arXiv papers from September 2018

Jian-Ke Sun, Zdravko Kochovski, Wei-Yi Zhang, Holm Kirmse

The capability to synthesize a broad spectrum of metal clusters (MCs) with their size controllable in a subnanometer scale presents an enticing prospect for exploring nanosize-dependent properties. Here we report an innovative design of a capping agent from a polytriazolium poly(ionic liquid) (PIL) in a vesicular form in solution that allows for crafting a v

Akihisa Koga, Hiroyuki Tomishige, Joji Nasu

We study ground state properties in the bilayer Kitaev model by means of the dimer expansion. The existence of parity symmetries in the system reduces the computational cost significantly. This allows us to expand the ground state energy and interlayer spin-spin correlation up to 30th order in the interdimer Kitaev coupling. The numerical calculations clarif

K. A. Bugaev, A. I. Ivanytskyi, V. V. Sagun, B. E. Grinyuk

In this work we discuss a novel approach to model the hadronic and nuclear matter equations of state using the induced surface tension concept. Since the obtained equations of state, classical and quantum, are among the most successful ones in describing the properties of low density phases of strongly interacting matter, they set strong restrictions on the

Patrick E. Lancaster, Joshua R. Smith, Siddhartha S. Srinivasa

We describe a single fingertip-mounted sensing system for robot manipulation that provides proximity (pre-touch), contact detection (touch), and force sensing (post-touch). The sensor system consists of optical time-of-flight range measurement modules covered in a clear elastomer. Because the elastomer is clear, the sensor can detect and range nearby objects

Maja Krivokuća, Maxim Koroteev, Philip A. Chou

Compression of point clouds has so far been confined to coding the positions of a discrete set of points in space and the attributes of those discrete points. We introduce an alternative approach based on volumetric functions, which are functions defined not just on a finite set of points, but throughout space. As in regression analysis, volumetric functions

Ofir Gorodetsky

A classical problem in number theory is showing that the mean value of an arithmetic function is asymptotic to its mean value over a short interval or over an arithmetic progression, with the interval as short as possible or the modulus as large as possible. We study this problem in the function field setting, and prove for a wide class of arithmetic functio

Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn

Reinforcement learning and planning methods require an objective or reward function that encodes the desired behavior. Yet, in practice, there is a wide range of scenarios where an objective is difficult to provide programmatically, such as tasks with visual observations involving unknown object positions or deformable objects. In these cases, prior methods

Srinivasan Arunachalam, Sourav Chakraborty, Troy Lee, Manaswi Paraashar

We present two new results about exact learning by quantum computers. First, we show how to exactly learn a $k$-Fourier-sparse $n$-bit Boolean function from $O(k^{1.5}(\log k)^2)$ uniform quantum examples for that function. This improves over the bound of $\widetilde{\Theta}(kn)$ uniformly random \emph{classical} examples (Haviv and Regev, CCC'15). Additiona

Alexandru B. Georgescu, Oleg E. Peil, Ankit Disa, Antoine Georges

In complex oxide materials, changes in electronic properties are often associated with changes in crystal structure, raising the question of the relative roles of the electronic and lattice effects in driving the metal-insulator transition. This paper presents a combined theoretical and experimental analysis of the dependence of the metal-insulator transitio

Alessandro Dani, Karoline Täuber, Weiyi Zhang, Helmut Schlaad

An imidazolium-based poly(ionic liquid) is covalently cross-linked via UV light-induced thiolene (click) chemistry to yield a stable porous polyelectrolyte membrane with gradients of crosslink density and pore size distribution along its cross-section.

Cristian E. Rusu, Cameron A. Lemon

Data mining through large, multi-band ground-based surveys and the recent availability of source catalogues from the {\it Gaia} space mission has led to a surge in the number of known gravitationally lensed quasars, including some unusual systems. One of these newly discovered systems is GraL~J181730853+272940139. This system was reported in Delchambre et al

Timothy Burton Warrington

Ciliopathies are a class of human diseases marked by dysfunction of the cellular organelle, cilia. While many of the molecular components that make up cilia have been identified and studied, comparatively little is understood about the transcriptional regulation of genes encoding these components. The conserved transcription factor Regulatory Factor X (RFX)/

Elena G. Ferreiro

Quarkonium has long been proposed as one of the golden probes to identify the phase transition from confined hadronic matter to the deconfined quark-gluon plasma in heavy-ion collisions. Since then, we have achieved a better understanding, not only about the propagation of quarkonium in-medium, but also about its production. Recent theoretical developments i

Siu-Hung Ng, Xingting Wang

We prove that a Hopf algebra of prime dimension $p$ over an algebraically closed field, whose characteristic is equal to $p$, is either a group algebra or a restricted universal enveloping algebra. Moreover, we show that any Hopf algebra of prime dimension $p$ over a field of characteristic $q>0$ is commutative and cocommutative when $q=2$ or $p<4q$. This pr

Riddhish Bhalodia, Anupama Goparaju, Tim Sodergren, Alan Morris

Left atrium shape has been shown to be an independent predictor of recurrence after atrial fibrillation (AF) ablation. Shape-based representation is imperative to such an estimation process, where correspondence-based representation offers the most flexibility and ease-of-computation for population-level shape statistics. Nonetheless, population-level shape

Jiang Gong, Huijuan Lin, Konrad Grygiel, Jiayin Yuan

Sustainable development and the recent fast growing global demands for energy and functional chemicals urgently call for effective methods for CO2 remediation and efficient metal-free catalysts for selective oxidation of aromatic alcohol. Herein, a unique main-chain poly(ionic liquid) (PIL) is employed as the precursor to prepare nitrogen doped micro and mes

Tao Wang, Toma Toncian, Mingsheng Wei, Alexey Arefiev

A solid density target irradiated by a high-intensity laser pulse can become relativistically transparent, which then allows it to sustain an extremely strong laser-driven longitudinal electron current. The current generates a filament with a slowly-varying MT-level azimuthal magnetic field that has been shown to prompt efficient emission of multi-MeV photon

C. D. Pemmaraju

An atomic-orbital basis set framework is presented for carrying out velocity- gauge real-time time-dependent density functional theory (TDDFT) simulations in periodic systems employing range-separated hybrid functionals. Linear optical response obtained from real-time propagation of the time-dependent Kohn-Sham equations including nonlocal exchange is consid

Yujie Xing, Raquel Fernández

Stylistic variation is critical to render the utterances generated by conversational agents natural and engaging. In this paper, we focus on sequence-to-sequence models for open-domain dialogue response generation and propose a new method to evaluate the extent to which such models are able to generate responses that reflect different personality traits.

Daniel McDuff, Roger Cheng, Ashish Kapoor

Machine learned models exhibit bias, often because the datasets used to train them are biased. This presents a serious problem for the deployment of such technology, as the resulting models might perform poorly on populations that are minorities within the training set and ultimately present higher risks to them. We propose to use high-fidelity computer simu

Kenneth T. Co, Luis Muñoz-González, Sixte de Maupeou, Emil C. Lupu

Deep Convolutional Networks (DCNs) have been shown to be vulnerable to adversarial examples---perturbed inputs specifically designed to produce intentional errors in the learning algorithms at test time. Existing input-agnostic adversarial perturbations exhibit interesting visual patterns that are currently unexplained. In this paper, we introduce a structur

Fabian Steiner, Gerhard Kramer

Protograph-based, off-the-shelf low-density parity-check (LDPC) codes are optimized for higher-order modulation and quantized sum-product decoders. As an example, for the recently proposed LDPC code from the upcoming IEEE 802.3ca standard for passive optical networks (PONs), an optimized mapping of the bit channels originating from bit-metric decoding to the

Francesca Tria, Vittorio Loreto, Vito D. P. Servedio

Zipf's, Heaps' and Taylor's laws are ubiquitous in many different systems where innovation processes are at play. Together, they represent a compelling set of stylized facts regarding the overall statistics, the innovation rate and the scaling of fluctuations for systems as diverse as written texts and cities, ecological systems and stock markets. Many model

Michalis K. Titsias, Sotirios Nikoloutsopoulos

We propose a probabilistic framework to directly insert prior knowledge in reinforcement learning (RL) algorithms by defining the behaviour policy as a Bayesian posterior distribution. Such a posterior combines task specific information with prior knowledge, thus allowing to achieve transfer learning across tasks. The resulting method is flexible and it can

Dimbinaina Ralaivaosaona, Matas Šileikis, Stephan Wagner

An additive functional of a rooted tree is a functional that can be calculated recursively as the sum of the values of the functional over the branches, plus a certain toll function. Janson recently proved a central limit theorem for additive functionals of conditioned Galton-Watson trees under the assumption that the toll function is local, i.e. only depend

Rodrigo Pérez-Dattari, Carlos Celemin, Javier Ruiz-del-Solar, Jens Kober

Deep Reinforcement Learning (DRL) has become a powerful strategy to solve complex decision making problems based on Deep Neural Networks (DNNs). However, it is highly data demanding, so unfeasible in physical systems for most applications. In this work, we approach an alternative Interactive Machine Learning (IML) strategy for training DNN policies based on

Y. A. Ageeva, O. A. Evseev, O. I. Melichev, V. A. Rubakov

We consider Genesis in the Horndeski theory as an alternative to or completion of the inflationary scenario. One of the options free of instabilities at all cosmological epochs is the one in which the early Genesis is naively plagued with strong coupling. We address this issue to see whether classical field theory description of the background evolution at t

Panagiotis Papadopoulos, Panagiotis Ilia, Michalis Polychronakis, Evangelos P. Markatos

The proliferation of web applications has essentially transformed modern browsers into small but powerful operating systems. Upon visiting a website, user devices run implicitly trusted script code, the execution of which is confined within the browser to prevent any interference with the user's system. Recent JavaScript APIs, however, provide advanced capab

Theo Johnson-Freyd, David Treumann

We compute the integral third homology of most of the sporadic finite simple groups and of their central extensions.

Longsheng Jiang, Yue Wang

Regret theory is a theory that describes human decision-making under risk. The key of obtaining a quantitative model of regret theory is to measure the preference in humans' mind when they choose among a set of options. Unlike physical quantities, measuring psychological preference is not procedure invariant, i.e. the readings alter when the methods change.

Priyanka Mandikal, Navaneet K L, R. Venkatesh Babu

We propose a mechanism to reconstruct part annotated 3D point clouds of objects given just a single input image. We demonstrate that jointly training for both reconstruction and segmentation leads to improved performance in both the tasks, when compared to training for each task individually. The key idea is to propagate information from each task so as to a

Lindah Kotut, Michael Horning, Derek Haqq, Shuo Niu

This paper compares the needs of groups and communities in outdoor settings, seeking to identify subtle but important differences in the ways that their needs can be supported. We first examine the questions of who uses technology in outdoor settings, what their technological uses and needs are, and what conflicts exist between different trail users regardin

Nathan F. Lepora, Martin Pearson, Luke Cramphorn

Here we propose and investigate a novel vibrissal tactile sensor - the TacWhisker array - based on modifying a 3D-printed optical cutaneous (fingertip) tactile sensor - the TacTip. Two versions are considered: a static TacWhisker array analogous to immotile tactile vibrissae (e.g. rodent microvibrissae) and a dynamic TacWhisker array analogous to motile tact

Gang Liu

This paper is the continuation of the previous two papers with the same title.

Benjamin B. McMillan

I consider the geometry of the general class of scalar 2nd-order differential equations with parabolic symbol, including non-linear and non-evolutionary parabolic equations. After defining the appropriate $G$-structure to model parabolic equations, I apply Cartan techniques to determine local geometric invariants (quantities invariant up to a generalized cha

Ciro Potena, Raghav Khanna, Juan Nieto, Roland Siegwart

The combination of aerial survey capabilities of Unmanned Aerial Vehicles with targeted intervention abilities of agricultural Unmanned Ground Vehicles can significantly improve the effectiveness of robotic systems applied to precision agriculture. In this context, building and updating a common map of the field is an essential but challenging task. The maps

Alan M. Lewis, Timothy C. Berkelbach

The $GW$ approximation is based on the neglect of vertex corrections, which appear in the exact self-energy and the exact polarizability. Here, we investigate the importance of vertex corrections in the polarizability only. We calculate the polarizability with equation-of-motion coupled-cluster theory with single and double excitations (EOM-CCSD), which rigo

Martin Farach-Colton, Meng Li, Meng-Tsung Tsai

Many classical algorithms are known for computing the convex hull of a set of $n$ point in $\mathbb{R}^2$ using $O(n)$ space. For large point sets, whose size exceeds the size of the working space, these algorithms cannot be directly used. The current best streaming algorithm for computing the convex hull is computationally expensive, because it needs to sol

Boyang Zhao, Jayakanth Ravichandran

Neuro-inspired computing architectures are one of the leading candidates to solve complex, large-scale associative learning problems. The two key building blocks for neuromorphic computing are the synapse and the neuron, which form the distributed computing and memory units. Solid state implementations of these units remain an active area of research. Specif

Vladimir Lifschitz, Patrick Lühne, Torsten Schaub

In a recent paper by Harrison et al., the concept of program completion is extended to a large class of programs in the input language of the ASP grounder gringo. We would like to automate the process of generating and simplifying completion formulas for programs in that language, because examining the output produced by this kind of software may help progra

Victor V. Zubkov

An equation describing the irreversible evolution of the local density of a continuous medium without involving any statistical hypotheses and assumptions is derived. The derivation is based on the smoothing of the microscopic dynamic characteristics of a many-body system, taking into account the retardation of the interactions between them. The resulting eq

Ruslan Ishkuvatov

The notion of generic reducibility was introduced by A.Rybalov in his CiE 2018 paper: a set A is generically reducible to set B if there exists a total computable function f that m-reduces A to B such that the f-preimage of every set that has density 0 has density 0. It may be considered as the ``generic version'' of the notion of m-reducibility. In this not

Yann-Meing Law, Alexandre Noll Marques, Jean-Christophe Nave

We propose a high-order FDTD scheme based on the correction function method (CFM) to treat interfaces with complex geometry without increasing the complexity of the numerical approach for constant coefficients. Correction functions are modeled by a system of PDEs based on Maxwell's equations with interface conditions. To be able to compute approximations of

Dawsen Hwang, Patrick Jaillet, Vahideh Manshadi

For online resource allocation problems, we propose a new demand arrival model where the sequence of arrivals contains both an adversarial component and a stochastic one. Our model requires no demand forecasting; however, due to the presence of the stochastic component, we can partially predict future demand as the sequence of arrivals unfolds. Under the pro

K. M. Taddei, L. Sanjeewa, J. W. Kolis, A. S. Sefat

The recent discoveries of proximate quantum spin-liquid compounds and their potential application in quantum computing informs the search for new candidate materials for quantum spin-ice and spin-liquid physics. While the majority of such work has centered on members of the pyrochlore family due to their inherently frustrated linked tetrahedral structure, th

Qinglin Zhang, Chris Benton, Daniela Inclezan

This paper presents a practical application of Answer Set Programming to the understanding of narratives about restaurants. While this task was investigated in depth by Erik Mueller, exceptional scenarios remained a serious challenge for his script-based story comprehension system. We present a methodology that remedies this issue by modeling characters in a

Andrei Constantin, Yang-Hui He, Andre Lukas

We derive an approximate analytic relation between the number of consistent heterotic Calabi-Yau compactifications of string theory with the exact charged matter content of the standard model of particle physics and the topological data of the internal manifold: the former scaling exponentially with the number of Kahler parameters. This is done by an estimat

Cristhiano Duarte, Samuraí Brito, Barbara Amaral, Rafael Chaves

Bell's theorem shows that local measurements on entangled states give rise to correlations incompatible with local hidden variable models. The degree of quantum nonlocality is not maximal though, as there are even more nonlocal theories beyond quantum theory still compatible with the nonsignalling principle. In spite of decades of research, we still have a v

Glenn Barnich, Fabrizio Del Monte

Lectures held at the 22nd "Saalburg" Summer School (2016)

Elena Mirela Babalic, Calin Iuliu Lazaroiu

We outline the geometric formulation of cosmological flows for FLRW models with scalar matter as well as certain aspects which arise in their study with methods originating from the geometric theory of dynamical systems. We briefly summarize certain results of numerical analysis which we carried out when the scalar manifold of the model is a hyperbolic surfa

Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato

While deep neural networks are a highly successful model class, their large memory footprint puts considerable strain on energy consumption, communication bandwidth, and storage requirements. Consequently, model size reduction has become an utmost goal in deep learning. A typical approach is to train a set of deterministic weights, while applying certain tec

Andres Romero-Wolf, P. W. Gorham, J. Nam, S. Hoover

These proceedings address a recent publication by the ANITA collaboration of four upward- pointing cosmic-ray-like events observed in the first flight of ANITA. Three of these events were consistent with stratospheric cosmic-ray air showers where the axis of propagation does not inter- sect the surface of the Earth. The fourth event was consistent with a pri

Ziyi Yang, Chenguang Zhu, Weizhu Chen

We propose a simple and robust non-parameterized approach for building sentence representations. Inspired by the Gram-Schmidt Process in geometric theory, we build an orthogonal basis of the subspace spanned by a word and its surrounding context in a sentence. We model the semantic meaning of a word in a sentence based on two aspects. One is its relatedness

Qi-Xin Yu, Xin-Heng Guo

A doubly heavy baryon can be regarded as composed of a heavy diquark and a light quark. In this picture, we study the masses of the doubly heavy diquarkes in the Bethe-Salpeter (BS) formalism first, which are then used as one of the inputs in studying the masses of the doubly heavy baryons in the quark-diquark model. We establish the BS equations for both th

Mark Bugden, Claudio Paganini

We study the $\Lambda \to 0$ behaviour of Schwarzschild-de Sitter spacetime and show, according to Geroch's notion of spacetime limits, that it converges to the Schwarzschild spacetime. We use an embedding into $AdS_3$ to illustrate and quantify this limiting behaviour. We use these quantitative observations to establish a hierarchy of validity between the E

Sergey Georgievich Merzlyakov, Sergey Victorovich Popenov

The study is made of the problem of multiple interpolation on an infinite nodes set by the sums of absolutely convergent series of exponentials whose exponents are from a given set. For entire function conditions on nodes and exponents are obtained that give solubility of the problem. A new approach is demonstrated that enable us, for the case of holomorphic

Huizi Mao, Taeyoung Kong, William J. Dally

Detecting objects in a video is a compute-intensive task. In this paper we propose CaTDet, a system to speedup object detection by leveraging the temporal correlation in video. CaTDet consists of two DNN models that form a cascaded detector, and an additional tracker to predict regions of interests based on historic detections. We also propose a new metric,

Dang-Zheng Liu, Dong Wang, Yanhui Wang

Products of $M$ i.i.d. random matrices of size $N \times N$ are related to classical limit theorems in probability theory ($N=1$ and large $M$), to Lyapunov exponents in dynamical systems (finite $N$ and large $M$), and to universality in random matrix theory (finite $M$ and large $N$). Under the two different limits of $M \to \infty$ and $N \to \infty$, the

S. D. Odintsov, V. K. Oikonomou, A. V. Timoshkin, Emmanuel N. Saridakis

We investigate the cosmological applications of fluids having an equation of state which is the analog to the one related to the isotropic deformation of crystalline solids, that is containing logarithmic terms of the energy density, allowing additionally for a bulk viscosity. We consider two classes of scenarios and we show that they are both capable of tri

Michael Bishop, Erick Aiken, Douglas Singleton

Current approaches to quantum gravity suggest there should be a modification of the standard quantum mechanical commutator, $[{\hat x} , {\hat p}] = i \hbar$. Typical modifications are phenomenological and designed to result in a minimal length scale. As a motivating principle for the modification of the position and momentum commutator, we assume the validi

Marc Casals, Adrian C. Ottewill, Niels Warburton

The spin-weighted spheroidal eigenvalues and eigenfunctions arise in the separation by variables of spin-field perturbations of Kerr black holes. We derive a large, real-frequency asymptotic expansion of the spin-weighted spheroidal eigenvalues and eigenfunctions to high order. This expansion corrects and extends existing results in the literature and we val

William Hanlon

Telescope Array (TA) has completed analysis of nearly nine years of data measuring the atmospheric depth of air shower maximum ($X_{\textrm{max}}$) utilizing the TA surface detector array and the Black Rock Mesa and Long Ridge fluorescence detector stations. By using both the surface array and the fluorescence detector, the geometry and arrival time of air s

Olga G. Novozhenova

We give a brief outline of biography, review 3 of his works on the use of confluent hypergeometric function for description asymmetric relaxation spectrum and provide an overview of the Soviet works of the past (20th) that are in tune with this topic.

Gauree Shanker, Ruchi Kaushik Sharma

The classification of Finsler spaces of constant curvature is an interesting and important topic of research in differential geometry. In this paper we obtain necessary and sufficient conditions for generalized Kropina space to be of constant flag curvature.

Saeed Najafi, Colin Cherry, Grzegorz Kondrak

Neural approaches to sequence labeling often use a Conditional Random Field (CRF) to model their output dependencies, while Recurrent Neural Networks (RNN) are used for the same purpose in other tasks. We set out to establish RNNs as an attractive alternative to CRFs for sequence labeling. To do so, we address one of the RNN's most prominent shortcomings, th

Alakabha Datta

An important prediction of the standard model is the universality of the gauge interactions of the three generation of charged leptons. Violation of this universality would be a clean evidence of new physics (NP) beyond the standard model. In recent times anomalies in measurements of certain $B$ decays indicate violation of lepton universality (LUV). I will

A. S. Ioselevich, N. S. Peshcherenko

Quasi-one-dimensional systems demonstrate Van Hove singularities in the density of states $\nu_F$ and the resistivity $\rho$, occurring when the Fermi level $E$ crosses a bottom $E_N$ of some subband of transverse quantization. We demonstrate that the character of smearing of the singularities crucially depends on the concentration of impurities. There is a

Xinbo Geng, Swati Gupta, Le Xie

Increasing penetration of highly variable components such as solar generation and electric vehicle charging loads pose significant challenges to keeping three-phase loads balanced in modern distribution systems. Failure to maintain balance across three phases would lead to asset deterioration and increasing delivery losses. Motivated by the real-world needs

Alexander Tong, David van Dijk, Jay S. Stanley, Matthew Amodio

While neural networks are powerful approximators used to classify or embed data into lower dimensional spaces, they are often regarded as black boxes with uninterpretable features. Here we propose Graph Spectral Regularization for making hidden layers more interpretable without significantly impacting performance on the primary task. Taking inspiration from

Sh. Khodabakhshi, M. Farhang, A. Shojai, M. S. Esmaeilian

de Sitter--G\"odel--de Sitter phase transition(dGd) is a possible geometrical phase transition in the very early universe. It induces fluctuations with possibly observable traces on matter and radiation fields. Here we present a simulation based on dGd to investigate possible perturbations which could be along with the standard inflationary fluctuations in t

Takeru Yokota, Kenichi Yoshida, Teiji Kunihiro

We demonstrate for the first time that a functional-renormalization-group aided density-functional theory (FRG-DFT) describes well the characteristic features of the excited states as well as the ground state of an interacting many-body system with infinite number of particles in a unified manner. The FRG-DFT is applied to a $(1+1)$-dimensional spinless nucl

Siddhartha Dhar Choudhury, Shashank Pandey

Neural network training process takes long time when the size of training data is huge, without the large set of training values the neural network is unable to learn features. This dilemma between time and size of data is often solved using fast GPUs, but we present a better solution for a subset of those problems. To reduce the time for training a regressi

Run-Qiu Yang, Cheng-Yong Zhang, Wen-Ming Li

We explore the properties of holographic entanglement of purification (EoP) for two disjoint strips in the Schwarzschild-AdS black brane and the Vaidya-AdS black brane spacetimes. For two given strips on the same boundary of Schwarzschild-AdS spacetime, there is an upper bound of the separation beyond which the holographic EoP will always vanish no matter ho

Jens O. Andersen, Prabal Adhikari, Patrick Kneschke

We use the Polyakov-loop extended two-flavor quark-meson model as a low-energy effective model for QCD to study 1) the possibility of inhomogeneous chiral condensates and its competition with a homogeneous pion condensate in the $\mu$--$\mu_I$ plane at $T=0$ and 2) the phase diagram in the $\mu_I$--$T$ plane. In the $\mu$--$\mu_I$ plane, we find that an inho

Yuri Imamura

The present paper establishes a discrete version of the result obtained by P. Carr and S. Nadtochiy (2011) for 1-dimensional diffusion processes. Our result is for Markov chains on $\mathbf{Z}^d$.

Phi Xuan Nguyen, Shafiq Joty

Most state-of-the-art neural machine translation systems, despite being different in architectural skeletons (e.g. recurrence, convolutional), share an indispensable feature: the Attention. However, most existing attention methods are token-based and ignore the importance of phrasal alignments, the key ingredient for the success of phrase-based statistical m

Norbert Bogya, Gábor P. Nagy

The aim of this paper is twofold: First we classify all abstract light dual multinets of order $6$ which have a unique line of length at least two. Then we classify the weak projective embeddings of these objects in projective planes over fields of characteristic zero. For the latter we present a computational algebraic method for the study of weak projectiv

Robert Max Williams, Roman V. Yampolskiy

Human vision is capable of performing many tasks not optimized for in its long evolution. Reading text and identifying artificial objects such as road signs are both tasks that mammalian brains never encountered in the wild but are very easy for us to perform. However, humans have discovered many very specific tricks that cause us to misjudge color, size, al

Mohammad J. Bereyhi, Alberto Beccari, Sergey A. Fedorov, Amir H. Ghadimi

Stressed nanomechanical resonators are known to have exceptionally high quality factors ($Q$) due to the dilution of intrinsic dissipation by stress. Typically, the amount of dissipation dilution and thus the resonator $Q$ is limited by the high mode curvature region near the clamps. Here we study the effect of clamp geometry on the $Q$ of nanobeams made of

G. Röpke

We investigate $\alpha$-like correlations in $^{20}$Ne. A quartet of nucleons (different spin/isospin) is moving in a mean field produced by the $^{16}$O core nucleus. Improving the Thomas-Fermi model (local density approach), a shell model is considered for the core nucleus. The effective potential of the $\alpha$-like quartet and the wave function for the

Tigran Ananyan, Melvin Hochster

In [2], the authors prove Stillman's conjecture in all characteristics and all degrees by showing that, independent of the algebraically closed field $K$ or the number of variables, $n$ forms of degree at most $d$ in a polynomial ring $R$ over $K$ are contained in a polynomial subalgebra of $R$ generated by a regular sequence consisting of at most ${}^\eta\!

Edgar Dobriban, Yue Sheng

Distributed statistical learning problems arise commonly when dealing with large datasets. In this setup, datasets are partitioned over machines, which compute locally, and communicate short messages. Communication is often the bottleneck. In this paper, we study one-step and iterative weighted parameter averaging in statistical linear models under data para

Christoph Breunig, Peter Haan

We consider the problem of regression with selectively observed covariates in a nonparametric framework. Our approach relies on instrumental variables that explain variation in the latent covariates but have no direct effect on selection. The regression function of interest is shown to be a weighted version of observed conditional expectation where the weigh

Georgia Benkart, Persi Diaconis, Martin W. Liebeck, Pham Huu Tiep

We analyze families of Markov chains that arise from decomposing tensor products of irreducible representations. This illuminates the Burnside-Brauer Theorem for building irreducible representations, the McKay Correspondence, and Pitman's 2M-X Theorem. The chains are explicitly diagonalizable, and we use the eigenvalues/eigenvectors to give sharp rates of co

Shi-Yang Shen, Ming-Wei Dai, Xue-Tao Zheng, Qi-Yao Sun

We use single homodyne detector to accomplish Continuous-Variable quantum key distribution(CV QKD) in a laboratory and urban environment free-space channel. This is based on Gaussian modulation with coherent-states in the polarization degree of freedom. We achieved a QKD distance at 460m, at the repetition rate of 10 kHz. We give the security of this protoco

Elena Ancona, Roman Ya. Kezerashvili, Gregory L. Matloff

We discuss a possibility to survey many Kuiper Belt Objects (KBO) with a single launch using a few smallscale spacecraft, each equipped with solar sails, which could be unfurled from a single interplanetary bus at the perihelion of that craft's solar orbit. Each small-scale spacecraft would carry a scientific payload and would be directed to intersect one or

Christian Kanzow, Daniel Steck

This paper deals with quasi-variational inequality problems (QVIs) in a generic Banach space setting. We provide a theoretical framework for the analysis of such problems which is based on two key properties: the pseudomonotonicity (in the sense of Brezis) of the variational operator and a Mosco-type continuity of the feasible set mapping. We show that these

Guillaume Baudart, Javier Burroni, Martin Hirzel, Louis Mandel

Stan is a probabilistic programming language that is popular in the statistics community, with a high-level syntax for expressing probabilistic models. Stan differs by nature from generative probabilistic programming languages like Church, Anglican, or Pyro. This paper presents a comprehensive compilation scheme to compile any Stan model to a generative lang

C. R. Argüelles, A. Krut, J. A. Rueda, R. Ruffini

We have recently introduced in paper I an extension of the Ruffini-Arg\"uelles-Rueda (RAR) model for the distribution of DM in galaxies, by including for escape of particle effects. Being built upon self-gravitating fermions at finite temperatures, the RAR solutions develop a characteristic \textit{dense quantum core-diluted halo} morphology which, for fermi

Kevin Conley, Neha Nayyar, Tuomas P. Rossi, Mikael Kuisma

We study the plasmonic properties of arrays of atomic chains which comprise noble (Cu, Ag, and Au) and transition (Pd, Pt) metal atoms using time-dependent density-functional theory. We show that the response to the electromagnetic radiation is related to both physics, the geometry-dependent confinement of sp-valence electrons, and chemistry, the energy posi

Ido Zachevsky, Yehoshua Y. Zeevi

The Fourier magnitude has been studied extensively, but less effort has been devoted to the Fourier phase, despite its well-established importance in image representation. Global phase was shown to be more important for image representation than the magnitude, whereas local phase, exhibited in Gabor filters, has been used for analysis purposes in detecting i

Laurent Gizon, Damien Fournier, Dan Yang, Aaron C. Birch

Helioseismic holography is an imaging technique used to study heterogeneities and flows in the solar interior from observations of solar oscillations at the surface. Holograms contain noise due to the stochastic nature of solar oscillations. We provide a theoretical framework for modeling signal and noise in Porter-Bojarski helioseismic holography. The wave

Raphael Hiesgen, Dominik Charousset, Thomas C. Schmidt

The message-driven nature of actors lays a foundation for developing scalable and distributed software. While the actor itself has been thoroughly modeled, the message passing layer lacks a common definition. Properties and guarantees of message exchange often shift with implementations and contexts. This adds complexity to the development process, limits po

Martin Friesen, Peng Jin, Barbara Rüdiger

Let X be a multi-type continuous-state branching process with immigration (CBI process) on state space $\mathbb{R}^d$. Denote by $g_t$, $t \geq 0$, the law of $X_{t}$. We provide sufficient conditions under which $g_t$ has, for each $t > 0$, a density with respect to the Lebesgue measure. Such density has, by construction, some anisotropic Besov regularity.

Atanu Guha, P. S. Bhupal Dev, Prasanta Kumar Das

We derive model-independent astrophysical constraints on leptophilic dark matter (DM), considering its thermal production in a supernova core and taking into account core temperature fluctuations within the framework of $q$-deformed Tsallis statistics. In an effective field theory approach, where the DM fermions interact with the Standard Model via dimension

Aditya A. Shastri, Kapil Ahuja, Milind B. Ratnaparkhe, Aditya Shah

We develop a Vector Quantized Spectral Clustering (VQSC) algorithm that is a combination of Spectral Clustering (SC) and Vector Quantization (VQ) sampling for grouping Soybean genomes. The inspiration here is to use SC for its accuracy and VQ to make the algorithm computationally cheap (the complexity of SC is cubic in-terms of the input size). Although the

Lorenzo Iorio

We study a general relativistic gravitomagnetic 3-body effect induced by the spin angular momentum ${\boldsymbol S}_\textrm{X}$ of a rotating mass $M_\textrm{X}$ orbited at distance $r_\textrm{X}$ by a local gravitationally bound restricted two-body system $\mathcal{S}$ of size $r\ll r_\textrm{X}$ consisting of a test particle revolving around a massive body

Roman Khudorozhkov, Dmitry Podvyaznikov

In this work we apply variations of ResNet architecture to the task of atrial fibrillation classification. Variations differ in number of filter after first convolution, ResNet block layout, number of filters in block convolutions and number of ResNet blocks between downsampling operations. We have found a range of model size in which models with quite diffe

Md. Kamrul Hasan, Fakrul Islam Tushar

Left ventricular non-compaction (LVNC) is a rare cardiomyopathy (CMP) that should be considered as a possible diagnosis because of its potential complications which are heart failure, ventricular arrhythmias, and embolic events. For analysis cardiac functionality, extracting information from the Left ventricular (LV) is already a broad field of Medical Imagi

A. Morozov

We demonstrate in some detail how Macdonald polynomials emerge from the recently introduced 3-Schur functions when the plane-partition vector time-variables are projected onto the ordinary scalar times under non-vanishing angles, which depend on $q$ and $t$. We also explain how the cut-and-join operators smoothly interpolate between different cases. Most of