-arm cone-beam computed tomography (CBCT) requires exact geometry information. If the geometry information is corrupted, e. g., by unexpected patient or system movement, the measured signal is misplaced in the backprojection operation. With prolonged acquisition times of interventional C-arm CBCT the likelihoo

Rajesh Chitnis, Andreas Emil Feldmann, MohammadTaghi Hajiaghayi, Dániel Marx

(see paper for full abstract) Given a vertex-weighted directed graph $G=(V,E)$ and a set $T=\{t_1, t_2, \ldots t_k\}$ of $k$ terminals, the objective of the SCSS problem is to find a vertex set $H\subseteq V$ of minimum weight such that $G[H]$ contains a $t_{i}\rightarrow t_j$ path for each $i\neq j$. The problem is NP-hard, but Feldman and Ruhl [FOCS '99; S

Felipe A. Cruz, Maxime Martinasso

As science gateways are becoming an increasingly popular digital interface for scientific communities, it is also becoming increasingly important for High-Performance Computing centers to provide a modern Web-enabled APIs. With such interface, science gateways can easily integrate access to HPC center resources. This work presents the FirecREST API, a RESTfu

Leo Feng, Luisa Zintgraf, Bei Peng, Shimon Whiteson

In few-shot learning, typically, the loss function which is applied at test time is the one we are ultimately interested in minimising, such as the mean-squared-error loss for a regression problem. However, given that we have few samples at test time, we argue that the loss function that we are interested in minimising is not necessarily the loss function mo

Russell Deitrick, João M. Mendonça, Urs Schroffenegger, Simon L. Grimm

THOR is the first open-source general circulation model (GCM) developed from scratch to study the atmospheres and climates of exoplanets, free from Earth- or Solar System-centric tunings. It solves the general non-hydrostatic Euler equations (instead of the primitive equations) on a sphere using the icosahedral grid. In the current study, we report major upg