November 2019 arXiv papers — page 59

Gunther Leobacher, Joscha Prochno

In this manuscript we discuss the notion of (statistical) independence embedded in its historical context. We focus in particular on its appearance and role in number theory, concomitantly exploring the intimate connection of independence and the famous Gaussian law of errors. As we shall see, this at times requires us to go adrift from the celebrated Kolmog

Patrick Follmann, Rebecca König

State-of-the-art instance-aware semantic segmentation algorithms use axis-aligned bounding boxes as an intermediate processing step to infer the final instance mask output. This often leads to coarse and inaccurate mask proposals due to the following reasons: Axis-aligned boxes have a high background to foreground pixel-ratio, there is a strong variation of

Bernhard Stimpel, Christopher Syben, Franziska Schirrmacher, Philipp Hoelter

Deep learning-based image processing is capable of creating highly appealing results. However, it is still widely considered as a "blackbox" transformation. In medical imaging, this lack of comprehensibility of the results is a sensitive issue. The integration of known operators into the deep learning environment has proven to be advantageous for the

Luc Frachon, Wei Pang, George M. Coghill

Current Neural Architecture Search techniques can suffer from a few shortcomings, including high computational cost, excessive bias from the search space, conceptual complexity or uncertain empirical benefits over random search. In this paper, we present ImmuNeCS, an attempt at addressing these issues with a method that offers a simple, flexible, and efficie

Patrick Serafini, Alberto Milani, Matteo Tommasini, Chiara Castiglioni

γ-graphdiyne is a 2D carbon structure beyond graphene: it is formed by sp and sp2 carbon atoms organized as hexagonal rings connected by linear links, and it is predicted to be a semiconductor. The lateral confinement of γ-graphdiyne nanoribbons significantly affects the electronic and vibrational properties. By means of periodic Density Functional Theory (D

Loqman Salamatian, Frederick Douzet, Kevin Limonier, Kavé Salamatian

The global expansion of the Internet has brought many challenges to geopolitics. Cyberspace is a space of strategic priority for many states. Understanding and representing its geography remains an ongoing challenge. Nevertheless, we need to comprehend Cyberspace as a space organized by humans to analyse the strategies of the actors. This geography requires

Lu Yihe, Scott C. Lowe, Penelope A. Lewis, Mark C. W. van Rossum

Despite remarkable advances in automated visual recognition by machines, some visual tasks remain challenging for machines. Fleuret et al. (2011) introduced the Synthetic Visual Reasoning Test (SVRT) to highlight this point, which required classification of images consisting of randomly generated shapes based on hidden abstract rules using only a few example

Przemysław Kosewski, Adam Kubica

We prove the existence of global in time solution to Kolmogorov's two-equation model of turbulence in three dimensional domain with periodic boundary conditions under smallness assumption imposed on initial data.

Eduardo Abi Jaber

We establish an explicit expression for the conditional Laplace transform of the integrated Volterra Wishart process in terms of a certain resolvent of the covariance function. The core ingredient is the derivation of the conditional Laplace transform of general Gaussian processes in terms of Fredholm's determinant and resolvent. Furthermore , we link the ch

Naichung Conan Leung, Ying Xie

The DK conjecture of Bondal-Orlov and Kawamata states that there should be an embedding of bounded derived categories for any $K$-inequivalence, which is proved to be true for the toroidal case. In this paper, we construct examples of non-toroidal $K$-inequivalences from Grassmannians inspired by Kuznetsov, Kanemitsu, Ueda, and Morimura, and we show that the

Hyun-Yong Lee, Naoki Kawashima, Yong Baek Kim

Recently there has been a great interest in understanding quantum spin liquid phases with varying spin magnitude, partly due to possible material realizations. A number of recent numerical computations suggest that the ground state of the S=1 Kitaev model may be a quantum spin liquid in analogy to the renowned $S$=$1/2$ model. On the other hand, the nature o

Silvia Caponi, Daniele Fioretto, Maurizio Mattarelli

Brillouin imaging is an emerging optical elastography technique able to generate maps of the mechanical properties at microscale, with great potential in biophysical and biomedical fields. A key parameter is its spatial resolution, which is usually identified with that of the confocal microscope coupled to the Brillouin interferometer. Conversely, here we de

Hongtao Lv, Chaoli Zhang, Zhenzhe Zheng, Tie Luo

Bike sharing systems have been widely deployed around the world in recent years. A core problem in such systems is to reposition the bikes so that the distribution of bike supply is reshaped to better match the dynamic bike demand. When the bike-sharing company or platform is able to predict the revenue of each reposition task based on historic data, an addi

Julia S. Meyer, Manuel Houzet

The Josephson current flowing in a junction between two superconductors is a striking manifestation of macroscopic quantum coherence, with applications in metrology and quantum information. This equilibrium current is related with the formation of Andreev states localized in the junction, whose energy depends periodically on the superconducting phase differe

Alexandru Dimca

We reformulate a fundamental result due to Cook, Harbourne, Migliore and Nagel on the existence and irreduciblity of unexpected plane curves of a set of points $Z$ in $\mathbb{P}^2$, using the minimal degree of a Jacobian syzygy of the defining equation for the dual line arrangement $\mathcal A_Z$. Several applications of this new approach are given. In part

Valerie Berthe, P Cecchi Bernales, Fabien Durand, J Leroy

Dimension groups are complete invariants of strong orbit equivalence for minimal Cantor systems. This paper studies a natural family of minimal Cantor systems having a finitely generated dimension group, namely the primitive unimodular proper S-adic subshifts. They are generated by iterating sequences of substitutions. Proper substitutions are such that the

Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi, Dietmar Jannach

The design of algorithms that generate personalized ranked item lists is a central topic of research in the field of recommender systems. In the past few years, in particular, approaches based on deep learning (neural) techniques have become dominant in the literature. For all of them, substantial progress over the state-of-the-art is claimed. However, indic

Nicolas Grelier

We consider the Minimum Convex Partition problem: Given a set P of n points in the plane, draw a plane graph G on P, with positive minimum degree, such that G partitions the convex hull of P into a minimum number of convex faces. We show that Minimum Convex Partition is NP-hard, and we give several approximation algorithms, from an O(log OPT)-approximation r

Rui Shi

In [10], Halmos proved an interesting result that the set of irreducible operators is dense in $\mathcal B(\mathcal H)$ in the sense of Hilbert-Schmidt approximation. In a von Neumann algebra $\mathcal M$ with separable predual, an operator $a\in \mathcal M$ is said to be {irreducible in} $\mathcal M$ if $W^*(a)$ is an irreducible subfactor of $\mathcal M$,

Gladis Pradolini, Jorgelina Recchi

In this paper we prove two-weighted norm estimates for higher order commutator of singular integral and fractional type operators between weighted $L^p$ and certain spaces that include Lipschitz, BMO and Morrey spaces. We also give the optimal parameters involved with these results, where the optimality is understood in the sense that the parameters defining

Vyacheslav I. Dokuchaev, Natalia O. Nazarova

In general relativity, isolated black holes are invisible due to an infinitely large redshift of photons propagating from the event horizon to the remote observer. However, the dark shadow (silhouette) of a black hole can be visible on the background of matter radiation lensed by the gravitational field of black holes. The black hole shadow is the celestial

Lu Bai, Yew-Soon Ong, Tiantian He, Abhishek Gupta

Multi-label learning studies the problem where an instance is associated with a set of labels. By treating single-label learning problem as one task, the multi-label learning problem can be casted as solving multiple related tasks simultaneously. In this paper, we propose a novel Multi-task Gradient Descent (MGD) algorithm to solve a group of related tasks s

Raphael Bennett-Tennenhaus

We consider the homotopy category of complexes of projective modules over any gentle algebra. We prove that indecomposable $Σ$-pure-injective objects in s must be shifts of string or band complexes. We begin with a survey of purity in compactly generated triangulated categories, recalling some characterisations of $Σ$-pure-injective objects that mimic classi

Giacomo Caria

We report a measurement of the ratios of branching fractions $\mathcal{R}(D^{(*)}) = {\cal B}(\bar{B} \to D^{(*)} \tau^- \bar{\nu}_{\tau})/{\cal B}(\bar{B} \to D^{(*)} \ell^- \bar{\nu}_{\ell})$ where $\ell$ denotes an electron or a muon. The results are based on a data sample containing $772 \times 10^6$ $B\bar{B}$ events recorded at the $\Upsilon(4S)$ reson

Paolo Notaro, Magdalini Paschali, Carsten Hopke, David Wittmann

Radar pulse streams exhibit increasingly complex temporal patterns and can no longer rely on a purely value-based analysis of the pulse attributes for the purpose of emitter classification. In this paper, we employ Recurrent Neural Networks (RNNs) to efficiently model and exploit the temporal dependencies present inside pulse streams. With the purpose of enh

Sergey Berezin, Azat Miftakhov

A characterization is presented of barycenters of the Radon probability measures supported on a closed convex subset of a given space. A case of particular interest is studied, where the underlying space is itself the space of finite signed Radon measures on a metric compact and where the corresponding support is the convex set of probability measures. For l

Alessandro Zannotti, Cornelia Denz, Miguel A. Alonso, Mark R. Dennis

Structured light has revolutionized optical particle manipulation and nano-scale material processing. In particular, propagation-invariant structured light fields, such as Bessel beams, have enabled applications that require robust intensity distributions. Their self-healing nature facilitates imaging with enhanced resolution e.g. in light-sheet microscopy.

Javid Naikoo, Subhashish Banerjee, R. Srikanth

The reliability of quantum channels for transmitting information is of profound importance from the perspective of quantum information. This naturally leads to the question as how well a quantum state is preserved when subjected to a quantum channel. We propose a measure of quantumness of channels based on non-commutativity of quantum states that is intuitiv

Tor Lattimore, Csaba Szepesvari, Gellert Weisz

The construction by Du et al. (2019) implies that even if a learner is given linear features in $\mathbb R^d$ that approximate the rewards in a bandit with a uniform error of $ε$, then searching for an action that is optimal up to $O(ε)$ requires examining essentially all actions. We use the Kiefer-Wolfowitz theorem to prove a positive result that by checkin

Yilun Jin, Guojie Song, Chuan Shi

It is not until recently that graph neural networks (GNNs) are adopted to perform graph representation learning, among which, those based on the aggregation of features within the neighborhood of a node achieved great success. However, despite such achievements, GNNs illustrate defects in identifying some common structural patterns which, unfortunately, play

Xuan-Hoai Thi Nguyen, Mahn-Soo Choi

In contrast to the standard quantum state tomography, the direct tomography seeks the direct access to the complex values of the wave function at particular positions (i.e., the expansion coefficient in a fixed basis). Originally put forward as a special case of weak measurement, it can be extended to arbitrary measurement setup. We generalize the idea of "q

Prabhanjan Ananth, Rolando L. La Placa

Knowledge extraction, typically studied in the classical setting, is at the heart of several cryptographic protocols. We introduce the notion of secure quantum extraction protocols. A secure quantum extraction protocol for an NP relation $\mathcal{R}$ is a classical interactive protocol between a sender and a receiver, where the sender gets the instance $z$

Zuzana Masáková, Tomáš Vávra, Francesco Veneziano

We consider continued fractions with partial quotients in the ring of integers of a quadratic number field $K$ and we prove a generalization to such continued fractions of the classical theorem of Lagrange. A particular example of these continued fractions is the $β$-continued fraction introduced by Bernat. As a corollary of our theorem we show that for any

David A. Clarke, Olaf Kaczmarek, Frithjof Karsch, Anirban Lahiri

In quenched QCD the Polyakov loop is an order parameter of the deconfinement transition, but with decreasing quark mass, the peak in the Polyakov loop susceptibility becomes less pronounced, and it loses its interpretation as an indicator for deconfinement. For this $N_f=2+1$ HISQ study, we fix the strange quark mass $m_s$ at its physical value and investiga

Xiaojin Zhang

Let $\Lambda $ be an artin algebra and $T$ a $\tau$-tilting $\Lambda$-module. We prove that $T$ is a tilting module if and only if ${\rm Ext}_{\Lambda}^{i}(T,\Fac T)=0$ for all $i\geq 1$, where $\Fac T$ is the full subcategory consisting of modules generated by $T$. Consequently, a $\tau$-tilting module $T$ of finite projective dimension is a tilting module

Eva Bayer-Fluckiger, Uriya A. First, Raman Parimala

We prove some new cases of the Grothendieck-Serre conjecture for classical groups. This is based on a new construction of the Gersten-Witt complex for Witt groups of Azumaya algebras with involution on regular semilocal rings, with explicit second residue maps; the complex is shown to be exact when the ring is of dimension $\le 2$ (or $\le 4$, with additiona

Yuan-Hang Su, Wan-Tong Li, Fei-Ying Yang

This paper studies the effects of the dispersal spread, which characterizes the dispersal range, on nonlocal diffusion equations with the nonlocal dispersal operator $\frac{1}{σ^{m}}\int_ΩJ_σ(x-y)(u(y,t)-u(x,t))dy$ and Neumann boundary condition in the spatial heterogeneity environment. More precisely, we are mainly concerned with asymptotic behaviors of gen

N. V. Antonov, M. M. Kostenko

The field theoretic renormalization group (RG) is applied to the model of a near-equilibrium fluid coupled to a scalar field (like temperature or density of an impurity) which is active, that is, influencing the dynamics of the fluid itself. It is shown that the only possible nontrivial infrared (IR) asymptotic regimes are governed by "passive" fixed points

Michael Kissner

A large chunk of research on the security issues of neural networks is focused on adversarial attacks. However, there exists a vast sea of simpler attacks one can perform both against and with neural networks. In this article, we give a quick introduction on how deep learning in security works and explore the basic methods of exploitation, but also look at t

Iñigo Querejeta-Azurmendi, Panagiotis Papadopoulos, Matteo Varvello, Antonio Nappa

Recent studies show that 20.4% of the internet traffic originates from automated agents. To identify and block such ill-intentioned traffic, mechanisms that verify the humanness of the user are widely deployed, with CAPTCHAs being the most popular. Traditional CAPTCHAs require extra user effort (e.g., solving mathematical puzzles), which can severely downgra

Jan P. Hackstein, Eva Hackmann

Astrophysical black holes are often embedded into electromagnetic fields, that can usually be treated as test fields not influencing the spacetime geometry. Here we analyse the innermost stable circular orbit (ISCO) of charged particles moving around a Schwarzschild black hole in the presence of a radial electric test field and an asymptotically uniform magn

Miguel Suau, Jinke He, Elena Congeduti, Rolf A. N. Starre

Due to its perceptual limitations, an agent may have too little information about the state of the environment to act optimally. In such cases, it is important to keep track of the observation history to uncover hidden state. Recent deep reinforcement learning methods use recurrent neural networks (RNN) to memorize past observations. However, these models ar

Yidong Luo

On bounded and simply connected planar analytic domain $ Ω$, by $ 2π$ periodic parametric representation of boundary curve $ \partial Ω$, Symm's integral equation of the first kind takes form $ K Ψ= g $, where $ K $ is seen as an operator mapping from $ L^2(0,2π) $ to itself. The classical result show complete convergence and error analysis in $ L^2 $ se

Benoît Collins, Pierre Yves Gaudreau Lamarre, Camille Male

In this paper, we pursue our study of asymptotic properties of families of random matrices that have a tensor structure. In previous work, the first- and second-named authors provided conditions under which tensor products of unitary random matrices are asymptotically free with respect to the normalized trace. Here, we extend this result by proving that asym

Jingwei Hu, Jian-Guo Liu, Yantong Xie, Zhennan Zhou

In this work, we are concerned with the Fokker-Planck equations associated with the Nonlinear Noisy Leaky Integrate-and-Fire model for neuron networks. Due to the jump mechanism at the microscopic level, such Fokker-Planck equations are endowed with an unconventional structure: transporting the boundary flux to a specific interior point. While the equations

Trygve K. Løken, Jean Rabault, Atle Jensen, Graig Sutherland

Increased research interest and economic activity in the Arctic raise the need for new observations of sea ice dynamics. Remote sensing as well as mathematical and numerical models of wave propagation in sea ice would benefit from more in situ data for validation. This study presents wave measurements in the marginal ice zone (MIZ) obtained from ship mounted

Arnab Chakrabarti, Rangeet Bhattacharyya

Periodically driven closed quantum many-body systems are known to exhibit prethermal or quasi-steady-state dynamics. In this work, we theoretically show that such prethermal phases can appear in the dynamics of a dipolar two-spin-$1/2$ system coupled to a heat bath if the cross terms between the drive and dipolar interactions are taken into consideration. To

Rocìo Cabrera Lozoya, Arnaud Baumann, Antonino Sabetta, Michele Bezzi

Deep learning methods, which have found successful applications in fields like image classification and natural language processing, have recently been applied to source code analysis too, due to the enormous amount of freely available source code (e.g., from open-source software repositories). In this work, we elaborate upon a state-of-the-art approach to t

Anas Barakat, Pascal Bianchi

Although ADAM is a very popular algorithm for optimizing the weights of neural networks, it has been recently shown that it can diverge even in simple convex optimization examples. Several variants of ADAM have been proposed to circumvent this convergence issue. In this work, we study the ADAM algorithm for smooth nonconvex optimization under a boundedness a

Ludovic Sacchelli, Lucas Brivadis, Vincent Andrieu, Ulysse Serres

Output feedback stabilization of control systems is a crucial issue in engineering. Most of these systems are not uniformly observable, which proves to be a difficulty to move from state feedback stabilization to dynamic output feedback stabilization. In this paper, we present a methodology to overcome this challenge in the case of dissipative systems by req

Oliver J. Tattersall

The odd parity gravitational Quasi-Normal Mode spectrum of black holes with non-trivial scalar hair in Horndeski gravity is investigated. We study `almost' Schwarzschild black holes such that any modifications to the spacetime geometry (including the scalar field profile) are treated as small quantities. A modified Regge-Wheeler style equation for the od

Stefano Gasperini, Magdalini Paschali, Carsten Hopke, David Wittmann

Radar signals have been dramatically increasing in complexity, limiting the source separation ability of traditional approaches. In this paper we propose a Deep Learning-based clustering method, which encodes concurrent signals into images, and, for the first time, tackles clustering with image segmentation. Novel loss functions are introduced to optimize a

David W. Romero, Mark Hoogendoorn

Equivariance is a nice property to have as it produces much more parameter efficient neural architectures and preserves the structure of the input through the feature mapping. Even though some combinations of transformations might never appear (e.g. an upright face with a horizontal nose), current equivariant architectures consider the set of all possible tr

Tsukasa Ishibashi, Shunsuke Kano

We introduce a property of mutation loops, called the sign stability, with a focus on an asymptotic behavior of the iteration of the tropical $\mathcal{X}$-transformation. A sign-stable mutation loop has a numerical invariant which we call the cluster stretch factor, in analogy with that of a pseudo-Anosov mapping class on a marked surface. We compute the al

Valentina Anita Carriero, Aldo Gangemi, Maria Letizia Mancinelli, Andrea Giovanni Nuzzolese

Ontology Design Patterns (ODPs) have become an established and recognised practice for guaranteeing good quality ontology engineering. There are several ODP repositories where ODPs are shared as well as ontology design methodologies recommending their reuse. Performing rigorous testing is recommended as well for supporting ontology maintenance and validating

Chris J Mitchell

This paper provides a detailed analysis of the impact of quantum computing on the security of 5G mobile telecommunications. This involves considering how cryptography is used in 5G, and how the security of the system would be affected by the advent of quantum computing. This leads naturally to the specification of a series of simple, phased, recommended chan

Farbod Taymouri, Marcello La Rosa, Marlon Dumas, Fabrizio Maria Maggi

Process variant analysis aims at identifying and addressing the differences existing in a set of process executions enacted by the same process model. A process model can be executed differently in different situations for various reasons, e.g., the process could run in different locations or seasons, which gives rise to different behaviors. Having intuition

Alessandro Berarducci, Marcello Mamino

Skolem (1956) studied the germs at infinity of the smallest class of real valued functions on the positive real line containing the constant $1$, the identity function $x$, and such that whenever $f$ and $g$ are in the set, $f+g,fg$ and $f^g$ are in the set. This set of germs is well ordered and Skolem conjectured that its order type is epsilon-zero. Van den

Yang Guo, Zhengyuan Liu, Pavitra Krishnswamy, Savitha Ramasamy

Real-world clinical time series data sets exhibit a high prevalence of missing values. Hence, there is an increasing interest in missing data imputation. Traditional statistical approaches impose constraints on the data-generating process and decouple imputation from prediction. Recent works propose recurrent neural network based approaches for missing data

M. N. Chernodub, Harold Erbin, I. V. Grishmanovskii, V. A. Goy

Vacuum fluctuations of quantum fields between physical objects depend on the shapes, positions, and internal composition of the latter. For objects of arbitrary shapes, even made from idealized materials, the calculation of the associated zero-point (Casimir) energy is an analytically intractable challenge. We propose a new numerical approach to this problem

Arash Shahmansoori

Sparsity of channel in the next generation of wireless communication for massive multiple-input-multiple-output (MIMO) systems can be exploited to reduce the overhead in the training. The multitask (MT)-sparse Bayesian learning (SBL) is applied for learning time-varying sparse channels in the uplink for multi-user massive MIMO orthogonal frequency division m

Muhammad Fitrah Alfian Rangga Sakti, Hadyan Lutfan Prihadi, Agus Suroso, Freddy Permana Zen

We find a charged spherically symmetric black hole solution with the existence of a cloud of strings and quintessential matter. Then we apply the Demianski-Newman-Janis algorithm to generate the rotating and twisting counterpart. The thermodynamic properties of this black hole solution are further investigated.

Gang Guo, Yong-Zhong Qian, Meng-Ru Wu

IceCube has detected many TeV--PeV neutrinos, but their astrophysical origins remain largely unknown. Motivated by the observed late-time X-ray/optical bumps in some gamma-ray bursts (GRBs), we examine the correlation between IceCube neutrinos and GRBs allowing delayed neutrinos $\sim$days after the prompt gamma rays. Although we have not found any definitiv

Alex Groce, Josselin Feist, Gustavo Grieco, Michael Colburn

An important problem in smart contract security is understanding the likelihood and criticality of discovered, or potential, weaknesses in contracts. In this paper we provide a summary of Ethereum smart contract audits performed for 23 professional stakeholders, avoiding the common problem of reporting issues mostly prevalent in low-quality contracts. These

Felipe Moser, Ruobing Huang, Aris T. Papageorghiou, Bartlomiej W. Papiez

To improve the performance of most neuroimiage analysis pipelines, brain extraction is used as a fundamental first step in the image processing. But in the case of fetal brain development, there is a need for a reliable US-specific tool. In this work we propose a fully automated 3D CNN approach to fetal brain extraction from 3D US clinical volumes with minim

Roberto Boccagna

We construct a solution for the $1d$ integro-differential stationary equation derived from a finite-volume version of the mesoscopic model proposed in [G. B. Giacomin, J. L. Lebowitz, "Phase segregation dynamics in particle system with long range interactions", Journal of Statistical Physics 87(1) (1997)]. This is the continuous limit of an Ising spin chain

So Katagiri

Measurement theory in classical mechanics is investigated in the formulation of classical mechanics by Koopman and von Neumann (KvN), using Hilbert space. It is shown that the classical and the quantum measurements give different "relative interpretations" of the measurement state and the recording state of the measurement device. The uncertainty rel

Laura Capuano, Amos Turchet

We prove the nonsplit case of the Lang-Vojta conjecture over function fields for surfaces of log general type that are ramified covers of $\mathbb{G}_m^2$. This extends results of Corvaja and Zannier, who proved the conjecture in the split case, and results of Corvaja and Zannier and the second author that were obtained in the case of the complement of a deg

Xu Qin, Zhilin Wang, Yuanchao Bai, Xiaodong Xie

In this paper, we propose an end-to-end feature fusion at-tention network (FFA-Net) to directly restore the haze-free image. The FFA-Net architecture consists of three key components: 1) A novel Feature Attention (FA) module combines Channel Attention with Pixel Attention mechanism, considering that different channel-wise features contain totally different w

CMS Collaboration

Results are reported from a search for new physics beyond the standard model in proton-proton collisions in final states with a single lepton; multiple jets, including at least one jet tagged as originating from the hadronization of a bottom quark; and large missing transverse momentum. The search uses a sample of proton-proton collision data at $\sqrt{s} =$

Sergey A. Dyachenko

We find a new class of solutions that are traveling waves on the boundary of two--dimensional droplet of ideal fluid. We assume that the free surface is subject only to the force of surface tension, and the fluid flow is potential. We use the canonical Hamiltonian variables discovered in the work of V.E. Zakharov in 1968, and conformally map lower complex pl

Bernardt Duvenhage

The paper presents a hierarchical naive Bayesian and lexicon based classifier for short text language identification (LID) useful for under resourced languages. The algorithm is evaluated on short pieces of text for the 11 official South African languages some of which are similar languages. The algorithm is compared to recent approaches using test sets from

R. Moradi, J. A. Rueda, R. Ruffini, Y. Wang

A multi-decade theoretical effort has been devoted to finding an efficient mechanism to use the rotational and electrodynamical extractable energy of a Kerr-Newman black hole (BH), to power the most energetic astrophysical sources such as gamma-ray bursts (GRBs) and active galactic nuclei (AGN). We show an efficient general relativistic electrodynamical proc

F. Ajejas, A. Anadón, A. Gudin, J. M. Diez

The development of graphene (Gr) spintronics requires the ability to engineer epitaxial Gr heterostructures with interfaces of high quality, in which the intrinsic properties of Gr are modified through proximity with a ferromagnet to allow for efficient room temperature spin manipulation or the stabilization of new magnetic textures. These heterostructures c

William Casbolt, Bryn Jones, Iñaki Esnaola

The performance of control systems with input packet losses on the controller to plant communication channel is analysed. The main contribution of this work is a proof that linear optimal control systems operating with UDP-like communication protocols have a larger quadratic cost than the same systems operating with TCP-like protocols. The proof is derived f

Andrea Coladangelo, Thomas Vidick, Tina Zhang

We initiate the study of non-interactive zero-knowledge (NIZK) arguments for languages in QMA. Our first main result is the following: if Learning With Errors (LWE) is hard for quantum computers, then any language in QMA has an NIZK argument with preprocessing. The preprocessing in our argument system consists of (i) the generation of a CRS and (ii) a single

J. G. Vale, C. D. Dashwood, E. Paris, L. S. I. Veiga

The excitations in honeycomb $α$-Li$_2$IrO$_3$ have been investigated with high-resolution resonant inelastic x-ray scattering (RIXS) at the O K edge. The low-energy response is dominated by a fully resolved ladder of excitations, which we interpret as being due to multi-phonon processes in the presence of strong electron-phonon coupling (EPC). At higher ene

Julien Gaboriaud, Luc Vinet, Stéphane Vinet

The Askey-Wilson algebra and its relatives such as the Racah and Bannai-Ito algebras were initially introduced in connection with the eponym orthogonal polynomials. They have since proved ubiquitous. In particular they admit presentations as commutants that are related through Howe duality. This paper surveys these results.

Xia Li, Qin Yue

Due to the wide applications in consumer electronics, data storage systems and communication systems, cyclic codes have been an interesting research topic in coding theory. In this paper, let $p$ be a prime with $p\ge 7$. We determine the weight distributions of all cyclic codes of length $5$ over $\f_q$ and the Hamming distances of all repeated-root cyclic

Ignacio Gimeno, Víctor Rollano, David Zueco, Yan Duan

A central goal in quantum technologies is to maximize $G$T$_{2}$, where $G$ stands for the coupling of a qubit to control and readout signals and T$_{2}$ is the qubit's coherence time. This is challenging, as increasing $G$ (e.g. by coupling the qubit more strongly to external stimuli) often leads to deleterious effects on T$_{2}$. Here, we study the couplin

Debayan Deb, Divyansh Aggarwal, Anil K. Jain

Given a gallery of face images of missing children, state-of-the-art face recognition systems fall short in identifying a child (probe) recovered at a later age. We propose an age-progression module that can age-progress deep face features output by any commodity face matcher. For time lapses larger than 10 years (the missing child is found after 10 or more

El Mahdi El Mhamdi, Rachid Guerraoui, Arsany Guirguis

Machine Learning (ML) solutions are nowadays distributed and are prone to various types of component failures, which can be encompassed in so-called Byzantine behavior. This paper introduces LiuBei, a Byzantine-resilient ML algorithm that does not trust any individual component in the network (neither workers nor servers), nor does it induce additional commu

Nicola Scianca, Ugo Rosolia, Francesco Borrelli

We propose a reference-free learning model predictive controller for periodic repetitive tasks. We consider a problem in which dynamics, constraints and stage cost are periodically time-varying. The controller uses the closed-loop data to construct a time-varying terminal set and a time-varying terminal cost. We show that the proposed strategy in closed-loop

Patric Muggli

We briefly describe the basic physics principles considered for planning of the AWAKE Run 2 experiment. These principles are based on experimental results obtained during Run 1 and knowledge obtained from numerical simulation results and other experiments. The goal of Run 2 is to accelerate an electron bunch with a narrow relative energy spread and an emitta

Michael Poli, Stefano Massaroli, Junyoung Park, Atsushi Yamashita

We introduce the framework of continuous--depth graph neural networks (GNNs). Graph neural ordinary differential equations (GDEs) are formalized as the counterpart to GNNs where the input-output relationship is determined by a continuum of GNN layers, blending discrete topological structures and differential equations. The proposed framework is shown to be c

Miguel Gutiérrez, Manuel Masip

High energy cosmic rays reach the surface of the Sun and start showers with thousands of secondary particles. Most of them will be absorbed by the Sun, but a fraction of the neutral ones will escape and reach the Earth. Here we incorporate a new ingredient that is essential to understand the flux of these solar particles: the cosmic ray shadow of the Sun. We

Peter Clifford, David Stirzaker

Ulam has defined a history-dependent random sequence of integers by the recursion $X_{n+1}$ $= X_{U(n)}+X_{V(n)}, n \geqslant r$ where $U(n)$ and $V(n)$ are independently and uniformly distributed on $\{1,\dots,n\}$, and the initial sequence, $X_1=x_1,\dots,X_r=x_r$, is fixed. We consider the asymptotic properties of this sequence as $n \to \infty$, showing,

Shubhangi Sikaria, Rituparna Sen, Neelesh S. Upadhye

For a long investment time horizon, it is preferable to rebalance the portfolio weights at intermediate times. This necessitates a multi-period market model in which portfolio optimization is usually done through dynamic programming. However, this assumes a known distribution for the parameters of the financial time series. We consider the situation where th

Junjie Huang, Zheng Zhu, Feng Guo, Guan Huang

Being a fundamental component in training and inference, data processing has not been systematically considered in human pose estimation community, to the best of our knowledge. In this paper, we focus on this problem and find that the devil of human pose estimation evolution is in the biased data processing. Specifically, by investigating the standard data

Kimet Jusufi, Mubasher Jamil, Hrishikesh Chakrabarty, Qiang Wu

In this paper, we use a suitable conformal rescaling to construct static and rotating regular black holes in conformal massive gravity. The new metric is characterized by the mass $M$, the "scalar charge" $Q$, the angular momentum parameter $a$, the "hair parameter" $λ$, and the conformal scale factor encoded in the parameter $L$. We explore

Debasis Mondal, Dagomir Kaszlikowski

We introduce a symmetric local hidden state $(slhs)$ model in a scenario, where two spacially separated parties receive quantum states from an unknown source. We derive an inequality based on the model. A completely new form of nonlocality emerges from the resource theoretic point of view. The inequality singles out a larger set of quantum correlated states

Andrea Pizzo, Thomas L. Marzetta, Luca Sanguinetti

We consider spatially-constrained apertures of rectangular symmetry and aim to retrieve the limit to the average number of spatial degrees of freedom (DoF), obtained elsewhere through different analyses and tools. Unlike prior works, we use the Fourier plane-wave series expansion, recently introduced in [1], where a statistical model for the small-scale fadi

Sébastien Mey, Erwan Liberge, Claudine Béghein

This paper deals with the numerical modelling of the interaction between a fluid and an incompressible solid (Neo Hookean) in small perturbations with the lattice Boltzmann method (LBM). In order to use a monolithic formulation and to solve the whole problem with the lattice Boltzmann method, an Eulerian approach is employed for the solid medium. The initial

José Bonet, Thomas Kalmes, Alfred Peris

We investigate dynamical properties such as topological transitivity, (sequential) hypercyclicity, and chaos for backward shift operators associated to a Schauder basis on LF-spaces. As an application, we characterize these dynamical properties for weighted generalized backward shifts on K\"othe coechelon sequence spaces $k_p((v^{(m)})_{m\in\mathbb{N}})$ in

Yermek Aldabergenov

We propose a novel realization of spontaneous supersymmetry breaking in de Sitter vacuum by F- and D-terms in $N=1$ four-dimensional supergravity coupled to a chiral superfield with $SU(1,1)/U(1)$ target space. Our construction features gauged $U(1)_R$ symmetry rotating the chiral scalar field by a phase. Both SUSY and R-symmetry can be spontaneously broken,

Florian Pfisterer, Laura Beggel, Xudong Sun, Fabian Scheipl

Time series classification problems have drawn increasing attention in the machine learning and statistical community. Closely related is the field of functional data analysis (FDA): it refers to the range of problems that deal with the analysis of data that is continuously indexed over some domain. While often employing different methods, both fields strive

Marwa Ben Jabra, Adel Ammar, Anis Koubaa, Omar Cheikhrouhou

Pilgrimage represents the most important Islamic religious gathering in the world where millions of pilgrims visit the holy places of Makkah and Madinah to perform their rituals. The safety and security of pilgrims is the highest priority for the authorities. In Makkah, 5000 cameras are spread around the holy for monitoring pilgrims, but it is almost impossi

Clément Elvira, Cédric Herzet

Spreading the information over all coefficients of a representation is a desirable property in many applications such as digital communication or machine learning. This so-called antisparse representation can be obtained by solving a convex program involving an $\ell_\infty$-norm penalty combined with a quadratic discrepancy. In this paper, we propose a new

Tania Biswas, Sheetal Dharmatti

Shell models of turbulence are representation of turbulence equations in Fourier domain. Various shell models along with numerical simulations have been studied earlier. One of the most suitable shell model of turbulence is so called sabra shell model. The existence, uniqueness and regularity property of this model are extensively studied in \cite{PBT}. In t

Abhijeet Melkani, Clemens Gneiting, Franco Nori

We discuss quantum state tomography via a stepwise reconstruction of the eigenstates of the mixed states produced in experiments. Our method is tailored to the experimentally relevant class of nearly pure states or simple mixed states, which exhibit dominant eigenstates and thus lend themselves to low-rank approximations. The developed scheme is applicable t