arXiv papers from November 2018

Leticia Cunqueiro, Mateusz Ploskon

We present a new method to expose the dead cone effect at colliders using iterative declustering techniques. Iterative declustering allows to unwind the jet clustering and to access the subjets or branches at different depths of the jet tree. Our method consists on declustering the heavy flavour-tagged jet using Cambridge-Achen algorithm following the branch

Guo Lu, Wanli Ouyang, Dong Xu, Xiaoyun Zhang

Conventional video compression approaches use the predictive coding architecture and encode the corresponding motion information and residual information. In this paper, taking advantage of both classical architecture in the conventional video compression method and the powerful non-linear representation ability of neural networks, we propose the first end-t

Armando Sosthene Kali Balogoun, Guy Martial Nkiet, Carlos Ogouyandjou

In this paper we deal with the problem of testing for the equality of $k$ probability distributions defined on $(\mathcal{X},\mathcal{B})$, where $\mathcal{X}$ is a metric space and $\mathcal{B}$ is the corresponding Borel $\sigma$-field. We introduce a test statistic based on reproducing kernel Hilbert space embeddings and derive its asymptotic distribution

Vidya Muthukumar, Tejaswini Pedapati, Nalini Ratha, Prasanna Sattigeri

Recent work shows unequal performance of commercial face classification services in the gender classification task across intersectional groups defined by skin type and gender. Accuracy on dark-skinned females is significantly worse than on any other group. In this paper, we conduct several analyses to try to uncover the reason for this gap. The main finding

Danielle C. Maddix, Yuyang Wang, Alex Smola

A large collection of time series poses significant challenges for classical and neural forecasting approaches. Classical time series models fail to fit data well and to scale to large problems, but succeed at providing uncertainty estimates. The converse is true for deep neural networks. In this paper, we propose a hybrid model that incorporates the benefit

G. Dimitriadis, C. Rojas-Bravo, C. D. Kilpatrick, R. J. Foley

We present late-time ($\sim$240-260 days after peak brightness) optical photometry and nebular (+236 and +264 days) spectroscopy of SN 2018oh, the brightest Type Ia supernova (SN Ia) observed by the Kepler telescope. The Kepler/K2 30-minute cadence observations started days before explosion and continued past peak brightness. For several days after explosion

Han Lin Shang, Yang Yang, Fearghal Kearney

As a forward-looking measure of future equity market volatility, the VIX index has gained immense popularity in recent years to become a key measure of risk for market analysts and academics. We consider discrete reported intraday VIX tick values as realisations of a collection of curves observed sequentially on equally spaced and dense grids over time and u

Hyunryung Kim, Eunho Kim, Jinkyu Yang

We propose a 3D-printed graded lattice made of hollow elliptical cylinders (HECs) as a new way to design impact mitigation systems. We observe asymmetric dynamics in the graded HEC chains with increasing and decreasing stiffness. Specifically, the increasing stiffness chain shows an acceleration of the propagating waves, while the decreasing stiffness chain

Abdennour Kitouni, Abdenacer Makhlouf, Sergei Silvestrov

The aim of this paper is to introduce $n$-ary BiHom-algebras, generalizing BiHom-algebras. We introduce an alternative concept of BiHom-Lie algebra called BiHom-Lie-Leibniz algebra and study various type of $n$-ary BiHom-Lie algebras and BiHom-associative algebras. We show that $n$-ary BiHom-Lie-Leibniz algebra can be represented by BiHom-Lie-Leibniz algebra

Lorenz M. Roebers, Aras Selvi, Juan C. Vera

We introduce a solution scheme for portfolio optimization problems with cardinality constraints. Typical portfolio optimization problems are extensions of the classical Markowitz mean-variance portfolio optimization model. We solve such type of problems using a method similar to column generation. In this scheme, the original problem is restricted to a subse

F. Gómez-Cubillo, S. Wickramasekara

Admissible vectors for unitary representations of locally compact groups are the basis for group-frame and covariant coherent state expansions. Main tools in the study of admissible vectors have been Plancherel and central integral decomposition, of applicability only under certain separability and semifiniteness restrictions. In this work we present a study

Yixiu Zhao, Ziyin Liu

In this work we propose a novel task framework under which a variety of physical reasoning puzzles can be constructed using very simple rules. Under sparse reward settings, most of these tasks can be very challenging for a reinforcement learning agent to learn. We build several simple environments with this task framework in Mujoco and OpenAI gym and attempt

Bichen Wu, Yanghan Wang, Peizhao Zhang, Yuandong Tian

Recent work in network quantization has substantially reduced the time and space complexity of neural network inference, enabling their deployment on embedded and mobile devices with limited computational and memory resources. However, existing quantization methods often represent all weights and activations with the same precision (bit-width). In this paper

In-Ho Yi

We present a novel approach to construction of a formal semantics for a programming language. Our approach, using a parametric denotational semantics, allows the semantics to be easily extended to support new language features, and abstracted to define program analyses. We apply this in analysing a duck-typed, reflective, curried dynamic language. The benefi

Paulo J. Silva, Orlando Oliveira

We study the Landau gauge quark propagator, at finite temperature, using quenched lattice simulations. Special focus is given to the behaviour of the momentum space form factors across the confinement-deconfinement phase transition.

Da Zhang, Xiyang Dai, Xin Wang, Yuan-Fang Wang

This research strives for natural language moment retrieval in long, untrimmed video streams. The problem is not trivial especially when a video contains multiple moments of interests and the language describes complex temporal dependencies, which often happens in real scenarios. We identify two crucial challenges: semantic misalignment and structural misali

Li Zhang, Heda Song, Nikolaos Aletras, Haiping Lu

Graph convolutional network (GCN) is an emerging neural network approach. It learns new representation of a node by aggregating feature vectors of all neighbors in the aggregation process without considering whether the neighbors or features are useful or not. Recent methods have improved solutions by sampling a fixed size set of neighbors, or assigning diff

Christopher Sutton, Luca M. Ghiringhelli, Takenori Yamamoto, Yury Lysogorskiy

Machine learning (ML) is increasingly used in the field of materials science, where statistical estimates of computed properties are employed to rapidly examine the chemical space for new compounds. However, a systematic comparison of several ML models for this domain has been hindered by the scarcity of appropriate datasets of materials properties, as well

Liqin Shi, Wenchi Cheng, Yinghui Ye, Hailin Zhang

Simultaneous wireless information and power transfer (SWIPT) has been recognized as a promising approach to improving the performance of energy constrained networks. In this paper, we investigate a SWIPT based three-step two-way decode-and-forward (DF) relay network with a non-linear energy harvester equipped at the relay. As most existing works require inst

Per Bäck

In these notes, we introduce formal hom-associative deformations of the quantum planes and the universal enveloping algebras of the two-dimensional non-abelian Lie algebras. We then show that these deformations induce formal hom-Lie deformations of the corresponding Lie algebras constructed by using the commutator as bracket.

Rafael Granero-Belinchón

In this work we study the nonlocal transport equation derived recently by Steinerberger when studying how the distribution of roots of a polynomial behaves under iterated differentation of the function. In particular, we study the well-posedness of the equation, establish some qualitative properties of the solution and give conditions ensuring the global exi

Sergey Bezuglyi, Palle E. T. Jorgensen

With view to applications, we here give an explicit correspondence between the following two: (i) the set of symmetric and positive measures $\rho$ on one hand, and (ii) a certain family of generalized Markov transition measures $P$, with their associated Markov random walk models, on the other. By a generalized Markov transition measure we mean a measurable

Ionut-Gabriel Farcas, Tobias Görler, Hans-Joachim Bungartz, Frank Jenko

Quantifying uncertainty in predictive simulations for real-world problems is of paramount importance - and far from trivial, mainly due to the large number of stochastic parameters and significant computational requirements. Adaptive sparse grid approximations are an established approach to overcome these challenges. However, standard adaptivity is based on

Liqin Shi, Yinghui Ye, Xiaoli Chu, Yangyang Zhang

In this paper, we investigate a simultaneous wireless information and power transfer (SWIPT) based two-way decode-and-forward (DF) relay network, where time switching (TS) is employed for SWIPT and time division broadcast (TDBC) is employed for two-way relaying. We focus on the design of a combining scheme that decides how the relay combines the signals rece

Rohan Padhye, Caroline Lemieux, Koushik Sen, Mike Papadakis

Programs expecting structured inputs often consist of both a syntactic analysis stage, which parses raw input, and a semantic analysis stage, which conducts checks on the parsed input and executes the core logic of the program. Generator-based testing tools in the lineage of QuickCheck are a promising way to generate random syntactically valid test inputs fo

Anthony D. Draper, Ryan K. Cole, Amanda S. Makowiecki, Jeffrey Mohr

We demonstrate fiber mode-locked dual frequency comb spectroscopy for broadband, high resolution measurements in a rapid compression machine (RCM). We apply an apodization technique to improve the short-term signal-to-noise-ratio (SNR), which enables broadband spectroscopy at combustion-relevant timescales. We measure the absorption on 24345 individual wavel

Íñigo Íncer Romeo, Marten Lohstroh, Antonio Iannopollo, Edward A. Lee

We propose a measure and a metric on the sets of infinite traces generated by a set of atomic propositions. To compute these quantities, we first map properties to subsets of the real numbers and then take the Lebesgue measure of the resulting sets. We analyze how this measure is computed for Linear Temporal Logic (LTL) formulas. An implementation for comput

Rachel Downing, Bjorn K. Berntson, Guilherme V. Bossa, Sylvio May

The Bragg-Williams free energy is used to incorporate nearest-neighbor interactions into the lattice gas model of a solvent-free ionic liquid near a planar electrode. We calculate the differential capacitance from solutions of the mean-field consistency relation, arriving at an explicit expression in the limit of a weakly charged electrode. The two additiona

Mark Weber, Jie Chen, Toyotaro Suzumura, Aldo Pareja

Organized crime inflicts human suffering on a genocidal scale: the Mexican drug cartels have murdered 150,000 people since 2006, upwards of 700,000 people per year are "exported" in a human trafficking industry enslaving an estimated 40 million people. These nefarious industries rely on sophisticated money laundering schemes to operate. Despite tremendous re

Jadwiga Daszynska-Daszkiewicz, Przemysław Walczak, Wojciech Szewczuk, Alosha Pamyatnykh

We review the main results obtained from our seismic studies of B-type main sequence pulsators, based on the ground-based, MOST, Kepler and BRITE observations. Important constraints on stellar opacities, convective overshooting and rotation are derived. In each studied case, a significant modification of the opacity profile at the depths corresponding to the

Yinghui Ye, Liqin Shi, Rose Hu, Guangyue Lu

In this letter, we consider a wireless-powered backscatter communication (WP-BackCom) network, where the transmitter first harvests energy from a dedicated energy RF source in the sleep state, and then backscatters information and harvests energy simultaneously through a reflection coefficient. Our goal is to maximize the achievable energy efficiency of the

Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li

Learning-to-Rank deals with maximizing the utility of a list of examples presented to the user, with items of higher relevance being prioritized. It has several practical applications such as large-scale search, recommender systems, document summarization and question answering. While there is widespread support for classification and regression based learni

Avik Dutt, Momchil Minkov, Qian Lin, Luqi Yuan

Modulated optical cavities have been proposed and demonstrated for applications in communications, laser frequency stabilization, microwave-to-optical conversion and frequency comb generation. However, most studies are restricted to the adiabatic regime, where either the maximum excursion of the modulation or the modulation frequency itself is below the line

Victor Gallego, David Rios Insua

We propose a unifying view of two different Bayesian inference algorithms, Stochastic Gradient Markov Chain Monte Carlo (SG-MCMC) and Stein Variational Gradient Descent (SVGD), leading to improved and efficient novel sampling schemes. We show that SVGD combined with a noise term can be framed as a multiple chain SG-MCMC method. Instead of treating each paral

Aleksandar Jovicic, Marko Jereminov, Larry Pileggi, Gabriela Hug

In this paper, a novel linear formulation for power system state estimation that simultaneously treats conventional and synchrophasor measurements is proposed. A linear circuit model for conventional measurements is introduced to enable a fully linear equivalent circuit representation of the power system. The estimated system state is then obtained by formul

Rostislav Grigorchuk, Roman Kogan, Yaroslav Vorobets

We introduce the notion of the Automatic Logarithm $\mathcal L_{\mathcal A, \mathcal B}$ with the purpose of studying the expanding properties of Schreier graphs of action of the group generated by two finite initial Mealy automata $\mathcal A$ and $\mathcal B$ on the levels of a regular $d$-ary rooted tree $\mathcal T$, where $\mathcal A$ is level-transitiv

Mohamed Elfeki, Camille Couprie, Morgane Riviere, Mohamed Elhoseiny

Generative models have proven to be an outstanding tool for representing high-dimensional probability distributions and generating realistic-looking images. An essential characteristic of generative models is their ability to produce multi-modal outputs. However, while training, they are often susceptible to mode collapse, that is models are limited in mappi

Ruslan Skuratovskii

We propose a lower estimation for computing quantity of the inverses of Euler's function. We answer the question about the multiplicity of $m$ in the equation $\varphi(x) = m$ \cite{Ford}. An analytic expression for exact multiplicity of $m = {{2}^{{{2}^{n}}+a}}$, where $a\in N$, $a<{{2}^{n}}$, $\varphi(t)={{2}^{{{2}^{n}}+a}}$ was obtained. A lower bound of

Marios Costa, Haralambos Panagopoulos

We study 4-dimensional SQCD with gauge group SU(Nc) and Nf flavors of chiral supermultiplets on the lattice. We perform extensive calculations of matrix elements and renormalization factors of composite operators in Perturbation Theory. In particular, we compute the renormalization factors of quark and squark bilinears, as well as their mixing at the quantum

Zeyu Zhou

Flow cardinality estimation is the problem of estimating the number of distinct elements in a data flow, often with a stringent memory constraint. It has wide applications in network traffic measurement and in database systems. The virtual LogLog algorithm proposed recently by Xiao, Chen, Chen and Ling estimates the cardinalities of a large number of flows w

Giulia Ricciardi

We summarize selected up-to-date results related to semileptonic $B$ meson decays, namely results on the exclusive determination of the parameter $|V_{cb}|$ of the CKM matrix, on the inclusive determination of $|V_{ub}|$, and on $R(D^{(*)})$.

Eric B. Norrgard, Daniel S. Barker, Stephen P. Eckel, James A. Fedchak

We investigate using optically trapped linear polyatomic molecules as probes of nuclear spin-dependent parity violation. The presence of closely spaced, opposite-parity $\ell$-doublets is a general feature of such molecules, allowing parity-violation-sensitive pairs of levels to be brought to degeneracy in magnetic fields typically 100 times smaller than in

Zhan Tu, Fan Fei, Matthew Eagon, Dongyan Xu

Micro Aerial Vehicles (MAVs) rely on onboard attitude and position sensors for autonomous flight. Due to their size, weight, and power (SWaP) constraints, most modern MAVs use miniaturized inertial measurement units (IMUs) to provide attitude feedback, which is critical for flight stabilization and control. However, recent adversarial attack studies have dem

F. Motahari, A. E. Carlsson

We investigate the effect of filament-obstacle interactions on the force-velocity relation of growing biopolymers, via calculations explicitly treating obstacle diffusion and stochastic addition and subtraction of subunits. We first show that the subunit on- and off-rates satisfy a rigorous thermodynamic relationship determined by the filament-obstacle inter

David Jewitt, Yoonyoung Kim, Jayadev Rajagopal, Susan Ridgway

Observations of active asteroid P/2017 S5 when near perihelion reveal the ejection of large (0.1 to 10 mm) particles at 0.2 to 2 m/s speeds, with estimated mass-loss rates of a few kg/s. The protracted nature of the mass loss (continuous over 150 days) is compatible with a sublimation origin, meaning that this object is likely an ice-bearing main-belt comet.

David Bergman, Carlos Cardonha, Saharnaz Mehrani

Bin Packing with Minimum Color Fragmentation (BPMCF) is an extension of the Bin Packing Problem in which each item has a size and a color and the goal is to minimize the sum of the number of bins containing items of each color. In this work, we introduce BPMCF and present a decomposition strategy to solve the problem, where the assignment of items to bins is

Sven Giesselbach, Katrin Ullrich, Michael Kamp, Daniel Paurat

We propose a novel transfer learning approach for orphan screening called corresponding projections. In orphan screening the learning task is to predict the binding affinities of compounds to an orphan protein, i.e., one for which no training data is available. The identification of compounds with high affinity is a central concern in medicine since it can b

Marcielis Espitia, Gabriel Ponce, Régis Varão

Let $f:M\to M$ be a homeomorphism over a compact Riemannian manifold, ergodic with respect to a measure $\mu$ defined on the completion of the Borel $\sigma$-algebra and $\mathcal F$ a $f$-invariant one dimensional continuous foliation of $M$ by $C^1$-leaves. Then, if $f$ preserves a continuous $\mathcal{F}$-arc length system, then we only have three possibi

Clotilde Fermanian-Kammerer, Veronique Fischer

In this paper, we develop a semi-classical analysis on H-type groups. We define semi-classical pseudodifferential operators, prove the boundedness of their action on square integrable functions and develop a symbolic calculus. Then, we define the semi-classical measures of bounded families of square integrable functions which consists of a pair formed by a m

Lu Lu, I-Chen Lee, Yili Hong

Traditional accelerated life test plans are typically based on optimizing the C-optimality for minimizing the variance of an interested quantile of the lifetime distribution. The traditional methods rely on some specified planning values for the model parameters, which are usually unknown prior to the actual tests. The ambiguity of the specified parameters c

Gabriel Synnaeve, Zeming Lin, Jonas Gehring, Dan Gant

We formulate the problem of defogging as state estimation and future state prediction from previous, partial observations in the context of real-time strategy games. We propose to employ encoder-decoder neural networks for this task, and introduce proxy tasks and baselines for evaluation to assess their ability of capturing basic game rules and high-level dy

Raphaël Beuzart-Plessis

In this paper, we partially complete the local Rankin-Selberg theory of Asai $L$-functions and $\epsilon$-factors as introduced by Flicker and Kable. In particular, we establish the relevant local functional equation at Archimedean places and prove the equality between Rankin-Selberg's and Langlands-Shahidi's $\epsilon$-factors at every place. Our proofs wor

Sylvestre Aureliano Carvalho, Marcelo Lobato Martins

Nowadays, evidence is mounting that the race of living organisms for adaptation to the chemicals synthesized by their neighbours may drive community structures. Particularly, some bacterial infections and plant invasions disruptive of the native community rely on the release of allelochemicals that inhibit or kill sensitive strains or individuals from their

Jean S. Joseph

We define a multiplication on the surreal numbers as higher inductive-inductive types.

Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier, Michael Rapp

Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels simultaneously. In this chapter, we advocate a rule-based approach to multi-label classification. Rule learning algorithms are often employed when one is not only interested in acc

Raphaël Beuzart-Plessis

We establish an explicit Plancherel decomposition for $\mathrm{GL}_n(F)\backslash \mathrm{GL}_n(E)$ where $E/F$ is a quadratic extension of local fields of characteristic zero by making use of a local functional equation for Asai $\gamma$-factors. We also give two applications of this Plancherel formula: first to the global Ichino-Ikeda conjecture for unitar

Juan Orendain

We use geometric ideas coming from certain classic algebraic constructions to associate, to every classical field theory, a symmetric monoidal double functor from the double category of cobordisms with corners to a certain symmetric monoidal double category. We call symmetric monoidal double functors so constructed cylinder topological quantum field theories

Bilal Kartal, Pablo Hernandez-Leal, Matthew E. Taylor

Deep reinforcement learning (DRL) has achieved great successes in recent years with the help of novel methods and higher compute power. However, there are still several challenges to be addressed such as convergence to locally optimal policies and long training times. In this paper, firstly, we augment Asynchronous Advantage Actor-Critic (A3C) method with a

Alyson M. Brooks

Much progress has been made in recent years by the galaxy simulation community in making realistic galaxies, mostly by more accurately capturing the effects of baryons on the structural evolution of dark matter halos at high resolutions. This progress has altered theoretical expectations for galaxy evolution within a Cold Dark Matter (CDM) model, reconciling

I. A. Luchnikov, S. V. Vintskevich, H. Ouerdane, S. N. Filippov

The difficulty to simulate the dynamics of open quantum systems resides in their coupling to many-body reservoirs with exponentially large Hilbert space. Applying a tensor network approach in the time domain, we demonstrate that effective small reservoirs can be defined and used for modeling open quantum dynamics. The key element of our technique is the time

V. V. Bavula, V. Levandovskyy

The Dixmier Conjecture says that every endomorphism of the (first) Weyl algebra $A_1$ (over a field of characteristic zero) is an automorphism, i.e., if $PQ-QP=1$ for some $P, Q \in A_1$ then $A_1 = K \langle P, Q \rangle$. The Weyl algebra $A_1$ is a $\Z$-graded algebra. We prove that the Dixmier Conjecture holds if the elements $P$ and $Q$ are sums of no m

Ismael Gutiérrez García, Anselmo Torresblanca-Badillo

In this article we prove that the heat kernel attached to the non-archimedean elliptic pseudodifferential operators determine a Feller semigroup and a uniformly stochastically continuous C_0 transition function of some strong Markov processes X with state space (Q_p)^n. We explicitly write the Feller semigroup and the Markov transition function associated wi

Mauro Lucci, Graciela Nasini, Daniel Severín

Coloring problems in graphs have been used to model a wide range of real applications. In particular, the List Coloring Problem generalizes the well-known Graph Coloring Problem for which many exact algorithms have been developed. In this work, we present a Branch-and-Price algorithm for the weighted version of the List Coloring Problem, based on the one dev

Elizabeth Kautz, Alexander Hagen, Jesse Johns, Douglas Burkes

A deep neural network was developed for the purpose of predicting thermal conductivity with a case study performed on neutron irradiated nuclear fuel. Traditional thermal conductivity modeling approaches rely on existing theoretical frameworks that describe known, relevant phenomena that govern the microstructural evolution processes during neutron irradiati

Peter Constantin, Joonhyun La

We discuss the Lagrangian-Eulerian framework for hydrodynamic models and provide a proof of Lipschitz dependence of solutions on initial data in path space. The paper presents a corrected version of the result in \cite{c1}.

Nadir Bizi

The subject of this PhD thesis is noncommutative geometry - more specifically spectral triples - and how it can be generalized to semi-Riemannian manifolds generally, and Lorentzian manifolds in particular. The first half of this thesis will thus be dedicated to the transition from Riemannian to semi-Riemannian manifolds. This entails a study of Clifford alg

Bo Sun, Nian-hsuan Tsai, Fangchen Liu, Ronald Yu

We propose an adversarial defense method that achieves state-of-the-art performance among attack-agnostic adversarial defense methods while also maintaining robustness to input resolution, scale of adversarial perturbation, and scale of dataset size. Based on convolutional sparse coding, we construct a stratified low-dimensional quasi-natural image space tha

Théophile Caby, Davide Faranda, Giorgio Mantica, Sandro Vaienti

Generalized dimensions of multifractal measures are usually seen as static objects, related to the scaling properties of suitable partition functions, or moments of measures of cells. When these measures are invariant for the flow of a chaotic dynamical system, generalized dimensions take on a dynamical meaning, as they provide the rate function for the larg

Mike Guidry, Jay Billings

A comprehensive introduction to the theory of the solar neutrino problem is given that is aimed at instructors who are not experts in quantum field theory but would like to incorporate these ideas into instruction of advanced undergraduate or beginning graduate students in courses like astrophysics or quantum mechanics, it is also aimed at the inquisitive st

A. Calamida, T. Matheson, A. Saha, E. Olszewski

We present precise photometry and spectroscopy for 23 candidate spectrophotometric standard white dwarfs. The selected stars are distributed in the Northern hemisphere and around the celestial equators and are all fainter than r ~ 16.5 mag. This network of stars, when established as standards, together with the three Hubble Space Telescope primary CALSPEC wh

Tong Yu, Didier Mutter, Jacques Marescaux, Nicolas Padoy

Vision algorithms capable of interpreting scenes from a real-time video stream are necessary for computer-assisted surgery systems to achieve context-aware behavior. In laparoscopic procedures one particular algorithm needed for such systems is the identification of surgical phases, for which the current state of the art is a model based on a CNN-LSTM. A num

Gabriel Khan, Jun Zhang

Let $X$ and $Y$ be domains of $\mathbb{R}^n$ equipped with respective probability measures $\mu$ and $ \nu$. We consider the problem of optimal transport from $\mu$ to $\nu$ with respect to a cost function $c: X \times Y \to \mathbb{R}$. To ensure that the solution to this problem is smooth, it is necessary to make several assumptions about the structure of

Daniel Alpay, Izchak Lewkowicz

We here first study the state space realization of a tensor-product of a pair of rational functions. At the expense of "inflating" the dimensions, we recover the classical expressions for realization of a regular product of rational functions. Then, under an additional assumption that the limit at infinity of a given rational function exists and is equal to

David Castells-Rufas, Adrià Galin-Pons, Jordi Carrabina

Radio communications using the unlicensed Sub-GHz bands are expected to play an important role in the deployment of the Internet of Things (IoT). The regulations of the sub-GHz unlicensed bands can affect the deployment of LPWAN networks in a similar way to how they affected the deployment of WLAN networks at the end of the twenty's century. This paper revie

Aaron J. Masino, Kaitlin A. Folweiler

Baseline injury categorization is important to traumatic brain injury (TBI) research and treatment. Current categorization is dominated by symptom-based scores that insufficiently capture injury heterogeneity. In this work, we apply unsupervised clustering to identify novel TBI phenotypes. Our approach uses a generalized low-rank model (GLRM) model for featu

Sambit Panda, Cencheng Shen, Joshua T. Vogelstein

Decision forests are widely used for classification and regression tasks. A lesser known property of tree-based methods is that one can construct a proximity matrix from the tree(s), and these proximity matrices are induced kernels. While there has been extensive research on the applications and properties of kernels, there is relatively little research on k

E. Aristidi, A. Agabi, M. Azouit, E. Fossat

We present wind and temperature profiles at Dome C measured by balloon born sonds during the polar summer. Data from 197 flights have been processed for 4 campaigns between 2000 and 2004. We show the exceptionnal wind conditions at Dome C, Average ground wind speed is 3.6 m/s. We noticed in mid-november the presence of high altitude strong winds (40 m/s) pro

Andrey Piatnitski, Elena Zhizhina

This paper deals with homogenization of parabolic problems for integral convolution type operators with a non-symmetric jump kernel in a periodic elliptic medium. It is shown that the homogenization result holds in moving coordinates. We determine the corresponding effective velocity and prove that the limit operator is a second order parabolic operator with

Andreas Deser, Christian Saemann

We describe the global geometry, symmetries and tensors for Double Field Theory over pairs of nilmanifolds with fluxes or gerbes. This is achieved by a rather straightforward application of a formalism we developed previously. This formalism constructs the analogue of a Courant algebroid over the correspondence space of a T-duality, using the language of gra

Alexander Pashevich, Danijar Hafner, James Davidson, Rahul Sukthankar

Solving tasks with sparse rewards is a main challenge in reinforcement learning. While hierarchical controllers are an intuitive approach to this problem, current methods often require manual reward shaping, alternating training phases, or manually defined sub tasks. We introduce modulated policy hierarchies (MPH), that can learn end-to-end to solve tasks fr

Bohdan Khomtchouk, Shyam Sudhakaran

Zipf's law predicts a power-law relationship between word rank and frequency in language communication systems and has been widely reported in a variety of natural language processing applications. However, the emergence of natural language is often modeled as a function of bias between speaker and listener interests, which lacks a direct way of relating inf

Martin Graham, Dirk K. Morr

Recent advances in the development of Josephson scanning tunneling spectroscopy (JSTS) have opened a new path for the exploration of unconventional superconductors. We demonstrate that the critical current, $I_c$, measured via JSTS, images the spatial form of the superconducting order parameter in $d_{x^2-y^2}$-wave superconductors around defects and in the

Qisheng Huang, Chunming Zhao, Ming Jiang, Xiaoming Li

In this paper, we consider using deep neural network for OFDM symbol detection and demonstrate its performance advantages in combating large Doppler Shift. In particular, a new architecture named Cascade-Net is proposed for detection, where deep neural network is cascading with a zero-forcing preprocessor to prevent the network stucking in a saddle point or

Laina D. Mercer, Fred Lu, Joshua L. Proctor

Ambitious global goals have been established to provide universal access to affordable modern contraceptive methods. The UN's sustainable development goal 3.7.1 proposes satisfying the demand for family planning (FP) services by increasing the proportion of women of reproductive age using modern methods. To measure progress toward such goals in populous coun

S. Orlando, M. Miceli, O. Petruk, M. Ono

Aims. We investigate the role played by a pre-supernova (SN) ambient magnetic field on the dynamics of the expanding remnant of SN 1987A and the origin and evolution of the radio emission from the remnant, in particular, during the interaction of the blast wave with the nebula surrounding the SN. Methods. We model the evolution of SN 1987A from the breakout

Jingwei Huang, Haotian Zhang, Li Yi, Thomas Funkhouser

We introduce, TextureNet, a neural network architecture designed to extract features from high-resolution signals associated with 3D surface meshes (e.g., color texture maps). The key idea is to utilize a 4-rotational symmetric (4-RoSy) field to define a domain for convolution on a surface. Though 4-RoSy fields have several properties favorable for convoluti

Dyas Utomo, Leo Blitz, Edith Falgarone

We utilize the multi-wavelength data of M33 to study the origin of turbulence in its interstellar medium. We find that the HI turbulent energy surface density inside 8 kpc is $\sim1-3~\times~10^{46}$ erg pc$^{-2}$, and has no strong dependence on galactocentric radius because of the lack of variation in HI surface density and HI velocity dispersion. Then, we

Felix Bischof, Hermann Kampermann, Dagmar Bruß

Quantum coherence is a fundamental feature of quantum mechanics and an underlying requirement for most quantum information tasks. In the resource theory of coherence, incoherent states are diagonal with respect to a fixed orthonormal basis, i.e., they can be seen as arising from a von Neumann measurement. Here, we introduce and study a generalization to a re

Chang-Yu Hou, Jiang Qian, Denise E. Freed

We study the low-frequency dielectric response of highly charged spheres arranged in a cubic lattice and immersed in an electrolyte solution. We focus on the influence of the out-of-phase current in the regime where the ionic charge is neutral. We consider the case where the charged spheres have no surface conductance and no frequency-dependent surface capac

Steve Mairs, Bhavana Lalchand, Geoffrey C. Bower, Jan Forbrich

The binary T Tauri system JW 566 in the Orion Molecular Cloud underwent an energetic, short-lived flare observed at submillimetre wavelengths by the SCUBA-2 instrument on 26 November 2016 (UT). The emission faded by nearly 50% during the 31 minute integration. The simultaneous source fluxes averaged over the observation are 500 +/- 107 mJy/beam at 450 micron

P. J. Grylls, F. Shankar, L. Zanisi, M. Bernardi

We present STEEL a STatistical sEmi-Empirical modeL designed to probe the distribution of satellite galaxies in groups and clusters. Our fast statistical methodology relies on tracing the abundances of central and satellite haloes via their mass functions at all cosmic epochs with virtually no limitation on cosmic volume and mass resolution. From mean halo a

Jeremy J. Webb, Marta Reina-Campos, J. M. Diederik Kruijssen

Understanding the evolution of stellar clusters in an evolving tidal field is critical for studying the disruption of stellar clusters in a cosmological context. We systematically characterise the response of stellar clusters to tidal shocks using controlled N-body simulations of clusters with various properties that are subjected to different types of shock

Laimei Nie, Masahiro Nozaki, Shinsei Ryu, Mao Tian Tan

We study operator entanglement measures of the unitary evolution operators of (1+1)-dimensional conformal field theories (CFTs), aiming to uncover their scrambling and chaotic behaviors. In particular, we compute the bi-partite and tri-partite mutual information for various configurations of input and output subsystems, and as a function of time. We contrast

Jakub Klencki, Gijs Nelemans

X-ray binaries with black hole (BH) accretors and massive star donors at short orbital periods of a few days can evolve into close binary BH systems (BBH) that merge within the Hubble time through stable mass transfer evolution. From observational point of view, upon the Roche-lobe overflow, such systems will most likely appear as ultra-luminous X-ray source

Benedikt Kloss, David Reichman, Roel Tempelaar

We show that the dynamics of (vertical) Franck-Condon excitations in the regime where Holstein-coupled vibrational modes mix strongly with electronic degrees of freedom sharply contrasts with the known self-localized behavior of vibrationally relaxed excitations. Instead, the strongly-coupled modes are found to periodically induce resonances between interact

Akishi Ikeda, Yu Qiu

Categorically, we introduce the Calabi-Yau-$\mathbb{X}$ categories $\mathcal{D}_{\mathbb{X}}$ of a graded marked surface $\mathbf{S}^\lambda$, as a $q$-deformation of the topological Fukaya category $\mathcal{D}_\infty$ of $\mathbf{S}^\lambda$. We show that $\mathcal{D}_\infty$ can be identified with the cluster-$\mathbb{X}$ category associated to $\mathcal{

S. Marassi, R. Schneider, M. Limongi, A. Chieffi

Supernovae (SNe) are considered to have a major role in dust enrichment of high redshift galaxies and, due to the short lifetimes of interstellar grains, in dust replenishment of local galaxies. Here we explore how SN dust yields depend on the mass, metallicity, and rotation rate of the progenitor stars, and on the properties of the explosion. To this aim, a

Yu Qiu

This is a survey on the project `Decorated Marked Surfaces', where we introduce the decoration $\Delta$ on a marked surfaces $\mathbf{S}$, to study Calabi-Yau-2 (cluster) categories, Calabi-Yau-3 (Fukaya) categories, braid groups for quivers with potential, quadratic differentials and stability conditions.

V. V. Gvaramadze, A. Y. Kniazev, N. Castro, E. K. Grebel

We report the discovery of two mid-infrared nebulae in the northern hemisphere with the Wide-field Infrared Survey Explorer and the results of optical spectroscopy of their central stars, BD+60 2668 (composed of two components, separated from each other by \approx 3 arcsec) and ALS 19653, with the Calar Alto 3.5-m telescope and the Southern African Large Tel

Riccardo Pavesi, Dominik A. Riechers, Andreas L. Faisst, Gordon J. Stacey

Using the VLA and ALMA, we have obtained CO(2-1), [C II], [N II] line emission and multiple dust continuum measurements in a sample of "normal" galaxies at $z=5-6$. We report the highest redshift detection of low-$J$ CO emission from a Lyman Break Galaxy, at $z\sim5.7$. The CO line luminosity implies a massive molecular gas reservoir of $(1.3\pm0.3)(\alpha_{