October 2020 arXiv papers — page 110

Hendrik Müller, Christoph Behrens, David James Edward Marsh

We present a novel procedure to estimate the Equation of State of the intergalactic medium in the quasi-linear regime of structure formation based on Ly$α$ forest tomography and apply it to 21 high quality quasar spectra from the UVES\_SQUAD survey at redshift $z=2.5$. Our estimation is based on a full tomographic inversion of the line of sight. We invert th

Nathan Chapelier-Laget

Let $W_a$ be an affine Weyl group with corresponding finite root system $Φ$. In \cite{JYS1} Jian-Yi Shi characterized each element $w \in W_a$ by a $ Φ^+$-tuple of integers $(k(w,α))_{α\in Φ^+}$ subject to certain conditions. In \cite{NC1} a new interpretation of the coefficients $k(w,α)$ is given. This description led us to define an affine variety $\wideha

Lilang Lin, Sijie Song, Wenhan Yan, Jiaying Liu

In this paper, we address self-supervised representation learning from human skeletons for action recognition. Previous methods, which usually learn feature presentations from a single reconstruction task, may come across the overfitting problem, and the features are not generalizable for action recognition. Instead, we propose to integrate multiple tasks to

Hui Yang, Fa Wang

In this work, we calculate the optical response and the nonlinear Hall response of twisted bilayer graphene (TBG) in the insulating states. Different insulating states, including spin-valley polarized (SPVP) state, spin-polarized quantum Hall(SPQH) state, spin-polarized valley Hall (SPVH) state, and spin polarized Kramers-intervalley coherence (SPKIVC) state

James McKevitt

Key questions surrounding the origin and evolution of Titan and the Saturnian system in which it resides remain following the Cassini-Huygens mission. In-situ measurements performed at key locations on the body are a highly effective way to address these questions, and the aerial-aquatic platform proposed in this report serves to deliver unprecedented access

Kohei Iwaki, Omar Kidwai

For the hypergeometric spectral curve and its confluent degenerations (spectral curves of "hypergeometric type"), we obtain a simple formula expressing the topological recursion free energies as a sum over BPS states (degenerate spectral networks) for a corresponding quadratic differential $φ$. In doing so, we generalize Gaiotto-Moore-Neitzke's c

Ting Han, Ximing Liu, Ryuichi Takanobu, Yixin Lian

Task-oriented dialogue systems have made unprecedented progress with multiple state-of-the-art (SOTA) models underpinned by a number of publicly available MultiWOZ datasets. Dialogue state annotations are error-prone, leading to sub-optimal performance. Various efforts have been put in rectifying the annotation errors presented in the original MultiWOZ datas

Giovanni Saraceno, Abhik Ghosh, Ayanendranath Basu, Claudio Agostinelli

Many real-life data sets can be analyzed using Linear Mixed Models (LMMs). Since these are ordinarily based on normality assumptions, under small deviations from the model the inference can be highly unstable when the associated parameters are estimated by classical methods. On the other hand, the density power divergence (DPD) family, which measures the dis

Yujin Guo

We consider ground states of rotating Bose-Einstein condensates with attractive interactions in non-radially harmonic traps $V(x)=x_1^2+Λ^2x_2^2 $, where $0<Λ\not =1$ and $x=(x_1, x_2)\in R^2$. For any fixed rotational velocity $0\le Ω<Ω^*:=2\min \{1, Λ\}$, it is known that ground states exist if and only if $ a<a^*$ for some critical constant $0<a^*<\infty$

Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz, Bernhard Schölkopf

The detection of exoplanets in high-contrast imaging (HCI) data hinges on post-processing methods to remove spurious light from the host star. So far, existing methods for this task hardly utilize any of the available domain knowledge about the problem explicitly. We propose a new approach to HCI post-processing based on a modified half-sibling regression sc

Nomvelo Sibisi

We study the growth of a time-ordered rooted tree by probabilistic attachment of new vertices to leaves. We construct a likelihood function of the leaves based on the connectivity of the tree. We take such connectivity to be induced by the merging of directed ordered paths from leaves to the root. Combining the likelihood with an assigned prior distribution

Iftach Haitner, Omer Reingold, Salil Vadhan, Hoeteck Wee

We put forth a new computational notion of entropy, measuring the (in)feasibility of sampling high-entropy strings that are consistent with a given generator. Specifically, the i&#39;th output block of a generator G has accessible entropy at most k if the following holds: when conditioning on its prior coin tosses, no polynomial-time strategy $\widetilde{G}$

Philipp J. di Dio

In this paper we study the periodic Navier--Stokes equation. From the periodic Navier--Stokes equation and the linear equation $\partial_t u = νΔu + \mathbb{P} [v\nabla u]$ we derive the corresponding equations for the time dependent Fourier coefficients $a_k(t)$. We prove the existence of a unique smooth solution $u$ of the linear equation by a Montel space

Nicolas Perez, Pierre Delplace, Antoine Venaille

Geometrical phases, such as the Berry phase, have proven to be powerful concepts to understand numerous physical phenomena, from the precession of the Foucault pendulum to the quantum Hall effect and the existence of topological insulators. The Berry phase is generated by a quantity named Berry curvature, describing the local geometry of wave polarization re

Jose J. Fernandez-Melgarejo, Javier Molina-Vilaplana

In this work we provide a method to study the entanglement entropy for non-Gaussian states that minimize the energy functional of interacting quantum field theories at arbitrary coupling. To this end, we build a class of non-Gaussian variational trial wavefunctionals with the help of exact nonlinear canonical transformations. The calculability \emph{bonanza}

Gleb Arutyunov, Cristian Bassi, Sylvain Lacroix

By using the general framework of affine Gaudin models, we construct a new class of integrable sigma models. They are defined on a coset of the direct product of $N$ copies of a Lie group over some diagonal subgroup and they depend on $3N-2$ free parameters. For $N=1$ the corresponding model coincides with the well-known symmetric space sigma model. Starting

Vicente Garzó, Ricardo Brito, Rodrigo Soto

The Navier--Stokes transport coefficients for a model of a confined quasi-two-dimensional granular binary mixture of inelastic hard spheres are determined from the Boltzmann kinetic equation. A normal or hydrodynamic solution to the Boltzmann equation is obtained via the Chapman--Enskog method for states near the local version of the homogeneous time-depende

Linchao Bao, Xiangkai Lin, Yajing Chen, Haoxian Zhang

We present a fully automatic system that can produce high-fidelity, photo-realistic 3D digital human heads with a consumer RGB-D selfie camera. The system only needs the user to take a short selfie RGB-D video while rotating his/her head, and can produce a high quality head reconstruction in less than 30 seconds. Our main contribution is a new facial geometr

Julian Weigt

Let $0<α<d$ and $1\leq p<d/α$. We present a proof that for all $f\in W^{1,p}(\mathbb{R}^d)$ both the centered and the uncentered Hardy-Littlewood fractional maximal operator $\mathcal M_αf$ are weakly differentiable and $ \|\nabla\mathcal M_αf\|_{p^*} \leq C_{d,α,p} \|\nabla f\|_p , $ where $ p^* = (p^{-1}-α/d)^{-1} . $ In particular it covers the endpoint c

Sachindranath Jayaraman, Yogesh Kumar Prajapaty, Shrihari Sridharan

The aim of this manuscript is to understand the dynamics of products of nonnegative matrices. We extend a well known consequence of the Perron-Frobenius theorem on the periodic points of a nonnegative matrix to products of finitely many nonnegative matrices associated to a word and later to products of nonnegative matrices associated to a word, possibly of i

Hayato Chiba

Weighted degrees of quasihomogeneous Hamiltonian functions of the Painlevé equations are investigated. A tuple of positive integers, called a regular weight, satisfying certain conditions related to singularity theory is classified. Each polynomial Painlevé equation has a regular weight. Conversely, for $2$ and $4$-dim cases, it is shown that there exists a

Tobias Heinrich, Marco Taucer, Ofer Kfir, P. B. Corkum

Strong-field methods in solids enable new strategies for ultrafast nonlinear spectroscopy and provide all-optical insights into the electronic properties of condensed matter in reciprocal and real space. Additionally, solid-state media offers unprecedented possibilities to control high-harmonic generation using modified targets or tailored excitation fields.

Arian Berdellima

Let $(f^n),f$ be a sequence of proper closed convex functions defined on a Hadamard space. We show that the convergence of proximal mappings $J^n_{\lambda}x$ to $J_{\lambda}x$, under certain additional conditions, imply Mosco convergence of $f^n$ to $f$. This result is a converse to a theorem of Bacak about Mosco convergence in Hadamard spaces.

Punam Gupta, Sanjay Kumar Singh

The purpose of the present paper to study a second order symmetric parallel tensor in generalized f.pk-space form. Second order symmetric parallel tensor in f.pk-space form is combination of the associated metric tensor and $1$-forms of structure vector fields. We prove that there does not exist second order skew-symmetric parallel tensor in f.pk-space form.

Uday Chand De, Shashikant Pandey, Punam Gupta

The present paper deals with the characterization of a new submersion named semi-invariant conformal $ζ^{\perp }$-Riemannian submersion from almost contact metric manifolds onto Riemannian manifolds which is the generalization of some known submersions on Riemannian manifolds. We give important and adequate conditions for such submersions to be totally geode

Martin Hupez, Jean-François Toubeau, Zacharie De Grève, François Vallée

This paper presents an original collaborative framework for power exchanges inside a low voltage community. The community seeks to minimize its total costs by scheduling on a daily basis the resources of its members. In this respect, their flexibility such as excess storage capacity, unused local generation or shiftable load are exploited. Total costs includ

Cyril Letrouit, Chenmin Sun

In this article, we study the observability (or, equivalently, the controllability) of some subelliptic evolution equations depending on their step. This sheds light on the speed of propagation of these equations, notably in the &#34;degenerated directions&#34; of the subelliptic structure. First, for any $γ\geq 1$, we establish a resolvent estimate for the

S. Yoshida, T. Koyama, H. Yamada, Y. Nakai

SmS, a prototypical intermediate valence compound, has been studied by performing high-pressure nuclear magnetic resonance measurements on a $^{33}$S-enriched sample. The observation of an additional signal below 15-20 K above a nonmagnetic-magnetic transition pressure $P_{\rm c2} \approx 2$ GPa gives evidence of a magnetic transition. The absence of a Curie

Robert Alicki, David Gelbwaser-Klimovsky, Alejandro Jenkins

We introduce the &#34;leaking elastic capacitor&#34; (LEC) model, a nonconservative dynamical system that combines simple electrical and mechanical degrees of freedom. We show that an LEC connected to an external voltage source can be destabilized (Hopf bifurcation) due to positive feedback between the mechanical separation of the plates and their electrical

Eduardo Vitral, Gary A. Mamon

We analyze proper motions from the Hubble Space Telescope (HST) and the second Gaia data release along with line-of-sight velocities from the MUSE spectrograph to detect imprints of an intermediate-mass black hole (IMBH) in the center of the nearby, core-collapsed, globular cluster NGC 6397. For this, we use the new MAMPOSSt-PM Bayesian mass-modeling code, a

Yuhao Qi, Jian Dang, Zaichen Zhang, Liang Wu

Filter bank multiple access (FBMA) without subbands orthogonality has been proposed as a new candidate waveform to better meet the requirements of future wireless communication systems and scenarios. It has the ability to process directly the complex symbols without any fancy preprocessing. Along with the usage of cyclic prefix (CP) and wide-banded subband d

Phanwadee Sinthong, Michael J. Carey

In the last few years, the field of data science has been growing rapidly as various businesses have adopted statistical and machine learning techniques to empower their decision making and applications. Scaling data analysis, possibly including the application of custom machine learning models, to large volumes of data requires the utilization of distribute

Barbara Dembin, Marie Théret

We consider the standard first passage percolation model in the rescaled lattice $\mathbb{Z}^d$ for $d\geq 2$ and a bounded domain $Ω$ in $\mathbb R ^d$. We denote by $Γ^1$ and $Γ^2$ two disjoint subsets of $\partial Ω$ representing respectively the source and the sink, i.e., where the water can enter in $Ω$ and escape from $Ω$. A maximal stream is a vector

Xiangru Tang, Alan Aw

Detection of semantic similarity plays a vital role in sentence matching. It requires to learn discriminative representations of natural language. Recently, owing to more and more sophisticated model architecture, impressive progress has been made, along with a time-consuming training process and not-interpretable inference. To alleviate this problem, we exp

Ömer Eğecioğlu, Vesna Iršič

Among the classical models for interconnection networks are hypercubes and Fibonacci cubes. Fibonacci cubes are induced subgraphs of hypercubes obtained by restricting the vertex set to those binary strings which do not contain consecutive 1s, counted by Fibonacci numbers. Another set of binary strings which are counted by Fibonacci numbers are those with a

Carolin Lawrence, Timo Sztyler, Mathias Niepert

Explaining the predictions of neural black-box models is an important problem, especially when such models are used in applications where user trust is crucial. Estimating the influence of training examples on a learned neural model&#39;s behavior allows us to identify training examples most responsible for a given prediction and, therefore, to faithfully ex

Luca Bedogni, Shakila Khan Rumi, Flora Salim

In 2020 the coronavirus outbreak changed the lives of people worldwide. After an initial time period in which it was unclear how to battle the virus, social distancing has been recognised globally as an effective method to mitigate the disease spread. This called for technological tools such as Mobile Contact Tracing Applications (MCTA), which are used to di

I. Delvecchio, E. Daddi, M. T. Sargent, M. J. Jarvis

Several works in the past decade have used the ratio between total (rest 8-1000$μ$m) infrared and radio (rest 1.4~GHz) luminosity in star-forming galaxies (q$_{IR}$), often referred to as the &#34;infrared-radio correlation&#34; (IRRC), to calibrate radio emission as a star formation rate (SFR) indicator. Previous studies constrained the evolution of q$_{IR}

Viktor Holubec, Rahul Marathe

Active Brownian engines rectify energy from reservoirs composed of self-propelling non-equilibrium molecules into work. We consider a class of such engines based on an underdamped Brownian particle trapped in a power-law potential. The energy they transform has thermodynamic properties of heat only if the non-equilibrium reservoir can be assigned a suitable

Shuji Yamamoto

The duality relation of one-variable multiple polylogarithms was proved by Hirose, Iwaki, Sato and Tasaka by means of iterated integrals. In this paper, we give a new proof using the method of connected sums, which was recently invented by Seki and the author. Interestingly, the connected sum involves the hypergeometric function in its connector. Moreover, w

Ruoyang Qi, Haoran Zhang, Jiancun Gao, Liuguo Yin

Robust, simple, and flexible quantum key distribution (QKD) is vital for realising practical applications of this technique. Contrary to typical phase-coded QKD schemes, the plug-and-play QKD design requires only one arm-length-insensitive interferometer without active feedback, in which the noise is automatically compensated by the two-way structure. Howeve

Abu Quwsar Ohi, M. F. Mridha, Md. Abdul Hamid, Muhammad Mostafa Monowar

Speaker recognition is an active research area that contains notable usage in biometric security and authentication system. Currently, there exist many well-performing models in the speaker recognition domain. However, most of the advanced models implement deep learning that requires GPU support for real-time speech recognition, and it is not suitable for lo

Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding

To alleviate the resource constraint for real-time point cloud applications that run on edge devices, in this paper we present BiPointNet, the first model binarization approach for efficient deep learning on point clouds. We discover that the immense performance drop of binarized models for point clouds mainly stems from two challenges: aggregation-induced f

Jonathan Wernersson, Jochen Zahn

We study the effect of boundary conditions on vacuum polarization for charged scalar fields in two space-time dimensions. We find that both Dirichlet and Neumann boundary conditions lead to screening. In the Dirichlet case, the vacuum polarization charge density vanishes at the boundary, whereas it attains its maximum there for Neumann boundary conditions. A

Junya Nakamura, Sayaka Kamei, Yukiko Yamauchi

A metamorphic robotic system (MRS) is composed of anonymous, memoryless, and autonomous modules that execute an identical distributed algorithm to move while keeping the connectivity of the modules. For an MRS, the number of modules required to solve a given task is an important complexity measure. Here, we consider evacuation from a finite two-dimensional s

HyeonJun Kim

Feature extraction is an important process of machine learning and deep learning, as the process make algorithms function more efficiently, and also accurate. In natural language processing used in deception detection such as fake news detection, several ways of feature extraction in statistical aspect had been introduced (e.g. N-gram). In this research, it

David Weisbart

A $p$-adic Brownian motion is a continuous time stochastic process in a $p$-adic state space that has a Vladimirov operator as its infinitesimal generator. The current work shows that any such process is the scaling limit of a discrete time random walk on a discrete group. Earlier work required the exponent of the Vladimirov operator to be in $(1, \infty)$,

Trenton Schulz, Till Halbach, Ivar Solheim

Social robots have been shown to help in language education for children. This can be good aid for immigrant children that need additional help to learn a second language their parents do not understand to attend school. We present the setup for a long-term study that is being carried out in blinded to aid immigrant children with poor skills in the Norwegian

William Oçafrain

This paper deals with ergodic theorems for particular time-inhomogeneous Markov processes, whose the time-inhomogeneity is asymptotically periodic. Under a Lyapunov/minorization condition, it is shown that, for any measurable bounded function $f$, the time average $\frac{1}{t} \int_0^t f(X_s)ds$ converges in $\mathbb{L}^2$ towards a limiting distribution, st

Senthil Velan S, Chitra Babu

Aspect Oriented Software Development (AOSD) is a promising methodology which provides powerful techniques to improve the modularity of the software by separating the cross-cutting concerns from the core functionality. Since evolution is a major requirement for the sustainability of any software, it is necessary to quantitatively measure its impact. In order

Tanya Goyal, Greg Durrett

Despite significant progress in text generation models, a serious limitation is their tendency to produce text that is factually inconsistent with information in the input. Recent work has studied whether textual entailment systems can be used to identify factual errors; however, these sentence-level entailment models are trained to solve a different problem

Xin Han, Ye Zhu, Kai Ming Ting, Gang Li

Agglomerative hierarchical clustering (AHC) is one of the popular clustering approaches. Existing AHC methods, which are based on a distance measure, have one key issue: it has difficulty in identifying adjacent clusters with varied densities, regardless of the cluster extraction methods applied on the resultant dendrogram. In this paper, we identify the roo

Jun Guo, Jinmian Li, Tianjun Li, Rao Zhang

By representing each collider event as a point cloud, we adopt the Graphic Convolutional Network (GCN) with focal loss to reconstruct the Higgs jet in it. This method provides higher Higgs tagging efficiency and better reconstruction accuracy than the traditional methods which use jet substructure information. The GCN, which is trained on events of the $H$+j

Francisco Leonardo Bezerra Martins, José Cláudio do Nascimento

Several populational networks present complex topologies when implemented in evolutionary algorithms. A common feature of these topologies is the emergence of a power law. Power law behavior with different scaling factors can also be observed in genealogical networks, but we still can not satisfactorily describe its dynamics or its relation to population evo

Manuel Friedrich, Matteo Perugini, Francesco Solombrino

We analyze the $Γ$-convergence of sequences of free-discontinuity functionals arising in the modeling of linear elastic solids with surface discontinuities, including phenomena as fracture, damage, or material voids. We prove compactness with respect to $Γ$-convergence and represent the $Γ$-limit in an integral form defined on the space of generalized specia

B Swaroopa Reddy, G V V Sharma

In this paper, we propose two models for scaling the transaction throughput in Proof-of-Work (PoW) based blockchain networks. In the first approach, a mathematical model has derived for optimal transaction throughput for PoW based longest chain rule blockchain. In this approach, the blockchain Peer-to-Peer (P2P) network is considered as Erdös-Rényi random ne

Jing Zhang, Bo Chen, Lingxi Zhang, Xirui Ke

Knowledge graph reasoning is the fundamental component to support machine learning applications such as information extraction, information retrieval, and recommendation. Since knowledge graphs can be viewed as the discrete symbolic representations of knowledge, reasoning on knowledge graphs can naturally leverage the symbolic techniques. However, symbolic r

Diksha Dhawan, Mekena Metcalf, Dominika Zgid

For noisy intermediate-scale quantum (NISQ) devices only a moderate number of qubits with a limited coherence is available thus enabling only shallow circuits and a few time evolution steps in the currently performed quantum computations. Here, we present how to bypass this challenge in practical molecular chemistry simulations on NISQ devices by employing a

Shu Sun, Xiaofeng Li, Sungho Moon

In this paper, we propose two novel and practical deep-learning-based algorithms to solve the wireless channel type (WCT) recognition problem. Specifically, the WCT recognition problem is recast as a classification problem in deep learning due to their similarities, where a deep neural network (DNN) is trained off-line with a diversity of typical WCTs for fi

Jessie Finocchiaro, Roland Maio, Faidra Monachou, Gourab K Patro

Decision-making systems increasingly orchestrate our world: how to intervene on the algorithmic components to build fair and equitable systems is therefore a question of utmost importance; one that is substantially complicated by the context-dependent nature of fairness and discrimination. Modern decision-making systems that involve allocating resources or i

Haruhisa Enomoto, Arashi Sakai

In this paper, we study ICE-closed (= Image-Cokernel-Extension-closed) subcategories of an abelian length category using torsion classes. To each interval $[\mathcal{U},\mathcal{T}]$ in the lattice of torsion classes, we associate a subcategory $\mathcal{T} \cap \mathcal{U}^\perp$ called the heart. We show that every ICE-closed subcategory can be realized as

Shayan Hassantabar, Prerit Terway, Niraj K. Jha

The human brain has the ability to carry out new tasks with limited experience. It utilizes prior learning experiences to adapt the solution strategy to new domains. On the other hand, deep neural networks (DNNs) generally need large amounts of data and computational resources for training. However, this requirement is not met in many settings. To address th

T. M. Dunster

Asymptotic expansions are derived for solutions of the parabolic cylinder and Weber differential equations. In addition the inhomogeneous versions of the equations are considered, for the case of polynomial forcing terms. The expansions involve exponential, Airy and Scorer functions and slowly varying analytic coefficient functions involving simple coefficie

Stephen Casper

As progress in AI continues to advance, it is important to know how advanced systems will make choices and in what ways they may fail. Machines can already outsmart humans in some domains, and understanding how to safely build ones which may have capabilities at or above the human level is of particular concern. One might suspect that artificially generally

Yoshiaki Sofue

An almost perfect round hole of CO-line emission with a diameter of 3.7 pc was found in a molecular cloud (MC) centered on G35.75-0.25 ($l = 35^\circ.75, b = -0^\circ.25$) at radial velocity of 28 km s$^{-1}$. The hole is quiet in radio continuum emission, unlike the usual supernova remnants (SNR), and the molecular edge is only weakly visible in 8 and 24 $μ

Jiaojiao Guo, Junsong Sun, Xingchuan Zhu, Chang-An Li

We study the higher-order topological spin phases based on a spin analogue of Benalcazar-Bernevig-Hughes model in two dimensions using large-scale quantum Monte Carlo simulations. A continuous Néel-valence bond solid quantum phase transition is revealed by tuning the ratio between dimerized spin couplings, namely, the weak and strong exchange couplings. Thro

Qiongling Li, Takuro Mochizuki

On a Riemann surface with a holomorphic $r$-differential, one can naturally define a Toda equation and a cyclic Higgs bundle with a grading. A solution of the Toda equation is equivalent to a harmonic metric of the Higgs bundle for which the grading is orthogonal. Here we focus on a general non-compact Riemann surface with an $r$-differential which is not ne

Sandeep Sharma, Gregory Beylkin

By using Poisson&#39;s summation formula, we calculate periodic integrals over Gaussian basis functions by partitioning the lattice summations between the real and reciprocal space, where both sums converge exponentially fast with a large exponent. We demonstrate that the summation can be performed efficiently to calculate 2-center Gaussian integrals over va

Derek Singh, Shuzhong Zhang

This paper expands the notion of robust moment problems to incorporate distributional ambiguity using Wasserstein distance as the ambiguity measure. The classical Chebyshev-Cantelli (zeroth partial moment) inequalities, Scarf and Lo (first partial moment) bounds, and semideviation (second partial moment) in one dimension are investigated. The infinite dimens

Yun Yue, Ming Li, Venkatesh Saligrama, Ziming Zhang

We propose a novel and efficient training method for RNNs by iteratively seeking a local minima on the loss surface within a small region, and leverage this directional vector for the update, in an outer-loop. We propose to utilize the Frank-Wolfe (FW) algorithm in this context. Although, FW implicitly involves normalized gradients, which can lead to a slow

Zhiyang Lu, Jun Li, Zheng Li, Hongjian He

Quantitative Susceptibility Mapping (QSM) is a new phase-based technique for quantifying magnetic susceptibility. The existing QSM reconstruction methods generally require complicated pre-processing on high-quality phase data. In this work, we propose to explore a new value of the high-pass filtered phase data generated in susceptibility weighted imaging (SW

Fred Glover

A variety of strategies have been proposed for overcoming local optimality in metaheuristic search. This paper examines characteristics of moves that can be exploited to make good decisions about steps that lead away from a local optimum and then lead toward a new local optimum. We introduce strategies to identify and take advantage of useful features of sol

Yanyu Jia, Pengjie Wang, Cheng-Li Chiu, Zhida Song

The interplay between topology and correlations can generate a variety of quantum phases, many of which remain to be explored. Recent advances have identified monolayer WTe2 as a promising material for doing so in a highly tunable fashion. The ground state of this two-dimensional (2D) crystal can be electrostatically tuned from a quantum spin Hall insulator

Shota Hamanaka

In this paper, we give a sufficient condition for a positive constant scalar curvature metric on a manifold with boundary to be a relative Yamabe metric, which is a natural relative version of the classical Yamabe metric. We also give examples of non-Einstein relative Yamabe metrics with positive scalar curvature.

Pengjie Wang, Guo Yu, Yanyu Jia, Michael Onyszczak

In strongly correlated materials, quasiparticle excitations can carry fractional quantum numbers. An intriguing possibility is the formation of fractionalized, charge-neutral fermions, e.g., spinons and fermionic excitons, that result in neutral Fermi surfaces and Landau quantization in an insulator. While previous experiments in quantum spin liquids, topolo

Ted Moskovitz, Michael Arbel, Ferenc Huszar, Arthur Gretton

A novel optimization approach is proposed for application to policy gradient methods and evolution strategies for reinforcement learning (RL). The procedure uses a computationally efficient Wasserstein natural gradient (WNG) descent that takes advantage of the geometry induced by a Wasserstein penalty to speed optimization. This method follows the recent the

Edoardo Lanari, Luis Scoccola

The homotopy interleaving distance, a distance between persistent spaces, was introduced by Blumberg and Lesnick and shown to be universal, in the sense that it is the largest homotopy-invariant distance for which sublevel-set filtrations of close-by real-valued functions are close-by. There are other ways of constructing homotopy-invariant distances, but no

Xiaoyu Cheng

Consider a persuasion game where both the sender and receiver are ambiguity averse with maxmin expected utility (MEU) preferences and the sender can choose an ambiguous information structure. This paper analyzes the game in an ex-ante formulation: the sender first commits to an information structure, and then the receiver best responds by choosing an ex-ante

Sadataka Furui

An overview of hadron spectroscopy obtained from an extension of superconformal field theory of de Alfaro, Fubini and Furlan, which originates from the supergauge transformation of Wess and Zumino and influenced on the string theory are preseted. The standard model of hadron dynamics is based on gauge theory. In the 4 dimensional ($4D$) QCD Lagrangian, the F

Raunak Sinha, Utkarsh Desai, Srikanth Tamilselvam, Senthil Mani

With the increase in the number of open repositories and discussion forums, the use of natural language for semantic code search has become increasingly common. The accuracy of the results returned by such systems, however, can be low due to 1) limited shared vocabulary between code and user query and 2) inadequate semantic understanding of user query and it

Vivien Cabannes, Thomas Kerdreux, Louis Thiry

We propose visual creations that put differences in algorithms and humans \emph{perceptions} into perspective. We exploit saliency maps of neural networks and visual focus of humans to create diptychs that are reinterpretations of an original image according to both machine and human attentions. Using those diptychs as a qualitative evaluation of perception,

Harikrishnan NB, Pranay SY, Nithin Nagaraj

There has been empirical evidence of presence of non-linearity and chaos at the level of single neurons in biological neural networks. The properties of chaotic neurons inspires us to employ them in artificial learning systems. Here, we propose a Neurochaos Learning (NL) architecture, where the neurons used to extract features from data are 1D chaotic maps.

Sabyasachi Chatterjee, Amit Acharya

A formal hierarchy of exact evolution equations are derived for physically relevant space-time averages of state functions of microscopic dislocation dynamics. While such hierarchies are undoubtedly of some value, a primary goal here is to expose the intractable complexity of such systems of nonlinear partial differential equations that, furthermore, remain

Isabel Santos-Santos, Rosa Dominguez-Tenreiro, Marcel S. Pawlowski

We present a detailed characterization of planes of satellite galaxies in the Milky Way (MW) and M31. For a positional analysis, we introduce an extension to the `4-galaxy-normal density plot&#39; method \citep[][P13]{Pawlowski13}. It finds the normal directions to the predominant planar configurations of satellites of a system, yielding for each a \textit{c

Yunkyu Bang, Y. M. Cho, Tieyan Si, Li-Ping Zou

We discuss the Abelian and non-Abelian monopoles which could exist in condensed matters. We show how the Dirac monopole can be regularized by the charge screening, and argue that the Dirac monopole of mass of hundred meVs could exist in dielectric condensed matters. Moreover, we generalize this result to non-Abelian condensed matters to show the existence of

Alejandro Cohen, Amit Solomon, Ken R. Duffy, Muriel Médard

We introduce Noise Recycling, a method that enhances decoding performance of channels subject to correlated noise without joint decoding. The method can be used with any combination of codes, code-rates and decoding techniques. In the approach, a continuous realization of noise is estimated from a lead channel by subtracting its decoded output from its recei

Mariia Mykhailova, Krysta M. Svore

Quantum computing harnesses quantum laws of nature to enable new types of algorithms, not efficiently possible on traditional computers, that may lead to breakthroughs in crucial areas like materials science and chemistry. There is rapidly growing demand for a quantum workforce educated in the basics of quantum computing, in particular in quantum programming

William M. McGovern

We give a necessary and sufficient condition in terms of pattern avoidance for the conjugates of the bottom vertex in the Bruhat graph attached to an O_n orbit O in the flag variety for GL_n to have degree equal to the rank of this graph as a poset, showing that this condition is equivalent to the rational smoothness of the closure of O. We also give a neces

Pablo Ouro, Unai Lopez-Novoa, Martyn Guest

No area of computing is hungrier for performance than High Performance Computing (HPC), the demands of which continue to be a major driver for processor performance and adoption of accelerators, and also advances in memory, storage, and networking technologies. A key feature of the Intel processor domination of the past decade has been the extensive adoption

Wei Hong

In this paper, we give an explicit description of holomorphic polyvector fields on smooth compact toric varieties, which generalizes Demazure&#39;s result of holomorphic vector fields on toric varieties.

Konstantinos Kyritsis, Christos Diou, Anastasios Delopoulos

The increased worldwide prevalence of obesity has sparked the interest of the scientific community towards tools that objectively and automatically monitor eating behavior. Despite the study of obesity being in the spotlight, such tools can also be used to study eating disorders (e.g. anorexia nervosa) or provide a personalized monitoring platform for patien

J. C. Buitrago-Casas, S. Christe, L. Glesener, S. Krucker

Imaging X-rays by direct focusing offers greater sensitivity and a higher dynamic range compared to techniques based on indirect imaging. The Focusing Optics X-ray Solar Imager (FOXSI) is a sounding rocket payload that uses seven sets of nested Wolter-I figured mirrors to observe the Sun in hard X-rays through direct focusing. Characterizing the performance

Drew Duncan, David B. Leep

We determine the minimal number of variables $Γ^*(d, K)$ which guarantees a nontrivial solution for every additive form of degree $d=2m$, $m$ odd, $m \ge 3$ over the six ramified quadratic extensions of $\mathbb{Q}_2$. We prove that if $K$ is one of $\{\mathbb{Q}_2(\sqrt{2}), \mathbb{Q}_2(\sqrt{10}), \mathbb{Q}_2(\sqrt{-2}), \mathbb{Q}_2(\sqrt{-10})\}$, $Γ^*

Quan Huu Cap, Hiroki Tani, Hiroyuki Uga, Satoshi Kagiwada

The collection of high-resolution training data is crucial in building robust plant disease diagnosis systems, since such data have a significant impact on diagnostic performance. However, they are very difficult to obtain and are not always available in practice. Deep learning-based techniques, and particularly generative adversarial networks (GANs), can be

Mariam Pirashvili

This paper is concerned with the nonabelian cohomology of groups with coefficients in crossed modules. These objects were introduced by Dedecker and studied by Breen, Borovoi, Noohi and many others. In this paper we study several important objects that are classified by these cohomologies and for them we develop a theory similar to the Schreier obstruction t

Lloyd Montgomery

Large software organizations handle many customer support issues every day in the form of bug reports, feature requests, and general misunderstandings as submitted by customers. Strategies to gather, analyze, and negotiate requirements are complemented by efforts to manage customer input after products have been deployed. For the latter, support tickets are

Abbas Rabiee, Andrew Keane, Alireza Soroudi

Extracting green hydrogen from renewable energy sources is a new concept in the energy industry. As an energy carrier, hydrogen is well capable of facilitating a strong coupling between various energy sectors, as well as integration of renewable energy sources. This paper investigates the system-wide technical factors that might limit the amount of producibl

Arjun Pawar

In this article, we present a short, non-exhaustive study of an important and well-known property of combinatorial sequences - unimodality. We shall have a look at a sample of classical results on unimodality and related properties, and then proceed to understand the unimodality of the Gaussian polynomial in more detail. We will look at an outline of O&#39;H

Yifei Liu, Emil Prodan

Quasi-periodic quantum spin chains were recently found to support many topological phases in the finite magnetization sectors. They can simulate strong topological phases from class A in arbitrary dimension that are characterized by first and higher order Chern numbers. In the present work, we use those findings to generate topological phases at finite magne

Hartmut Pecher

The Cauchy problem for the Yang-Mills system in two space dimensions is treated for data with minimal regularity assumptions. In the classical case of data in $L^2$-based Sobolev spaces we have to assume that the number of derivatives is more than $3/4$ above the critical regularity with respect to scaling. For data in $L^r$-based Fourier-Lebesgue spaces thi