November 2018 arXiv papers — page 20

Rong Zhou, Yihang Zhu

We analyze the asymptotic behavior of certain twisted orbital integrals arising from the study of affine Deligne-Lusztig varieties. The main tools include the Base Change Fundamental Lemma and $q$-analogues of the Kostant partition functions. As an application we prove a conjecture of Miaofen Chen and Xinwen Zhu, relating the set of irreducible components of

Christian T. Byrnes, Philippa S. Cole, Subodh P. Patil

We derive analytic bounds on the shape of the primordial power spectrum in the context of single-field inflation. In particular, the steepest possible growth has a spectral index of $n_s - 1 = 4$ once transients have died down. Its primary implication is that any constraint on the power spectrum at a particular scale can be extrapolated to an upper bound ove

Alice K. Harding, Constantinos Kalapotharakos, Monica Barnard, Christo Venter

Pulsed emission from the Vela pulsar at energies above 3 TeV has recently been detected by the H.E.S.S. II air-Cherenkov telescope. We present a model for the broad-band spectrum of Vela from infra-red (IR) to beyond 10 TeV. Recent simulations of the global pulsar magnetosphere have shown that most of the particle acceleration occurs in the equatorial curren

Bekir Baytas, Martin Bojowald, Sean Crowe

The paradigmatic models often used to highlight cosmological features of loop quantum gravity and group field theory are shown to be equivalent, in the sense that they are different realizations of the same model given by harmonic cosmology. The loop version of harmonic cosmology is a canonical realization, while the group-field version is a bosonic realizat

Krishna Kumar Singh, Utkarsh Ojha, Yong Jae Lee

We propose FineGAN, a novel unsupervised GAN framework, which disentangles the background, object shape, and object appearance to hierarchically generate images of fine-grained object categories. To disentangle the factors without supervision, our key idea is to use information theory to associate each factor to a latent code, and to condition the relationsh

Jiahao Chen, Nathan Kallus, Xiaojie Mao, Geoffry Svacha

Assessing the fairness of a decision making system with respect to a protected class, such as gender or race, is challenging when class membership labels are unavailable. Probabilistic models for predicting the protected class based on observable proxies, such as surname and geolocation for race, are sometimes used to impute these missing labels for complian

G. A. Wade, J. V. Smoker, C. J. Evans, I. D. Howarth

We report new spectroscopic observations of the magnetic Of?p star HD 148937 obtained since 2015 that differ qualitatively from its extensive historical record of weak, periodic spectral variations. This remarkable behaviour represents clear evidence for an unprecedented change in the character of variability of the star. In this paper we describe the new sp

Kevin K. Chen, Anthony C. Gamst, Alden K. Walker

The weights of a neural network are typically initialized at random, and one can think of the functions produced by such a network as having been generated by a prior over some function space. Studying random networks, then, is useful for a Bayesian understanding of the network evolution in early stages of training. In particular, one can investigate why neu

Kunal Garg, Parag Bobade, Dimitra Panagou

This paper presents extensions of finite-time stability results to some prototypical adaptive control and estimation frameworks. First, we present a novel scheme of online parameter estimation that guarantees convergence of the estimation error in a fixed time under a relaxed persistence of excitation condition. Subsequently, we design a novel Model Referenc

Eugenio Aulisa, Giacomo Capodaglio

A monolithic coupling between the material point method (MPM) and the finite element method (FEM) is presented. The MPM formulation described is implicit, and the exchange of information between particles and background grid is minimized. The reduced information transfer from the particles to the grid improves the stability of the method. Once the residual i

P. Béjot

In this paper, the unidirectional pulse propagation equation generalized to structured media is derived. A fast modal transform linking the spatio-temporal representation of the field and its modal distribution is presented. This transform is used for solving the propagation equation by using a split-step algorithm. As an example, we present, to the best of

Clément L. Canonne, Gautam Kamath, Audra McMillan, Adam Smith

Hypothesis testing plays a central role in statistical inference, and is used in many settings where privacy concerns are paramount. This work answers a basic question about privately testing simple hypotheses: given two distributions $P$ and $Q$, and a privacy level $\varepsilon$, how many i.i.d. samples are needed to distinguish $P$ from $Q$ subject to $\v

Arun Mukundan, Giorgos Tolias, Andrei Bursuc, Hervé Jégou

We propose a multiple-kernel local-patch descriptor based on efficient match kernels from pixel gradients. It combines two parametrizations of gradient position and direction, each parametrization provides robustness to a different type of patch mis-registration: polar parametrization for noise in the patch dominant orientation detection, Cartesian for impre

Shu-Xu Yi, K. S. Cheng, Rui Luo

We propose a new model of Fast Radio Bursts (FRBs) based on stellar mass black hole-massive star binaries. We argue that the inhomogeneity of the circumstellar materials or/and the time varying wind activities of the stellar companion will cause the black hole to accrete at a transient super-Eddington rate. The collision among the clumpy ejecta in the result

Md-Nafiz Hamid, Iddo Friedberg

Antibiotic resistance monitoring is of paramount importance in the face of this on-going global epidemic. Deep learning models trained with traditional optimization algorithms (e.g. Adam, SGD) provide poor posterior estimates when tested against out-of-distribution (OoD) antibiotic resistant/non-resistant genes. In this paper, we introduce a deep learning mo

Julieta Gruszko, Brian Naranjo, Byron Daniel, Andrey Elagin

The FlatDot detector has been used to demonstrate the separation of Cherenkov and scintillation light for 1 to 2MeV electrons in linear alkylbenzene (LAB). With an average PMT transit time spread (TTS) of 200ps, the early light in each event is clearly dominated by the Cherenkov signal, which on average comprises $86^{+2}_{-3}\%$ of the light collected in th

Yuwen Li

In this paper, we present several new a posteriori error estimators and two adaptive mixed finite element methods \textsf{AMFEM1} and \textsf{AMFEM2} for the Hodge Laplacian problem in finite element exterior calculus. We prove that \textsf{AMFEM1} and \textsf{AMFEM2} are both convergent starting from any initial coarse mesh. A suitably defined quasi error i

C. V. H. B. Uhlig, R. S. Sarthour, I. S. Oliveira, A. M. Souza

Utilizing the highly correlated quantum NOON states of particles, we have implemented a proof-of-principle quantum thermometer using the NMR technique for measuring the variation of local magnetic field with the temperature variation. The system used was the star-topology system of hexafluorophosphate molecules and the thermometer showed a sensitivity of $85

Shaohuai Shi, Xiaowen Chu, Bo Li

Distributed synchronous stochastic gradient descent has been widely used to train deep neural networks on computer clusters. With the increase of computational power, network communications have become one limiting factor on system scalability. In this paper, we observe that many deep neural networks have a large number of layers with only a small amount of

A. Sollima, F. R. Ferraro

We investigate the evolution of the radial distribution of Blue Straggler Stars through a set of Monte Carlo simulations of star clusters under a variety of initial conditions. We used a novel technique based on the "artificial oversampling" of the distribution function of the Blue Stragglers and control population to tear down the effect of statistical fluc

Delong Zhang, Lu Lan, Yeran Bai, Hassaan Majeed

Phase-contrast microscopy converts the optical phase introduced by transparent, unlabeled specimens into modulation in the intensity image. Modern phase imaging techniques are capable of quantifying phase shift at each point in the field of view, enabling non-destructive applications in materials and life sciences. However, these attractive features come wit

M. P. Frías, A. Torres-Signes, M. D. Ruiz-Medina, J. Mateu

We introduce a new class of spatial Cox processes driven by a Hilbert--valued random log--intensity. We adopt a parametric framework in the spectral domain, to estimate its spatial functional correlation structure. Specifically, we consider a spectral functional, based on the periodogram operator, inspired on Whittle estimation methodology. Strong-consistenc

Wojciech Górny

We study existence of minimisers to the least gradient problem on a strictly convex domain in two settings. On a bounded domain, we allow the boundary data to be discontinuous and prove existence of minimisers in terms of the Hausdorff measure of the discontinuity set. Later, we allow the domain to be unbounded, prove existence of minimisers and study their

Silvia de Juan, Judi Hewitt, Maria Dulce Subida, Simon Thrush

It is crucial that societies are informed on the risks of impoverished ecosystem health for their well-being. For this purpose, Ecological Integrity (EI) is a useful concept that seeks to capture the complex nature of ecosystems and their interaction with social welfare. But the challenge remains to measure EI and translate scientific terminology into operat

Daniel Blixt, Manuel Hohmann, Christian Pfeifer

We derive the kinematic Hamiltonian for the so-called "new general relativity" class of teleparallel gravity theories, which is the most general class of theories whose Lagrangian is quadratic in the torsion tensor and does not contain parity violating terms. Our approach makes use of an explicit expression for the flat, in general, nonvanishing spin connect

TonTon Hsien-De Huang, Po-Wei Hong, Ying-Tse Lee, Yi-Lun Wang

The cryptocurrency is attracting more and more attention because of the blockchain technology. Ethereum is gaining a significant popularity in blockchain community, mainly due to the fact that it is designed in a way that enables developers to write smart contracts and decentralized applications (Dapps). There are many kinds of cryptocurrency information on

Himanshu Akolkar, SioHoi Ieng, Ryad Benosman

Optical flow is a crucial component of the feature space for early visual processing of dynamic scenes especially in new applications such as self-driving vehicles, drones and autonomous robots. The dynamic vision sensors are well suited for such applications because of their asynchronous, sparse and temporally precise representation of the visual dynamics.

Angela Carnevale, Matteo Cavaleri

We investigate partial Equality and Word Problems for finitely generated groups. After introducing Upper Banach (UB) density on free groups, we prove that solvability of the Equality Problem on squares of UB-generic sets implies solvability of the whole Word Problem. In particular, we prove that solvability of generic EP implies WP. We then exploit another d

Stefano Marchesin

The goal of case-based retrieval is to assist physicians in the clinical decision making process, by finding relevant medical literature in large archives. We propose a research that aims at improving the effectiveness of case-based retrieval systems through the use of automatically created document-level semantic networks. The proposed research tackles diff

Eyal M. Subag, Ehud Moshe Baruch

We lift any (infinitesimal) unitary irreducible representation of $GL_n(\mathbb{R})$ to a family of representations that strongly contracts to a certain type of (infinitesimal) unitary irreducible representations of $\mathbb{R}^n\rtimes {M}_n$, with $M_n$ being the mirabolic subgroup of $GL_n(\mathbb{R})$. For the case of $n=2$ we obtain the full unitary dua

S. Bouledjedj, A. Khodja, F. Benamira, L. Guechi

The Nikiforov-Uvarov polynomial method employed by Aguda to solve the Dirac equation with an improved Rosen-Morse potential plus a Coulomb-like tensor potential is shown inappropriate because the conditions of its application are not fulfilled. We clarify the problem and construct the correct solutions in the spin and pseudospin symmetric regimes via the sta

Richa Kundu, Dante Minniti, Harinder P. Singh

We used extra-tidal RR Lyrae stars to study the dynamics of Galactic globular clusters and know how effects like dynamical friction and tidal disruption affect these clusters. The Gaia DR2 catalog for RR Lyrae stars (Clementini et al. 2018) is used along with the proper motions and tidal radii data for the globular clusters compiled from literature. A sample

Tim Brooks, Ben Mildenhall, Tianfan Xue, Jiawen Chen

Machine learning techniques work best when the data used for training resembles the data used for evaluation. This holds true for learned single-image denoising algorithms, which are applied to real raw camera sensor readings but, due to practical constraints, are often trained on synthetic image data. Though it is understood that generalizing from synthetic

Debaprasad Maity, Pankaj Saha

We have studied the preheating phase for a class of plateau inflationary model considering the four-legs interaction term $(1/2)g^2\phi^2\chi^2$ between the inflaton $(\phi)$ and reheating field $(\chi)$. We specifically focus on the effects of a parameter $\phi_*$ that controls inflationary dynamics and the shape of the inflaton potential. For $\phi_* < M_p

Zong-Xing Ding, Chang-Sheng Hu, Li-Tuo Shen, Zhen-Biao Yang

Preparation of entangled steady states via dissipation and pumping in Rydberg atoms has been recently found to be useful for quantum information processing. The driven-dissipative dynamics is closely related to the natural linewidth of the Rydberg states and can be usually modulated by engineering the thermal reservior. Instead of modifying the effectively r

J. Barranco, A. Bernal, D. Delepine

The equation of state for a degenerate gas of fermions at zero temperature in the non-relativistic case is a polytrope, i.e. $p \sim\rho^{5/3}/m_F^{8/3}$. If dark matter is modeled by such a non-interacting fermion, this dependence in the mass of the fermion $m_F$ explains why if dark matter is very heavy the effective pressure of dark matter is negligible.

Hsin-Pai Cheng, Patrick Yu, Haojing Hu, Feng Yan

Distributed learning systems have enabled training large-scale models over large amount of data in significantly shorter time. In this paper, we focus on decentralized distributed deep learning systems and aim to achieve differential privacy with good convergence rate and low communication cost. To achieve this goal, we propose a new learning algorithm LEASG

Yanyan Li, Bo Wang

In this paper, we prove a form of the strong comparison principle for a class of fully nonlinear subelliptic operators of the form $\nabla^{2}_{H}\psi+L(\cdot,\psi,\nabla_{H}\psi)$ on the Heisenberg group, which include the CR invariant operators.

Yuri Lyubarsky

The pulsar radio emission is commonly associated with the plasma outflow in the open field line tube; then a pencil beam is emitted along the pulsar magnetic axis. Observations suggest that there is an additional radio emission mechanism specific for pulsars with high magnetic field at the light cylinder. These pulsars are known to be strong sources of non-t

Marcelo Augusto Muniz Teixeira, Fábio Manoel França Lobato, Beatriz Nery Rodrigues Chagas, Antonio Fernando Lavareda Jacob Junior

The internet development and the consequent change in communication forms have strengthened as online social networks, increasing the involvement of people with this media and making consumers of products and services, which are more informed and demanding for companies. This context has given rise to Social CRM, which can be put into practice by means of el

Samuel Braunfeld

For a finite lattice $\Lambda$, $\Lambda$-ultrametric spaces have, among other reasons, appeared as a means of constructing structures with lattices of equivalence relations embedding $\Lambda$. This makes use of an isomorphism of categories between $\Lambda$-ultrametric spaces and structures equipped with certain families of equivalence relations. We extend

Omer Nguena Timo, Dimitri Prestat, Florent Avellaneda

Recently, an efficient constraint solving-based approach has been developed to detect logical faults in systems specified with classical finite state machines (FSMs). The approach is unsuitable to detect violations of time constraints. In this paper, we lift the approach to generated tests detecting both logical faults and violations of time constraints in s

Andrei Velicu

In this paper we study the Sobolev inequality in the Dunkl setting using two new approaches which provide a simpler elementary proof of the classical case $p=2$, as well as an extension to the coefficient $p=1$ that was previously unknown. We also find estimates of the sharp constants for the Sobolev inequality for Dunkl gradient. Related inequalities and so

Le Wang, Yingge Du, Peter V. Sushko, Mark E. Bowden

We have investigated the electronic and optical properties of epitaxial La1-xSrxFeO3 for x from 0 to 1 prepared by molecular beam epitaxy. Core-level and valence-band x-ray photoemission features monotonically shift to lower binding energy with increasing x, indicating downward movement of the Fermi level toward to the valence band maximum. Both Fe 2p and O

Adam Blumenthal, Bernard Lidicky, Ryan R. Martin, Sergey Norin

The Hall ratio of a graph $G$ is the maximum value of $v(H) / \alpha(H)$ taken over all non-null subgraphs $H$ of $G$. For any graph, the Hall ratio is a lower-bound on its fractional chromatic number. In this note, we present various constructions of graphs whose fractional chromatic number grows much faster than their Hall ratio. This refutes a conjecture

Yashar Komijani, Anna Toth, Premala Chandra, Piers Coleman

The confluence of quantum mechanics and complexity, which leads to the emergence of rich, exotic states of matter, motivates the extension of our concepts of quantum ordering. The twin concepts of spontaneously broken symmetry, described in terms of a Landau order parameter, and of off-diagonal long-range order (ODLRO), are fundamental to our understanding o

Lorenzo Paolozzi, Yves Bandi, Roberto Cardarelli, Stephane Debieux

The TT-PET collaboration is developing a small animal TOF-PET scanner based on monolithic silicon pixel sensors in SiGe BiCMOS technology. The demonstrator chip, a small-scale version of the final detector ASIC, consists of a 3 x 10 pixel matrix integrated with the front-end, a 50 ps binning TDC and read out logic. The chip, thinned down to 100 {\mu}m and ba

Jimmy Devillet, Jean-Luc Marichal, Bruno Teheux

We investigate classifications of quasitrivial semigroups defined by certain equivalence relations. The subclass of quasitrivial semigroups that preserve a given total ordering is also investigated. In the special case of finite semigroups, we address and solve several related enumeration problems.

Michael C. Ogilvie, Leandro Medina

Many scalar field theory models with complex actions are invariant under the antilinear ($PT$) symmetry operation $L^{\ast}(-\chi)=L(\chi)$. Models in this class include the $i\phi^{3}$ model, the Bose gas at finite density and Polyakov loop spin models at finite density. This symmetry may be used to obtain a dual representation where weights in the function

Jetanat Datephanyawat, Paul D. Beale

Parallel supercomputer-based Monte Carlo and stochastic simulations require pseudorandom number generators that can produce distinct pseudorandom streams across many independent processes. We propose a scalable class of parallel and vectorizable pseudorandom number generators based on a non-cryptographic version of the RSA public-key exponentiation cipher. O

Benjamin Assel

Monopole operators in Chern-Simons theories with charged matter have been studied using the state-operator map in CFTs, as states on $\mathbb{R}\times S^2$ with background magnetic flux on $S^2$. Gauge invariance requires a dressing with matter modes which provides non-zero spin to the monopoles. In this note we propose a description of the monopole operator

Denis S. Grebenkov, Ralf Metzler, Gleb Oshanin

The first-passage time (FPT), i.e., the moment when a stochastic process reaches a given threshold value for the first time, is a fundamental mathematical concept with immediate applications. In particular, it quantifies the statistics of instances when biomolecules in a biological cell reach their specific binding sites and trigger cellular regulation. Typi

Gloria Fabris, Alessandro Lucantonio, Nico Hampe, Erik Noetzel

Basement membranes (BMs) are thin layers of condensed extracellular matrix proteins serving as permeability filters, cellular anchoring sites, and barriers against cancer cell invasion. It is believed that their biomechanical properties play a crucial role in determining cellular behavior and response, especially in mechanically active tissues like breast gl

Christian Blohmann, Alan Weinstein

In previous work with M.C. Fernandes, we found a Lie algebroid symmetry for the Einstein evolution equations of general relativity. The present work was motivated by the effort to explain the coisotropic structure of the constraint subset for the initial value problem by extending the notion of hamiltonian structure from Lie algebra actions to general Lie al

Yijia Zhou, Igor Lesanovsky, Thomas Fernholz, Weibin Li

Sagnac interferometers with massive particles promise unique advantages in achieving high precision measurements of rotation rates over their optical counterparts. Recent proposals and experiments are exploring non-ballistic Sagnac interferometers where trapped atoms are transported along a closed path. This is achieved by using superpositions of internal qu

Noam Soker, Aldana Grichener, Avishai Gilkis

We propose a common-envelope jets supernova (CEJSN) scenario for the fast-rising blue optical transient AT2018cow. In a CEJSN a neutron star (NS) spirals-in inside the extended envelope of a massive giant star and enters the core. The NS accretes mass from the core through an accretion disc and launches jets. These jets explode the core and the envelope. In

Xu Liu, Yuning Zhang, Roland Nagel, Walter Reisner

Methods for reducing and directly controlling the speed of DNA through a nanopore are needed to enhance sensing performance for direct strand sequencing and detection/mapping of sequence-specific features. We have created a method for reducing and controlling the speed of DNA that uses two independently controllable nanopores operated with an active control

Jordy de Vries, Marieke Postma, Jorinde van de Vis

We investigate the role of leptons in electroweak baryogenesis by studying a relatively simple framework inspired by effective field theory that satisfies all Sakharov conditions. In particular, we study the effectiveness of CP-violating source terms induced by dimension-six Yukawa interactions for quarks and charged leptons. Despite the relatively small Yuk

Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz Üstebay

Recently, techniques for applying convolutional neural networks to graph-structured data have emerged. Graph convolutional neural networks (GCNNs) have been used to address node and graph classification and matrix completion. Although the performance has been impressive, the current implementations have limited capability to incorporate uncertainty in the gr

Juliette Millet, Neil Zeghidour

Speech classifiers of paralinguistic traits traditionally learn from diverse hand-crafted low-level features, by selecting the relevant information for the task at hand. We explore an alternative to this selection, by learning jointly the classifier, and the feature extraction. Recent work on speech recognition has shown improved performance over speech feat

Michael Karkulik, Jens Markus Melenk, Alexander Rieder

We consider fractional Sobolev spaces $H^\theta(\Gamma)$, $\theta \in [0,1]$, on a 2D surface $\Gamma$. We show that functions in $H^\theta(\Gamma)$ can be decomposed into contributions with local support in a stable way. Stability of the decomposition is inherited by piecewise polynomial subspaces. Applications include the analysis of additive Schwarz preco

ATLAS Collaboration

The inclusive production of four isolated charged leptons in $pp$ collisions is analysed for the presence of hard double-parton scattering, using 20.2 fb$^{-1}$ of data recorded in the ATLAS detector at the LHC at centre-of-mass energy $\sqrt{s}$ = 8 TeV. In the four-lepton invariant-mass range of $80<m_{4\ell}<1000$ GeV, an artificial neural network is used

Wenda Li, Lawrence C. Paulson

Many problems in computer algebra and numerical analysis can be reduced to counting or approximating the real roots of a polynomial within an interval. Existing verified root-counting procedures in major proof assistants are mainly based on the classical Sturm theorem, which only counts distinct roots. In this paper, we have strengthened the root-counting ab

Marcus Valtonen Örnhag, Carl Olsson, Anders Heyden

Low rank approximation is a commonly occurring problem in many computer vision and machine learning applications. There are two common ways of optimizing the resulting models. Either the set of matrices with a given rank can be explicitly parametrized using a bilinear factorization, or low rank can be implicitly enforced using regularization terms penalizing

Andrei Druzhinin

We construct geometric models for the $\mathbb P^1$-spectrum $M_{\mathbb P^1}(Y)$, which computes in Garkusha-Panin's theory of framed motives \cite{GP14} a positively motivically fibrant $\Omega_{\mathbb P^1}$ replacement of $\Sigma_{\mathbb P^1}^\infty Y$ for a smooth scheme $Y\in \Sm_k$ over a perfect field $k$. Namely, we get the $T$-spectrum in the cate

Jörg P. Bachmann, Johann-Christoph Freytag

A time series is a sequence of data items; typical examples are streams of temperature measurements, stock ticker data, or gestures recorded with modern virtual reality motion controllers. Quite some research has been devoted to comparing and indexing time series. Especially, when the comparison should not be affected by time warping, the ubiquitous Dynamic

Kevin J Liang, Chunyuan Li, Guoyin Wang, Lawrence Carin

Generative Adversarial Networks (GANs) have proven to be a powerful framework for learning to draw samples from complex distributions. However, GANs are also notoriously difficult to train, with mode collapse and oscillations a common problem. We hypothesize that this is at least in part due to the evolution of the generator distribution and the catastrophic

Chi Nhan Duong, Khoa Luu, Kha Gia Quach, Nghia Nguyen

This paper presents a novel approach to synthesize automatically age-progressed facial images in video sequences using Deep Reinforcement Learning. The proposed method models facial structures and the longitudinal face-aging process of given subjects coherently across video frames. The approach is optimized using a long-term reward, Reinforcement Learning fu

Ravi Kashikar, Bramhachari Khamari, B. R. K. Nanda

Perovskite structure is one of the five symmetry families suitable for exhibiting topological insulator phase. However, none of the halides and oxides stabilizing in this structure exhibit the same. Through density functional calculations on cubic perovskites (CsSnX$_3$ ; X = Cl, Br, and I), we predict a band insulator -- Dirac semimetal -- topological insul

Chi Nhan Duong, Kha Gia Quach, Ibsa Jalata, Ngan Le

Deep neural networks have been widely used in numerous computer vision applications, particularly in face recognition. However, deploying deep neural network face recognition on mobile devices has recently become a trend but still limited since most high-accuracy deep models are both time and GPU consumption in the inference stage. Therefore, developing a li

Suproteem K. Sarkar, Kojin Oshiba, Daniel Giebisch, Yaron Singer

Algorithms are increasingly common components of high-impact decision-making, and a growing body of literature on adversarial examples in laboratory settings indicates that standard machine learning models are not robust. This suggests that real-world systems are also susceptible to manipulation or misclassification, which especially poses a challenge to mac

Wen-Chin Huang, Yi-Chiao Wu, Hsin-Te Hwang, Patrick Lumban Tobing

This paper presents a refinement framework of WaveNet vocoders for variational autoencoder (VAE) based voice conversion (VC), which reduces the quality distortion caused by the mismatch between the training data and testing data. Conventional WaveNet vocoders are trained with natural acoustic features but conditioned on the converted features in the conversi

Alister Burr, Manijeh Bashar, Dick Maryopi

In this paper we discuss the requirements for a radio access network architecture for ultra-dense networks for "smart city" applications, and show that coordination is required between access points to overcome the effects of interference. We propose a new paradigm, Fog Massive MIMO, based on a combination of the "cell-free" massive MIMO concept and the Fog

Jörg P. Bachmann, Johann-Christoph Freytag

Dynamic time warping ($\texttt{DTW}$) is one of the most used distance functions to compare time series, e.$\,$g. in nearest neighbor classifiers. Yet, fast state of the art algorithms only compare 1-dimensional time series efficiently. One of these state of the art algorithms uses a lower bound ($\texttt{LB}_\texttt{Keogh}$) introduced by E. Keogh to prune

Graham S. Kerr, Mats Carlsson, Joel C. Allred, Peter R. Young

The Interface Region Imaging Spectrograph (IRIS) routinely observes the Si IV resonance lines. When analyzing observations of these lines it has typically been assumed they form under optically thin conditions. This is likely valid for the quiescent Sun, but this assumption has also been applied to the more extreme flaring scenario. We used 36 electron beam

Yao Lu, Hau-tieng Wu, John Malik

Purpose: Biomedical sensors often exhibit cardiogenic artifacts which, while distorting the signal of interest, carry useful hemodynamic information. We propose an algorithm to remove and extract hemodynamic information from these cardiogenic artifacts. Methods: We apply a nonlinear time-frequency analysis technique, the de-shape synchrosqueezing transform (

Han Yu

In this paper, we study a problem posed by Furstenberg on intersections between $\times 2, \times 3$ invariant sets. We present here a direct geometrical counting argument to revisit a theorem of Wu and Shmerkin. This argument can be used to obtain further improvements. For example, we show that if $A_2,A_3\subset [0,1]$ are closed and $\times 2, \times 3$ i

Luis F. Campos, Mark E. Glickman, Kristen B. Hunter

One of the most significant barriers to medication treatment is patients' non-adherence to a prescribed medication regimen. The extent of the impact of poor adherence on resulting health measures is often unknown, and typical analyses ignore the time-varying nature of adherence. This paper develops a modeling framework for longitudinally recorded health meas

Yongchao Rao, Zhaoqin Chu, Xiao Gu, Xiangmei Duan

Designing an efficient membrane for He purification is quite crucial in scientific and industrial applications. Ultrathin membranes with intrinsic pores are highly desirable for gas purification because of their controllable aperture and homogeneous hole distribution. Based on the first-principles density function theory and molecular dynamics simulations, w

Xin Xu, Luofu Liu, Hongya Geng, Jianjun Wang

The performance of graphene oxide(GO)-based materials strongly depends on the lateral size and size distribution of GO nanosheets. Various methods are employed to prepare GO nanosheets with a narrow size distribution. One of the promising method was proposed recently by directionally freezing of a GO aqueous dispersion at a controlled growth rate of the free

Noam Bernstein, Bishal Bhattarai, Gábor Csányi, David A. Drabold

Amorphous materials are coming within reach of realistic computer simulations, but new approaches are needed to fully understand their intricate atomic structures. Here, we show how machine-learning (ML)-based techniques can give new, quantitative chemical insight into the atomic-scale structure of amorphous silicon (a-Si). Based on a similarity function ("k

Tom Bannink, Jop Briët, Harry Buhrman, Farrokh Labib

We bound separations between the entangled and classical values for several classes of nonlocal $t$-player games. Our motivating question is whether there is a family of $t$-player XOR games for which the entangled bias is $1$ but for which the classical bias goes down to $0$, for fixed $t$. Answering this question would have important consequences in the st

Pavel Solovev, Vladimir Aliev, Pavel Ostyakov, Gleb Sterkin

Representation learning becomes especially important for complex systems with multimodal data sources such as cameras or sensors. Recent advances in reinforcement learning and optimal control make it possible to design control algorithms on these latent representations, but the field still lacks a large-scale standard dataset for unified comparison. In this

Carlos M. Correia

Geared by the increasing need for enhanced performance, both optical and computational, new dynamic control laws have been researched in recent years for next generation adaptive optics systems on current 10 m-class and extremely large telescopes up to 40 m. We provide an overview of these developments and point out prospects to making such controllers drive

L. Capogna, V. Granata, B. Ouladdiaf, J. A. Rodriguez-Velamazan

We have investigated the metamagnetic-like transition in the triple layer ruthenate Sr4Ru3O10 by means of neutron diffraction from single crystals. The magnetic structure of the compound appears to be determined in a complex way by the two substructures of inequivalent ruthenium ions. At Tc=105K the system has a sharp transition into a ferromagnetic state al

Nikhil Krishnaswamy, Scott Friedman, James Pustejovsky

Many modern machine learning approaches require vast amounts of training data to learn new concepts; conversely, human learning often requires few examples--sometimes only one--from which the learner can abstract structural concepts. We present a novel approach to introducing new spatial structures to an AI agent, combining deep learning over qualitative spa

Kai-Xing Lu, Yinghe Zhao, Jin-Ming Bai, Xu-Liang Fan

We selected an active galactic nuclei (AGN) sample ($0 < z \le 0.35$) from Sloan Digital Sky Survey Data Release 7, and measured the broad- (${\rm H\alpha^{b}/H\beta^{b}}$) and narrow-line Balmer decrements (${\rm H\alpha^{n}/H\beta^{n}}$) of 554 selected AGNs. We found that the distributions of Balmer decrements can be fitted by a Gaussian function and give

M. S. Rosito, P. B. Tissera, S. E. Pedrosa, Y. Rosas-Guevara

Despite the insights gained in the last few years, our knowledge about the formation and evolution scenario for the spheroid-dominated galaxies is still incomplete. New and more powerful cosmological simulations have been developed that together with more precise observations open the possibility of more detailed study of the formation of early-type galaxies

P. Bevington, R. Gartman, W. Chalupczak

Imaging of structural defects in a material can be realized with a radio-frequency atomic magnetometer by monitoring the material's response to a radio-frequency excitation field. We demonstrate two measurement configurations that enable the increase of the amplitude and phase contrast in images that represent a structural defect in highly electrically condu

Lluís Masanes, Thomas D. Galley, Markus P. Müller

Understanding the core content of quantum mechanics requires us to disentangle the hidden logical relationships between the postulates of this theory. Here we show that the mathematical structure of quantum measurements, the formula for assigning outcome probabilities (Born's rule) and the post-measurement state-update rule, can be deduced from the other qua

Matteo Frigo, Thorsten Naab, Michaela Hirschmann, Ena Choi

We present a series of 20 cosmological zoom simulations of the formation of massive galaxies with and without a model for AGN feedback. Differences in stellar population and kinematic properties are evaluated by constructing mock integral field unit (IFU) maps. The impact of the AGN is weak at high redshift when all systems are mostly fast-rotating and disc-

E. A. Golovastova

Consider the reliability problem in a system with two different devices, which can break down.

Adam Dor-On, Christopher Linden

In this paper we show that every non-cycle finite transitive directed graph has a Cuntz-Krieger family whose WOT-closed algebra is $B(\mathcal{H})$. This is accomplished through a new construction that reduces this problem to in-degree $2$-regular graphs, which is then treated by applying the periodic Road Coloring Theorem of B\'eal and Perrin. As a conseque

Shiyao Wang, Hongchao Lu, Zhidong Deng

Object detection in videos has drawn increasing attention since it is more practical in real scenarios. Most of the deep learning methods use CNNs to process each decoded frame in a video stream individually. However, the free of charge yet valuable motion information already embedded in the video compression format is usually overlooked. In this paper, we p

Vasyl Gorkavyy, Raisa Posylaieva

The optimality of the integral inequality $\int\limits_\gamma\sqrt{k_1^2+k_2^2+k_3^2}ds>2\pi$ for closed curves with non-vanishing curvatures in $\mathbb R^4$ is discussed. We prove that an arbitrary closed curve of constant positive curvatures in $\mathbb R^4$ satisfies the inequality $\int\limits_\gamma\sqrt{k_1^2+k_2^2+k_3^2}ds \geq 2\sqrt{5}\pi$.

Y. R. Cochetti, C. Arcos, S. Kanaan, A. Meilland

Be stars are rapid rotators surrounded by a gaseous disk envelope whose origin is still under debate. This envelope is responsible for observed emission lines and large infrared excess. To progress in the understanding of the physical processes involved in the disk formation, we estimate the disk parameters for a sample of Be stars and search for correlation

Christopher Lutsko

We prove a theorem describing the limiting fine-scale statistics of orbits of a point in hyperbolic space under the action of a discrete subgroup. Similar results have been proved only in the lattice case, with two recent infinite-volume exceptions by Zhang for Apollonian circle packings and certain Schottky groups. Our results hold for general Zariski dense

Li Chen, Hailun Ding, Qi Li, Zhuo Li

Understanding the internal representations of deep neural networks (DNNs) is crucal to explain their behavior. The interpretation of individual units, which are neurons in MLPs or convolution kernels in convolutional networks, has been paid much attention given their fundamental role. However, recent research (Morcos et al. 2018) presented a counterintuitive

Jonathan Bennett, Neal Bez, Stefan Buschenhenke, Michael G. Cowling

We prove a nonlinear variant of the general Brascamp-Lieb inequality. Instances of this inequality are quite prevalent in analysis, and we illustrate this with substantial applications in harmonic analysis and partial differential equations. Our proof consists of running an efficient, or "tight", induction on scales argument, which uses the existence of gaus

Idan Kligvasser, Tomer Michaeli

Deep net architectures have constantly evolved over the past few years, leading to significant advancements in a wide array of computer vision tasks. However, besides high accuracy, many applications also require a low computational load and limited memory footprint. To date, efficiency has typically been achieved either by architectural choices at the macro