April 2019 arXiv papers — page 52

Roméo Juge, Soong-Geun Je, Dayane de Souza Chaves, Liliana D. Buda-Prejbeanu

Magnetic skyrmions are chiral spin textures that hold great promise as nanoscale information carriers. Since their first observation at room temperature, progress has been made in their current-induced manipulation, with fast motion reported in stray-field-coupled multilayers. However, the complex spin textures with hybrid chiralities and large power dissipa

Aditya Kar, Taniya Mandal, Arunabha Saha

We find the membrane equations which describe the leading order in $1/D$ dynamics of black holes in the $D\rightarrow\infty$ limit for the most general four-derivative theory of gravity in the presence of a cosmological constant. We work up to linear order in the parameter determining the strength of the four-derivative corrections to the gravity action and

Sheng-Juan Jiang, S. Sakai, Wei-Hong Liang, E. Oset

We perform a theoretical study of the $χ_{cJ} \to ϕK^* \bar K \to ϕKπ\bar K$ reaction taking into account the $K^* \bar K$ final state interaction, which in the chiral unitary approach is responsible, together with its coupled channels, for the formation of the low lying axial vector mesons, in this case the $h_1(1380)$ given the selection of quantum numbers

Benjamin Hennion

We prove that the tangent complex of K-theory, in terms of (abelian) deformation problems over a characteristic 0 field k, is cyclic homology (over k). This equivalence is compatible with the $\lambda$-operations. In particular, the relative algebraic K-theory functor fully determines the absolute cyclic homology over any field k of characteristic 0. We also

K. Azizi, Y. Sarac, H. Sundu

The recent deviations of the experimental data on some parameters of the tree-level semileptonic $B$ and $B_c$ mesons decays from the standard model (SM) predictions indicate considerable violations of the lepton flavor universality, and as a result possible new physics (NP) effects. To better understand the possible NP effects it is necessary to study deepl

Bas Hensen, Wister Wei Huang, Chih-Hwan Yang, Kok Wai Chan

Single nuclear spins in the solid state have long been envisaged as a platform for quantum computing, due to their long coherence times and excellent controllability. Measurements can be performed via localised electrons, for example those in single atom dopants or crystal defects. However, establishing long-range interactions between multiple dopants or def

Hiroshi Sato

In this paper, we introduce the notion of toric special weak Fano manifolds, which have only special primitive crepant contractions. We study the structure of them, and in particular completely classify smooth toric special weak Fano 4-folds. As a result, we can confirm that almost every smooth toric special weak Fano 4-fold is a weakened Fano manifold, that

W. Oliveira dos Santos, E. R. Bezerra de Mello, H. F. Mota

In this paper, we analyze the vacuum expectation values (VEVs) of the field squared and the energy-momentum tensor associated with a charged and massive scalar quantum field in a generalized $(D+1)$-dimensional anti-de Sitter space in the presence of a cosmic string, admitting a magnetic flux running along the string's core. In addition we admit that an

Leonardo Rundo, Changhee Han, Yudai Nagano, Jin Zhang

Prostate cancer is the most common malignant tumors in men but prostate Magnetic Resonance Imaging (MRI) analysis remains challenging. Besides whole prostate gland segmentation, the capability to differentiate between the blurry boundary of the Central Gland (CG) and Peripheral Zone (PZ) can lead to differential diagnosis, since tumor's frequency and sev

Boris Beranger, Simone A. Padoan, Scott A. Sisson

Estimation of extreme quantile regions, spaces in which future extreme events can occur with a given low probability, even beyond the range of the observed data, is an important task in the analysis of extremes. Existing methods to estimate such regions are available, but do not provide any measures of estimation uncertainty. We develop univariate and bivari

Sujay Khandagale, Han Xiao, Rohit Babbar

Extreme multi-label classification (XMC) refers to supervised multi-label learning involving hundreds of thousand or even millions of labels. In this paper, we develop a suite of algorithms, called Bonsai, which generalizes the notion of label representation in XMC, and partitions the labels in the representation space to learn shallow trees. We show three c

Marcello Carioni, Andrea Marchese, Annalisa Massaccesi, Alessandra Pluda

In this note we introduce a new model for the mailing problem in branched transportation in order to allow the cost functional to take into account the orientation of the moving particles. This gives an effective answer to [Problem 15.9] of the book "Optimal transportation networks" by Bernot, Caselles, and Morel. Moreover we define a convex relaxati

Daniel Gehrig, Antonio Loquercio, Konstantinos G. Derpanis, Davide Scaramuzza

Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events". They have appealing advantages over frame-based cameras for computer vision, including high temporal resolution, high dynamic range, and no motion blur. Due to the sparse, non-uniform spatiotemporal layout of the event signal, p

Jean-Paul Blaizot, Naoto Tanji

We use an expansion in angular mode functions in order to solve the Boltzmann equation for a gluon plasma undergoing longitudinal expansion. By comparing with the exact solution obtained numerically by other means we show that the expansion in mode functions converges rapidly for all cases of practical interest, and represents a substantial gain in numerical

Qing Li, Shaoyang Chen, Cheng Wang, Xin Li

We present a novel deep convolutional network pipeline, LO-Net, for real-time lidar odometry estimation. Unlike most existing lidar odometry (LO) estimations that go through individually designed feature selection, feature matching, and pose estimation pipeline, LO-Net can be trained in an end-to-end manner. With a new mask-weighted geometric constraint loss

Emmanuel Cabanillas

In this article, we study the quotients of numerical semigroups, generated by two coprime positive numbers, named (a,b) over d. We give formulae for the usual invariants of these semigroups, expressed in terms of continued fraction expansions and Ostrowski-like numeration of some rationals, simply related to entries a, b, d. So, we obtain quadratic complexit

S. Goldstein, J. L. Lebowitz, E. R. Speer

We obtain the exact solution of the facilitated totally asymmetric simple exclusion process (F-TASEP) in 1D. The model is closely related to the conserved lattice gas (CLG) model and to some cellular automaton traffic models. In the F-TASEP a particle at site $j$ in $\mathbb{Z}$ jumps, at integer times, to site $j+1$, provided site $j-1$ is occupied and site

Paraskevas Parisiades, Federico Cova, Gaston Garbarino

Melting experiments require rapid data acquisition due to instabilities of the molten sample and optical drifting due to the high required laser power. In this work, the melting curve of zirconium has been determined for the first time up to 80 GPa and 4000 K using in-situ fast x-ray diffraction (XRD) in a laser-heated diamond anvil cell (LH-DAC). The main m

Charlotte Dion, Sarah Lemler

We consider a 1-dimensional diffusion process X with jumps. The particularity of this model relies in the jumps which are driven by a multidimensional Hawkes process denoted N. This article is dedicated to the study of a nonparametric estimator of the drift coefficient of this original process. We construct estimators based on discrete observations of the pr

Yuji Igarashi, Katsumi Itoh, Tim R. Morris

We show that the Quantum Master Equation and the Wilsonian renormalization group (RG) flow equation can be combined such that for the continuum effective action, quantum BRST invariance is not broken by the presence of an effective ultraviolet cutoff $Λ$, despite the fact that the structure demands quantum corrections that naively break the gauge invariance,

Paweł Sawicki, Jarosław Pykacz, Paweł Bytner

An algorithm for finding all Berge equilibria in the sense of Zhukovskii in n-person 2-strategy games in pure and mixed strategies is given.

Yves Aubry, Elena Berardini, Fabien Herbaut, Marc Perret

We provide a theoretical study of Algebraic Geometry codes constructed from abelian surfaces defined over finite fields. We give a general bound on their minimum distance and we investigate how this estimation can be sharpened under the assumption that the abelian surface does not contain low genus curves. This approach naturally leads us to consider Weil re

Dongho Chae, Joerg Wolf

In this paper we study the transport equation in $\mathbb{R}^n \times (0,T)$, $T >0$, \[ \partial _t f + v\cdot \nabla f = g, \quad f(\cdot ,0)= f_0 \quad \text{in}\quad \mathbb{R}^n \] in generalized Campanato spaces $\mathscr{L}^s_{ q(p, N)}(\mathbb{R}^n)$. The critical case is particularly interesting, and is applied to the local well-posedness problem in

Matan Harel, Frank Mousset, Wojciech Samotij

Suppose that $X$ is a bounded-degree polynomial with nonnegative coefficients on the $p$-biased discrete hypercube. Our main result gives sharp estimates on the logarithmic upper tail probability of $X$ whenever an associated extremal problem satisfies a certain entropic stability property. We apply this result to solve two long-standing open problems in pro

L. Derome, D. Maurin, P. Salati, M. Boudaud

AMS-02 on the International Space Station has been releasing data of unprecedented accuracy. This poses new challenges for their interpretation. We refine the methodology to get a statistically sound determination of the cosmic-ray propagation parameters. We inspect the numerical precision of the model calculation, nuclear cross-section uncertainties, and en

Xue Gong, Chong-Xing Yue, Yu-Chen Guo

Vector-like quarks (VLQs) are predicted in many new physics scenarios beyond the standard model (SM). We consider a search strategy for vector-like bottom quark (VLQ-$B$) at the LHC in a model independent fashion. Our analysis is based on single production of VLQ-$B$ with decaying to the $ Zb$ mode. The production cross sections and the signal significance $

Léonard Torossian, Aurélien Garivier, Victor Picheny

We propose and analyze StoROO, an algorithm for risk optimization on stochastic black-box functions derived from StoOO. Motivated by risk-averse decision making fields like agriculture, medicine, biology or finance, we do not focus on the mean payoff but on generic functionals of the return distribution. We provide a generic regret analysis of StoROO and ill

Stefan Hollands

We introduce a new approach to find the Tomita-Takesaki modular flow for multi-component regions in general chiral conformal field theory. Our method is based on locality and analyticity of primary fields as well as the so-called Kubo-Martin-Schwinger (KMS) condition. These features can be used to transform the problem to a Riemann-Hilbert problem on a cover

Xu-Guang Huang, Hidetoshi Taya

We study electron and positron pair production from the vacuum by a strong slow electric field superimposed by a weak fast electric field pointing in an arbitrary direction as a perturbation (the dynamically assisted Schwinger mechanism). An analytical formula for the production number is derived on the basis of the perturbation theory in the Furry picture.

Xiaoxue Shen, Liyang Gu, Adele Lu Jia

Community-based Question and Answering (CQA) platforms are nowadays enlightening over a billion people with crowdsourced knowledge. A key design issue in CQA platforms is how to find the potential answerers and to provide the askers timely and suitable answers, i.e., the so-called \textit{question routing} problem. State-of-art approaches often rely on extra

Ziv Aqua, M. S. Kim, Barak Dayan

We introduce a multi-step protocol for optical quantum state engineering that performs as deterministic "bright quantum scissors" (BQS), namely truncates an arbitrary input quantum state to have at least a certain number of photons. The protocol exploits single-photon pulses and is based on the effect of single-photon Raman interaction, which is implemented

Kurt Johansson

The two-time distribution gives the limiting joint distribution of the heights at two different times of a local 1D random growth model in the curved geometry. This distribution has been computed in a specific model but is expected to be universal in the KPZ universality class. Its marginals are the GUE Tracy-Widom distribution. In this paper we study two li

Tom Pelsmaeker, Wilker Aziz

Advances in variational inference enable parameterisation of probabilistic models by deep neural networks. This combines the statistical transparency of the probabilistic modelling framework with the representational power of deep learning. Yet, due to a problem known as posterior collapse, it is difficult to estimate such models in the context of language m

Kristen Kaasbjerg, Antti-Pekka Jauho

We study the spectral function and quasiparticle scattering in Li-decorated graphene (Li@graphene) with an atomistic $T$-matrix formalism and uncover adatom-induced spectral effects which shed light on experimentally observed angle-resolved photoemission spectroscopy (ARPES) features. From transport studies, alkali adatoms are known to introduce charged-impu

Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi

In object detection, keypoint-based approaches often suffer a large number of incorrect object bounding boxes, arguably due to the lack of an additional look into the cropped regions. This paper presents an efficient solution which explores the visual patterns within each cropped region with minimal costs. We build our framework upon a representative one-sta

Dongwen Liu, Zhicheng Wang

Inspired by the Gan-Gross-Prasad conjecture and the descent problem for classical groups, in this paper we study the descents of unipotent representations of unitary groups over finite fields. We give the first descents of unipotent representations explicitly, which are unipotent as well. Our results include both the Bessel case and Fourier-Jacobi case, whic

T. Emil Rivera-Thorsen, Håkon Dahle, John Chisholm, Michael K. Florian

During the epoch of reionisation, neutral gas in the early Universe was ionized by hard ultraviolet radiation emitted by young stars in the first galaxies. To do so, ionizing ultraviolet photons must escape from the host galaxy. We present Hubble Space Telescope observations of the gravitationally lensed galaxy PSZ1-ARC G311.6602-18.4624, revealing bright, m

Julio E. Perez-Carbajo, Salvador R. G. Balestra, Sofia Calero, Patrick J. Merkling

Water adsorption within zeolites of the Linde Type A (LTA) structure plays an important role in processes of water removal from solvents. For this purpose, knowing in which adsorption sites water is preferably found is of interest. In this paper, the distribution of water within LTA is investigated in several aluminum-substituted frameworks ranging from a Si

Xu-Guang Huang, Dmitri E. Kharzeev, Hidetoshi Taya

We show that the coherent axion field spontaneously decays by emitting axion particles via quantum tunneling if axion potential has more than one minimum. By employing the $\hbar$-expansion and mean field approximation, we develop a formalism to trace the real-time dynamics of the axion particle production including its backreaction to the coherent axion fie

Hamid Alemi Ardakani

A new derivation of the Bernoulli equation for water waves in three-dimensional rotating and translating coordinate systems is given. An alternative view on the Bateman-Luke variational principle is presented. The variational principle recovers the boundary value problem governing the motion of potential water waves in a container undergoing prescribed rigid

Daniele Binosi, Ralf-Arno Tripolt

We determine the gluon and ghost spectral functions along with the analytic structure of the associated propagators from numerical data describing gauge correlators at space-like momenta obtained by either solving the Dyson-Schwinger equations or through lattice simulations. Our novel reconstruction technique shows the expected branch cut for the gluon and t

Xin Jin, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang

Objects at different spatial positions in an image exhibit different scales. Adaptive receptive fields are expected to capture suitable ranges of context for accurate pixel level semantic prediction. Recently, atrous convolution with different dilation rates has been used to generate features of multi-scales through several branches which are then fused for

Thomas Hudson, Dennis Peters

In this paper we express the class of the structure sheaves of the closures of Deligne--Lusztig varieties as explicit double Grothendieck polynomials in the first Chern classes of appropriate line bundles on the ambient flag variety. This is achieved by viewing such closures as degeneracy loci of morphisms of vector bundles.

Poulami Dutta Roy, Jagannath Das, Sayan Kar

Quasi-normal modes (QNMs) of the massless scalar wave in $1+1$ dimensions are obtained for a symmetric, finite, triangular barrier potential. This problem is exactly solvable, with Airy functions involved in the solutions. Before obtaining the QNMs, we demonstrate how such a triangular barrier may arise in the context of scalar wave propagation in a tailor-m

Vladimir G. Tkachev

In this short survey we give a background and explain some recent developments in algebraic minimal cones and nonassociative algebras. A good deal of this paper is recollections of my collaboration with my teacher, PhD supervisor and a colleague, Vladimir Miklyukov on minimal surface theory that motivated the present research. This paper is dedicated to his

M. Kachelriess, D. V. Semikoz

We review progress in high-energy cosmic ray physics focusing on recent experimental results and models developed for their interpretation. Emphasis is put on the propagation of charged cosmic rays, covering the whole range from $\sim (20-50)$ GV, i.e. the rigidity when solar modulations can be neglected, up to the highest energies observed. We discuss model

Daniel Koguciuk, Łukasz Chechliński, Tarek El-Gaaly

In this study, we present an analysis of model-based ensemble learning for 3D point-cloud object classification and detection. An ensemble of multiple model instances is known to outperform a single model instance, but there is little study of the topic of ensemble learning for 3D point clouds. First, an ensemble of multiple model instances trained on the sa

Tianshu Lyu, Fei Sun, Peng Jiang, Wenwu Ou

Network embedding has proved extremely useful in a variety of network analysis tasks such as node classification, link prediction, and network visualization. Almost all the existing network embedding methods learn to map the node IDs to their corresponding node embeddings. This design principle, however, hinders the existing methods from being applied in rea

Benjamin Doerr

In the first runtime analysis of an estimation-of-distribution algorithm (EDA) on the multi-modal jump function class, Hasenöhrl and Sutton (GECCO 2018) proved that the runtime of the compact genetic algorithm with suitable parameter choice on jump functions with high probability is at most polynomial (in the dimension) if the jump size is at most logarithmi

Mustafa Korkmaz

We prove that the mapping class group of a closed connected orientable surface of genus at least eight is generated by three involutions.

Théophile Griveau-Billion, Ben Calderhead

We propose a heterogeneous simultaneous graphical dynamic linear model (H-SGDLM), which extends the standard SGDLM framework to incorporate a heterogeneous autoregressive realised volatility (HAR-RV) model. This novel approach creates a GPU-scalable multivariate volatility estimator, which decomposes multiple time series into economically-meaningful variable

Andreas Danzer, Thomas Griebel, Martin Bach, Klaus Dietmayer

For many automated driving functions, a highly accurate perception of the vehicle environment is a crucial prerequisite. Modern high-resolution radar sensors generate multiple radar targets per object, which makes these sensors particularly suitable for the 2D object detection task. This work presents an approach to detect 2D objects solely depending on spar

Ozan Çatal, Johannes Nauta, Tim Verbelen, Pieter Simoens

Learning to take actions based on observations is a core requirement for artificial agents to be able to be successful and robust at their task. Reinforcement Learning (RL) is a well-known technique for learning such policies. However, current RL algorithms often have to deal with reward shaping, have difficulties generalizing to other environments and are m

Giovanni Catino, Alberto Roncoroni, Luigi Vezzoni

We prove that under some assumptions on the mean curvature the set of umbilical points of an immersed surface in a $3$-dimensional space form has positive measure. In case of an immersed sphere our result can be seen as a generalization of the celebrated Hopf theorem.

Feiyang Chen, Ziqian Luo, Yanyan Xu, Dengfeng Ke

Sentiment analysis, mostly based on text, has been rapidly developing in the last decade and has attracted widespread attention in both academia and industry. However, the information in the real world usually comes from multiple modalities, such as audio and text. Therefore, in this paper, based on audio and text, we consider the task of multimodal sentimen

Vedran Sohinger

We study the derivation of the Gibbs measure for the nonlinear Schrödinger equation (NLS) from many-body quantum thermal states in the high-temperature limit. In this paper, we consider the nonlocal NLS with defocusing and unbounded $L^p$ interaction potentials on $\mathbb{T}^d$ for $d=1,2,3$. This extends the author's earlier joint work with Fröhlich, K

Yong Shi, Bo Li, Wen Long

There are various types of pyramid schemes which have inflicted or are inflicting losses on many people in the world. We propose a pyramid scheme model which has the principal characters of many pyramid schemes appeared in recent years: promising high returns, rewarding the participants recruiting the next generation of participants, and the organizer will t

Po-Chen Kuo, Neill Lambert, Adam Miranowicz, Hong-Bin Chen

Exceptional points, resulting from non-Hermitian degeneracies, have the potential to enhance the capabilities of quantum sensing. Thus, finding exceptional points in different quantum systems is vital for developing such future sensing devices. Taking advantage of the enhanced light-matter interactions in a confined volume on a metal nanoparticle surface, he

Ionel Popescu, Tushar Vaidya

We develop original models to study interacting agents in financial markets and in social networks. Within these models randomness is vital as a form of shock or news that decays with time. Agents learn from their observations and learning ability to interpret news or private information in time-varying networks. Under general assumption on the noise, a limi

Yuji Kanagawa, Tomoyuki Kaneko

In this paper, we propose Rogue-Gym, a simple and classic style roguelike game built for evaluating generalization in reinforcement learning (RL). Combined with the recent progress of deep neural networks, RL has successfully trained human-level agents without human knowledge in many games such as those for Atari 2600. However, it has been pointed out that a

Fabian Isensee, Paul F. Jäger, Simon A. A. Kohl, Jens Petersen

Biomedical imaging is a driver of scientific discovery and core component of medical care, currently stimulated by the field of deep learning. While semantic segmentation algorithms enable 3D image analysis and quantification in many applications, the design of respective specialised solutions is non-trivial and highly dependent on dataset properties and har

Jun Gao, Qingyi Huo, Chun-Hung Liu, Jie Ma

In this paper, we prove a tight minimum degree condition in general graphs for the existence of paths between two given endpoints, whose lengths form a long arithmetic progression with common difference one or two. This allows us to obtain a number of exact and optimal results on cycle lengths in graphs of given minimum degree, connectivity or chromatic numb

Cătălin Paşcu Moca, Chirla Razvan, Balázs Dóra, Gergely Zárand

While much is known about repulsive quantum impurity models, significantly less attention has been devoted to their attractive counterparts. This motivated us to study the attractive SU(N) Anderson impurity model. While for the repulsive case, the phase diagram features mild N dependence and the ground state is always a Fermi liquid, in the attractive case a

Dirk-Mathys Spangenberg, Erich Rohwer, Michael Brügmann, Thomas Feurer

We extend the time-domain ptychographic iterative engine to generalized spectral phase-only transfer functions. The modified algorithm, i$^2$PIE, is described and its robustness is demonstrated by different numeric simulations. The concept is experimentally verified by reconstruction of a complex supercontinuum pulse from an all normal dispersion fiber.

Sho Nakazono, Hiroyuki Uchiyama, Yasuhiro Fujiwara, Yasuhiro Nakamura

Concurrency control protocols are the key to scaling current DBMS performances. They efficiently interleave read and write operations in transactions, but occasionally they restrict concurrency by using coordination such as exclusive lockings. Although exclusive lockings ensure the correctness of DBMS, it incurs serious performance penalties on multi-core en

Jingwen He, Chao Dong, Yu Qiao

In image restoration tasks, like denoising and super resolution, continual modulation of restoration levels is of great importance for real-world applications, but has failed most of existing deep learning based image restoration methods. Learning from discrete and fixed restoration levels, deep models cannot be easily generalized to data of continuous and u

Hua Wei, Guanjie Zheng, Vikash Gayah, Zhenhui Li

Traffic signal control is an important and challenging real-world problem, which aims to minimize the travel time of vehicles by coordinating their movements at the road intersections. Current traffic signal control systems in use still rely heavily on oversimplified information and rule-based methods, although we now have richer data, more computing power a

Hui Li, Zili Chen

In this paper, we present some necessary and sufficient conditions for semi-compact operators being almost L-weakly compact (resp. almost M-weakly compact) and the converse. Mainly, we prove that if $X$ is a nonzero Banach space, then every semi-compact operator $T: X\rightarrow E$ is almost L-weakly compact if and only if the norm of $E$ is order continuous

Yan-Jiang Wang, Shuai Shao, Rui Xu, Werifeng Liu

Dictionary learning methods can be split into: i) class specific dictionary learning ii) class shared dictionary learning. The difference between the two categories is how to use discriminative information. With the first category, samples of different classes are mapped into different subspaces, which leads to some redundancy with the class specific base ve

Simone Farinelli, Hideyuki Takada

We apply Geometric Arbitrage Theory to obtain results in Mathematical Finance, which do not need stochastic differential geometry in their formulation. First, for a generic market dynamics given by a multidimensional It\^o's process we specify and prove the equivalence between (NFLVR) and expected utility maximization. As a by-product we provide a geometric

Tom Gur, Oded Lachish

A locally decodable code (LDC) C:{0,1}^k -> {0,1}^n is an error correcting code wherein individual bits of the message can be recovered by only querying a few bits of a noisy codeword. LDCs found a myriad of applications both in theory and in practice, ranging from probabilistically checkable proofs to distributed storage. However, despite nearly two decades

Y. Urata, K. Toma, K. Huang, K. Asada

We report the first detection of radio polarization of a GRB afterglow with the first intensive combined use of telescopes in the millimeter and submillimeter ranges for GRB171205A. The linear polarization degree in the millimeter band at the sub-percent level ($0.27 \pm 0.04\%$) is lower than those observed in late-time optical afterglows (weighted average

Hongsu Kim, Uicheol Jang, Yu Yi

Studying accretion phenomena is a window into understanding most heavenly bodies, from the birth of stars to Active galactic nuclei(AGN). We would adopt the effect of the radiation pressure which reduces accretion rates M on the accretion phenomena. Shakura-Sunyaev$\alpha$-disk model of disk accretion can be regarded as a good candidate theory of ADAF. Reduc

Kui Chen, Cheng Zhang, Da-jun Zhang

In this paper squared eigenfunction symmetry of the differential-difference modified Kadomtsev-Petviashvili (D$\Delta$mKP) hierarchy and its constraint are considered. Under the constraint, the Lax triplets of the D$\Delta$mKP hierarchy, together with their adjoint forms, give rise to the positive relativistic Toda (R-Toda) hierarchy. An invertible transform

Sudipta Hensh, Ahmadjon Abdujabbarov, Jan Schee, Zdeněk Stuchlík

We study the optical properties of the Kehagias-Sfetsos (KS) compact objects, characterized by the "Ho\v{r}ava" parameter $\omega_{_{KS}}$, in the presence of plasma, considering its homogeneous or power-law density distribution. The strong effects of both "Ho\v{r}ava" parameter $\omega_{_{KS}}$ and plasma on the shadow cast by the KS compact objects are dem

Shinichi Saito, Isao Tomita

Topology is a central concept of mathematics, which allows us to distinguish two isolated rings with linked ones. In material science, researchers discovered topologically different carbon allotropes in a form of a cage, a tube, and a sheet, which have unique translational and rotational symmetries, described by a crystallographic group theory, and the atoms

Jee-weon Jung, Hee-Soo Heo, Ju-ho Kim, Hye-jin Shim

Recently, direct modeling of raw waveforms using deep neural networks has been widely studied for a number of tasks in audio domains. In speaker verification, however, utilization of raw waveforms is in its preliminary phase, requiring further investigation. In this study, we explore end-to-end deep neural networks that input raw waveforms to improve various

Elham Ziaali, Timothy R. Bedding, Simon J. Murphy, Timothy Van Reeth

We have examined the period-luminosity (P-L) relation for delta Scuti stars using Gaia DR2 parallaxes. We included 228 stars from the catalogue of Rodriguez et al. (2000), as well as 1124 stars observed in the four-year Kepler mission. For each star we considered the dominant pulsation period, and used DR2 parallaxes and extinction corrections to determine a

Vinoj Jayasundara, Sandaru Jayasekara, Hirunima Jayasekara, Jathushan Rajasegaran

Many localized languages struggle to reap the benefits of recent advancements in character recognition systems due to the lack of substantial amount of labeled training data. This is due to the difficulty in generating large amounts of labeled data for such languages and inability of deep learning techniques to properly learn from small number of training sa

Andrew Balchunas, Leroy L. Jia, Mark Zakhary, Zvonimir Dogic

We study the emergence of helical structures subjected to a stretching force, demonstrating that the force transforms disk-shaped colloidal membranes into twisted chiral ribbons of predetermined handedness. Using an experimental technique that enforces torque-free boundary conditions we simultaneously measure the force-extension curve and quantify the shape

Yuxian Qiu, Jingwen Leng, Cong Guo, Quan Chen

Recently, researchers have started decomposing deep neural network models according to their semantics or functions. Recent work has shown the effectiveness of decomposed functional blocks for defending adversarial attacks, which add small input perturbation to the input image to fool the DNN models. This work proposes a profiling-based method to decompose t

Ko Nakamura, Tomoya Takiwaki, Kei Kotake

Core-collapse supernovae (CCSNe) are the final stage of massive stars, marking the birth of neutron stars (NSs). The aspherical mass ejection drives a natal kick of the forming NS. In this work we study the properties of the NS kick based on our long-term hydrodynamics CCSN simulations. We perform two-dimensional (2D) simulations for ten progenitors from a 1

Stefano Longhi

Topological pumping of edge states in finite crystals or quasicrystals with non-trivial topological phases provides a powerful means for robust excitation transfer. In most schemes of topological pumping, the edge states become delocalized and immersed into the continuum during the adiabatic cycle, requiring extremely slow evolution to avoid nonadiabatic eff

Simon Riche, Geordie Williamson

In this paper we prove a character formula expressing the classes of simple representations in the principal block of a simply-connected semisimple algebraic group G in terms of baby Verma modules, under the assumption that the characteristic of the base field is bigger than 2h-1, where h is the Coxeter number of G. This provides a replacement for Lusztig's

L. Nanni, S. Brahnam, S. Ghidoni, G. Maguolo

Bioimage classification plays a crucial role in many biological problems. In this work, we present a new General Purpose (GenP) ensemble that boosts performance by combining local features, dense sampling features, and deep learning approaches. First, we introduce three new methods for data augmentation based on PCA/DCT; second, we show that different data a

Junhyun Lee, Inyeop Lee, Jaewoo Kang

Advanced methods of applying deep learning to structured data such as graphs have been proposed in recent years. In particular, studies have focused on generalizing convolutional neural networks to graph data, which includes redefining the convolution and the downsampling (pooling) operations for graphs. The method of generalizing the convolution operation t

Ahmed Abbas, Paul Swoboda

We consider general discrete Markov Random Fields(MRFs) with additional bottleneck potentials which penalize the maximum (instead of the sum) over local potential value taken by the MRF-assignment. Bottleneck potentials or analogous constructions have been considered in (i) combinatorial optimization (e.g. bottleneck shortest path problem, the minimum bottle

Jeremiah Blocki, Seunghoon Lee, Samson Zhou

The cumulative pebbling complexity of a directed acyclic graph $G$ is defined as $\mathsf{cc}(G) = \min_P \sum_i |P_i|$, where the minimum is taken over all legal (parallel) black pebblings of $G$ and $|P_i|$ denotes the number of pebbles on the graph during round $i$. Intuitively, $\mathsf{cc}(G)$ captures the amortized Space-Time complexity of pebbling $m$

Xiaoyu Chen, Junbin Dong

Let ${\bf G}$ be a connected reductive group defined over $\mathbb{F}_q$, the finite field with $q$ elements. Let ${\bf B}$ be an Borel subgroup defined over $\mathbb{F}_q$. In this paper, we completely determine the composition factors of the induced module $\mathbb{M}(\op{tr})=\Bbbk{\bf G}\otimes_{\Bbbk{\bf B}}\op{tr}$ ($\op{tr}$ is the trivial ${\bf B}$-m

Xiao-Lu Gao, Shou-Jun Xu

A graph $G$ is a cocomparability graph if there exists an acyclic transitive orientation of the edges of its complement graph $\overline{G}$. LBFS$^{+}$ is a variant of the generic Lexicographic Breadth First Search (LBFS), which uses a specific tie-breaking mechanism. Starting with some ordering $\sigma_{0}$ of $G$, let $\{\sigma_{i}\}_{i\geq 1}$ be the seq

Lewis R. B. Picard, Manfred J. Mark, Francesca Ferlaino, Rick van Bijnen

We present a novel method for the analysis of quantum gas microscope images, which uses deep learning to improve the fidelity with which lattice sites can be classified as occupied or unoccupied. Our method is especially suited to addressing the case of imaging without continuous cooling, in which the accuracy of existing threshold-based reconstruction metho

Nilesh K Tiwari, A K Jha, S P Singh, M Jaleel Akhtar

A magnetic measurement of the bar shaped test specimen placed inside the planar sensor is presented. A magnetic material characterization approach using planar cavity is proposed in this work. The proposed planar sensor relaxes the main limitations of conventional approach by using the proper feeding section. The proposed sensor is numerically verified using

Robert M. Guralnick, Michael Larsen, Pham Huu Tiep

This paper is a continuation of [GLT], which develops a level theory and establishes strong character bounds for finite simple groups of linear and unitary type in the case that the centralizer of the element has small order compared to $|G|$ in a logarithmic sense. We strengthen the results of [GLT] and extend them to all groups of classical type.

Ramakrishna Tipireddy, David A Barajas-Solano, Alexandre M. Tartakovsky

We use a conditional Karhunen-Lo\`eve (KL) model to quantify and reduce uncertainty in a stochastic partial differential equation (SPDE) problem with partially-known space-dependent coefficient, $Y(x)$. We assume that a small number of $Y(x)$ measurements are available and model $Y(x)$ with a KL expansion. We achieve reduction in uncertainty by conditioning

Manuel Gonzalez-Espinoza, Giovanni Otalora, Nelson Videla, Joel Saavedra

We study the dynamics of inflation in a generalized scalar-torsion gravity scenario by assuming a canonical scalar field non-minimally coupled to torsion with a Galileon-type self-interaction. After obtaining the field equations for a flat FRW background, we derive the second order action for both scalar and tensor perturbations to compute the power spectra

Kamran Kowsari, Kiana Jafari Meimandi, Mojtaba Heidarysafa, Sanjana Mendu

In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches have achieved surpassing results in natural language processing. The success of these learning algorit

Fei Ma

Most of various large-size complex systems in nature and society can be well described as complex networks (graphs) to better understand the evolutional mechanisms and dynamical functions behind themselves. Of some part follow scale-free behavior, that is, the ratio of the number of vertices with degree more than or equal to $k$ and order of the whole networ

Xixi Li, Yanfei Kang, Feng Li

Feature-based time series representations have attracted substantial attention in a wide range of time series analysis methods. Recently, the use of time series features for forecast model averaging has been an emerging research focus in the forecasting community. Nonetheless, most of the existing approaches depend on the manual choice of an appropriate set

Alex Stivala, Garry Robins, Alessandro Lomi

Exponential random graph models (ERGMs) are widely used for modeling social networks observed at one point in time. However the computational difficulty of ERGM parameter estimation has limited the practical application of this class of models to relatively small networks, up to a few thousand nodes at most, with usually only a few hundred nodes or fewer. In

Reiichiro Nakano

We explore neural painters, a generative model for brushstrokes learned from a real non-differentiable and non-deterministic painting program. We show that when training an agent to "paint" images using brushstrokes, using a differentiable neural painter leads to much faster convergence. We propose a method for encouraging this agent to follow human-