November 2019 arXiv papers — page 22

Johannes Braathen, Shinya Kanemura

We compute the dominant two-loop corrections to the Higgs trilinear coupling $\lambda_{hhh}$ and to the Higgs quartic coupling $\lambda_{hhhh}$ in models with extended Higgs sectors, using the effective-potential approximation. We provide in this paper all necessary details about our calculations, and present general $\overline{\text{MS}}$ expressions for de

Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani

Pre-trained word embeddings encode general word semantics and lexical regularities of natural language, and have proven useful across many NLP tasks, including word sense disambiguation, machine translation, and sentiment analysis, to name a few. In supervised tasks such as multiclass text classification (the focus of this article) it seems appealing to enha

Masha Vlasenko

This text can be considered as a non-technical and arithmetically motivated introduction to the definition of the limiting mixed Hodge structure. We state several assertions in terms natural to the classical theory of ordinary differential operators and prove them using elementary arguments.

Rishi Mouland

Recently, a class of non-Lorentzian supersymmetric Lagrangian field theories was considered, in some cases describing M-theory brane configurations, but more generally found as fixed points of non-Lorentzian RG flows induced upon Lorentzian theories. In this paper, we demonstrate how the dynamics of such theories can be reduced to motion on the supersymmetri

Georgi Georgiev, Valentin Zhikov, Petya Osenova, Kiril Simov

We present experiments with part-of-speech tagging for Bulgarian, a Slavic language with rich inflectional and derivational morphology. Unlike most previous work, which has used a small number of grammatical categories, we work with 680 morpho-syntactic tags. We combine a large morphological lexicon with prior linguistic knowledge and guided learning from a

Ya Zhao, Rui Xu, Xinchao Wang, Peng Hou

Lip reading has witnessed unparalleled development in recent years thanks to deep learning and the availability of large-scale datasets. Despite the encouraging results achieved, the performance of lip reading, unfortunately, remains inferior to the one of its counterpart speech recognition, due to the ambiguous nature of its actuations that makes it challen

Masaaki Fujii

In this work, we systematically investigate mean field games and mean field type control problems with multiple populations using a coupled system of forward-backward stochastic differential equations of McKean-Vlasov type stemming from Pontryagin's stochastic maximum principle. Although the same cost functions as well as the coefficient functions of the sta

Marco Voigt

The classical decision problem, as it is understood today, is the quest for a delineation between the decidable and the undecidable parts of first-order logic based on elegant syntactic criteria. In this paper, we treat the concept of separateness of variables and explore its applicability to the classical decision problem. Two disjoint sets of first-order v

Yun-Peng Huang, Jin-Wei Dong, Panagiotis Kotetes, Sen Zhou

We employ the Hartree-Fock approximation to identify the magnetic ground state of the Hubbard model on a frustrated square lattice. We investigate the phase diagram as a function of the Coulomb repulsion's strength $U$, and the ratio $t'/t$ between the nearest and next nearest neighbor hoppings $t$ and $t'$. At half-filling and for a sufficiently large $U$,

S. T. H. Hartman, H. A. Winther, D. F. Mota

We intend to understand cosmological structure formation within the framework of superfluid models of dark matter with finite temperatures. Of particular interest is the evolution of small-scale structures where the pressure and superfluid properties of the dark matter fluid are prominent. We compare the growth of structures in these models with the standard

Enis Belgacem, Stefano Foffa, Michele Maggiore, Tao Yang

Recent work has shown that modified gravitational wave (GW) propagation can be a powerful probe of dark energy and modified gravity, specific to GW observations. We use the technique of Gaussian processes, that allows the reconstruction of a function from the data without assuming any parametrization, to measurements of the GW luminosity distance from simula

Tobias Fiebig

"Moving fast, and breaking things", instead of "being safe and secure", is the credo of the IT industry. In this paper, we take a look at how we keep falling for the same security issues, and what we can learn from aviation safety to learn building and operating IT systems securely. We find that computer security should adopt the idea of safety. This entails

Dominik Dürrschnabel, Tom Hanika, Maximilian Stubbemann

Embedding large and high dimensional data into low dimensional vector spaces is a necessary task to computationally cope with contemporary data sets. Superseding latent semantic analysis recent approaches like word2vec or node2vec are well established tools in this realm. In the present paper we add to this line of research by introducing fca2vec, a family o

Hemza Azri, Salah Nasri

Multiple scalar fields nonminimally interacting through pure affine gravity are considered to generate primordial perturbations during an inflationary phase. The couplings considered give rise to two distinct sources of entropy perturbations that may not be suppressed in the long wavelength limit. The first is merely induced by the presence of more than one

Rosa Becerra, Christopher Thraves Caro

A metric space $\mathcal{T}$ is a \emph{real tree} if for any pair of points $x, y \in \mathcal{T}$ all topological embeddings $\sigma$ of the segment $[0,1]$ into $\mathcal{T}$, such that $\sigma (0)=x$ and $\sigma (1)=y$, have the same image (which is then a geodesic segment from $x$ to $y$). A \emph{signed graph} is a graph where each edge has a positive

Ulrike Nabholz, Florian Stockmar, Jan E. Mehner, Peter Degenfeld-Schonburg

Sensors and actuators based on resonant micro-electro-mechanical systems (MEMS), such as scanning micro mirrors, are well-established in automotive and consumer products. As the areas of application broaden, the requirements for the MEMS are increasing. Devices outside of the performance specifications have to be rejected which is costly due to the high proc

Yuan Ye, Yansong Feng, Bingfeng Luo, Yuxuan Lai

Recent years have seen rapid progress in identifying predefined relationship between entity pairs using neural networks NNs. However, such models often make predictions for each entity pair individually, thus often fail to solve the inconsistency among different predictions, which can be characterized by discrete relation constraints. These constraints are o

Seonghyeon Lee, Chanyoung Park, Hwanjo Yu

The goal of network embedding is to transform nodes in a network to a low-dimensional embedding vectors. Recently, heterogeneous network has shown to be effective in representing diverse information in data. However, heterogeneous network embedding suffers from the imbalance issue, i.e. the size of relation types (or the number of edges in the network regard

M. Kieburg, A. Mielke, M. Rud, K. Splittorff

Hermitian operators with exact zero modes subject to non-Hermitian perturbations are considered. Specific focus is on the average distribution of the initial zero modes of the Hermitian operators. The broadening of these zero modes is found to follow an elliptic Gaussian random matrix ensemble of fixed size, where the symmetry class of the perturbation deter

Sabine Thater, Davor Krajnović, Dieu D. Nguyen, Satoru Iguchi

We present our ongoing work of using two independent tracers to estimate the supermassive black hole mass in the nearby early-type galaxy NGC 6958; namely integrated stellar and molecular gas kinematics. We used data from the Atacama Large Millimeter/submillimeter Array (ALMA), and the adaptive-optics assisted Multi-Unit Spectroscopic Explorer (MUSE) and con

Udo Schilcher, Siddhartha Borkotoky, Jorge F. Schmidt, Christian Bettstetter

We derive the probability distribution of the link outage duration at a typical receiver in a wireless network with Poisson distributed interferers sending messages with slotted random access over a Rayleigh fading channel. This result is used to analyze the performance of random linear network coding, showing that there is an optimum code rate and that inte

Xin Li, Piji Li, Wei Bi, Xiaojiang Liu

Despite the effectiveness of sequence-to-sequence framework on the task of Short-Text Conversation (STC), the issue of under-exploitation of training data (i.e., the supervision signals from query text is \textit{ignored}) still remains unresolved. Also, the adopted \textit{maximization}-based decoding strategies, inclined to generating the generic responses

Laleh Tafakori, Armin Pourkhanali, Riccardo Rastelli

This paper introduces a novel framework to study default dependence and systemic risk in a financial network that evolves over time. We analyse several indicators of risk, and develop a new latent space model to assess the health of key European banks before, during, and after the recent financial crises. First, we adopt the measure of CoRisk to determine th

Jiang Long

Zero modes of modular Hamiltonian of one interval are found in momentum space for two dimensional massless free scalar theory. Finite correlators are extracted from separate region connected correlation functions with the insertion of zero modes. Correlators of $(n,1)$-type are claimed to be conformal block up to a set of theory dependent constants. We fix t

Bert-Jan Butijn, Damian A. Tamburri, Willem-Jan Van Den Heuvel

Blockchain technology has gained tremendous popularity both in practice and academia. The goal of this article is to develop a coherent overview of the state of the art in blockchain technology, using a systematic(i.e.,protocol-based, replicable), multivocal (i.e., featuring both white and grey literature alike) literature review, to (1) define blockchain te

Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu

We formalize networks with evolving structures as temporal networks and propose a generative link prediction model, Generative Link Sequence Modeling (GLSM), to predict future links for temporal networks. GLSM captures the temporal link formation patterns from the observed links with a sequence modeling framework and has the ability to generate the emerging

Christina Kaiser, Stefan Zeiske, Paul Meredith, Ardalan Armin

Energy states below the bandgap of a semiconductor, such as trap states or charge transfer states in organic donor acceptor blends, can contribute to light absorption. Due to their low number density or ultrasmall absorption cross-section, the absorption coefficient of these states is challenging to measure using conventional transmission reflection spectrop

Weizhe Liu, Mathieu Salzmann, Pascal Fua

State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density. While effective, deep learning approaches are vulnerable to adversarial attacks, which, in a crowd-counting context, can lead to serious security issues. However, attack and defense mechanisms have been virtually unexplored in regression tasks, let

Subhadeep Roy, Santanu Sinha, Alex Hansen

We present a theoretical framework for immiscible incompressible two-phase flow in homogeneous porous media that connects the distribution of local fluid velocities to the average seepage velocities. By dividing the pore area along a cross-section transversal to the average flow direction up into differential areas associated with the local flow velocities,

Chang Yang, Fabrice Deluzet, Jacek Narski

In this paper we study the loss of precision of numerical methods discretizing anisotropic problems and propose alternative approaches free from this drawback. The deterioration of the accuracy is observed when the coordinates and the mesh are unrelated to the anisotropy direction. While this issue is commonly addressed by increasing the scheme approximation

Alina Dubatovka, Efi Kokiopoulou, Luciano Sbaiz, Andrea Gesmundo

Neural architecture search has recently attracted lots of research efforts as it promises to automate the manual design of neural networks. However, it requires a large amount of computing resources and in order to alleviate this, a performance prediction network has been recently proposed that enables efficient architecture search by forecasting the perform

Kai-Feng Chen, Masamune Oguri, Yen-Ting Lin, Satoshi Miyazaki

We estimate the bias on weak lensing mass measurements of shear-selected galaxy cluster samples. The mass bias is expected to be significant because constructions of cluster samples from peaks in weak lensing mass maps and measurements of cluster masses from their tangential shear profiles share the same noise. We quantify this mass bias from large sets of m

Tianyuan Zhang, Bichen Wu, Xin Wang, Joseph Gonzalez

Deep neural networks with more parameters and FLOPs have higher capacity and generalize better to diverse domains. But to be deployed on edge devices, the model's complexity has to be constrained due to limited compute resource. In this work, we propose a method to improve the model capacity without increasing inference-time complexity. Our method is based o

Symon Serbenyuk

The present article is devoted to the investigation of some properties of the generalized shift operator of numbers represented in terms of numeral systems with a variable alphabet.

Yunliang Zheng, Shiyin Shen

A compact group (CG) is a kind of special galaxy system where the galaxy members are separated at the distances of the order of galaxy size. The strong interaction between the galaxy members makes CGs ideal labs for studying the environmental effects on galaxy evolution. The traditional photometric selection algorithm biases against the CG candidates at low

Wandong Zhao, Jianhan Liang, Mingbo Sun, Xiaodong Cai

A hybrid thermal lattice Boltzmann phase-change model was performed to simulate the pool boiling above a smooth horizontal heater. The effects of homogenous and heterogeneous wettability on entire boiling curves from the onset of nucleate boiling (ONB) to fully developed film boiling were investigated comprehensively. Results show that concerning the homogen

Timothy M. Pollington, Michael J. Tildesley, T. Déirdre Hollingsworth, Lloyd A. C. Chapman

Introduction The tau statistic is a recent second-order correlation function that can assess the magnitude and range of global spatiotemporal clustering from epidemiological data containing geolocations of individual cases and, usually, disease onset times. This is the first review of its use, and the aspects of its computation and presentation that could af

Will Hicks

In this article we model a financial derivative price as an observable on the market state function. We apply geometric techniques to integrating the Heisenberg Equation of Motion. We illustrate how the non-commutative nature of the model introduces quantum interference effects that can act as either a drag or a boost on the resulting return. The ultimate ob

Anmin Zhang, Xiaoli Ma, Changle Liu, Rui Lou

We present experimental evidence of an intriguing phase transition between distinct topological states in the type-II Weyl semimetal MoTe2. We observe anomalies in the Raman phonon frequencies and linewidths as well as electronic quasielastic peaks around 70 K, which, together with structural, thermodynamic measurements, and electron-phonon coupling calculat

Dat Quoc Nguyen, Dai Quoc Nguyen, Son Bao Pham, The Duy Bui

Search engines have become an indispensable tool for browsing information on the Internet. The user, however, is often annoyed by redundant results from irrelevant Web pages. One reason is because search engines also look at non-informative blocks of Web pages such as advertisement, navigation links, etc. In this paper, we propose a fast algorithm called Fas

Keiichi Kato, Masaki Kawamoto, Koichiro Nanbu

We investigate the time propagation of singularity of a solution to linearized KdV equation by using the characterization of wave front sets with using to the wave packet transform (short time Fourier transform).

Raquel Pérez-Arnal, Dario Garcia-Gasulla, David Torrents, Ferran Parés

Finding tumour genetic markers is essential to biomedicine due to their relevance for cancer detection and therapy development. In this paper, we explore a recently released dataset of chromosome rearrangements in 2,586 cancer patients, where different sorts of alterations have been detected. Using a Random Forest classifier, we evaluate the relevance of sev

Dai Quoc Nguyen, Dat Quoc Nguyen, Son Bao Pham

Question answering systems aim to produce exact answers to users' questions instead of a list of related documents as used by current search engines. In this paper, we propose an ontology-based Vietnamese question answering system that allows users to express their questions in natural language. To the best of our knowledge, this is the first attempt to enab

Alessia Caponera, Claudio Durastanti, Anna Vidotto

The purpose of the present paper is to investigate on a class of spherical functional autoregressive processes in order to introduce and study LASSO (Least Absolute Shrinkage and Selection Operator) type estimators for the corresponding autoregressive kernels, defined in the harmonic domain by means of their spectral decompositions. Some crucial properties f

Sebastian Posur

For an additive category $\mathbf{P}$ we provide an explict construction of a category $\mathcal{Q}( \mathbf{P} )$ whose objects can be thought of as formally representing $\frac{\mathrm{im}( \gamma )}{\mathrm{im}( \rho ) \cap \mathrm{im}( \gamma )}$ for given morphisms $\gamma: A \rightarrow B$ and $\rho: C \rightarrow B$ in $\mathbf{P}$, even though $\math

Ishfaq Hussain, Janibul Bashir

With an increase in the number of internet users and the need to secure internet traffic, the unreliable IPv4 protocol has been replaced by a more secure protocol, called IPv6 for Internet system. The IPv6 protocol does not allow intermediate routers to fragment the on-going IPv6 packet. Moreover, due to IP tunneling, some extra headers are added to the IPv6

Vladimir Stephanovich, Wlodzimierz Godlowski, Monika Biernacka, Blazej Mrzyglod

We study the influence of the astronomical objects masses randomness on the distribution function of their gravitational fields. Based on purely theoretical arguments and comparison with extensive data, collected from observations and numerical simulations, we have shown that while mass randomness does not alter the non-Gaussian character of the gravitationa

J. Sicacha-Parada, I. Steinsland, B. Cretois, J. Borgelt

Citizen Scientists together with an increasing access to technology provide large datasets that can be used to study e.g. ecology and biodiversity. Unknown and varying sampling effort is a major issue when making inference based on citizen science data. In this paper we propose a modeling approach for accounting for variation in sampling effort due to access

Nimrod Sherf, Maoz Shamir

Rhythmic activity has been associated with a wide range of cognitive processes. Previous studies have shown that spike-timing-dependent plasticity can facilitate the transfer of rhythmic activity downstream the information processing pathway. However, STDP has also been known to generate strong winner-take-all like competitions between subgroups of correlate

Masanori Hanada, Goro Ishiki, Hiromasa Watanabe

We provide the evidence for the existence of partially deconfined phase in large-$N$ gauge theory. In this phase, the SU($M$) subgroup of SU($N$) gauge group deconfines, where $\frac{M}{N}$ changes continuously from zero (confined phase) to one (deconfined phase). The partially deconfined phase may exist in real QCD with $N=3$.

Parbati Sahoo, Sanjay Mandal, P. K. Sahoo

In the present article we propose a new hybrid shape function for wormhole (WH)s in the modified $f(R,T)$ gravity. The proposed shape function satisfied the conditions of WH geometry. Geometrical behavior of WH solutions are discussed in both anisotropic and isotropic cases respectively. Also, the stability of this model is obtained by determining the equili

Vitaly Fedoseev, Fernando Luna, Ian Hedgepeth, Wolfgang Löffler

Stimulated Raman adiabatic passage (STIRAP) describes adiabatic population transfer between two states coherently coupled via a mediating state that remains unoccupied. This renders STIRAP robust against loss in the mediating state, leading to profound applications in atomic- and molecular-beam research, trapped-ion physics, superconducting circuits, other s

Julia El Zini, Yara Rizk, Mariette Awad

Recurrent neural networks (RNN) have been successfully applied to various sequential decision-making tasks, natural language processing applications, and time-series predictions. Such networks are usually trained through back-propagation through time (BPTT) which is prohibitively expensive, especially when the length of the time dependencies and the number o

Mark de Rooij, Bunga Citra Pratiwi, Marjolein Fokkema, Elise Dusseldorp

Machine and Statistical learning techniques become more and more important for the analysis of psychological data. Four core concepts of machine learning are the bias variance trade-off, cross-validation, regularization, and basis expansion. We present some early psychometric papers, from almost a century ago, that dealt with cross-validation and regularizat

Mengmeng Xu, Chen Zhao, David S. Rojas, Ali Thabet

Temporal action detection is a fundamental yet challenging task in video understanding. Video context is a critical cue to effectively detect actions, but current works mainly focus on temporal context, while neglecting semantic context as well as other important context properties. In this work, we propose a graph convolutional network (GCN) model to adapti

Angelo Bella, Santi Spadaro

We prove that if $X$ is a regular space with no uncountable free sequences, then the tightness of its $G_\delta$ topology is at most continuum and if $X$ is in addition Lindel\"of then its $G_\delta$ topology contains no free sequences of length larger then the continuum. We also show that the higher cardinal generalization of our theorem does not hold, by c

Olivier Billaud, Maxence Soubeyrand, Sandra Luque, Maxime Lenormand

GIS-based Multi-Criteria Decision Analysis is a well-known decision support tool that can be used in a wide variety of contexts. It is particularly useful for territorial planning in situations where several actors with different, and sometimes contradictory, point of views have to take a decision regarding land use development. While the impact of the weigh

A. V. Artemyev, A. I. Neishtadt, A. A. Vasiliev

The resonant interaction of relativistic electrons and whistler waves is an important mechanism of electron acceleration and scattering in the Earth radiation belts and other space plasma systems. For low amplitude waves, such an interaction is well described by the quasi-linear diffusion theory, whereas nonlinear resonant effects induced by high-amplitude w

David Schwörer, Nick R. Walkden, Benjamin D. Dudson, Fulvio Militello

The here presented work studies the dynamics of filaments using 3D fluid simulations in the presence of detached background profiles. It was found that evolving the neutrals on the time-scale of the filament did not have a significant impact on the dynamics of the filament. In general a decreasing filament velocity with increasing plasma background density h

Yakine Bahri, Yvan Martel, Pierre Raphaël

We construct radially symmetric self-similar blow-up profiles for the mass supercritical nonlinear Schr\"odinger equation $i\partial_t u + \Delta u + |u|^{p-1}u=0$ on $\mathbf{R}^d$, close to the mass critical case and for any space dimension $d\ge 1$. These profiles bifurcate from the ground state solitary wave. The argument relies on the classical matched

Vincent T. Engl, Nikolaj G. Ebensperger, Lars Wendel, Marc Scheffler

The complex dielectric constant $\hat{\epsilon} = \epsilon_1 + i \epsilon_2$ of SrTiO$_3$ reaches high values $\epsilon_1 \approx 2*10^{4}$ at cryogenic temperatures, while the dielectric losses ($\epsilon_2$) are much stronger than for other crystalline dielectrics. SrTiO$_3$ is a common substrate for oxide thin films, like the superconducting LaAlO$_3$/SrT

Tony Gracious, Shubham Gupta, Arun Kanthali, Rui M. Castro

Although static networks have been extensively studied in machine learning, data mining, and AI communities for many decades, the study of dynamic networks has recently taken center stage due to the prominence of social media and its effects on the dynamics of social networks. In this paper, we propose a statistical model for dynamically evolving networks, t

Valentin Robu, David Flynn, Merlinda Andoni, Maizura Mokhtar

Artificial Intelligence and Machine Learning are increasingly seen as key technologies for building more decentralised and resilient energy grids, but researchers must consider the ethical and social implications of their use

Clemens Kirisits, Eric Setterqvist, Otmar Scherzer

A recent result by Lasica, Moll and Mucha about the $\ell^1$-anisotropic Rudin-Osher-Fatemi model in $\mathbb{R}^2$ asserts that the solution is piecewise constant on a rectilinear grid, if the datum is. By means of a new proof we extend this result to $\mathbb{R}^n$. The core of our proof consists in showing that averaging operators associated to certain re

L Zhao, C. -C. Li, C. -C. Yang, M. -K. Wu

The quasi-1D spin chain compound CuBr2 has been found to be multiferroic below TN (73.5K) under ambient pressure, in which the spontaneous electric polarization is induced by emerging spin spiral ordering propagating along b-axis. Herein we studied the hydrostatic pressure effect on the magnetic, dielectric and structural properties of CuBr2. The multiferroi

D A Artemenkov, V Bradnova, E Firu, M Haiduc

Status and prospects of nuclear clustering studies by dissociation of relativistic nuclei in nuclear track emulsion are presented. The unstable $^{8}$Be and $^{9}$B nuclei are identified in dissociation of the isotopes $^{9}$Be, $^{10}$B, $^{10}$C and $^{11}$C, and the Hoyle state in the cases $^{12}$C and $^{16}$O. On this ground searching for the Hoyle sta

Benjamin Doerr, Carola Doerr, Aneta Neumann, Frank Neumann

Submodular optimization plays a key role in many real-world problems. In many real-world scenarios, it is also necessary to handle uncertainty, and potentially disruptive events that violate constraints in stochastic settings need to be avoided. In this paper, we investigate submodular optimization problems with chance constraints. We provide a first analysi

Odysse Halim, Carlo Vigorito, Claudio Casentini, Giulia Pagliaroli

Core-Collapse Supernovae, failed supernovae and quark novae are expected to release an energy of few $10^{53}$ ergs through MeV neutrinos and a network of detectors is operative to look online for these events. However, when the source distance increases and/or the average energy of emitted neutrinos decreases, the signal statistics drops and the identificat

Ruiqi Lu, Huimin Ma

Training a robust classifier and an accurate box regressor are difficult for occluded pedestrian detection. Traditionally adopted Intersection over Union (IoU) measurement does not consider the occluded region of the object and leads to improper training samples. To address such issue, a modification called visible IoU is proposed in this paper to explicitly

Taum Wuthicharn, Supakchai Ponglertsakul, Piyabut Burikham

Two numerical methods are used to calculate quasinormal modes (QNMs) of near-extremal black holes/strings in the generalized spherically/cylindrically symmetric background, the Asymptotic Iteration Method (AIM) and the Spectral Method. The numerical results confirm the accuracy of the approximate analytic formula using the P\"{o}schl-Teller potential. Our an

Igor I. Zinchenko, Sheng-Yuan Liu, Yu-Nung Su, Kuo-Song Wang

We investigate at a high angular resolution the spatial and kinematic structure of the S255IR high mass star-forming region, which demonstrated recently the first disk-mediated accretion burst in the massive young stellar object. The observations were performed with ALMA in Band 7 at an angular resolution $ \sim 0.1^{\prime\prime}$, which corresponds to $ \s

Pierre Capel

In this contribution, the eikonal approximation developed by Roy Glauber to describe high-energy quantum collisions is presented. This approximation has been-and still is-extensively used to analyse reaction measurements performed to study the structure of nuclei far from stability. This presentation focuses more particularly on the application of the eikona

Jun Wei, Shuhui Wang, Qingming Huang

Most of existing salient object detection models have achieved great progress by aggregating multi-level features extracted from convolutional neural networks. However, because of the different receptive fields of different convolutional layers, there exists big differences between features generated by these layers. Common feature fusion strategies (additio

Francesco De Lellis, Fabrizia Auletta, Giovanni Russo, Mario di Bernardo

In this extended abstract we introduce a novel control-tutored Q-learning approach (CTQL) as part of the ongoing effort in developing model-based and safe RL for continuous state spaces. We validate our approach by applying it to a challenging multi-agent herding control problem.

Khemendra Shukla, Po-Sung Chen, Jun-Ren Chen, Yu-Hsuan Chang

Quantum tunneling is a phenomenon of non-equilibrium quantum dynamics and its detailed process is largely unexplored. We report the experimental observation of macroscopic quantum tunneling of Bose-Einstein Condensate in a hybrid trap. By exerting a non-adiabatic kick to excite a collective rotation mode of the trapped condensate, a periodic pulse train, whi

J. Hamann, Q. T. Le Gia, I. H. Sloan, Y. G. Wang

We introduce a new mathematical tool (a direction-dependent probe) to analyse the randomness of purported isotropic Gaussian random fields on the sphere. We apply the probe to assess the full-sky cosmic microwave background (CMB) temperature maps produced by the {\it Planck} collaboration (PR2 2015 and PR3 2018), with special attention to the inpainted maps.

Anna Cima, Armengol Gasull, Víctor Mañosa

We study the phase portraits with positive probability of random planar homogeneous vector fields of degree n. In particular, for n=1,2,3, we give a complete solution of the problem and, moreover, either we give the exact value of each probability or we estimate it by using the Monte Carlo method. It is remarkable that all but two of these phase portraits ar

Elie Casbi

We show that for a finite-type Lie algebra $\mathfrak{g}$, the representation theory of quiver Hecke algebras provides a natural framework for the construction of Newton-Okounkov bodies associated to the quantum coordinate rings $\Aqnw$. When $\mathfrak{g}$ is simply-laced, we use Kang-Kashiwara-Kim-Oh's monoidal categorification to investigate the cluster t

Michael Thies

The phase diagram of the two-dimensional Nambu--Jona-Lasinio model with isospin is explored in the large Nc limit with semiclassical methods. We consider finite temperature and include chemical potentials for all conserved charges. In the chiral limit, a full analytical solution is presented, expressed in terms of known results for the single-flavor Gross-Ne

Chen Yang, Zi-Qi Chen, Li Zhao

In this paper, we study the localization of Kalb-Ramond (KR) tensorial gauge field on a non-flat de Sitter thick brane. The localization and resonance of KR gauge field are discussed for three kinds of couplings. For the first coupling there is no localized tensorial zero mode. For the other two couplings, the zero mode of KR field can be localized under cer

Muhammad Asad Khan, Sajid Saleem, Amir A Khan

In this paper, new results on convolution of spectral components in binary fields have been presented for combiatorial sequences. A novel method of convolution of DFT points through Chinese Remainder Theorem (CRT) is presented which has lower complexity as compared to known methods of spectral point computations. Exploring the inherent structures in cyclic n

Jagannath Pal, Amar Kumar Banerjee

Here we have studied the ideas of $ sg_\lambda,s\lambda$ and $ s\beta_\lambda $-closed sets and investigated some of their properties in generalized topological spaces. We have also studied some low separation axioms namely $ s\lambda T_\frac{1}{4} $, $ s\lambda T_\frac{3}{8} $, $ s\lambda T_\frac{1}{2} $ axioms and their mutual relations with $ s\lambda T_0

María Teresa Lozano, José María Montesinos-Amilibia

A group of matrices $G$ with entries in a number field $K$ is defined to be numerical if $G$ has a finite index subgroup of matrices whose entries are algebraic integers. It is shown that an irreducible or completely reducible subgroup of $GL(n,K)\subset GL(n,\mathbb{C})$ is numerical if and only if the traces of its elements are algebraic integers. Some exa

Alejandra Castro, Beatrix Mühlmann

We revisit the holographic description of the near horizon geometry of the BTZ black hole in AdS$_3$ gravity, with a gravitational Chern-Simons term included. After a dimensional reduction of the three dimensional theory, we use the framework of nAdS$_2$/nCFT$_1$ to describe the near horizon physics. This setup allows us to contrast the role of the gravitati

Ameya Prabhu, Riddhiman Dasgupta, Anush Sankaran, Srikanth Tamilselvam

For an unknown (new) classification dataset, choosing an appropriate deep learning architecture is often a recursive, time-taking, and laborious process. In this research, we propose a novel technique to recommend a suitable architecture from a repository of known models. Further, we predict the performance accuracy of the recommended architecture on the giv

Dandan Li, Qingquan Chang, Chunyou Sun

The aim of this paper is to analyze the long-time dynamical behavior of the solution for a degenerate wave equation with time-dependent damping term $\partial_{tt}u + \beta(t)\partial_tu = \mathcal{L}u(x,t) + f(u)$ on a bounded domain $\Omega\subset\mathbb{R}^N$ with Dirichlet boundary conditions. Under some restrictions on $\beta(t)$ and critical growth res

Alma Eguizabal, Peter J. Schreier, Jürgen Schmidt

Statistical shape models are a useful tool in image processing and computer vision. A Procrustres registration of the contours of the same shape is typically perform to align the training samples to learn the statistical shape model. A Procrustes registration between two contours with known correspondences is straightforward. However, these correspondences a

Yanbei Liu, Xiao Wang, Shu Wu, Zhitao Xiao

We address the problem of disentangled representation learning with independent latent factors in graph convolutional networks (GCNs). The current methods usually learn node representation by describing its neighborhood as a perceptual whole in a holistic manner while ignoring the entanglement of the latent factors. However, a real-world graph is formed by t

Arnob Ray, Dibakar Ghosh

We propose a new simple three-dimensional continuous autonomous model with two nonlinear terms and observe the dynamical behavior with respect to system parameters. This system changes the stability of fixed point via Hopf bifurcation and then undergoes a cascade of a period-doubling route to chaos. We analytically derive the first Lyapunov coefficient to in

Ngoc Hoang Anh Mai, Jean-Bernard Lasserre, Victor Magron

In a first contribution, we revisit two certificates of positivity on (possibly non-compact) basic semialgebraic sets due to Putinar and Vasilescu [Comptes Rendus de l'Acad\'emie des Sciences-Series I-Mathematics, 328(6) (1999) pp. 495-499]. We use Jacobi's technique from [Mathematische Zeitschrift, 237(2) (2001) pp. 259-273] to provide an alternative proof

Umair Zulfiqar, Victor Sreeram, Xin Du

In this paper, we present an adaptive framework for constructing a pseudo-optimal reduced model for the frequency-limited H2-optimal model order reduction problem. We show that the frequency-limited pseudo-optimal reduced-order model has an inherent property of monotonic decay in error if the interpolation points and tangential directions are selected approp

Ansgar Jüngel, Antoine Zurek

A finite-volume scheme for a cross-diffusion model arising from the mean-field limit of an interacting particle system for multiple population species is studied. The existence of discrete solutions and a discrete entropy production inequality is proved. The proof is based on a weighted quadratic entropy that is not the sum of the entropies of the population

Armand Wirgin

We establish the abstract and semi-abstract equations that translate the conservation law for a totally-filled, or totally-empty basin of arbitrary shape submitted to a SH plane seismic body wave. This law states that the input flux is equal to the sum of the scattered and absorbed fluxes, the latter being equal to zero when the filler medium is non-lossy. W

F. N. Womack, P. W. Adams, J. M. Valles, G. Catelani

We report magnetotransport measurements of the critical field behavior of thin Al films deposited onto multiply connected substrates. The substrates were fabricated via a standard electrochemical process that produced a triangular array of 66 nm diameter holes having a lattice constant of 100 nm. The critical field transition of the Al films was measured nea

Stephen Merity

The leading approaches in language modeling are all obsessed with TV shows of my youth - namely Transformers and Sesame Street. Transformers this, Transformers that, and over here a bonfire worth of GPU-TPU-neuromorphic wafer scale silicon. We opt for the lazy path of old and proven techniques with a fancy crypto inspired acronym: the Single Headed Attention

Asaf Weinstein

In a compound decision problem, consisting of $n$ statistically independent copies of the same problem to be solved under the sum of the individual losses, any reasonable compound decision rule $\delta$ satisfies a natural symmetry property, entailing that $\delta(\sigma(\boldsymbol{y})) = \sigma(\delta(\boldsymbol{y}))$ for any permutation $\sigma$. We deri

Yefeng Liu, Jincheng Lu, Rongqian Wang, Chen Wang

The energy efficiency and power of a quantum thermoelectric system with multiple electric currents and only one heat currents are studied. The system is connected to the hot heat bath with one terminal but the cold bath with multiple terminals or vice versal. We find that the cooperative effects can be a potentially useful tool in improving the energy effici

Alireza Nouri, Alireza Soroudi, Andrew Keane

This paper shows that a relation can be found between the voltage at the terminals of an inverter-interfaced Renewable Energy Source RES and its optimal reactive power support. This relationship, known as Volt-Var Curve VVC, enables the decentral operation of RES for Active Voltage Management (AVM). In this paper, the decentralized AVM technique is modified

Kekai Sheng, Weiming Dong, Menglei Chai, Guohui Wang

Visual aesthetic assessment has been an active research field for decades. Although latest methods have achieved promising performance on benchmark datasets, they typically rely on a large number of manual annotations including both aesthetic labels and related image attributes. In this paper, we revisit the problem of image aesthetic assessment from the sel

Hongyang Du, Jiayi Zhang, Kostas P. Peppas, Hui Zhao

The Fisher-Snedecor $\mathcal{F}$ distribution has been recently proposed as a more accurate and mathematically tractable composite fading model than traditional established models in some practical cases. In this paper, we firstly derive exact closed-form expressions for the main statistical characterizations of the ratio of products of $\mathcal{F}$-distri