February 2019 arXiv papers — page 7

Hugo A. Akitaya, Matthew D. Jones, Matias Korman, Christopher Meierfrankenfeld

Motivated by recent computational models for redistricting and detection of gerrymandering, we study the following problem on graph partitions. Given a graph $G$ and an integer $k\geq 1$, a $k$-district map of $G$ is a partition of $V(G)$ into $k$ nonempty subsets, called districts, each of which induces a connected subgraph of $G$. A switch is an operation

Hubing Xiao, Junhui Fan, Jianghe Yang, Yi Liu

Active galactic nuclei (AGNs) have been attracting research attention due to their special observable properties. Specifically, a majority of AGNs are detected by Fermi-LAT missions, but not by Fermi-LAT, which raises the question of whether any differences exist between the two. To answer this issue, we compile a sample of 291 superluminal AGNs (189 FDSs an

Eriko Hironaka

The Epstein deformation space parameterizes marked rational maps with prescribed combinatorial and dynamical structure. For the family of quadratic rational maps with a periodic critical cycle of order 4 and an extra critical point not lying in this cycle, S. Koch and I recently showed that the deformation space has infinitely many connected components. In t

Arinbjörn Kolbeinsson, Jean Kossaifi, Yannis Panagakis, Adrian Bulat

CNNs achieve remarkable performance by leveraging deep, over-parametrized architectures, trained on large datasets. However, they have limited generalization ability to data outside the training domain, and a lack of robustness to noise and adversarial attacks. By building better inductive biases, we can improve robustness and also obtain smaller networks th

D. B. Horoshko, G. Patera, M. I. Kolobov

Quantum superpositions of coherent states are produced both in microwave and optical domains, and are considered realizations of the famous "Schrödinger cat" state. The recent progress shows an increase in the number of components and the number of modes involved. Our work creates a theoretical framework for treatment of multicomponent two-mode Schrö

Fazle Karim, Somshubra Majumdar, Houshang Darabi

Long Short Term Memory Fully Convolutional Neural Networks (LSTM-FCN) and Attention LSTM-FCN (ALSTM-FCN) have shown to achieve state-of-the-art performance on the task of classifying time series signals on the old University of California-Riverside (UCR) time series repository. However, there has been no study on why LSTM-FCN and ALSTM-FCN perform well. In t

Fazle Karim, Somshubra Majumdar, Houshang Darabi

Time series classification models have been garnering significant importance in the research community. However, not much research has been done on generating adversarial samples for these models. These adversarial samples can become a security concern. In this paper, we propose utilizing an adversarial transformation network (ATN) on a distilled model to at

D. Fiorentini

We address the issue of the all order multiplicative renormalizability of $SU(2)$ Gribov-Zwanziger theories quantized in the maximal Abelian gauge in presence of confined matter fields. The non-linear character of the maximal Abelian gauge requires the introduction of quartic interaction terms in the Faddeev-Popov ghosts as well as in the localizing Zwanzige

Ali Tayyebi, Dominic Groß, Adolfo Anta, Friederich Kupzog

An inevitable consequence of the global power system transition towards nearly 100% renewable-based generation is the loss of conventional bulk generation by synchronous machines, their inertia, and accompanying frequency and voltage control mechanisms. This gradual transformation of the power system to a low-inertia system leads to critical challenges in ma

Mikael Brudfors, Yaël Balbastre, John Ashburner

Although convolutional neural networks (CNNs) currently dominate competitions on image segmentation, for neuroimaging analysis tasks, more classical generative approaches based on mixture models are still used in practice to parcellate brains. To bridge the gap between the two, in this paper we propose a marriage between a probabilistic generative model, whi

Carlos Maldonado, James Unwin

If the early universe is dominated by an energy density which evolves other than radiation-like the normal Hubble-temperature relation $H\propto T^2$ is broken and dark matter relic density calculations in this era can be significantly different. We first highlight that for a population of states $ϕ$ sourcing an initial expansion rate of the form $H\propto T

Weibing Huang, Sergio Pulido, Mathieu Rosenbaum, Pamela Saliba

We build an agent-based model for the order book with three types of market participants: informed trader, noise trader and competitive market makers. Using a Glosten-Milgrom like approach, we are able to deduce the whole limit order book (bid-ask spread and volume available at each price) from the interactions between the different agents. More precisely, w

Nicholas Woolsey, Rong-Rong Chen, Mingyue Ji

Coded distributed computing (CDC) introduced by Li et. al. is an effective technique to trade computation load for communication load in a MapReduce framework. CDC achieves an optimal trade-off by duplicating map computations at $r$ computing nodes to yield multicasting opportunities such that $r$ nodes are served simultaneously in the Shuffle phase. However

Hamzeh Khanpour

The goal of this study is to determine a set of diffractive parton distribution function (diffractive PDFs) from a QCD analysis of all available and up-to-date diffractive deep inelastic scattering (diffractive DIS) data sets from HERA $ep$ collider, including the most recent H1 and ZUES combined inclusive diffractive cross section measurements. This extract

Panagiotis Agrafiotis, Dimitrios Skarlatos, Andreas Georgopoulos, Konstantinos Karantzalos

The determination of accurate bathymetric information is a key element for near offshore activities, hydrological studies such as coastal engineering applications, sedimentary processes, hydrographic surveying as well as archaeological mapping and biological research. UAV imagery processed with Structure from Motion (SfM) and Multi View Stereo (MVS) techniqu

Aroonkumar Beesham, Alireza Sepehri

When a brane and an anti-brane come close to each other, the tachyonic potential between them increases and a tachyon wormhole is formed. This configuration, which consists of two branes and a tachyonic wormhole, is called a thermal tachyonic BIon. By considering the thermodynamic behaviour of this system, one finds that its entropy has the same form as that

Ray Jiang, Silvia Chiappa, Tor Lattimore, András György

Machine learning is used extensively in recommender systems deployed in products. The decisions made by these systems can influence user beliefs and preferences which in turn affect the feedback the learning system receives - thus creating a feedback loop. This phenomenon can give rise to the so-called "echo chambers" or "filter bubbles" that

Lichen Liang, Robert Feldmann, Dušan Kereš, Nick Z. Scoville

Dust temperature is an important property of the interstellar medium (ISM) of galaxies. It is required when converting (sub)millimeter broadband flux to total infrared luminosity (L_IR), and hence star formation rate, in high-z galaxies. However, different definitions of dust temperatures have been used in the literature, leading to different physical interp

S. Huber, S. H. Suyu, U. M. Noebauer, V. Bonvin

The upcoming Large Synoptic Survey Telescope (LSST) will detect many strongly lensed Type Ia supernovae (LSNe Ia) for time-delay cosmography. This will provide an independent and direct way for measuring the Hubble constant $H_0$, which is necessary to address the current $4.4 σ$ tension in $H_0$ between the local distance ladder and the early Universe measu

Omri Golan, Carlos Hoyos, Sergej Moroz

We derive a low energy effective field theory for chiral superfluids, which accounts for both spontaneous symmetry breaking and fermionic ground-state topology. Using the theory, we show that the odd (or Hall) viscosity tensor, at small wave-vector, contains a dependence on the chiral central charge $c$ of the boundary degrees of freedom, as well as addition

Anna Zoldan, Gabriella De Lucia, Lizhi Xie, Fabio Fontanot

We extend our previous work focused at $z\sim0$, studying the redshift evolution of galaxy dynamical properties using the state-of-the-art semi-analytic model GAEA: we show that the predicted size-mass relation for disky/star forming and quiescent galaxies is in good agreement with observational estimates, up to $z\sim2$. Bulge dominated galaxies have sizes

Mason J. Gray, Josef Freudenstein, Shu Yang F. Zhao, Ryan OConnor

Combining topology and superconductivity provides a powerful tool for investigating fundamental physics as well as a route to fault-tolerant quantum computing. There is mounting evidence that the Fe-Based Superconductor FeTe$_{0.55}$Se$_{0.45}$ (FTS) may also be topologically non-trivial. Should the superconducting order be s$^{\pm}$, then FTS could be a hig

A. Alexandradinata, Zhijun Wang, B. Andrei Bernevig, Michael Zaletel

The two classes of 3D, time-reversal-invariant insulators are known to subdivide into four classes in the presence of glide symmetry. Here, we extend this classification of insulators to include glide-symmetric Weyl metals, and find a finer $Z_4\oplus Z$ classification. We further elucidate the smoking-gun experimental signature of each class in the photoemi

Bartomeu Monserrat, Sharon E. Ashbrook, Chris J. Pickard

An unambiguous crystallographic structure solution for the observed phases II-VI of high pressure hydrogen does not exist due to the failure of standard structural probes at extreme pressure. In this work we propose that nuclear magnetic resonance spectroscopy provides a complementary structural probe for high pressure hydrogen. We show that the best structu

Fangli Liu, Seth Whitsitt, Jonathan B. Curtis, Rex Lundgren

We use Nielsen's geometric approach to quantify the circuit complexity in a one-dimensional Kitaev chain across a topological phase transition. We find that the circuit complexities of both the ground states and non-equilibrium steady states of the Kitaev model exhibit non-analytical behaviors at the critical points, and thus can be used to detect both {

A. Miguel Holgado, Paul M. Ricker

In the quadrupole approximation of General Relativity in the weak-field limit, a time-varying quadrupole moment generates gravitational radiation. Binary orbits are one of the main mechanisms for producing gravitational waves and are the main sources and backgrounds for gravitational-wave detectors across the multi-band spectrum. In this Paper, we introduce

Benedikt Diemer, Adam R. H. Stevens, Claudia del P. Lagos, A. R. Calette

We have recently developed a post-processing framework to estimate the abundance of atomic and molecular hydrogen (HI and H2, respectively) in galaxies in large-volume cosmological simulations. Here we compare the HI and H2 content of IllustrisTNG galaxies to observations. We mostly restrict this comparison to $z \approx 0$ and consider six observational met

Mauro Stefanon, Ivo Labbé, Rychard J. Bouwens, Pascal Oesch

We present 16 new ultrabright $H_{AB}\lesssim25$ galaxy candidates at z~8 identified over the COSMOS/UltraVISTA field. The new search takes advantage of the deepest-available ground-based optical and near-infrared observations, including the DR3 release of UltraVISTA and full-depth Spitzer/IRAC observations from the SMUVS and SPLASH programs. Candidates are

Kimmy K. Cushman, George T. Fleming

We propose an algebraic method for extracting excited states from lattice gauge theory correlation functions. Instead of fitting to a sum of decaying exponentials, we adopt a variant of Prony's method to obtain $M$ energies (exponential decay rates) by finding the roots of an $M^{\rm th}$ order polynomial, and then solving for the amplitudes linearly. Th

Matteo Martinelli, Natalie B. Hogg, Simone Peirone, Marco Bruni

We investigate an interacting dark sector scenario in which the vacuum energy is free to interact with cold dark matter (CDM), which itself is assumed to cluster under the sole action of gravity, i.e. it is in free fall (geodesic), as in $Λ$CDM. The interaction is characterised by a dimensionless coupling $q_{\rm V}$ that we constrain using cosmic microwave

Bill S. Wright, Kazuya Koyama, Hans A. Winther, Gong-Bo Zhao

There is a well known degeneracy between the enhancement of the growth of large-scale structure produced by modified gravity models and the suppression due to the free-streaming of massive neutrinos at late times. This makes the matter power-spectrum alone a poor probe to distinguish between modified gravity and the concordance $Λ$CDM model when neutrino mas

Silvia Penati, Davide Polvara

We study quantum integrability of affine Toda theories with a line of defect. In particular, we focus on the problem of constructing quantum higher-spin conserved currents in models defined by two A_r^{(1)} Toda theories separated by a non-trivial type-I defect. For a suitable choice of the defect potential these theories are known to be classically integrab

Dina Traykova, Emilio Bellini, Pedro G. Ferreira

We study the phenomenology of the beyond Horndeski class of scalar-tensor theories of gravity, which on cosmological scales can be characterised in terms of one extra function of time, $α_{\rm H}$, as well as the usual four Horndeski set of free functions. We show that $α_{\rm H}$ can be directly related to the the damping of the matter power spectrum on bot

Kenneth Ascher, Dori Bejleri

We construct various modular compactifications of the space of elliptic K3 surfaces using tools from the minimal model program, and explicitly describe the surfaces parametrized by their boundaries. The coarse spaces of our constructed compactifications admit morphisms to the Satake-Baily-Borel compactification. Finally, we show that one of our spaces is smo

Huizhen Yu

We consider average-cost Markov decision processes (MDPs) with Borel state spaces, countable, discrete action spaces, and strictly unbounded one-stage costs. For the minimum pair approach, we introduce a new majorization condition on the state transition stochastic kernel, in place of the commonly required continuity conditions on the MDP model. We combine t

Maria Papageorgiou, Jason Pye

Can a relativistic quantum field theory be consistently described as a theory of localizable particles? There are many known issues with such a description, indicating an answer in the negative. In this paper, we examine these obstructions by tracing how they (partially) subside in passing to an approximation of ordinary quantum mechanics in the non-relativi

Vitaly Feldman, Jan Vondrak

Algorithmic stability is a classical approach to understanding and analysis of the generalization error of learning algorithms. A notable weakness of most stability-based generalization bounds is that they hold only in expectation. Generalization with high probability has been established in a landmark paper of Bousquet and Elisseeff (2002) albeit at the exp

Shi Zong, Alan Ritter, Graham Mueller, Evan Wright

Breaking cybersecurity events are shared across a range of websites, including security blogs (FireEye, Kaspersky, etc.), in addition to social media platforms such as Facebook and Twitter. In this paper, we investigate methods to analyze the severity of cybersecurity threats based on the language that is used to describe them online. A corpus of 6,000 tweet

Tyler Takeshita, Nicholas C. Rubin, Zhang Jiang, Eunseok Lee

Proposals for near-term experiments in quantum chemistry on quantum computers leverage the ability to target a subset of degrees of freedom containing the essential quantum behavior, sometimes called the active space. This approximation allows one to treat more difficult problems using fewer qubits and lower gate depths than would otherwise be possible. Howe

Saroch Leedumrongwatthanakun, Luca Innocenti, Hugo Defienne, Thomas Juffmann

Reconfigurable quantum circuits are fundamental building blocks for the implementation of scalable quantum technologies. Their implementation has been pursued in linear optics through the engineering of sophisticated interferometers. While such optical networks have been successful in demonstrating the control of small-scale quantum circuits, scaling up to l

Tal Friedman, Guy Van den Broeck

Increasing amounts of available data have led to a heightened need for representing large-scale probabilistic knowledge bases. One approach is to use a probabilistic database, a model with strong assumptions that allow for efficiently answering many interesting queries. Recent work on open-world probabilistic databases strengthens the semantics of these prob

Riccardo Moriconi, Marc P. Deisenroth, K. S. Sesh Kumar

Bayesian optimization (BO) is a powerful approach for seeking the global optimum of expensive black-box functions and has proven successful for fine tuning hyper-parameters of machine learning models. However, BO is practically limited to optimizing 10--20 parameters. To scale BO to high dimensions, we usually make structural assumptions on the decomposition

Muhammad Zaid Hameed, Andras Gyorgy, Deniz Gunduz

We consider a communication scenario, in which an intruder tries to determine the modulation scheme of the intercepted signal. Our aim is to minimize the accuracy of the intruder, while guaranteeing that the intended receiver can still recover the underlying message with the highest reliability. This is achieved by perturbing channel input symbols at the enc

Ian D. Kivlichan, Craig Gidney, Dominic W. Berry, Nathan Wiebe

Recent work has deployed linear combinations of unitaries techniques to reduce the cost of fault-tolerant quantum simulations of correlated electron models. Here, we show that one can sometimes improve upon those results with optimized implementations of Trotter-Suzuki-based product formulas. We show that low-order Trotter methods perform surprisingly well w

Bernd C. Kellner, Jonathan Sondow

We give a new characterization of the set $\mathcal{C}$ of Carmichael numbers in the context of $p$-adic theory, independently of the classical results of Korselt and Carmichael. The characterization originates from a surprising link to the denominators of the Bernoulli polynomials via the sum-of-base-$p$-digits function. More precisely, we show that such a

R. I. de Oliveira Junior, M. O. Tahim, G. Alencar, R. R. Landim

In this paper we study the localization of a model with kinetic gauge mixing on a thin membrane. The model we discuss is a theory for millicharged particles, proposed by Holdom in 1985, and that now is object of study in the LHC. We propose a geometrical coupling between the gauge fields, the Ricci scalar and the Ricci tensor. We show that it is possible to

Omid Rohanian, Shiva Taslimipoor, Samaneh Kouchaki, Le An Ha

We introduce a new method to tag Multiword Expressions (MWEs) using a linguistically interpretable language-independent deep learning architecture. We specifically target discontinuity, an under-explored aspect that poses a significant challenge to computational treatment of MWEs. Two neural architectures are explored: Graph Convolutional Network (GCN) and m

Danny Panknin, Stefan Chmiela, Klaus-Robert Müller, Shinichi Nakajima

Inhomogeneities in real-world data, e.g., due to changes in the observation noise level or variations in the structural complexity of the source function, pose a unique set of challenges for statistical inference. Accounting for them can greatly improve predictive power when physical resources or computation time is limited. In this paper, we draw on recent

Elke C. Aschenauer, Ignacio Borsa, Rodolfo Sassot, Charlotte Van Hulse

We present a quantitative assessment of the impact a future Electron-Ion Collider would have in the determination of parton distribution functions in the proton and parton-to-hadron fragmentation functions through semi-inclusive deep-inelastic electron-proton scattering data. Specifically, we estimate the kinematic configurations for which the forthcoming da

Siddharth Mayya, Gennaro Notomista, Dylan Shell, Seth Hutchinson

In robot swarms operating under highly restrictive sensing and communication constraints, individuals may need to use direct physical proximity to facilitate information exchange. However, in certain task-related scenarios, this requirement might conflict with the need for robots to spread out in the environment, e.g., for distributed sensing or surveillance

Jan Bok, Nikola Jedličková, Jana Maxová

The \emph{Wiener index} is a widely studied topological index of graphs. One of the main problems in the area is to determine which graphs of given properties attain the extremal values of Wiener index. In this paper we resolve an open problem posed by Du in 2012. To this end we determine the unicyclic bipartite graphs with given size of parts having the max

Hongge Chen, Huan Zhang, Duane Boning, Cho-Jui Hsieh

Although adversarial examples and model robustness have been extensively studied in the context of linear models and neural networks, research on this issue in tree-based models and how to make tree-based models robust against adversarial examples is still limited. In this paper, we show that tree based models are also vulnerable to adversarial examples and

Baihan Lin

Inspired by the adaptation phenomenon of neuronal firing, we propose the regularity normalization (RN) as an unsupervised attention mechanism (UAM) which computes the statistical regularity in the implicit space of neural networks under the Minimum Description Length (MDL) principle. Treating the neural network optimization process as a partially observable

Michael Burke, Svetlin Penkov, Subramanian Ramamoorthy

Hybrid systems are a compact and natural mechanism with which to address problems in robotics. This work introduces an approach to learning hybrid systems from demonstrations, with an emphasis on extracting models that are explicitly verifiable and easily interpreted by robot operators. We fit a sequence of controllers using sequential importance sampling un

Prashanth L. A., Sanjay P. Bhat

This paper presents a unified approach based on Wasserstein distance to derive concentration bounds for empirical estimates for two broad classes of risk measures defined in the paper. The classes of risk measures introduced include as special cases well known risk measures from the finance literature such as conditional value at risk (CVaR), optimized certa

Karoliina Lehtinen, Udi Boker

The complexity of parity games is a long standing open problem that saw a major breakthrough in 2017 when two quasi-polynomial algorithms were published. This article presents a third, independent approach to solving parity games in quasi-polynomial time, based on the notion of register game, a parameterised variant of a parity game. The analysis of register

Jie Li, Lei Gu, Ruqian Wu

By using the first-principles calculations and model analyses, we found that the combination of defected tungsten disulfide monolayer and sparse manganese adsorption may give a KK` valley spin splitting up to 210 meV. This system also has a tunable magnetic anisotropy energy, a clean band gap, and an appropriate band alignment, with the Fermi level sitting r

Guannan Zhang, Jiaxin Zhang, Jacob Hinkle

We developed a Nonlinear Level-set Learning (NLL) method for dimensionality reduction in high-dimensional function approximation with small data. This work is motivated by a variety of design tasks in real-world engineering applications, where practitioners would replace their computationally intensive physical models (e.g., high-resolution fluid simulators)

Rishav Chourasia, Adish Singla

Ensemble methods have been widely applied in Reinforcement Learning (RL) in order to enhance stability, increase convergence speed, and improve exploration. These methods typically work by employing an aggregation mechanism over actions of different RL algorithms. We show that a variety of these methods can be unified by drawing parallels from committee voti

Sandip Banerjee, Sujoy Bhore

Given a graph $G=(V,E)$, the dominating set problem asks for a minimum subset of vertices $D\subseteq V$ such that every vertex $u\in V\setminus D$ is adjacent to at least one vertex $v\in D$. That is, the set $D$ satisfies the condition that $|N[v]\cap D|\geq 1$ for each $v\in V$, where $N[v]$ is the closed neighborhood of $v$. In this paper, we study two v

Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar

We study the problem of meta-learning through the lens of online convex optimization, developing a meta-algorithm bridging the gap between popular gradient-based meta-learning and classical regularization-based multi-task transfer methods. Our method is the first to simultaneously satisfy good sample efficiency guarantees in the convex setting, with generali

Igor Uljarevic

We prove a generalization of the Monge-Cayley-Salmon theorem on osculation and ruled submanifolds using elementary geometric measure theory.

Sandra Fortini, Sonia Petrone

Bayesian methods are often optimal, yet increasing pressure for fast computations, especially with streaming data, brings renewed interest in faster, possibly sub-optimal, solutions. The extent to which these algorithms approximate Bayesian solutions is a question of interest, but often unanswered. We propose a methodology to address this question in predict

J. P. Boroński, J. Kupka, P. Oprocha

We show that every (invertible, or noninvertible) minimal Cantor system embeds in $\mathbb{R}$ with vanishing derivative everywhere. We also study relations between local shrinking and periodic points.

Patrick Stähli, Maju Kuriakose, Martin Frenz, Michael Jaeger

Computed ultrasound tomography in echo mode (CUTE) allows determining the spatial distribution of speed-of-sound (SoS) inside tissue using handheld pulse-echo ultrasound (US). This technique is based on measuring the changing phase of beamformed echoes obtained under varying transmit (Tx) and/or receive (Rx) steering angles. The SoS is reconstructed by inver

Miha E. Habič, Radek Honzík

We investigate the extent to which ultrapowers by normal measures on $κ$ can be correct about powersets $\mathcal{P}(λ)$ for $λ>κ$. We consider two versions of this questions, the capturing property $\mathrm{CP}(κ,λ)$ and the local capturing property $\mathrm{LCP}(κ,λ)$. $\mathrm{CP}(κ,λ)$ holds if there is an ultrapower by a normal measure on $κ$ which corr

Walaa I. Eshraim

We expand the study of the pseudoscalar glueball and its first excited state by constructing an interaction Lagrangian which produces the two- and three-body decays of the pseudoscalar glueball, $J^{PC}=0^{-+}$, into the (pseudo)scalar and the excited (pseudo)scalar mesons as well as by constructing other two different chiral Lagrangians which describe the t

Xiangqian Meng, Erkan Nane

We consider non-linear time-fractional stochastic heat type equation $$\frac{\partial^βu}{\partial t^β}+ν(-Δ)^{α/2} u=I^{1-β}_t \bigg[\int_{\mathbb{R}^d}σ(u(t,x),h) \stackrel{\cdot}{\tilde N }(t,x,h)\bigg]$$ and $$\frac{\partial^βu}{\partial t^β}+ν(-Δ)^{α/2} u=I^{1-β}_t \bigg[\int_{\mathbb{R}^d}σ(u(t,x),h) \stackrel{\cdot}{N }(t,x,h)\bigg]$$ in $(d+1)$ dimen

Kanhaiya L. Pandey, Tanvi Karwal, Subinoy Das

The Hubble tension between the $Λ$CDM-model-dependent prediction of the current expansion rate $H_0$ using Planck data and direct, model-independent measurements in the local universe from the SH0ES collaboration disagree at $>3.5σ$. Moreover, there exists a milder $\sim 2σ$ tension between similar predictions for the amplitude $S_8$ of matter fluctuations a

José G. Fernández-Trincado, Ronald Mennickent, Mauricio Cabezas, Olga Zamora

We report the serendipitous discovery of a nitrogen-rich, mildly metal-poor ([Fe/H]=-1.08) giant star in a single-lined spectroscopic binary system found in the SDSS-IV Apache Point Observatory Galactic Evolution Experiment (APOGEE-2) survey, Data Release 14 (DR14). Previous work has assumed that the two percent of halo giants with unusual elemental abundanc

Amichai Lampert

We investigate the structure of polynomials of degree four in many variables over a fixed prime field $\mathbb{F}=\mathbb{F}_{p}$. In 2007, Green and Tao proved that if a polynomial $f:\mathbb{F}^{n}\rightarrow\mathbb{F}$ is poorly distributed, then it is a function of a few polynomials of smaller degree. In 2009, Haramaty and Shpilka found an effective boun

S. Amaducci, L. Cosentino, M. Barbagallo, N. Colonna

The 235U(n,f) cross section was measured in a wide energy range at n_TOF relative to 6Li(n,t) and 10B(n,alpha), with high resolution and in a wide energy range, with a setup based on a stack of six samples and six silicon detectors placed in the neutron beam. This allowed us to make a direct comparison of the reaction yields under the same experimental condi

Fangxin Shang, Hao Zhang

Training recurrent neural networks (RNNs) with backpropagation through time (BPTT) has known drawbacks such as being difficult to capture longterm dependencies in sequences. Successful alternatives to BPTT have not yet been discovered. Recently, BP with synthetic gradients by a decoupled neural interface module has been proposed to replace BPTT for training

W. J. Pearson, L. Wang, J. W. Trayford, C. E. Petrillo

Mergers are an important aspect of galaxy formation and evolution. We aim to test whether deep learning techniques can be used to reproduce visual classification of observations, physical classification of simulations and highlight any differences between these two classifications. With one of the main difficulties of merger studies being the lack of a truth

Michael Jurkutat, Marija Avramovska, Grant V. M. Williams, Daniel Dernbach

Nuclear relaxation is an important thermodynamic probe of electronic excitations, in particular in conducting and superconducting systems. Here, an empirical phenomenology based on all available literature data for planar Cu in hole-doped cuprates is developed. It is found that most of the seemingly different relaxation rates among the systems are due to a t

Sai Prasanna, Sri Ananda Seelan

This paper describes our submission for the SemEval-2019 Suggestion Mining task. A simple Convolutional Neural Network (CNN) classifier with contextual word representations from a pre-trained language model was used for sentence classification. The model is trained using tri-training, a semi-supervised bootstrapping mechanism for labelling unseen data. Tri-t

Jaeseop Ahn, Jimyeong Kim, Ihyeok Seo

In this paper we study spatial analyticity of solutions to the defocusing nonlinear Schrödinger equations $iu_t + Δu = |u|^{p-1}u$, given initial data which is analytic with fixed radius. It is shown that the uniform radius of spatial analyticity of solutions at later time $t$ cannot decay faster than $1/|t|$ as $|t|\rightarrow\infty$. This extends the previ

Emiel Lorist, Mark Veraar

In this paper we introduce Calderón-Zygmund theory for singular stochastic integrals with operator-valued kernel. In particular, we prove $L^p$-extrapolation results under a Hörmander condition on the kernel. Sparse domination and sharp weighted bounds are obtained under a Dini condition on the kernel, leading to a stochastic version of the solution to the $

Vered Shwartz, Ido Dagan

Building meaningful phrase representations is challenging because phrase meanings are not simply the sum of their constituent meanings. Lexical composition can shift the meanings of the constituent words and introduce implicit information. We tested a broad range of textual representations for their capacity to address these issues. We found that as expected

S. Armatas, C. Bouratzis, A. Hillaris, C. E. Alissandrakis

Aims. We examine high time resolution dynamic spectra for fine structures in type II solar radio bursts Methods. We used data obtained with the (SAO) receiver of the Artemis-JLS (ARTEMIS-IV) solar radio spectrograph in the 450-270 MHz range at 10 ms cadence and identified more than 600 short, narrowband features. Their characteristics, such as instantaneous

Sourav Karar, Shounak Datta, Sibasish Ghosh, A. S. Majumdar

We explore a thermodynamical effect of anharmonicity in quantum mechanical oscillators. We show that small quartic perturbations to the oscillator potential lead to an enhancement of performance of quantum refrigerators for both the Otto and Stirling cycles. A similar nonlinearity driven enhancement of performance is also observed for an analogous spin-qubit

Frederic Charve

In this article we prove highly improved and flexible Strichartz-type estimates allowing us to generalize the asymptotics we obtained for a stratified and rotating incompressible Navier-Stokes system: for large (and less regular) initial data, we obtain global well-posedness, asymptotics (as the Rossby number $ε$ goes to zero) and convergence rates as a powe

Solenne Gaucher, Olga Klopp

Estimating the matrix of connections probabilities is one of the key questions when studying sparse networks. In this work, we consider networks generated under the sparse graphon model and the in-homogeneous random graph model with missing observations. Using the Stochastic Block Model as a parametric proxy, we bound the risk of the maximum likelihood estim

Lorenzo Traldi

Joyce showed that for a classical knot $K$, the involutory medial quandle $\text{IMQ}(K)$ is isomorphic to the core quandle of the homology group $H_1(X_2)$, where $X_2$ is the cyclic double cover of $\mathbb S ^3$, branched over $K$. It follows that $|\text{IMQ}(K)| = | \det K |$. In the present paper, the extension of Joyce's result to classical links

Olivier Garet

The aim of this note is to provide a Master Theorem for some discrete divide and conquer recurrences: $$X_{n}=a_n+\sum_{j=1}^m b_j X_{\lfloor{\frac{n}{m_j}}\rfloor},$$ where the $m_i$'s are integers with $m_i\ge 2$. The main novelty of this work is there is no assumption of regularity or monotonicity for $(a_n)$. Then, this result can be applied to vario

Jérémie Vidal, David Cébron, Asif Ud-Doula, Evelyne Alecian

Surface magnetic fields have been detected in 5 to 10% of isolated massive stars, hosting outer radiative envelopes. They are often thought to have a fossil origin, resulting from the stellar formation phase. Yet, magnetic massive stars are scarcer in (close) short-period binaries, as reported by the BinaMIcS (Binarity and Magnetic Interaction in various cla

Christian Clason, Vu Huu Nhu

In this paper, we consider a modified Levenberg--Marquardt method for solving an ill-posed inverse problem where the forward mapping is not Gâteaux differentiable. By relaxing the standard assumptions for the classical smooth setting, we derive asymptotic stability estimates that are then used to prove the convergence of the proposed method. This method can

J. F. Assunção, T. Mariz, J. R. Nascimento, A. Yu. Petrov

In this paper, we formulate a theory of the second-rank antisymmetric (pseudo)tensor field minimally coupled to a spinor, calculate the one-loop effective potential of the (pseudo)tensor field, and, explicitly, demonstrate that it is positively defined and possesses a continuous set of minima, both for tensor and pseudotensor cases. Therefore, our model turn

José A. Cañizo, Chuqi Cao, Josephine Evans, Havva Yoldaş

We study convergence to equilibrium of the linear relaxation Boltzmann (also known as linear BGK) and the linear Boltzmann equations either on the torus $(x,v) \in \mathbb{T}^d \times \mathbb{R}^d$ or on the whole space $(x,v) \in \mathbb{R}^d \times \mathbb{R}^d$ with a confining potential. We present explicit convergence results in total variation or weigh

Nikola Kamburov, Luciano Sciaraffia

We construct nontrivial smooth bounded domains $Ω\subseteq \mathbb{R}^n$ of the form $Ω_0 \setminus \overlineΩ_1$, bifurcating from annuli, for which there exists a positive solution to the overdetermined boundary value problem \[ -Δu = 1, \; u>0 \quad \text{in } Ω, \qquad u = 0 ,\; \partial_νu = \text{const} \quad \text{on } \partialΩ_0, \qquad u = \text{co

Jinyong Jeong, Lucas Y. Cho, Ayoung Kim

This paper presents a framework for the targetless extrinsic calibration of stereo cameras and Light Detection and Ranging (LiDAR) sensors with a non-overlapping Field of View (FOV). In order to solve the extrinsic calibrations problem under such challenging configuration, the proposed solution exploits road markings as static and robust features among the v

Joaquim Jornet-Somoza, Irina Lebedeva

Photo-active systems are characterized by their capacity of absorbing light energy and transforming it. Usually, more than one chromophore is involved in the light absorption and excitation transport processes in complex systems. Linear-Response Time-Dependent Density Functional (LR-TDDFT) is commonly used to identify excitation energies and transition prope

Yuko Kuroki, Liyuan Xu, Atsushi Miyauchi, Junya Honda

We study the problem of stochastic combinatorial pure exploration (CPE), where an agent sequentially pulls a set of single arms (a.k.a. a super arm) and tries to find the best super arm. Among a variety of problem settings of the CPE, we focus on the full-bandit setting, where we cannot observe the reward of each single arm, but only the sum of the rewards.

Benjamin Cooper, Peter Samuelson

We refine and prove the central conjecture of our first paper for annuli with at least two marked intervals on each boundary component by computing the derived Hall algebras of their Fukaya categories.

V. V. Sivak, N. E. Frattini, V. R. Joshi, A. Lingenfelter

Quantum-limited Josephson parametric amplifiers are crucial components in circuit QED readout chains. The dynamic range of state-of-the-art parametric amplifiers is limited by signal-induced Stark shifts that detune the amplifier from its operating point. Using a Superconducting Nonlinear Asymmetric Inductive eLement (SNAIL) as an active component, we show t

I. C. Cloët, R. Dupré, S. Riordan, W. Armstrong

The fundamental theory of the strong interaction -- quantum chromodynamics (QCD) -- provides the foundational framework with which to describe and understand the key properties of atomic nuclei. A deep understanding of the explicit role of quarks and gluons in nuclei remains elusive however, as these effects have thus far been well-disguised by confinement e

Stefano Foffa, Pierpaolo Mastrolia, Riccardo Sturani, Christian Sturm

We determine the gravitational interaction between two compact bodies up to the sixth power in Newton's constant GN, in the static limit. This result is achieved within the effective field theory approach to General Relativity, and exploits a manifest factorization property of static diagrams which allows to derive static post Newtonian (PN) contribution

Jin Yang, Tao Zhang, Chunling Liu, Kam Chuen Yuen

Multivariate functional data has received considerable attention but testing for equality of mean surfaces and its profile has limited progress. The existing literature has tested equality of either mean curves of univariate functional samples directly, or mean surfaces of bivariate functional data samples but turn into functional curves comparison again. In

Axel Maas

The question of whether confining effects are visible in correlation functions is a long-standing one. Complementing investigations on the propagators of fundamental and adjoint scalar matter particles here the quenched scalar-gluon vertex is investigated. For this purpose a multitude of lattice setups in two, three, and four dimensions is analyzed in quench

C. Quesne

Infinite families of quasi-exactly solvable position-dependent mass Schrödinger equations with known ground and first excited states are constructed in a deformed supersymmetric background. The starting points consist in one- and two-parameter trigonometric Pöschl-Teller potentials endowed with a deformed shape invariance property and, therefore, exactly sol