November 2018 arXiv papers — page 95

Wenqi Liang, Guangcong Wang, Jianhuang Lai, Junyong Zhu

Cross-domain transfer learning (CDTL) is an extremely challenging task for the person re-identification (ReID). Given a source domain with annotations and a target domain without annotations, CDTL seeks an effective method to transfer the knowledge from the source domain to the target domain. However, such a simple two-domain transfer learning method is unav

Xin Long, Jigang Wu, Long Chen

Multiple access mobile edge computing is an emerging technique to bring computation resources close to end mobile users. By deploying edge servers at WiFi access points or cellular base stations, the computation capabilities of mobile users can be extended. Existing works mostly assume the remote cloud server can be viewed as a special edge server or the edg

Mikołaj Bińkowski, Charles-Albert Lehalle

In this paper we investigate the endogenous information contained in four liquidity variables at a five minutes time scale on equity markets around the world: the traded volume, the bid-ask spread, the volatility and the volume at first limits of the orderbook. In the spirit of Granger causality, we measure the level of information by the level of accuracy o

Jaroslaw Blasiok, Mark Bun, Aleksandar Nikolov, Thomas Steinke

We study efficient mechanisms for the query release problem in differential privacy: given a workload of $m$ statistical queries, output approximate answers to the queries while satisfying the constraints of differential privacy. In particular, we are interested in mechanisms that optimally adapt to the given workload. Building on the projection mechanism of

Youru Li, Zhenfeng Zhu, Deqiang Kong, Hua Han

Time series prediction with deep learning methods, especially long short-term memory neural networks (LSTMs), have scored significant achievements in recent years. Despite the fact that the LSTMs can help to capture long-term dependencies, its ability to pay different degree of attention on sub-window feature within multiple time-steps is insufficient. To ad

Tsuyoshi Adachi, Kazuki Fujimoto, Sho Sakaino, Toshiaki Tsuji

This study proposes an imitation learning method based on force and position information. Force information is required for precise object manipulation but is difficult to obtain because the acting and reaction forces cannnot be separated. To separate the forces, we proposed to introduce bilateral control, in which the acting and reaction forces are divided

Dong Eui Chang, Matthew Perlmutter

The theory of feedback integrators is extended to handle mechanical systems with nonholonomic constraints with or without symmetry, so as to produce numerical integrators that preserve the nonholonomic constraints as well as other conserved quantities. To extend the feedback integrators, we develop a suitable extension theory for nonholonomic systems, and al

Haim Horowitz, Saharon Shelah

We consider the definability of mad families in vector spaces of the form $\underset{n<ω}{\bigoplus} F$ where $F$ is a field of cardinality $\leq \aleph_0$. We show that there is no analytic mad family of subspaces when $F=\mathbb{F}_2$, partially answering a question of Smythe. Our proof relies on a variant of Mathias forcing restricted to a certain idempot

Naoto Sato, Hironobu Kuruma, Masanori Kaneko, Yuichiroh Nakagawa

In recent years, a number of methods for verifying DNNs have been developed. Because the approaches of the methods differ and have their own limitations, we think that a number of verification methods should be applied to a developed DNN. To apply a number of methods to the DNN, it is necessary to translate either the implementation of the DNN or the verific

Niharika Jain, Lydia Manikonda, Alberto Olmo Hernandez, Sailik Sengupta

The use of synthetic data generated by Generative Adversarial Networks (GANs) has become quite a popular method to do data augmentation for many applications. While practitioners celebrate this as an economical way to get more synthetic data that can be used to train downstream classifiers, it is not clear that they recognize the inherent pitfalls of this te

Yuu Hasegawa, Tomoya Kitamura, Sho Sakaino, Toshiaki Tsuji

Bilateral control, a remote-control technique, is used to work at a distance. However, many existing bilateral control systems have two common problems: 1) it is difficult to create a system like a human hand, that has multiple degrees of freedom and 2) if the mechanism becomes too complicated, operators feel restrained and experience discomfort. Because, fo

Anindya De, Philip M. Long, Rocco A. Servedio

We study density estimation for classes of shift-invariant distributions over $\mathbb{R}^d$. A multidimensional distribution is &#34;shift-invariant&#34; if, roughly speaking, it is close in total variation distance to a small shift of it in any direction. Shift-invariance relaxes smoothness assumptions commonly used in non-parametric density estimation to

Jingwei Liu, Lihuan Zhang, Rong Sun, Xiaojiang Du

With the emerging of mobile communication technologies, we are entering the fifth generation mobile communication system (5G) era. Various application scenarios will arise in the 5G era to meet the different service requirements. Different 5G network slicings may deploy different public key cryptosystems. The security issues among the heterogeneous systems s

Yu Bai, JiFeng Liu, Song Wang, Fan Yang

In modern astrophysics, the machine learning has increasingly gained more popularity with its incredibly powerful ability to make predictions or calculated suggestions for large amounts of data. We describe an application of the supervised machine-learning algorithm, random forests (RF), to the star/galaxy/QSO classification and the stellar effective tempera

Shuaijun Ge, Guixiang Ma, Sihong Xie, Philip S. Yu

Reviews spams are prevalent in e-commerce to manipulate product ranking and customers decisions maliciously. While spams generated based on simple spamming strategy can be detected effectively, hardened spammers can evade regular detectors via more advanced spamming strategies. Previous work gave more attention to evasion against text and graph-based detecto

Dubovichenko S. B., Burkova N. A., Dzhazairov-Kakhramanov A. V., Tkachenko A. S

The astrophysical S-factor for the process p7Be --> 8Bgamma of radiative capture by the 8B ground state is described up to 5 MeV, within the modified potential cluster model. The signatures of the S-factor resonances at 0.632, 2.18 and 3.36 MeV due to M1 and E2 transitions from the scattering of resonance 3P1, 3F3 and 3D2 waves to the ground 3P2 state are il

Xiaoshuai Sun

In this paper, we proposed an integrated model of semantic-aware and contrast-aware saliency combining both bottom-up and top-down cues for effective saliency estimation and eye fixation prediction. The proposed model processes visual information using two pathways. The first pathway aims to capture the attractive semantic information in images, especially f

Lu Zhang, Sudipto Banerjee

This note is devoted to the comparison between two Nearest-neighbor Gaussian processes (NNGP) based models: the response NNGP model and the latent NNGP model. We exhibit that the comparison based on the Kullback-Leibler divergence (KL-D) from the NNGP based models to their parent GP based model can result in reverse conclusions in different parameter spaces.

Peng-Bi Cui, Wei Wang, Shi-Min Cai, Tao Zhou

An outstanding problem of interdisciplinary interest is to understand quantitatively the role of social contacts in contagion dynamics. In general, there are two types of contacts: close ones among friends, colleagues and family members, etc., and ordinary contacts from encounters with strangers. Typically, social reinforcement occurs for close contacts. Tak

Jingwei Liu, Qingqing Li, Huijuan Cao, Rong Sun

Along with the development of vehicular sensors and wireless communication technology, Internet of Vehicles (IoV) is emerging that can improve traffic efficiency and provide a comfortable driving environment. However, there is still a challenge how to ensure the survivability of IoV. Fortunately, this goal can be achieved by quickly verifying real-time monit

Yanran Li, Wenjie Li, Ziqiang Cao, Chengyao Chen

To sustain engaging conversation, it is critical for chatbots to make good use of relevant knowledge. Equipped with a knowledge base, chatbots are able to extract conversation-related attributes and entities to facilitate context modeling and response generation. In this work, we distinguish the uses of attribute and entity and incorporate them into the enco

Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig

While machine learning (ML) models are being increasingly trusted to make decisions in different and varying areas, the safety of systems using such models has become an increasing concern. In particular, ML models are often trained on data from potentially untrustworthy sources, providing adversaries with the opportunity to manipulate them by inserting care

Jingwei Liu, Jinping Han, Longfei Wu, Rong Sun

Along with the miniaturization of various types of sensors, a mass of intelligent terminals are gaining stronger sensing capability, which raises a deeper perception and better prospect of Internet of Things (IoT). With big sensing data, IoT provides lots of convenient services for the monitoring and management of smart cities and people&#39;s daily lives. H

P. E. Rodman, R. J. Turner, S. S. Shabala, J. K. Banfield

We investigate the role of environment on radio galaxy properties by constructing a sample of large ($\gtrsim100$~kpc), nearby ($z<0.3$) radio sources identified as part of the Radio Galaxy Zoo citizen science project. Our sample consists of 16 Fanaroff-Riley Type II (FR-II) sources, 6 FR-I sources, and one source with a hybrid morphology. FR-I sources appea

Jingwei Liu, Fanghui Cai, Longfei Wu, Rong Sun

As a popular application, mobile crowd sensing systems aim at providing more convenient service via the swarm intelligence. With the popularity of sensor-embedded smart phones and intelligent wearable devices, mobile crowd sensing is becoming an efficient way to obtain various types of sensing data from individuals, which will make people&#39;s life more con

Xianyong Bai, Hector Socas-Navarro, Daniel Nóbrega-Siverio, Jiangtao Su

Dynamical jets are generally found on Light bridges (LBs), which are key to studying sunspots decays. So far, their formation mechanism is not fully understood. In this paper, we used state-of-the-art observations from the Goode Solar Telescope, the Interface Region Imaging Spectrograph, the Spectro-Polarimeter on board Hinode and the Atmospheric Imaging Ass

Christoph Vogel, Patrick Knöbelreiter, Thomas Pock

Modern optical flow methods are often composed of a cascade of many independent steps or formulated as a black box neural network that is hard to interpret and analyze. In this work we seek for a plain, interpretable, but learnable solution. We propose a novel inpainting based algorithm that approaches the problem in three steps: feature selection and matchi

N. Higa, Q. -P. Ding, A. Teruya, M. Yogi

$^{59}$Co and $^{31}$P nuclear magnetic resonance (NMR) measurements in external magnetic and zero magnetic fields have been performed to investigate the magnetic properties of the A-type antiferromagnetic (AFM) CaCo$_2$P$_2$. NMR data, especially, the nuclear spin lattice relaxation rates 1/$T_1$ exhibiting a clear peak, provide clear evidence for the AFM t

Konrad Tudyka, Andrzej Bluszcz, Grzegorz Poręba, Sebastian Miłosz

The $μ$Dose system was developed to allow the measurement of environmental levels of natural radioactive isotopes. The system records $α$ and $β$ particles along with four decay pairs arising from subsequent decays of $^{214}$Bi/$^{214}$Po, $^{220}$Rn/$^{216}$Po, $^{212}$Bi/$^{212}$Po and $^{219}$Rn/$^{215}$Po. Under the assumption of secular equilibrium thi

Samuel Chevalier, Petr Vorobev, Konstantin Turitsyn, Bin Wang

Despite wide-scale deployment of phasor measurement unit technology, locating the sources of low frequency forced oscillations in power systems is still an open research topic. The dissipating energy flow method is one source location technique which has performed remarkably well in both simulation and real time application at ISO New England. The method has

Oliver R. A. Dunbar, Charles M. Elliott

We propose a double obstacle phase field methodology for binary recovery of the slowness function of an Eikonal equation found in first traveltime tomography. We treat the inverse problem as an optimization problem with quadratic misfit functional added to a phase field relaxation of the perimeter penalization functional. Our approach yields solutions as we

W Oukil, Ph Thieullen, A Kessi

In this article we prove the stability of mean field systems as the Winfree model in the synchronized state. The model is governed by the coupling strength parameter $κ$ and the natural frequency of each oscillator. The stability is proved independently of the number of os-cillators and the distribution of the natural frequencies. In order to prove the main

Wenjie Liu, Li-Lian Wang, Huiyuan Li

In this paper, we introduce a new theoretical framework built upon fractional Sobolev-type spaces involving Riemann-Liouville (RL) fractional integrals/derivatives, which is naturally arisen from exact representations of Chebyshev expansion coefficients, for optimal error estimates of Chebyshev approximations to functions with limited regularity. The essenti

Christophe Denis, Pablo De Oliveira Castro, Eric Petit

Numerical accuracy of floating point computation is a well studied topic which has not made its way to the end-user in scientific computing. Yet, it has become a critical issue with the recent requirements for code modernization to harness new highly parallel hardware and perform higher resolution computation. To democratize numerical accuracy analysis, it i

Marta Lewicka, Juan Manfredi, Diego Ricciotti

We study the mean value properties of $\mathbf{p}$-harmonic functions on the first Heisenberg group $\mathbb{H}$, in connection to the dynamic programming principles of certain stochastic processes. We implement the approach of Peres-Scheffield to provide the game-theoretical interpretation of the sub-elliptic $\mathbf{p}$-Laplacian; and of Manfredi-Parviain

Michał Dereziński

Given a fixed $n\times d$ matrix $\mathbf{X}$, where $n\gg d$, we study the complexity of sampling from a distribution over all subsets of rows where the probability of a subset is proportional to the squared volume of the parallelepiped spanned by the rows (a.k.a. a determinantal point process). In this task, it is important to minimize the preprocessing co

Jared M. Smith, Kyle Birkeland, Tyler McDaniel, Max Schuchard

The security of the Internet&#39;s routing infrastructure has underpinned much of the past two decades of distributed systems security research. However, the converse is increasingly true. Routing and path decisions are now important for the security properties of systems built on top of the Internet. In particular, BGP poisoning leverages the de facto routi

Debraj Chakrabarti, Phillip S. Harrington

We prove a modified form of the classical Morrey-Kohn-Hörmander identity, adapted to pseudoconcave boundaries. Applying this result to an annulus between two bounded pseudoconvex domains in $\mathbb{C}^n$, where the inner domain has $\mathcal{C}^{1,1}$ boundary, we show that the $L^2$ Dolbeault cohomology group in bidegree $(p,q)$ vanishes if $1\leq q\leq n-

Grammateia Kotsialou, Luke Riley

Liquid democracy allows members of an electorate to either directly vote over alternatives, or delegate their voting rights to someone they trust. Most of the liquid democracy literature and implementations allow each voter to nominate only one delegate per election. However, if that delegate abstains, the voting rights assigned to her are left unused. To mi

Hafida Laasri, Delio Mugnolo

We develop a variational approach in order to study the qualitative properties of non-autonomous parabolic equations. Based on the method of product integrals, we discuss long-time behavior, invariance properties, and ultracontractivity of evolution families in Hilbert space. Our main results give sufficient conditions for the heat kernel of the evolution fa

Giovanni Sutanto, Nathan Ratliff, Balakumar Sundaralingam, Yevgen Chebotar

To achieve a dexterous robotic manipulation, we need to endow our robot with tactile feedback capability, i.e. the ability to drive action based on tactile sensing. In this paper, we specifically address the challenge of tactile servoing, i.e. given the current tactile sensing and a target/goal tactile sensing --memorized from a successful task execution in

Marcelo Jaime, Krzysztof Gofryk, Eric D. Bauer

We use a recently developed optical fiber Bragg grating technique, in continuous and pulsed magnetic fields in excess of 90T, to study magnetoelastic correlations in magnetic materials at cryogenic temperatures. Both insulating UO2 and metallic CeRhIn5 present antiferromagnetic ground states, at T_N = 30.3K and T_N = 3.85K respectively. A strong coupling of

Chao Weng, Dong Yu

In this work, three lattice-free (LF) discriminative training criteria for purely sequence-trained neural network acoustic models are compared on LVCSR tasks, namely maximum mutual information (MMI), boosted maximum mutual information (bMMI) and state-level minimum Bayes risk (sMBR). We demonstrate that, analogous to LF-MMI, a neural network acoustic model c

Deepak Mishra, Prathosh A. P., Aravind Jayendran, Varun Srivastava

Generative adversarial networks (GANs) have shown remarkable success in generation of unstructured data, such as, natural images. However, discovery and separation of modes in the generated space, essential for several tasks beyond naive data generation, is still a challenge. In this paper, we address the problem of imposing desired modal properties on the g

Matt Harrington, Andrea J. Liu, Douglas J. Durian

Structural defects within amorphous packings of symmetric particles can be characterized using a machine learning approach that incorporates structure functions of radial distances and angular arrangement. This yields a scalar field, \emph{softness}, that correlates with the probability that a particle is about to rearrange. However, when particle shapes are

Andrea Maselli, Paolo Pani, Vitor Cardoso, Tiziano Abdelsalhin

Supermassive binaries detectable by the future space gravitational-wave interferometer LISA might allow to distinguish black holes from ultracompact horizonless objects, even when the latter are motivated by quantum-gravity considerations. We show that a measurement of very small tidal Love numbers at the level of $10\%$ accuracy (as achievable with &#34;gol

I. Y. Park

We present a foliation-focused critical review of the boundary conditions and dynamics of 4D gravitational theories. A general coordinate transformation introduces a new foliation and changes the hypersurface on which a natural boundary condition is imposed; in this sense gauge transformations must be viewed as changing the boundary conditions. The issue of

David Bryant, Petru Cioica-Licht, Lisa Orloff Clark, Rachael Young

We define a set inner product to be a function on pairs of convex bodies which is symmetric, Minkowski linear in each dimension, positive definite, and satisfies the natural analogue of the Cauchy-Schwartz inequality (which is not implied by the other conditions). We show that any set inner product can be embedded into an inner product space on the associate

Muhammad Amjad, Leila Musavian, Mubashir Husain Rehmani

Low latency applications, such as multimedia communications, autonomous vehicles, and Tactile Internet are the emerging applications for next-generation wireless networks, such as 5th generation (5G) mobile networks. Existing physical-layer channel models, however, do not explicitly consider quality-of-service (QoS) aware related parameters under specific de

Samuel Kessler, Arnold Salas, Vincent W. C. Tan, Stefan Zohren

We introduce a novel framework for the estimation of the posterior distribution over the weights of a neural network, based on a new probabilistic interpretation of adaptive optimisation algorithms such as AdaGrad and Adam. We demonstrate the effectiveness of our Bayesian Adam method, Badam, by experimentally showing that the learnt uncertainties correctly r

Jacques Carette, Roshan P. James, Amr Sabry

Our main models of computation (the Turing Machine and the RAM) make fundamental assumptions about which primitive operations are realizable. The consensus is that these include logical operations like conjunction, disjunction and negation, as well as reading and writing to memory locations. This perspective conforms to a macro-level view of physics and inde

Alejandro Cuetos, Effran Mirzad Rafael, Daniel Corbett, Alessandro Patti

We investigate the phase behavior of colloidal suspensions of board-like particles under the effect of an external field and assess the still disputed occurrence of the biaxial nematic (N$_\text{B}$) liquid crystal phase. The external field promotes the rearrangement of the initial isotropic (I) or uniaxial nematic (N$_\text{U}$) phase and the formation of t

Francesca Aicardi, Jesus Juyumaya

We introduce a two-parameters bt-algebra which, by specialization, becomes the one-parameter bt-algebra, introduced by the authors, as well as another one-parameter presentation of it; the invariant for links and tied links, associated to this two-parameter algebra via Jones recipe, contains as specializations the invariants obtained from these two presentat

Assaf Lanir, Amos Ori, Noa Zilberman, Orr Sela

We numerically compute the renormalized expectation value $\langle\hat{\Phi}^{2}\rangle_{ren}$ of a minimally-coupled massless quantum scalar field in the interior of a four-dimensional Reissner-Nordstrom black hole, in both the Hartle-Hawking and Unruh states. To this end we use a recently developed mode-sum renormalization scheme based on covariant point s

Erik Christensen

Given two m x n matrices A = (a_{ij}) and B=(b_{ij}) with entries in B(H), the Schur block product is the m x n matrix A \square B := (a_{ij}b_{ij}). There exists an m x n contraction matrix S = (s_{ij}), such that A \square B = diag(AA*)^(1/2) S diag(B*B)^(1/2). This decomposition is also valid for the block Schur tensor product. It is shown, via the theory

Tommaso De Lorenzo, Alejandro Perez

When probed with conformally invariant matter fields, light cones in Minkowski spacetime satisfy thermodynamical relations which are the analog of those satisfied by stationary black holes coupled to standard matter fields. These properties stem from the fact that light cones are conformal Killing horizons stationary with respect to observers following the r

Daeyoung Choi, Kyungeun Lee, Duhun Hwang, Wonjong Rhee

In this study, the effects of eight representation regularization methods are investigated, including two newly developed rank regularizers (RR). The investigation shows that the statistical characteristics of representations such as correlation, sparsity, and rank can be manipulated as intended, during training. Furthermore, it is possible to improve the ba

Rodney D. Wiersma, Xinmin Liu

A central problem in the field of radiation therapy (RT) is how to optimally deliver dose to a patient in a way that fully accounts for anatomical position changes over time. As current RT is a static process, where beam intensities are calculated before the start of treatment, anatomical deviations can result in poor dose conformity. To overcome these limit

J. G. Russo, P. K. Townsend

We investigate the implications of energy conditions on cosmological compactification solutions of the higher-dimensional Einstein field equations. It is known that the Strong Energy Condition forbids time-independent compactifications to de Sitter space but allows time-dependent compactifications to other (homogeneous and isotropic) expanding universes that

G. G. L. Nashed, Emmanuel N. Saridakis

The investigation on higher-dimensional AdS black holes is of great importance under the light of AdS/CFT correspondence. In this work we study static and rotating, uncharged and charged, AdS black holes in higher-dimensional $f(T)$ gravity, focusing on the power-law ansatz which is the most viable according to observations. We extract AdS solutions characte

Steve Jeffrey Tueno Fotso, Marc Frappier, Régine Laleau, Amel Mammar

This paper is related to the generalised/generic version of the SysML/KAOS domain metamodel and on translation and back propagation rules between the new domain models and B System specifications.

Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic

What is the best way to define algorithmic fairness? While many definitions of fairness have been proposed in the computer science literature, there is no clear agreement over a particular definition. In this work, we investigate ordinary people&#39;s perceptions of three of these fairness definitions. Across two online experiments, we test which definitions

Jason M. Pittman, Jesus P. Espinoza, Courtney Crosby

Awareness of the possible impacts associated with artificial intelligence has risen in proportion to progress in the field. While there are tremendous benefits to society, many argue that there are just as many, if not more, concerns related to advanced forms of artificial intelligence. Accordingly, research into methods to develop artificial intelligence sa

Stephen Spurrier, Nigel R. Cooper

We show that electronic materials with disallowed rotational symmetries that enforce quasiperiodic order can exhibit quantum oscillations and that these are generically associated with exotic &#34;spiral Fermi surfaces.&#34; These Fermi surfaces are self-intersecting, and characterized by a winding number of their surface tangent---a topological invariant---

R. A. Heinonen, P. H. Diamond

In confined plasmas, a localized fluctuation in a marginal or weakly damped region will propagate and generate an avalanche if it exceeds a threshold. In this letter, a new model for turbulence spreading based on subcritical instability in the turbulence intensity is introduced. We derive a quantitative threshold for spreading from a seed in a stable region,

Olaf Lechtenfeld, Alexander D. Popov

Compactifying type $A_{N-1}$ 6d ${\cal N}{=}(2,0)$ supersymmetric CFT on a product manifold $M^4\timesΣ^2=M^3\times\tilde{S}^1\times S^1\times{\cal I}$ either over $S^1$ or over $\tilde{S}^1$ leads to maximally supersymmetric 5d gauge theories on $M^4\times{\cal I}$ or on $M^3\timesΣ^2$, respectively. Choosing the radii of $S^1$ and $\tilde{S}^1$ inversely p

Stefan Kebekus, Christian Schnell

We investigate under what conditions holomorphic forms defined on the regular locus of a reduced complex space extend to holomorphic (or logarithmic) forms on a resolution of singularities. We give a simple necessary and sufficient condition for this, whose proof relies on the Decomposition Theorem and Saito's theory of mixed Hodge modules. We use it to gene

Fabio Antonini, Mark Gieles, Alessia Gualandris

In a star cluster with a sufficiently large escape velocity, black holes (BHs) that are produced by BH mergers can be retained, dynamically form new BH binaries, and merge again. This process can repeat several times and lead to significant mass growth. In this paper, we calculate the mass of the largest BH that can be formed through repeated mergers of stel

Zhefu Yu, Paul Martini, T. M. Davis, R. A. Gruendl

Measurements of the physical properties of accretion disks in active galactic nuclei are important for better understanding the growth and evolution of supermassive black holes. We present the accretion disk sizes of 22 quasars from continuum reverberation mapping with data from the Dark Energy Survey (DES) standard star fields and the supernova C fields. We

Joel Leja, Adam C. Carnall, Benjamin D. Johnson, Charlie Conroy

Nonparametric star formation histories (SFHs) have long promised to be the `gold standard&#39; for galaxy spectral energy distribution (SED) modeling as they are flexible enough to describe the full diversity of SFH shapes, whereas parametric models rule out a significant fraction of these shapes {\it a priori}. However, this flexibility is not fully constra

A. C. Carnall, J. Leja, B. D. Johnson, R. J. McLure

Parametric models for galaxy star-formation histories (SFHs) are widely used, though they are known to impose strong priors on physical parameters. This has consequences for measurements of the galaxy stellar-mass function (GSMF), star-formation-rate density (SFRD) and star-forming main sequence (SFMS). We investigate the effects of the exponentially declini

Ismael Delgado Gaspar, Juan Carlos Hidalgo, Roberto A. Sussman

We examine the fully relativistic evolution of cosmic voids constituted by baryons and cold dark matter (CDM), represented by two non-comoving dust sources in a $Λ$CDM background. For this purpose, we consider numerical solutions of Einstein&#39;s field equations in a fluid-flow representation adapted to spherical symmetry and multiple components. We present

Alexander Avdoshkin, Lev Astrakhantsev, Anatoly Dymarsky, Michael Smolkin

In quantum field theory with a mass gap correlation function between two spatially separated operators decays exponentially with the distance. This fundamental result immediately implies an exponential suppression of all higher point correlation functions, but the predicted exponent is not optimal. We argue that in a general quantum field theory the optimal

A. A. Burkov

We present a derivation of the recently discovered duality between the free massless (2+1)-dimensional Dirac fermion and QED$_3$. Our derivation is based on a regularized lattice model of the Dirac fermion and is similar to the more familiar derivation of the boson-vortex duality. It also highlights the important role played by the parity anomaly, which is s

Ana Bonaca, David W. Hogg, Adrian M. Price-Whelan, Charlie Conroy

We present a model for the interaction of the GD-1 stellar stream with a massive perturber that naturally explains many of the observed stream features, including a gap and an off-stream spur of stars. The model involves an impulse by a fast encounter, after which the stream grows a loop of stars at different orbital energies. At specific viewing angles, thi

D. Keith, S. K. Gorman, L. Kranz, Y. He

Determination of qubit initialisation and measurement fidelity is important for the overall performance of a quantum computer. However, the method by which it is calculated in semiconductor qubits varies between experiments. In this paper we present a full theoretical analysis of electronic single-shot readout and describe critical parameters to achieve high

Youjie Li, Mingchao Yu, Songze Li, Salman Avestimehr

Distributed training of deep nets is an important technique to address some of the present day computing challenges like memory consumption and computational demands. Classical distributed approaches, synchronous or asynchronous, are based on the parameter server architecture, i.e., worker nodes compute gradients which are communicated to the parameter serve

Timo Wunderlich, Akos F. Kungl, Eric Müller, Andreas Hartel

Neuromorphic devices represent an attempt to mimic aspects of the brain&#39;s architecture and dynamics with the aim of replicating its hallmark functional capabilities in terms of computational power, robust learning and energy efficiency. We employ a single-chip prototype of the BrainScaleS 2 neuromorphic system to implement a proof-of-concept demonstratio

Mingchao Yu, Zhifeng Lin, Krishna Narra, Songze Li

Data parallelism can boost the training speed of convolutional neural networks (CNN), but could suffer from significant communication costs caused by gradient aggregation. To alleviate this problem, several scalar quantization techniques have been developed to compress the gradients. But these techniques could perform poorly when used together with decentral

Attaallah Almasi, Junyi Lee, Himawan Winarto, Marc Smiciklas

We report the results of a new search for long range spin-dependent interactions using a Rb -$^{21}$Ne atomic comagnetometer and a rotatable electron spin source based on a SmCo$_{5}$ magnet with an iron flux return. By looking for signal correlations with the orientation of the spin source we set new constrains on the product of the pseudoscalar electron an

Ádám Gyenge

We obtain explicit formulas for the trivialization functions of the ${\rm SU}(3)$ principal bundle $G_2 \to S^6$ over two affine charts. We also calculate the explicit transition function of this fibration over the equator of the six-sphere. In this way we obtain a new proof of the known fact that this fibration corresponds to a generator of $π_{5}({\rm SU}(

P. F. Rohde, S. Walch, D. Seifried, A. P. Whitworth

Young low-mass protostars undergo short phases of high accretion and outburst activity leading to lumpy outflows. Recent observations have shown that the position-velocity and mass-velocity diagrams of such outflows exhibit individual bullet-like features; some of these bullets subscribe to a `Hubble Law&#39; velocity relation, and others are manifest as `Hu

R. M. Goshadze, V. I. Berezhiani, Z. Osmanov

The filamentation instability of the electromagnetic (EM) beam in an underdense plasma with high level of degeneracy is examined by means of the momentum equation, continuity equation and Maxwell&#39;s equations. It has been demonstrated that the instability develops for weakly as well as strongly relativistic degenerate plasma and arbitrary strong amplitude

Sheel Ganatra, Daniel Pomerleano

We construct a multiplicative spectral sequence converging to the symplectic cohomology ring of any affine variety $X$, with first page built out of topological invariants associated to strata of any fixed normal crossings compactification $(M,\mathbf{D})$ of $X$. We exhibit a broad class of pairs $(M,\mathbf{D})$ (characterized by the absence of relative ho

Marco Cirelli, Yann Gouttenoire, Kalliopi Petraki, Filippo Sala

We point out that current and planned telescopes have the potential of probing annihilating Dark Matter (DM) with a mass of O(100) TeV and beyond. As a target for such searches, we propose models where DM annihilates into lighter mediators, themselves decaying into Standard Model (SM) particles. These models allow to reliably compute the energy spectra of th

Werner Dobrautz, Hongjun Luo, Ali Alavi

Similarity transformation of the Hubbard Hamiltonian using a Gutzwiller correlator leads to a non-Hermitian effective Hamiltonian, which can be expressed exactly in momentum-space representation, and contains three-body interactions. We apply this methodology to study the two-dimensional Hubbard model with repulsive interactions near half-filling in the inte

Filippo Bonchi, Tom van Bussel, Matias David Lee, Jurriaan Rot

Stream GSOS is a specification format for operations and calculi on infinite sequences. The notion of bisimilarity provides a canonical proof technique for equivalence of closed terms in such specifications. In this paper, we focus on open terms, which may contain variables, and which are equivalent whenever they denote the same stream for every possible ins

Kevin Zambello, Francesco Di Renzo

At finite density, lattice simulations are hindered by the well-known sign problem: for finite chemical potentials, the QCD action becomes complex and the Boltzmann weight $e^{-S}$ cannot be interpreted as a probability distribution to determine expectation values by Monte Carlo techniques. Different workarounds have been devised to study the QCD phase diagr

Andrew Hard, Kanishka Rao, Rajiv Mathews, Swaroop Ramaswamy

We train a recurrent neural network language model using a distributed, on-device learning framework called federated learning for the purpose of next-word prediction in a virtual keyboard for smartphones. Server-based training using stochastic gradient descent is compared with training on client devices using the Federated Averaging algorithm. The federated

M. Reza Shaebani, Robin Jose, Christian Sand, Ludger Santen

We study the problem of random search in finite networks with a tree topology, where it is expected that the distribution of the first-passage time F(t) decays exponentially. We show that the slope of the exponential tail is independent of the initial conditions of entering the tree in general, and scales exponentially or as a power law with the extent of th

Christopher J. Shallue, Jaehoon Lee, Joseph Antognini, Jascha Sohl-Dickstein

Recent hardware developments have dramatically increased the scale of data parallelism available for neural network training. Among the simplest ways to harness next-generation hardware is to increase the batch size in standard mini-batch neural network training algorithms. In this work, we aim to experimentally characterize the effects of increasing the bat

Martin Marenz, Johannes Zierenberg, Wolfhard Janke

Spherical confinement can act either stabilizing or destabilizing on the collapsed state of a semi-flexible polymer. General free-energy arguments suggest that the order of the unconstrained collapse transition is the distinguishing factor: First order implies stabilization, second order causes destabilization. We confirm this conjecture by Monte Carlo simul

Tokiro Numasawa

In this paper we consider the maximal volume and the action, which are conjectured to be gravity duals of the complexity, in the black hole geometries with end of the world branes. These geometries are duals of boundary states in CFTs which have small real space entanglement. When we raise the black hole temperature while keeping the cutoff radius, black hol

Johannes U. Lange, Frank C. van den Bosch, Andrew R. Zentner, Kuan Wang

We present new results on the relationship between central galaxies and dark matter haloes inferred from observations of satellite kinematics in the Sloan Digital Sky Survey (SDSS) DR7. We employ an updated analysis framework that includes detailed mock catalogues to model observational effects in SDSS. Our results constrain the colour-dependent conditional

Kitti Gelle, Szabolcs Ivan

A prefix grammar is a context-free grammar whose nonterminals generate prefix-free languages. A prefix grammar $G$ is an ordinal grammar if the language $L(G)$ is well-ordered with respect to the lexicographic ordering. It is known that from a finite system of parametric fixed point equations one can construct an ordinal grammar $G$ such that the lexicograph

J. D. Emberson, Nicholas Frontiere, Salman Habib, Katrin Heitmann

A challenging requirement posed by next-generation observations is a firm theoretical grasp of the impact of baryons on structure formation. Cosmological hydrodynamic simulations modeling gas physics are vital in this regard. A high degree of modeling flexibility exists in this space making it important to explore a range of methods in order to gauge the acc

Dekel Tsur

In the 4-path vertex cover problem, the input is an undirected graph $G$ and an integer $k$. The goal is to decide whether there is a set of vertices $S$ of size at most $k$ such that every path with 4 vertices in $G$ contains at least one vertex of $S$. In this paper we give a parameterized algorithm for 4-path vertex cover whose time complexity is $O^*(2.6

Wenting Xiong, Iftitahu Ni&#39;mah, Juan M. G. Huesca, Werner van Ipenburg

Layer-wise Relevance Propagation (LRP) and saliency maps have been recently used to explain the predictions of Deep Learning models, specifically in the domain of text classification. Given different attribution-based explanations to highlight relevant words for a predicted class label, experiments based on word deleting perturbation is a common evaluation m

Laura Doval, Vasiliki Skreta

We provide tools to analyze information design problems subject to constraints. We do so by extending the insight in Le Treust and Tomala (2019) to the case of multiple inequality and equality constraints. Namely, that an information design problem subject to constraints can be represented as an unconstrained information design problem with a additional stat

V. Cherepanov, E. Richter-Was, Z. Was

Status of tau lepton decay Monte Carlo generator TAUOLA, and its main recent applications are reviewed. It is underlined, that in recent efforts on development of new hadronic currents, the multi-dimensional nature of distributions of the experimental data must be taken with a great care. Studies for H to tau tau; tau to hadrons indeed demonstrate that multi