May 2019 arXiv papers — page 4

Shaon Sahoo, Imke Schneider, Sebastian Eggert

Driving a quantum system periodically in time can profoundly alter its long-time correlations and give rise to exotic quantum states of matter. The complexity of the combination of many-body correlations and dynamic manipulations has the potential to uncover a whole field of new phenomena, but the theoretical and numerical understanding becomes extremely dif

Pheerawich Chitnelawong, Francesco Sciortino, Peter H. Poole

The stability-limit conjecture (SLC) proposes that the liquid spinodal of water returns to positive pressure in the supercooled region, and that the apparent divergence of water's thermodynamic response functions as temperature decreases are explained by the approach to this reentrant spinodal. Subsequently, it has been argued that the predictions of the

Alkan Soysal, Sennur Ulukus

We consider the age of information in G/G/1/1 systems under two service discipline models. In the first model, if a new update arrives when the service is busy, it is blocked; in the second model, a new update preempts the current update in service. For the blocking model, we first derive an exact age expression, then we propose two simple to calculate upper

Yuri Cavecchi, Anatoly Spitkovsky

We present the first realistic 3D simulations of flame front instabilities during type I X-ray bursts. The unperturbed front is characterised by the balance between the pressure gradient and the Coriolis force of a spinning neutron star (ν = 450 Hz in our case). This balance leads to a fast horizontal velocity field parallel to the flame front. This flow is

G. S. Bisnovatyi-Kogan

The exact time-dependent solution is obtained for a magnetic field growth during a spherically symmetric accretion into a black hole (BH) with a Schwarzschild metric. Magnetic field is increasing with time, changing from the initially uniform into a quasi-radial field. Equipartition between magnetic and kinetic energies in the falling gas is established in t

David Moews

Given a distribution of pebbles on the vertices of a graph, say that we can pebble a vertex if a pebble is left on it after some sequence of moves, each of which takes two pebbles from some vertex and places one on an adjacent vertex. A distribution is solvable if all vertices are pebblable; the pebbling threshold of a sequence of graphs is, roughly speaking

Davi B. Costa, Bogdan A. Dobrescu, Patrick J. Fox

The anomaly cancellation equations for the $U(1)$ gauge group can be written as a cubic equation in $n-1$ integer variables, where $n$ is the number of Weyl fermions carrying the $U(1)$ charge. We solve this Diophantine cubic equation by providing a parametrization of the charges in terms of $n-2$ integers, and prove that this is the most general solution.

Ziniu Hu, Changjun Fan, Ting Chen, Kai-Wei Chang

Graph neural networks (GNNs) are shown to be successful in modeling applications with graph structures. However, training an accurate GNN model requires a large collection of labeled data and expressive features, which might be inaccessible for some applications. To tackle this problem, we propose a pre-training framework that captures generic graph structur

Alessandro Pigati, Daniel Stern

Given a Hermitian line bundle $L\to M$ over a closed, oriented Riemannian manifold $M$, we study the asymptotic behavior, as $ε\to 0$, of couples $(u_ε,\nabla_ε)$ critical for the rescalings \begin{align*} &E_ε(u,\nabla)=\int_M\Big(|\nabla u|^2+ε^2|F_\nabla|^2+\frac{1}{4ε^2}(1-|u|^2)^2\Big) \end{align*} of the self-dual Yang-Mills-Higgs energy, where $u$ is

Pasquale Candito, Roberto Livrea, Abdelkrim Moussaoui

In this paper we establish existence of smooth positive solutions for a singular quasilinear elliptic system involving gradient terms. The approach combines sub-supersolutions method and Schauder's fixed point theorem.

Livio Pizzocchero, Emanuele Tassi

Inspired by an approach proposed previously for the incompressible Navier-Stokes (NS) equations, we present a general framework for the a posteriori analysis of the equations of incompressible magnetohydrodynamics (MHD) on a torus of arbitrary dimension d; this setting involves a Sobolev space of infinite order, made of C^infinity vector fields (with vanishi

Wen-Ji Zhou, Yang Yu, Yingfeng Chen, Kai Guan

Experience reuse is key to sample-efficient reinforcement learning. One of the critical issues is how the experience is represented and stored. Previously, the experience can be stored in the forms of features, individual models, and the average model, each lying at a different granularity. However, new tasks may require experience across multiple granularit

D. G. Bussandri, T. M. Osán, A. P. Majtey, P. W. Lamberti

In this paper we use the Fano representation of two-qubit states from which we can identify a correlation matrix containing the information about the classical and quantum correlations present in the bipartite quantum state. To illustrate the use of this matrix, we analyze the behavior of the correlations under non-dissipative decoherence in two-qubit states

Julia Strout, Ye Zhang, Raymond J. Mooney

Work on "learning with rationales" shows that humans providing explanations to a machine learning system can improve the system's predictive accuracy. However, this work has not been connected to work in "explainable AI" which concerns machines explaining their reasoning to humans. In this work, we show that learning with rationales can a

B. G. Christensen, C. D. Wilen, A. Opremcak, J. Nelson

We have used Ramsey tomography to characterize charge noise in a weakly charge-sensitive superconducting qubit. We find a charge noise that scales with frequency as $1/f^α$ over 5 decades with $α= 1.93$ and a magnitude $S_q(\text{1Hz})= 2.9\times10^{-4}~e^2/\text{Hz}$. The noise exponent and magnitude of the low-frequency noise are much larger than those see

N. Bahjat-Abbas, D. Bonocore, J. Sinninghe Damsté, E. Laenen

Perturbative cross-sections in QCD are beset by logarithms of kinematic invariants, whose arguments vanish when heavy particles are produced near threshold. Contributions of this type often need to be summed to all orders in the coupling, in order to improve the behaviour of the perturbative expansion, and it has long been known how to do this at leading pow

Shahrazad M. A. Malek, Peter H. Poole, Ivan Saika-Voivod

We estimate the liquid-vapour surface tension from simulations of TIP4P/2005 water nanodroplets of size $N$=100 to 2880 molecules over a temperature $T$ range of 180 K to 300 K. We compute the planar surface tension $γ_p$, the curvature-dependent surface tension $γ_s$, and the Tolman length $δ$, via two approaches, one based on the pressure tensor (the "

Maurice Oliva-Leyva, Gerardo Gonzalez de la Cruz

In this work, we present a theoretical study of the dispersion of linearly polarized light between two dielectric media separated by an anisotropic two-dimensional (2D) material under oblique incidence. Assuming that the 2D material is a conducting sheet of negligible thickness, generalized Fresnel coefficients are derived as a function of usual quantities (

Stephanie Weirich, Pritam Choudhury, Antoine Voizard, Richard A. Eisenberg

Modern Haskell supports zero-cost coercions, a mechanism where types that share the same run-time representation may be freely converted between. To make sure such conversions are safe and desirable, this feature relies on a mechanism of roles to prohibit invalid coercions. In this work, we show how to integrate roles with dependent type systems and prove, u

Yi-Qi Hu, Yang Yu, Jun-Da Liao

An automatic machine learning (AutoML) task is to select the best algorithm and its hyper-parameters simultaneously. Previously, the hyper-parameters of all algorithms are joint as a single search space, which is not only huge but also redundant, because many dimensions of hyper-parameters are irrelevant with the selected algorithms. In this paper, we propos

Bo Y. Chang, Seokmin Shin, Vladimir S. Malinovsky, Ignacio R. Sola

The two-dimensional electron-nuclear Schrödinger equation using soft-core Coulomb potentials has been a cornerstone for modeling and predicting the behavior of one-active-electron diatomic molecules, particularly for processes where both bound and continuum states are important. The model, however, is computationally expensive to extend to more electron or n

Takayuki KOBAYASHI, Kazuyuki TSUDA

Time decay estimate of solutions to the compressible Navier-Stokes-Korteweg system is studied. Concerning the linearized problem, the decay estimate with diffusion wave property for an initial data is derived. As an application, the time decay estimate of solutions to the nonlinear problem is given. In contrast to the compressible Navier-Stokes system, for l

Martin Jankowiak, Jacob Gardner

We construct flexible likelihoods for multi-output Gaussian process models that leverage neural networks as components. We make use of sparse variational inference methods to enable scalable approximate inference for the resulting class of models. An attractive feature of these models is that they can admit analytic predictive means even when the likelihood

Charles Ringer, James Alfred Walker, Mihalis A. Nicolaou

Video game streaming provides the viewer with a rich set of audio-visual data, conveying information both with regards to the game itself, through game footage and audio, as well as the streamer's emotional state and behaviour via webcam footage and audio. Analysing player behaviour and discovering correlations with game context is crucial for modelling

Marija Kranjcevic, Shahnam Gorgi Zadeh, Andreas Adelmann, Peter Arbenz

High current storage rings, such as the Z-pole operating mode of the FCC-ee, require accelerating cavities that are optimized with respect to both the fundamental mode and the higher order modes. Furthermore, the cavity shape needs to be robust against geometric perturbations which could, for example, arise from manufacturing inaccuracies or harsh operating

Gael Reecht, Nils Krane, Christian Lotze, Katharina J. Franke

For a molecular radical to be stable, the environment needs to be inert. Furthermore, an unpaired electron is less likely to react chemically, when it is placed in an extended orbital. Here, we use the tip of a scanning tunneling microscope to abstract one of the pyrrolic hydrogen atoms from phthalocyanine (H2Pc) deposited on a single layer of molybdenum dis

Abigail Folha, Harold Rosenberg

For $0\leq H< 1/2$, we construct entire $H$-graphs in $\mathbb{H}^2\times\mathbb{R}$ that are parabolic and not invariant by one parameter groups of isometries of $\mathbb{H}^2\times\mathbb{R}$. Their asymptotic boundaries are $(\partial_\infty\mathbb{H}^2)\times\mathbb{R}$; they are dense at infinity. When $H=0$ the examples are minimal graphs constructed b

Daniel Schäufele, Renato L. G. Cavalcante, Slawomir Stanczak

Radio maps are important enablers for many applications in wireless networks, ranging from network planning and optimization to fingerprint based localization. Sampling the complete map is prohibitively expensive in practice, so methods for reconstructing the complete map from a subset of measurements are increasingly gaining attention in the literature. In

Federico Baldassarre, Hossein Azizpour

Graph Networks are used to make decisions in potentially complex scenarios but it is usually not obvious how or why they made them. In this work, we study the explainability of Graph Network decisions using two main classes of techniques, gradient-based and decomposition-based, on a toy dataset and a chemistry task. Our study sets the ground for future devel

Adarsh M. Subramaniam, Anoosheh Heiderzadeh, Krishna R. Narayanan

We show that polynomial codes (and some related codes) used for distributed matrix multiplication are interleaved Reed-Solomon codes and, hence, can be collaboratively decoded. We consider a fault tolerant setup where $t$ worker nodes return erroneous values. For an additive random Gaussian error model, we show that for all $t < N-K$, errors can be corrected

Joshua Isralowitz, Sandra Pott, Israel P. Rivera-Ríos

Given $1\leq q<p<\infty$ quantitative weighted L^p estimates, in terms of Aq weights, for vector valued maximal functions, Calderón-Zygmund operators, commutators and maximal rough singular integrals are obtained. The results for singular operators will rely upon suitable convex body domination results, which in the case of commutators will be provided in th

Hideo Takaoka

We study a dynamics and energy exchanges between a linear oscillator and a nonlinear interaction state for the one dimensional, quintic nonlinear Schrodinger equation. Grebert and Thomann proved that there exist solutions with initial data built on four Fourier modes, that confirms the conservative exchange of wave energy. Captured multi resonance in multipl

Shalini Tomar, Barun Ghosh, Sougata Mardanya, Priyank Rastogi

Two dimensional magnetic materials, with tunable electronic properties could lead to new spintronic, magnetic and magneto-optic applications. Here, we explore intrinsic magnetic ordering in two dimensional monolayers of transition metal tri-halides (MX$_3$, M = V, Cr, Mn, Fe and Ni, and X = F, Cl, Br and I), using density functional theory. We find that othe

A. Alexandrov, M. Ye. Zhuravlev, Evgeny Y. Tsymbal

Using a simple quantum-mechanical model, we explore a tunneling anisotropic magnetoresistance (TAMR) effect in ferroelectric tunnel junctions (FTJs) with a ferromagnetic electrode and a ferroelectric barrier layer, which spontaneous polarization gives rise to the Rashba and Dresselhaus spin-orbit coupling (SOC). For realistic parameters of the model, we pred

Song Yaoxian, Cheng Chun, Fei Yuejiao, Li Xiangqing

We consider the problem of robotic grasping using depth + RGB information sampling from a real sensor. we design an encoder-decoder neural network to predict grasp policy in real time. This method can fuse the advantage of depth image and RGB image at the same time and is robust for grasp and observation height.We evaluate our method in a physical robotic sy

Gerald Baumgartner, Konstantin Läufer, Vincent F. Russo

Design patterns are distilled from many real systems to catalog common programming practice. However, some object-oriented design patterns are distorted or overly complicated because of the lack of supporting programming language constructs or mechanisms. For this paper, we have analyzed several published design patterns looking for idiomatic ways of working

Tatsuma Yamaguchi, Yuichiro Matsuzaki, Shiro Saito, Hideyuki Watanabe

Recently we have demonstrated AC magnetic field sensing scheme using a simple continuous-wave optically detected magnetic resonance of nitrogen-vacancy centers in diamond [Appl. Phys. Lett. 113, 082405 (2018)]. This scheme is based on electronic spin double resonance excited by continuous microwaves and radio-frequency (RF) fields. Here we measured and analy

STAR Collaboration, J. Adam, L. Adamczyk, J. R. Adams

$J/ψ$ suppression has long been considered a sensitive signature of the formation of the Quark-Gluon Plasma (QGP) in relativistic heavy-ion collisions. In this letter, we present the first measurement of inclusive $J/ψ$ production at mid-rapidity through the dimuon decay channel in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV with the STAR experiment. These

Jens Schreiber, Artjom Buschin, Bernhard Sick

Despite the increasing importance of forecasts of renewable energy, current planning studies only address a general estimate of the forecast quality to be expected and selected forecast horizons. However, these estimates allow only a limited and highly uncertain use in the planning of electric power distribution. More reliable planning processes require cons

Liudmila Tumash, Simona Olmi, Eckehard Schöll

In the present study we consider a random network of Kuramoto oscillators with inertia in order to mimic and investigate the dynamics emerging in high-voltage power grids. The corresponding natural frequencies are assumed to be bimodally Gaussian distributed, thus modeling the distribution of both power generators and consumers: for the stable operation of p

Federica Mura, Grzegorz Gradziuk, Chase P. Broedersz

Biological assemblies such as chromosomes, membranes, and the cytoskeleton are driven out of equilibrium at the nanoscale by enzymatic activity and molecular motors. Similar non-equilibrium dynamics can be realized in synthetic systems, such as chemically fueled colloidal particles. Characterizing the stochastic non-equilibrium dynamics of such active soft a

A. Streblyanska, A. Aguado-Barahona, A. Ferragamo, R. Barrena

Using telescopes at the Canary Island observatories, we conducted the long-term observational programme 128-MULTIPLE-16/15B (LP15), a large and complete optical follow-up campaign of all the unidentified PSZ2 sources in the northern sky (Dec>-15 deg) and no correspondence in the first Planck catalogue PSZ1. We perform this optical validation of SZ clusters i

Niall Twomey, Rafael Poyiadzi, Callum Mann, Raúl Santos-Rodríguez

This paper extends the class of ordinal regression models with a structured interpretation of the problem by applying a novel treatment of encoded labels. The net effect of this is to transform the underlying problem from an ordinal regression task to a (structured) classification task which we solve with conditional random fields, thereby achieving a cohere

Aleksei Shestov, Mikhail Kumskov

This paper is devoted to the problem of blob detection in manifold-valued images. Our solution is based on new definitions of blob response functions. We define the blob response functions by means of curvatures of an image graph, considered as a submanifold. We call the proposed framework Riemannian blob detection. We prove that our approach can be viewed a

S. Asim Ahmed

We consider complexity of Deep Neural Networks (DNNs) and their associated massive over-parameterization. Such over-parametrization may entail susceptibility to adversarial attacks, loss of interpretability and adverse Size, Weight and Power - Cost (SWaP-C) considerations. We ask if there are methodical ways (regularization) to reduce complexity and how can

J. A. Crespo, H. P. de Oliveira

We study the nonlinear stage of preheating in a model consisting of a single inflaton field $ϕ$ nonminimally coupled to the spacetime curvature and considering a self-coupling quartic potential V ($ϕ$) = $λϕ^4/4$. As the first motivation, we mention that this nonminimally coupled model agrees with the observational data. The second and the central issue of t

M. Rosenblum, M. Frühwirth, M. Moser, A. Pikovsky

We develop a technique for the multivariate data analysis of perturbed self-sustained oscillators. The approach is based on the reconstruction of the phase dynamics model from observations and on a subsequent exploration of this model. For the system, driven by several inputs, we suggest a dynamical disentanglement procedure, allowing us to reconstruct the v

Harsh K. Gandhi, Arnab Laha, Somnath Ghosh

We exploit the interaction between supported proximity resonances in an open non-uniformly pumped optical microcavity to host a Bound State in Continuum (BIC). Using the modeling of the S-matrix, we study the coupling between the interacting states forming a BIC. We report the divergence of Quality Factor (Q-factor) of one of the interacting states, numerica

Jaechang Lim, Sang-Yeon Hwang, Seungsu Kim, Seokhyun Moon

Searching new molecules in areas like drug discovery often starts from the core structures of candidate molecules to optimize the properties of interest. The way as such has called for a strategy of designing molecules retaining a particular scaffold as a substructure. On this account, our present work proposes a scaffold-based molecular generative model. Th

Jayadev Vijayan, Pimonpan Sompet, Guillaume Salomon, Joannis Koepsell

Elementary particles such as the electron carry several quantum numbers, for example, charge and spin. However, in an ensemble of strongly interacting particles, the emerging degrees of freedom can fundamentally differ from those of the individual constituents. Paradigmatic examples of this phenomenon are one-dimensional systems described by independent quas

Wenpeng Hu, Zhangming Chan, Bing Liu, Dongyan Zhao

Existing neural models for dialogue response generation assume that utterances are sequentially organized. However, many real-world dialogues involve multiple interlocutors (i.e., multi-party dialogues), where the assumption does not hold as utterances from different interlocutors can occur &#34;in parallel.&#34; This paper generalizes existing sequence-base

Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio

Equilibrium Propagation (EP) is a biologically inspired learning algorithm for convergent recurrent neural networks, i.e. RNNs that are fed by a static input x and settle to a steady state. Training convergent RNNs consists in adjusting the weights until the steady state of output neurons coincides with a target y. Convergent RNNs can also be trained with th

Clelia Marchionna, Stefano Panizzi

We study the asymptotics for the lengths $L_N(q)$ of the instability tongues of Hill equations that arise as iso-energetic linearization of two coupled oscillators around a single-mode periodic orbit. We show that for small energies, i.e. $q\rightarrow 0$, the instability tongues have the same behavior that occurs in the case of the Mathieu equation: $L_N(q)

M. Rosenblum, A. Pikovsky

Phase reduction is a general tool widely used to describe forced and interacting self-sustained oscillators. Here we explore the phase coupling functions beyond the usual first-order approximation in the strength of the force. Taking the periodically forced Stuart-Landau oscillator as the paradigmatic model, we determine and numerically analyse the coupling

Katrin Fässler, Tuomas Orponen

Let $α\geq 0$, $1 < p < \infty$, and let $\mathbb{H}^{n}$ be the Heisenberg group. Folland in 1975 showed that if $f \colon \mathbb{H}^{n} \to \mathbb{R}$ is a function in the horizontal Sobolev space $S^{p}_{2α}(\mathbb{H}^{n})$, then $φf$ belongs to the Euclidean Sobolev space $S^{p}_α(\mathbb{R}^{2n + 1})$ for any test function $φ$. In short, $S^{p}_{2α}(

Tailai Wen, Roy Keyes

Time series anomaly detection plays a critical role in automated monitoring systems. Most previous deep learning efforts related to time series anomaly detection were based on recurrent neural networks (RNN). In this paper, we propose a time series segmentation approach based on convolutional neural networks (CNN) for anomaly detection. Moreover, we propose

Sebastián D. López, Diego G. Arbó

A theoretical study of the interference pattern imprinted on the doubly differential momentum distribution of the photoelectron due to atomic ionization induced by a short laser pulse is developed from a semiclassical standpoint. We use the semiclassical two-step model of Shvetsov-Shilovski et al. (Phys. Rev. A 94, 013415) to elucidate the nature of the holo

Eric I. Barnes, Robert J. Ragan

In an effort to better understand collisionless relaxation processes in gravitational systems, we investigate one-dimensional models. Taking advantage of a Hermite-Legendre expansion of relevant distribution functions, we present analytical and numerical behaviors of Maxwell-Boltzmann entropy. In particular, we modestly perturb systems about a separable-solu

Modjtaba Ghorbani, Xueliang Li, Hamid Reza Maimani, Yaping Mao

The Steiner distance in a graph, introduced by Chartrand et al. in 1989, is a natural generalization of the concept of classical graph distance. For a connected graph $G$ of order at least 2 and $S\subseteq V(G)$, the Steiner distance $d_G(S)$ of the set $S$ of vertices in $G$ is the minimum size of a connected subgraph whose vertex set contains or connects

Enrica Troiano, Sebastian Padó, Roman Klinger

Sentiment analysis has a range of corpora available across multiple languages. For emotion analysis, the situation is more limited, which hinders potential research on cross-lingual modeling and the development of predictive models for other languages. In this paper, we fill this gap for German by constructing deISEAR, a corpus designed in analogy to the wel

Misha Bialy, Andrey Mironov, Serge Tabachnikov

Wire billiard is defined by a smooth embedded closed curve of non-vanishing curvature $k$ in $\mathbb{R}^n$ (a wire). For a class of curves, that we call nice wires, the wire billiard map is area preserving twist map of the cylinder. In this paper we are investigating whether the basic features of conventional planar billiards extend to this more general sit

Robert J. Ragan, Eric I. Barnes

Building on the development of a Hermite-Legendre analysis of one-dimensional gravitating collisionless systems, we present a technique for determining the steady states of such systems. This provides an important component for understanding the physics involved in the relaxation of these kinds of systems. As the dark matter structures in the universe should

Rémy Garnier, Arnaud Belletoile

Sales forecasts are crucial for the E-commerce business. State-of-the-art techniques typically apply only univariate methods to make prediction for each series independently. However, due to the short nature of sales times series in E-commerce, univariate methods don&#39;t apply well. In this article, we propose a global model which outperforms state-of-the-

Dimitrios Rafailidis

The data scarcity of user preferences and the cold-start problem often appear in real-world applications and limit the recommendation accuracy of collaborative filtering strategies. Leveraging the selections of social friends and foes can efficiently face both problems. In this study, we propose a strategy that performs social deep pairwise learning. Firstly

Fabian Reimers

This note provides a set of separating invariants for the ring of vector invariants $K[V^2]^{S_n}$ of two copies of the natural $S_n$-representation $V = K^n$ over a field of characteristic 0. This set is much smaller than generating sets of $K[V^2]^{S_n}$. For $n \leq 4$ we show that this set is minimal with respect to inclusion among all separating sets.

Gary Storey, Richard Jiang, Shelagh Keogh, Ahmed Bouridane

The capability to perform facial analysis from video sequences has significant potential to positively impact in many areas of life. One such area relates to the medical domain to specifically aid in the diagnosis and rehabilitation of patients with facial palsy. With this application in mind, this paper presents an end-to-end framework, named 3DPalsyNet, fo

Tania Pernas-Castaño, Juan J. L. Velázquez

In this work we study the evolution of the interface between two different fluids in two concentric cylinders when the velocity is given by the Navier-Stokes equation and one of the fluids is thin. We present a formal asymptotic derivation of the evolution equation for the interface under different scaling assumptions for the surface tension. We then study t

Xianhao Chen, Gang Liu, Zheng Ma, Xi Zhang

Non-orthogonal multiple access (NOMA) is a promising radio access technology for the 5G wireless systems. The core of NOMA is to support multiple users in the same resource block via power or code domain multiplexing, which provides great enhancement in spectrum efficiency and connectivity. Meanwhile, with the recent advance in self-interference (SI) cancela

Zhenhai Yu, Wei Xia, Kailang Xu, Ming Xu

Layered transition-metal trichalcogenides have become one of the research frontiers as two-dimensional magnets and candidate materials used for phase-change memory devices. Herein we report the high-pressure synchrotron X-ray diffraction and resistivity measurements on Cr2Ge2Te6 (CGT) single crystal by using diamond anvil cell techniques, which reveal a mixt

Tomoyuki Kajiwara, Chihiro Tanikawa, Yuujin Shimizu, Chenhui Chu

We work on the task of automatically designing a treatment plan from the findings included in the medical certificate written by the dentist. To develop an artificial intelligence system that deals with free-form certificates written by dentists, we annotate the findings and utilized the natural language processing approach. As a result of the experiment usi

Ashley Weber

The pants graph has proved to be influential in understanding 3-manifolds concretely. This stems from a quasi-isometry between the pants graph and the Teichmüller space with the Weil-Petersson metric. Currently, all estimates on the quasi-isometry constants are dependent on the surface in an undiscovered way. This paper starts effectivising some constants wh

Shuming Jiao, Yang Gao, Ting Lei, Zhenwei Xie

In many previous works, a single-pixel imaging (SPI) system is constructed as an optical image encryption system. Unauthorized users are not able to reconstruct the plaintext image from the ciphertext intensity sequence without knowing the illumination pattern key. However, little cryptanalysis about encrypted SPI has been investigated in the past. In this w

Yanwei Li, Chandan K. Mishra, Zhaoyan Sun, Kun Zhao

Long-wavelength Mermin-Wagner fluctuations prevent the existence of translational long-range order, in two-dimensional systems at finite temperature. Their dynamical signature, which is the divergence of the vibrational amplitude with the system size, also affects disordered solids and washes out the transient solid-like response generally exhibited by liqui

M. Lopez-Corredoira, Y. -W. Lee, F. Garzon, D. Lim

CONTEXT. Claims of an X-shaped Galactic bulge were based on the assumption of red clump stars as standard candles in some lines of sight crossing the off-plane bulge. However, some doubts have been cast on whether the two peaks in star counts along the line of sight really represent a double peak in the density distribution, or whether there is something wro

A. Revelli, M. Moretti Sala, G. Monaco, C. Hickey

In the quest for realizations of quantum spin liquids, the exploration of Kitaev materials - spin-orbit entangled Mott insulators with strong bond-directional exchanges - has taken center stage. However, in these materials the local spin-orbital j=1/2 moments typically show long-range magnetic order at low temperature, thus defying the formation of a spin-li

Sören Laue, Matthias Mitterreiter, Joachim Giesen

Although optimization is the longstanding algorithmic backbone of machine learning, new models still require the time-consuming implementation of new solvers. As a result, there are thousands of implementations of optimization algorithms for machine learning problems. A natural question is, if it is always necessary to implement a new solver, or if there is

Haoxin Li, Yijun Cai, Wei-Shi Zheng

Egocentric interaction recognition aims to recognize the camera wearer&#39;s interactions with the interactor who faces the camera wearer in egocentric videos. In such a human-human interaction analysis problem, it is crucial to explore the relations between the camera wearer and the interactor. However, most existing works directly model the interactions as

Mikolaj Fraczyk, Wouter van Limbeek

We study infinite analogues of expander graphs, namely graphs where subgraphs weighted by heat kernels form an expander family. Our main result is that there does not exist any infinite expander in this sense. This proves the analogue for random walks of Benjamini&#39;s conjecture that there is no infinite graph whose metric balls are uniformly expander. The

E. Y. Emelyanov, S. G. Gorokhova

We characterize vector lattices in which unbounded order convergence is eventually order bounded. Among other things, the characterization provides a solution to \cite[Probl.23]{Az}.

Kari Enqvist, Till Sawala, Tomo Takahashi

We discuss structure formation in models with a spectator field in small-field inflation which accommodate a secondary period of inflation. In such models, subgalactic scale primordial fluctuations can be much suppressed in comparison to the usual power-law $Λ$CDM model while the large scale fluctuations remain consistent with current observations. We discus

Sebastian Krauss, Simeon Völkel, Christoph Dobner, Alexandra Völkel

The Margravial Opera House Bayreuth, built between 1745 and 1750, is a well preserved Baroque court theatre designed by Giuseppe Galli Bibiena [1]. It provides an opportunity to experience not only the visual but also the acoustic design of opera theatres in the 18th century, as the bell-shaped auditorium along with the decoratively painted canvas remains in

John A. Armstrong, Lyndsay Fletcher

The volume of data being collected in solar physics has exponentially increased over the past decade and with the introduction of the $\textit{Daniel K. Inouye Solar Telescope}$ (DKIST) we will be entering the age of petabyte solar data. Automated feature detection will be an invaluable tool for post-processing of solar images to create catalogues of data re

Sheldon Dantas, Sun Kwang Kim, Han Ju Lee, Martin Mazzitelli

We continue a line of study about some local versions of Bishop-Phelps-Bollobás type properties for bounded linear operators. We introduce and focus our attention on two of these local properties, which we call L$_{p, o}$ and L$_{o, p}$, and we explore the relation between them and some geometric properties of the underlying spaces, such as spaces having str

Paolo Leonetti, Jens Schwaiger

Fix non-zero reals $α_1,\ldots,α_n$ with $n\ge 2$ and let $K$ be a non-empty open connected set in a topological vector space such that $\sum_{i\le n}α_iK\subseteq K$ (which holds, in particular, if $K$ is an open convex cone and $α_1,\ldots,α_n>0$). Let also $Y$ be a vector space over $\mathbb{F}:=\mathbb{Q}(α_1,\ldots,α_n)$. We show, among others, that a f

S. R. Hassan, Ankita Chakrabarti, R. Shankar

There has been much work in the recent past in developing the idea of quantum geometry to characterize and understand the structure of many-particle states. For mean-field states, the quantum geometry has been defined and analysed in terms of the quantum distances between two points in the space of single particle spectral parameters (the Brillioun zone for

Adrián González-Sieira, Manuel Mucientes, Alberto Bugarín

We present a novel approach for motion planning in mobile robotics under sensing and motion uncertainty based on state lattices with graduated fidelity. The probability of collision is reliably estimated considering the robot shape, and the fidelity adapts to the complexity of the environment, improving the planning efficiency while maintaining the performan

Wei N. Tang, Jingjin Yu

We examine an important combinatorial challenge in clearing clutter using a mobile robot equipped with a manipulator, seeking to compute an optimal object removal sequence for minimizing the task completion time, assuming that each object is grasped once and then subsequently removed. On the structural side, we establish that such an optimal sequence can be

Mohamad Jaber, Yliès Falcone, Paul Attie, Al-Abbass Khalil

We define a method to automatically synthesize provably-correct efficient distributed implementations from high-level global choreographies. A global choreography describes the execution and communication logic between a set of provided processes which are described by their interfaces. The operations at the level of choreographies include multiparty communi

Daniele Castellana, Davide Bacciu

Bottom-Up Hidden Tree Markov Model is a highly expressive model for tree-structured data. Unfortunately, it cannot be used in practice due to the intractable size of its state-transition matrix. We propose a new approximation which lies on the Tucker factorisation of tensors. The probabilistic interpretation of such approximation allows us to define a new pr

Hongyuan Wang, Hao Su, Jiuyang Zhang, Wei Xia

We report systematic magneto-transport measurements and ab initio calculations on single-crystalline TaP2, a new member of the transition-metal dipnictides. We observed unsaturated magnetoresistance (MR) reaching ~ 700% at a magnetic field (B) of 9 T at 2 K along with striking Shubnikov-de Hass (SdH) oscillations. Our analysis on the SdH oscillations reveals

Jonas M. Kübler, Krikamol Muandet, Bernhard Schölkopf

The kernel mean embedding of probability distributions is commonly used in machine learning as an injective mapping from distributions to functions in an infinite dimensional Hilbert space. It allows us, for example, to define a distance measure between probability distributions, called maximum mean discrepancy (MMD). In this work, we propose to represent pr

Francisco Criado, Andrew Newman

We consider the question of the largest possible combinatorial diameter among $(d-1)$-dimensional simplicial complexes on $n$ vertices, denoted $H_s(n, d)$. Using a probabilistic construction we give a new lower bound on $H_s(n, d)$ that is within an $O(d^2)$ factor of the upper bound. This improves on the previously best-known lower bound which was within a

Li-Cheng Lan, Wei Li, Ting-Han Wei, I-Chen Wu

Many of the strongest game playing programs use a combination of Monte Carlo tree search (MCTS) and deep neural networks (DNN), where the DNNs are used as policy or value evaluators. Given a limited budget, such as online playing or during the self-play phase of AlphaZero (AZ) training, a balance needs to be reached between accurate state estimation and more

D. Andre, T. Burlet, F. Koerkemeyer, G. Gerstein

A promising approach to deform metallic-intermetallic composite materials is the application of electric current pulses during the deformation process to achieve a lower yield strength and enhanced elongation to fracture. This is known as the electroplastic effect. We developed a novel setup to study the electroplastic effect during nanoindentation on indivi

Christopher Hahn, Marvin Stenger, Leander Tentrup

Verifying hyperproperties at runtime is a challenging problem as hyperproperties, such as non-interference and observational determinism, relate multiple computation traces with each other. It is necessary to store previously seen traces, because every new incoming trace needs to be compatible with every run of the system observed so far. Furthermore, the ne

Cameron Browne, Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson

Digital Archaeoludology (DAL) is a new field of study involving the analysis and reconstruction of ancient games from incomplete descriptions and archaeological evidence using modern computational techniques. The aim is to provide digital tools and methods to help game historians and other researchers better understand traditional games, their development th

Bernd Finkbeiner, Christopher Hahn, Hazem Torfah

Hyperproperties are properties of sets of computation traces. In this paper, we study quantitative hyperproperties, which we define as hyperproperties that express a bound on the number of traces that may appear in a certain relation. For example, quantitative non-interference limits the amount of information about certain secret inputs that is leaked throug

Ana Budiša, Xiaozhe Hu

In this paper, we are interested in an efficient numerical method for the mixed-dimensional approach to modeling single-phase flow in fractured porous media. The model introduces fractures and their intersections as lower-dimensional structures, and the mortar variable is used for flow coupling between the matrix and fractures. We consider a stable mixed fin

Subhajeet Karmakar, Jeewan C. Pandey, Sachindra Naik, Igor S. Savanov

We present results obtained from the studies of magnetic activities on four solar-type stars (F-type star KIC 6791060, K-type star LO Peg, and two M-type planet-hosting stars K2-33 and EPIC 211901114) by using optical observations from several ground- and space-based telescopes. In this study, we investigate magnetic activities such as spot-topographic evolu

Bernd Finkbeiner, Christopher Hahn, Philip Lukert, Marvin Stenger

We study the reactive synthesis problem for hyperproperties given as formulas of the temporal logic HyperLTL. Hyperproperties generalize trace properties, i.e., sets of traces, to sets of sets of traces. Typical examples are information-flow policies like noninterference, which stipulate that no sensitive data must leak into the public domain. Such propertie