August 2018 arXiv papers — page 20

Xin Shi, Robert Qiu, Tiebin Mi, Xing He

With the deployment of online monitoring systems in distribution networks, massive amounts of data collected through them contains rich information on the operating states of the networks. By leveraging the data, an unsupervised approach based on bidirectional generative adversarial networks (BiGANs) is proposed for operational risk assessment in distributio

Mariusz Mirek, Elias M. Stein, Pavel Zorin-Kranich

The aim of this paper is to present an abstract and general approach to jump inequalities in harmonic analysis. Our principal conclusion is the refinement of $r$-variational estimates, previously known for $r>2$, to end-point results for the jump quasi-seminorm corresponding to $r=2$. This is applied to the dimension-free results recently obtained by the fir

Grant Backlund, James P. Hobert, Yeun Ji Jung, Kshitij Khare

Gibbs sampling is a widely popular Markov chain Monte Carlo algorithm that can be used to analyze intractable posterior distributions associated with Bayesian hierarchical models. There are two standard versions of the Gibbs sampler: The systematic scan (SS) version, where all variables are updated at each iteration, and the random scan (RS) version, where a

A. T. Deller, W. M. Goss, W. F. Brisken, S. Chatterjee

We present the results of PSR$π$, a large astrometric project targeting radio pulsars using the Very Long Baseline Array (VLBA). From our astrometric database of 60 pulsars, we have obtained parallax-based distance measurements for all but 3, with a parallax precision of typically 40 $μ$as and approaching 10 $μ$as in the best cases. Our full sample doubles t

Giovanni Caviglia, Javier J. Gutiérrez

Generalizing a result of Dwyer and Kan for simplicial categories, we characterize the morphisms of multi-sorted simplicial algebraic theories and simplicial coloured operads which induce a Quillen equivalence between the corresponding categories of algebras.

Alexey Romanov, Anna Rumshisky, Anna Rogers, David Donahue

In this paper, we present a method for adversarial decomposition of text representation. This method can be used to decompose a representation of an input sentence into several independent vectors, each of them responsible for a specific aspect of the input sentence. We evaluate the proposed method on two case studies: the conversion between different social

Piotr Kokocki

In this paper, we establish a formula determining the value of the Cauchy integrals of the real and purely imaginary Ablowitz-Segur solutions for the inhomogeneous second Painlevé equation. Our approach relies on the analysis of the corresponding Riemann-Hilbert problem and the construction of an appropriate parametrix in a neighborhood of the origin. Obtain

Chico Q. Camargo, Scott A. Hale, Peter John, Helen Z. Margetts

Recent election surprises, regime changes, and political shocks indicate that political agendas have become more fast-moving and volatile. The ability to measure the complex dynamics of agenda change and capture the nature and extent of volatility in political systems is therefore more crucial than ever before. This study proposes a definition and operationa

Justin Domke, Daniel Sheldon

Recent work used importance sampling ideas for better variational bounds on likelihoods. We clarify the applicability of these ideas to pure probabilistic inference, by showing the resulting Importance Weighted Variational Inference (IWVI) technique is an instance of augmented variational inference, thus identifying the looseness in previous work. Experiment

A. Urichuk, Y. Oez, A. Klümper, J. Sirker

Based on a generalized free energy we derive exact thermodynamic Bethe ansatz formulas for the expectation value of the spin current, the spin current-charge, charge-charge correlators, and consequently the Drude weight. These formulas agree with recent conjectures within the generalized hydrodynamics formalism. They follow, however, directly from a proper t

Yurui Qu, Li Jing, Yichen Shen, Min Qiu

Deep learning is known to be data-hungry, which hinders its application in many areas of science when datasets are small. Here, we propose to use transfer learning methods to migrate knowledge between different physical scenarios and significantly improve the prediction accuracy of artificial neural networks trained on a small dataset. This method can help r

Sarah Jo Weinstein, Irena Swanson

For arbitrary positive integers $q_1 \ge q_2 \ge q_3 \ge \cdots$ we construct a family of monomial ideals such that for each positive integer $e$ and for each ideal $I$ in the family, the number of associated primes of $I^e$ is the $q_e$. We present the associated primes explicitly.

Daniel Neider, Alexander Weinert, Martin Zimmermann

Linear Temporal Logic (LTL) is the standard specification language for reactive systems and is successfully applied in industrial settings. However, many shortcomings of LTL have been identified in the literature, among them the limited expressiveness, the lack of quantitative features, and the inability to express robustness. There is work on overcoming the

Sergey Gordeychik, Denis Kolegov, Antony Nikolaev

The concept of software defined wide area network (SD-WAN or SDWAN) is central to modern computer networking, particularly in enterprise networks. By definition, these systems form network perimeter and connect Internet, WAN, extranet, and branches that makes them crucial from cybersecurity point of view. The goal of this paper is to provide the results of p

Mizanur Rahman, Mhafuzul Islam, Jon Calhoun, Mashrur Chowdhury

Vehicle-to-Pedestrian (V2P) communication can significantly improve pedestrian safety at a signalized intersection. It is unlikely that pedestrians will carry a low latency communication enabled device and activate a pedestrian safety application in their hand-held device all the time. Because of this limitation, multiple traffic cameras at the signalized in

Matthew Forslund, Nikolaos Kidonakis

We discuss the associated production of a top quark with a photon via anomalous $t$-$q$-$γ$ couplings, and present higher-order corrections from soft-gluon emission for the processes $gq \rightarrow tγ$ at LHC energies. We perform soft-gluon resummation at next-to-leading-logarithm accuracy and derive approximate next-to-next-to-leading order (aNNLO) double-

Haakon T. Simensen, Roberto E. Troncoso, Arne Brataas

We consider magnetostriction in magnetic materials. Starting from a microscopic lattice model of the magneto-elastic coupling, we derive the continuum magnetostriction Hamiltonian in cubic ferromagnets and antiferromagnets. In ferromagnets, our results agree with established results. In antiferromagnets, we find a new central contribution which reflects the

Yaowu Liu, Jun Xie

Combining individual p-values to aggregate multiple small effects has a long-standing interest in statistics, dating back to the classic Fisher's combination test. In modern large-scale data analysis, correlation and sparsity are common features and efficient computation is a necessary requirement for dealing with massive data. To overcome these challeng

A. W. Wise, S. E. Dodson-Robinson, K. Bevenour, A. Provini

Starspots, plages, and activity cycles cause radial velocity variations that can either mimic planets or hide their existence. To verify the authenticity of newly discovered planets, observers may search for periodicity in spectroscopic activity indices such as Ca H & K and H$α$, then mask out any Doppler signals that match the activity period or its harmoni

Mohamed Taoufiq Damir, Lenny Fukshansky

Ideal lattices in the plane coming from real quadratic number fields have been investigated by several authors in the recent years. In particular, it has been proved that every such ideal has a basis that can be twisted by the action of the diagonal group into a Minkowski reduced basis for a well-rounded lattice. We explicitly study such twists on the canoni

Marzieh Fadaee, Christof Monz

Neural Machine Translation has achieved state-of-the-art performance for several language pairs using a combination of parallel and synthetic data. Synthetic data is often generated by back-translating sentences randomly sampled from monolingual data using a reverse translation model. While back-translation has been shown to be very effective in many cases,

Jia-Chun Lin, Ming-Chang Lee, Ingrid Chieh Yu, Einar Broch Johnsen

As more and more devices connect to Internet of Things, unbounded streams of data will be generated, which have to be processed "on the fly" in order to trigger automated actions and deliver real-time services. Spark Streaming is a popular realtime stream processing framework. To make efficient use of Spark Streaming and achieve stable stream process

Jason Gaddis, Daniel Yee

We study the congeniality property of algebras, as defined by Bao, He, and Zhang, in order to establish a version of Auslander's theorem for various families of filtered algebras. It is shown that the property is preserved under homomorphic images and tensor products under some mild conditions. Examples of congenial algebras in this paper include envelop

A. Veledina, A. V. Berdyugin, I. A. Kosenkov, J. J. E. Kajava

Aims. The optical emission of black hole transients increases by several magnitudes during the X-ray outbursts. Whether the extra light arises from the X-ray heated outer disc, from the inner hot accretion flow, or from the jet is currently debated. Optical polarisation measurements are able to distinguish the relative contributions of these components. Meth

Erik Curiel

The question of the existence of gravitational stress-energy in general relativity has exercised investigators in the field since the inception of the theory. Folklore has it that no adequate definition of a localized gravitational stress-energetic quantity can be given. Most arguments to that effect invoke one version or another of the Principle of Equivale

Li-Chun Zhang, Ingvild Johansen, Ragnhild Nygaard

There is generally a need to deal with quality change and new goods in the consumer price index due to the underlying dynamic item universe. Traditionally axiomatic tests are defined for a fixed universe. We propose five tests explicitly formulated for a dynamic item universe, and motivate them both from the perspectives of a cost-of-goods index and a cost-o

Iddo Eliazar, Ralf Metzler, Shlomi Reuveni

"A chain is only as strong as its weakest link" says the proverb. But what about a collection of statistically identical chains: How long till all chains fail? The answer to this question is given by the Max-Min of a matrix whose $\left(i,j\right)$ entry is the failure time of link $j$ of chain $i$: take the minimum of each row, and then the maximum

Natalia Chepiga, Frédéric Mila

We investigate the nature of the phase transition between the period-three charge-density wave and the disordered phase of a hard-boson model proposed in the context of cold-atom experiments. Building on a density-matrix renormalization group algorithm that takes full advantage of the hard-boson constraints, we study systems with up to 9'000 sites and ca

Maurice Chandoo

We show how to systematically implement an algorithm in any imperative or functional programming language. The method is based on the premise that it is easy to write down how an algorithm proceeds on a concrete input. This information---which we call execution trace---is used as a starting point to derive the desired program. In contrast to test-driven deve

Maria Quadeer, Marco Tomamichel, Christopher Ferrie

We investigate minimax estimators for quantum state tomography under general Bregman divergences. First, generalizing the work of Komaki et al. $\href{http://dx.doi.org/10.3390/e19110618}{\textrm{[Entropy 19, 618 (2017)]}}$ for relative entropy, we find that given any estimator for a quantum state, there always exists a sequence of Bayes estimators that asym

Zhe Wang, Dylan Cashman, Mingwei Li, Jixian Li

Visual exploration of large multidimensional datasets has seen tremendous progress in recent years, allowing users to express rich data queries that produce informative visual summaries, all in real time. Techniques based on data cubes are some of the most promising approaches. However, these techniques usually require a large memory footprint for large data

Chenglong Ye, Lin Zhang, Mingxuan Han, Yanjia Yu

This paper aims to better predict highly skewed auto insurance claims by combining candidate predictions. We analyze a version of the Kangaroo Auto Insurance company data and study the effects of combining different methods using five measures of prediction accuracy. The results show the following. First, when there is an outstanding (in terms of Gini Index)

Maarten van Reeuwijk, Markus Holzner, C. P. Caulfield

We explore the dynamics of inclined temporal gravity currents using direct numerical simulation, and find that the current creates an environment in which the flux Richardson number $Ri_f$, gradient Richardson number $Ri_g$, and turbulent flux coefficient $Γ$ are constant across a large portion of the depth. Changing the slope angle $α$ modifies these mixing

Theo Heimel, Gregor Kasieczka, Tilman Plehn, Jennifer M Thompson

Autoencoder networks, trained only on QCD jets, can be used to search for anomalies in jet-substructure. We show how, based either on images or on 4-vectors, they identify jets from decays of arbitrary heavy resonances. To control the backgrounds and the underlying systematics we can de-correlate the jet mass using an adversarial network. Such an adversarial

Ofer Aharony, Shouvik Datta, Amit Giveon, Yunfeng Jiang

We study families of two dimensional quantum field theories, labeled by a dimensionful parameter $μ$, that contain a holomorphic conserved $U(1)$ current $J(z)$. We assume that these theories can be consistently defined on a torus, so their partition sum, with a chemical potential for the charge that couples to $J$, is modular covariant. We further require t

Jonathan Wurtz, Anatoli Polkovnikov

Connecting short time microscopic dynamics with long time hydrodynamics in strongly correlated quantum systems is one of the outstanding questions. In particular, it is very difficult to determine various hydrodynamic coefficients like the diffusion constant or viscosity starting from a microscopic model: exact quantum simulations are limited to either small

Alexandre Alves, Tathagata Ghosh, Huai-Ke Guo, Kuver Sinha

We perform a complementarity study of gravitational waves and colliders in the context of electroweak phase transitions choosing as our template the xSM model, which consists of the Standard Model augmented by a real scalar. We carefully analyze the gravitational wave signal at benchmark points compatible with a first order phase transition, taking into acco

G. G. Batrouni, Richard T. Scalettar

We present a Quantum Monte Carlo (QMC) study, based on the Langevin equation, of a Hamiltonian describing electrons coupled to phonon degrees of freedom. The bosonic part of the action helps control the variation of the field in imaginary time. As a consequence, the iterative conjugate gradient solution of the fermionic action, which depends on the boson coo

Olaf Lechtenfeld, Alexander D. Popov

Firstly, we consider Yang-Mills theory on ${\mathbb R}^{3,1}$ with an adjoint Higgs field spontaneously breaking a compact gauge group $G$ to a subgroup $H$, so that the Higgs vacuum manifold forms the coset $G/H$. It is shown that in the low-energy limit, when the Higgs vacuum value is large, the 4d Yang-Mills-Higgs theory reduces to the Faddeev sigma model

Yanou Cui, Marek Lewicki, David E. Morrissey, James D. Wells

Many motivated extensions of the Standard Model predict the existence of cosmic strings. Gravitational waves originating from the dynamics of the resulting cosmic string network have the ability to probe many otherwise inaccessible properties of the early universe. In this study we show how the spectrum of gravitational waves from a cosmic string network can

Michele Cicoli, Senarath de Alwis, Anshuman Maharana, Francesco Muia

De Sitter solutions have been recently conjectured to be incompatible with quantum gravity. In this paper we critically assess the progress and challenges of different mechanisms to obtain de Sitter vacua in string compactifications and compare them to quintessence models. We argue that, despite recent criticisms, de Sitter models reached a level of concrete

Dumitru Calugaru, Vladimir Juricic, Bitan Roy

We propose a general principle for constructing higher-order topological (HOT) phases. We argue that if a $D$-dimensional first-order or regular topological phase involves $m$ Hermitian matrices that anti-commute with additional $p-1$ mutually anti-commuting matrices, it is conceivable to realize an $n$th-order HOT phase, where $n=1, \cdots, p$, with appropr

Lev Vidmar, Lucas Hackl, Eugenio Bianchi, Marcos Rigol

Much has been learned about universal properties of entanglement entropies in ground states of quantum many-body lattice systems. Here we unveil universal properties of the average bipartite entanglement entropy of eigenstates of the paradigmatic quantum Ising model in one dimension. The leading term exhibits a volume-law scaling that we argue is universal f

Vitor Cardoso, Masashi Kimura, Andrea Maselli, Leonardo Senatore

Effective field theory methods suggest that some rather-general extensions of General Relativity include, or are mimicked by, certain higher-order curvature corrections, with coupling constants expected to be small but otherwise arbitrary. Thus, the tantalizing prospect to test the fundamental nature of gravity with gravitational-wave observations, in a syst

Vivian Poulin, Pierre Salati, Ilias Cholis, Marc Kamionkowski

We discuss the origin of the anti-helium-3 and -4 events possibly detected by AMS-02. Using up-to-date semi-analytical tools, we show that spallation from primary hydrogen and helium nuclei onto the ISM predicts a $\overline{{}^3{\rm He}}$ flux typically one to two orders of magnitude below the sensitivity of AMS-02 after 5 years, and a $\overline{{}^4{\rm H

Masanori Hanada, Paul Romatschke

We perform microcanonical classical statistical lattice simulations of SU(N) Yang-Mills theory with eight scalars on a circle. Measuring the eigenvalue distribution of the spatial Wilson loop we find two distinct phases depending on the total energy and circle radius, which we tentatively interpret as corresponding to black hole and black string phases in a

J. Goldstein, R. H. D. Townsend, E. G. Zweibel

The Tayler instability (TI) is a non-axisymmetric linear instability of an axisymmetric toroidal magnetic field in magneto-hydrostatic equilibrium (MHSE). Spruit (1999, 2002) has proposed that in a differentially rotating radiative region of a star, the TI drives a dynamo which generates magnetic fields that can efficiently transport angular momentum; a para

Maximilian Dax, Tobias Isken, Bastian Kubis

We study the quark-mass dependence of $ω\to3π$ decays, based on a dispersion-theoretical framework. We rely on the quark-mass-dependent scattering phase shift for the pion-pion $P$-wave extracted from unitarized chiral perturbation theory. The dispersive representation then takes into account the final-state rescattering among all three pions. The described

Matthew Baumgart, Timothy Cohen, Emmanuel Moulin, Ian Moult

We provide precise predictions for the hard photon spectrum resulting from neutral SU$(2)_W$ triplet (wino) dark matter annihilation. Our calculation is performed utilizing an effective field theory expansion around the endpoint region where the photon energy is near the wino mass. This has direct relevance to line searches at indirect detection experiments.

Matthew E. Peters, Mark Neumann, Luke Zettlemoyer, Wen-tau Yih

Contextual word representations derived from pre-trained bidirectional language models (biLMs) have recently been shown to provide significant improvements to the state of the art for a wide range of NLP tasks. However, many questions remain as to how and why these models are so effective. In this paper, we present a detailed empirical study of how the choic

Gongbo Tang, Mathias Müller, Annette Rios, Rico Sennrich

Recently, non-recurrent architectures (convolutional, self-attentional) have outperformed RNNs in neural machine translation. CNNs and self-attentional networks can connect distant words via shorter network paths than RNNs, and it has been speculated that this improves their ability to model long-range dependencies. However, this theoretical argument has not

Izael A. Lima, Eric J. R. Parteli, Yaping Shao, José S. Andrade

Sand fences are often erected to reduce wind speed, prevent aeolian soil erosion, and induce sand deposition and dune formation in areas affected by sand encroachment and desertification. However, the search for the most efficient array of fences by means of field experiments alone poses a challenging task given that field experiments are affected by weather

Martin H. Weissman

If $G$ is a group acting on a tree $X$, and ${\mathcal S}$ is a $G$-equivariant sheaf of vector spaces on $X$, then its compactly-supported cohomology is a representation of $G$. Under a finiteness hypothesis, we prove that if $H_c^0(X, {\mathcal S})$ is an irreducible representation of $G$, then $H_c^0(X, {\mathcal S})$ arises by induction from a vertex or

S. Baines, N. E. Mavromatos, V. A. Mitsou, J. L. Pinfold

In this work we consider point-like monopole production via photon-fusion and Drell-Yan processes in the framework of an effective U(1) gauge field theory obtained from conventional models describing the interaction of spin 0, 1/2, 1 magnetically-charged fields with ordinary photons, upon electric-magnetic dualisation. We present arguments based on such dual

Tom Hutchcroft

Around 2008, Schramm conjectured that the critical probabilities for Bernoulli bond percolation satisfy the following continuity property: If $(G_n)_{n\geq 1}$ is a sequence of transitive graphs converging locally to a transitive graph $G$ and $\limsup_{n\to\infty} p_c(G_n) < 1$, then $ p_c(G_n)\to p_c(G)$ as $n\to\infty$. We verify this conjecture under the

Yu-Ting Lin, Yu-Lun Lo, Chen-Yun Lin, Hau-Tieng Wu

Object: It is increasingly popular to collect as much data as possible in the hospital setting from clinical monitors for research purposes. However, in this setup the data calibration issue is often not discussed and, rather, implicitly assumed, while the clinical monitors might not be designed for the data analysis purpose. We hypothesize that this calibra

Jean Gillibert, Aaron Levin

We introduce the use of $p$-descent techniques for elliptic surfaces over a perfect field of characteristic not $2$ or $3$. Under mild hypotheses, we obtain an upper bound for the rank of a non-constant elliptic surface. When $p=2$, this bound is an arithmetic refinement of a well-known geometric bound for the rank deduced from Igusa&#39;s inequality. This a

Felipe A. Asenjo

A pair plasma in hidrostatic equilibrium near the horizon of a Schwarzschild black hole is an exact state. In this work, we show that an exact non--hidrostatic equilibrium state can be sustained for a pair plasma, in which its constituents are moving near the horizon of the black hole. This equilibrium state solution is not due to a vortical formalism, but b

Filippo Mazzoli

Given a differentiable deformation of geometrically finite hyperbolic $3$-manifolds $(M_t)_t$, the Bonahon-Schläfli formula expresses the derivative of the volume of the convex cores $(C M_t)_t$ in terms of the variation of the geometry of its boundary, as the classical Schläfli formula does for the volume of hyperbolic polyhedra. Here we study the analogous

Hamid Mohammadi, Roozbeh Dargazany

This paper presents a micro-mechanical approach to describe the effects of thermo-oxidation on the constitutive behavior of aged elastomers at the long-range timescales. In particular, this model focuses on the effects of thermo-oxidative aging on the quasi-static mechanical response of elastomer and their inelastic responses such as Mullins effect and perma

Xilun Chen, Claire Cardie

Multilingual Word Embeddings (MWEs) represent words from multiple languages in a single distributional vector space. Unsupervised MWE (UMWE) methods acquire multilingual embeddings without cross-lingual supervision, which is a significant advantage over traditional supervised approaches and opens many new possibilities for low-resource languages. Prior art f

Zhengyang Wang, Shuiwang Ji

Dilated convolutions, also known as atrous convolutions, have been widely explored in deep convolutional neural networks (DCNNs) for various dense prediction tasks. However, dilated convolutions suffer from the gridding artifacts, which hampers the performance. In this work, we propose two simple yet effective degridding methods by studying a decomposition o

Patrizio Angelini, Peter Eades, Seok-Hee Hong, Karsten Klein

Motivated by hybrid graph representations, we introduce and study the following beyond-planarity problem, which we call $h$-Clique2Path Planarity: Given a graph $G$, whose vertices are partitioned into subsets of size at most $h$, each inducing a clique, remove edges from each clique so that the subgraph induced by each subset is a path, in such a way that t

Muhammad Sajid, János K. Asbóth, Dieter Meschede, Reinhard F. Werner

We propose a realistic scheme to construct anomalous Floquet Chern topological insulators using spin-1/2 particles carrying out a discrete-time quantum walk in a two-dimensional lattice. By Floquet engineering the quantum-walk protocol, an Aharonov-Bohm geometric phase is imprinted onto closed-loop paths in the lattice, thus realizing an abelian gauge field-

Nico Lombardi, Jie Xiao

This note discovers not only an affine non-sharp-Poisson trace inequality but also its sharp-non-Poisson version for a Sobolev function with the fractional antiderivative.

Aliakbar Daemi, Kenji Fukaya

In this paper, Floer homology for Lagrangian submanifolds in an open symplectic manifold given as the complement of a smooth divisor is discussed. The main new feature of this construction is that we do not make any assumption on positivity or negativity of the divisor. To achieve this goal, we use a compactification of the moduli space of pseudo-holomorphic

Zhenguo Nie, Haoliang Jiang, Levent Burak Kara

The demand for fast and accurate structural analysis is becoming increasingly more prevalent with the advance of generative design and topology optimization technologies. As one step toward accelerating structural analysis, this work explores a deep learning based approach for predicting the stress fields in 2D linear elastic cantilevered structures subjecte

Abijith S. Kowligy, Henry Timmers, Alex Lind, Ugaitz Elu

Molecular spectroscopy in the mid-infrared portion of the electromagnetic spectrum (3--25 um) has been a cornerstone interdisciplinary analytical technique widely adapted across the biological, chemical, and physical sciences. Applications range from understanding mesoscale trends in climate science via atmospheric monitoring to microscopic investigations of

David Doty, Mahsa Eftekhari

We study uniform population protocols: networks of anonymous agents whose pairwise interactions are chosen at random, where each agent uses an identical transition algorithm that does not depend on the population size $n$. Many existing polylog$(n)$ time protocols for leader election and majority computation are nonuniform: to operate correctly, they require

Shlomo Dado, Arnon Dar

The direction of the axis of the orbital motion of the merging binary neutron stars in the GW170817 event coincided with that of the apparent superluminal jet, which produced the short hard gamma ray burst (SHB) 170817A, if the local value of the Hubble constant is that provided by standard candle Type Ia supernovae, H_0=73.24 +/- 1.74 km/s Mpc. This value d

V. Bosch-Ramon

The reionization of the Universe ends the dark ages that started after the recombination era. In the case of H, reionization finishes around $z\sim 6$. Faint star-forming galaxies are the best candidate sources of the H-ionizing radiation, although active galactic nuclei may have also contributed. We have explored whether the termination regions of the jets

Marin Bukov

I demonstrate the potential of reinforcement learning (RL) to prepare quantum states of strongly periodically driven non-linear single-particle models. The ability of Q-Learning to control systems far away from equilibrium is exhibited by steering the quantum Kapitza oscillator to the Floquet-engineered stable inverted position in the presence of a strong pe

Nishant K. Singh, Harsha Raichur, Maarit J. Käpylä, Matthias Rheinhardt

Recent numerical work in helioseismology has shown that a periodically varying subsurface magnetic field leads to a fanning of the $f$-mode, which emerges from the density jump at the surface. In an attempt to model a more realistic situation, we now modulate this periodic variation with an envelope, giving thus more emphasis on localized bipolar magnetic st

Arthur D. Yaghjian

The concept of hidden momentum is reviewed and the first rigorous derivation from Maxwell&#39;s equations is provided for the electromagnetic force on electrically small perfect electric conductors of arbitrary shape in bandlimited but otherwise arbitrarily time-varying fields. It is proven for the Amperian magnetic dipoles of these perfect conductors that a

Radosław Adamczak, Michał Kotowski, Piotr Miłoś

We study a family of random permutation models on the Hamming graph $H(2,n)$ (i.e., the $2$-fold Cartesian product of complete graphs), containing the interchange process and the cycle-weighted interchange process with parameter $θ> 0$. This family contains the random walk representation of the quantum Heisenberg ferromagnet. We show that in these models the

A. Ariga, A. Ereditato, R. Ferragut, M. Giammarchi

In 1924 Louis de Broglie introduced the concept of wave-particle duality: the Planck constant $h$ relates the momentum $p$ of a massive particle to its de Broglie wavelength $λ=h/p$. The superposition principle is one of the main postulates of quantum mechanics; diffraction and interference phenomena are therefore predicted and have been observed on objects

Thomas L. Carroll

Analyzing data from dynamical systems often begins with creating a reconstruction of the trajectory based on one or more variables, but not all variables are suitable for reconstructing the trajectory. The concept of nonlinear observability has been investigated as a way to determine if a dynamical system can be reconstructed from one signal or a combination

Chen Luo, Michael J. Carey

In recent years, the Log Structured Merge (LSM) tree has been widely adopted by NoSQL and NewSQL systems for its superior write performance. Despite its popularity, however, most existing work has focused on LSM-based key-value stores with only a primary LSM-tree index; auxiliary structures, which are critical for supporting ad-hoc queries, have received muc

M. C. Atkinson, H. P. Blok, L. Lapikás, R. J. Charity

The nonlocal implementation of the dispersive optical model (DOM) provides all the ingredients for distorted-wave impulse-approximation (DWIA) calculations of the $(e,e&#39;p)$ reaction. It provides both the overlap function, including its normalization, and the outgoing proton distorted wave. This framework is applied to describe the knockout of a proton fr

Sean Eberhard

The Ewens sampling formula with parameter $α$ is the distribution on $S_n$ which gives each $π\in S_n$ weight proportional to $α^{C(π)}$, where $C(π)$ is the number of cycles of $π$. We show that, for any fixed $α$, two Ewens-random permutations generate at least $A_n$ with high probability. More generally we work out how many permutations are needed for $α$

Dan-Bo Zhang, Zheng-Yuan Xue, Shi-Liang Zhu, Z. D. Wang

In order to exploit quantum advantages, quantum algorithms are indispensable for operating machine learning with quantum computers. We here propose an intriguing hybrid approach of quantum information processing for quantum linear regression, which utilizes both discrete and continuous quantum variables, in contrast to existing wisdoms based solely upon disc

Fabien Tran, Peter Blaha

An alternative type of approximation for the exchange and correlation functional in density functional theory is proposed. This approximation depends on a variable $u$ that is able to detect inhomogeneities in the electron density $ρ$ without using derivatives of $ρ$. Instead, $u$ depends on the orbital energies which can also be used to measure how a system

Xiao-Dong Yu, Otfried Gühne

Coherence is a basic phenomenon in quantum mechanics and considered to be an essential resource in quantum information processing. Although the quantification of coherence has attracted a lot of interest, the lack of efficient methods to measure the coherence in experiments limits the applications. We address this problem by introducing an experiment-friendl

Guy David, Max Engelstein, Svitlana Mayboroda

In this paper, we characterize the rectifiability (both uniform and not) of an Ahlfors regular set, E, of arbitrary co-dimension by the behavior of a regularized distance function in the complement of that set. In particular, we establish a certain version of the Riesz transform characterization of rectifiability for lower-dimensional sets. We also uncover a

Hansjörg Scherer, Dietmar Drung, Christian Krause, Martin Götz

We performed calibrations of four different commercial picoammeters using the Ultrastable Low-noise Current Amplifier (ULCA) as a calibrator current source operated in the range between 1 femtoampere and 1 microampere. The results allow the comprehensive characterization of the devices under test regarding noise, settling and burden voltage behavior as well

Romaric Duvignau, Vincenzo Gulisano, Marina Papatriantafilou, Vladimir Savic

Piecewise Linear Approximation (PLA) is a well-established tool to reduce the size of the representation of time series by approximating the series by a sequence of line segments while keeping the error introduced by the approximation within some predetermined threshold. With the recent rise of edge computing, PLA algorithms find a complete new set of applic

Zhi-Chao Liang, Laurent Gizon, Aaron C. Birch, Thomas L. Duvall

The south-north travel-time differences are measured by applying time-distance helioseismology to the MDI and HMI medium-degree Dopplergrams covering May 1996-April 2017. Our data analysis corrects for several sources of systematic effects: P-angle error, surface magnetic field effects, and center-to-limb variations. An interpretation of the travel-time meas

Wei Chen, Mark Fuge

Many real-world objects are designed by smooth curves, especially in the domain of aerospace and ship, where aerodynamic shapes (e.g., airfoils) and hydrodynamic shapes (e.g., hulls) are designed. To facilitate the design process of those objects, we propose a deep learning based generative model that can synthesize smooth curves. The model maps a low-dimens

LHCb collaboration, I. Bediaga, M. Cruz Torres, J. M. De Miranda

The LHCb Upgrade II will fully exploit the flavour-physics opportunities of the HL-LHC, and study additional physics topics that take advantage of the forward acceptance of the LHCb spectrometer. The LHCb Upgrade I will begin operation in 2020. Consolidation will occur, and modest enhancements of the Upgrade I detector will be installed, in Long Shutdown 3 o

Carlos Meniño Cotón, Paul A. Schweitzer

We show that any simply connected topological closed $4$-manifold punctured along any compact, totally disconnected tame subset $Λ$ admits a continuum of smoothings which are not diffeomorphic to any leaf of a $C^{1,0}$ codimension one foliation on a compact manifold. This includes the remarkable case of $S^4$ punctured along a tame Cantor set. This is the l

Dmitry A. Zezyulin, Yaroslav V. Kartashov

We consider dark solitons and their stability in spin-orbit coupled polariton condensates. The system supports spinor solitons of two types: conventional (symmetric) dark solitons and asymmetric half-dark solitons. They demonstrate essentially different behavior upon variation of the strength of spin-orbit coupling. One-dimensional spin-orbit coupled dark so

Nikolay Bogoychev, Marcin Junczys-Dowmunt, Kenneth Heafield, Alham Fikri Aji

In order to extract the best possible performance from asynchronous stochastic gradient descent one must increase the mini-batch size and scale the learning rate accordingly. In order to achieve further speedup we introduce a technique that delays gradient updates effectively increasing the mini-batch size. Unfortunately with the increase of mini-batch size

Satoshi Ishiwata, Hiroshi Kawabi, Ryuya Namba

In the present paper, as a continuation of our preceding paper [10], we study another kind of central limit theorems (CLTs) for non-symmetric random walks on nilpotent covering graphs from a viewpoint of discrete geometric analysis developed by Kotani and Sunada. We introduce a one-parameter family of random walks which interpolates between the original non-

Fahimeh Sepehripour, Parisa Karimi, Amin Khavasi

In this paper, we propose a new approach for realizing antireflection coating using metamaterials. In this approach, a subwavelength array of metallic pillars (with square cross-section) is used for implementing antireflection coating. The effective impedance of the array can be duly adjusted by the size and distance of pillars. Therefore, we design the effe

Shankey Kumar, Swadesh Kumar Sahoo

For each $ α> 0 $, the $α$-Bloch space is consisting of all analytic functions $f$ on the unit disk satisfying $ \sup_{|z|<1} (1-|z|^2)^α|f&#39;(z)| < + \infty.$ In this paper, we consider the following complex integral operator, namely the $β$-Cesàro operator \begin{equation} C_β(f)(z)=\int_{0}^{z}\frac{f(w)}{w(1-w)^β}dw \nonumber \end{equation} and its gen

Merlin Schüler, Hlynur Davíð Hlynsson, Laurenz Wiskott

We propose Power Slow Feature Analysis, a gradient-based method to extract temporally slow features from a high-dimensional input stream that varies on a faster time-scale, as a variant of Slow Feature Analysis (SFA) that allows end-to-end training of arbitrary differentiable architectures and thereby significantly extends the class of models that can effect

Ahmet Fatih Tabak

Hydrodynamic interactions play a key role in the swimming behavior and power consumption of bio-inspired and bio-mimetic micro-swimmers, Cybernetic or artificial alike. As micro-robotic devices, bio-inspired micro-swimmers require fast and reliable numerical models for robust control in order to carry out demanding therapeutic tasks as envisaged for more tha

Dimitri Surinx, Jan Van den Bussche

When a relational database is queried, the result is normally a relation. Some queries, however, only require a yes/no answer; such queries are often called boolean queries. It is customary in database theory to express boolean queries by testing nonemptiness of query expressions. Another interesting way for expressing boolean queries are containment stateme

Xiao Zhao, Dengfeng Zhang, Wenlong Li, Changyu Li

Following the Higgs particle discovery, the Large Hadron Collider complex will be upgraded in several phases allowing the luminosity to increase to $7 \times 10^{34}cm^{-2}s^{-1}$. In order to adapt the ATLAS detector to the higher luminosity environment after the upgrade, part of the ATLAS muon end-cap system, the Small Wheel, will be replaced by the New Sm

Jörg Stork, A. E. Eiben, Thomas Bartz-Beielstein

Surrogate-based optimization, nature-inspired metaheuristics, and hybrid combinations have become state of the art in algorithm design for solving real-world optimization problems. Still, it is difficult for practitioners to get an overview that explains their advantages in comparison to a large number of available methods in the scope of optimization. Avail