April 2020 arXiv papers — page 45

Jan de Boer, Jelle Hartong, Emil Have, Niels A. Obers

We consider uncharged fluids without any boost symmetry on an arbitrary curved background and classify all allowed transport coefficients up to first order in derivatives. We assume rotational symmetry and we use the entropy current formalism. The curved background geometry in the absence of boost symmetry is called absolute or Aristotelian spacetime. We pre

Po-Shen Hsin, Anton Kapustin, Ryan Thorngren

We study aspects of Berry phase in gapped many-body quantum systems by means of effective field theory. Once the parameters are promoted to spacetime-dependent background fields, such adiabatic phases are described by Wess-Zumino-Witten (WZW) and similar terms. In the presence of symmetries, there are also quantized invariants capturing generalized Thouless

Remco F. J. van der Burg, Gregory Rudnick, Michael L. Balogh, Adam Muzzin

We study the stellar mass functions (SMFs) of star-forming and quiescent galaxies in 11 galaxy clusters at 1.0<z<1.4, drawn from the Gemini Observations of Galaxies in Rich Early Environments (GOGREEN) survey. Based on more than 500 hours of Gemini/GMOS spectroscopy, and deep multi-band photometry taken with a range of observatories, we probe the SMFs down t

Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi

Kernel methods augmented with random features give scalable algorithms for learning from big data. But it has been computationally hard to sample random features according to a probability distribution that is optimized for the data, so as to minimize the required number of features for achieving the learning to a desired accuracy. Here, we develop a quantum

Matthew C. Nixon, Nikku Madhusudhan

Atmospheric retrieval of exoplanets from spectroscopic observations requires an extensive exploration of a highly degenerate and high-dimensional parameter space to accurately constrain atmospheric parameters. Retrieval methods commonly conduct Bayesian parameter estimation and statistical inference using sampling algorithms such as Markov Chain Monte Carlo

Paolo Creminelli, Or Hershkovits, Leonardo Senatore, András Vasy

We study, using Mean Curvature Flow methods, 3+1 dimensional cosmologies with a positive cosmological constant, matter satisfying the dominant and the strong energy conditions, and with spatial slices that can be foliated by 2-dimensional surfaces that are the closed orbits of a symmetry group. If these surfaces have non-positive Euler characteristic (or in

P. A. Maksimov, A. L. Chernyshev

We argue that several empirical constraints strongly restrict parameters of the effective microscopic spin model describing $\alpha$-RuCl$_3$. In particular, such constraints dictate a substantial \emph{positive} off-diagonal anisotropic coupling, $\Gamma^\prime\!>\!0$, not anticipated previously. The renormalization by quantum fluctuations allows to reconci

Nicola T. Locatelli, Kamlesh Rajpurohit, Franco Vazza, Fabio Gastaldello

The origin of radio relics is usually explained via diffusive shock acceleration (DSA) or re-acceleration of electrons at/from merger shocks in galaxy clusters. The case of acceleration is challenged by the low predicted efficiency of low-Mach number merger shocks, unable to explain the power observed in most radio relics. In this Letter we present the disco

Elena Farahbakhsh Touli

The purpose of this paper is to extend the definition of Frechet distance which measures the distance between two curves to a distance (Frechet-Like distance) which measures the similarity between two rooted trees. The definition of Frechet-Like distance is as follows: Tow men start from the roots of two trees. When they reach to a node with the degree of mo

Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe Jiang

In this work, we present a learning-based approach to chip placement, one of the most complex and time-consuming stages of the chip design process. Unlike prior methods, our approach has the ability to learn from past experience and improve over time. In particular, as we train over a greater number of chip blocks, our method becomes better at rapidly genera

Raniere de Menezes, Raffaele D'Abrusco, Francesco Massaro, Dario Gasparrini

Associating gamma-ray sources to their low-energy counterparts is one of the major challenges of modern gamma-ray astronomy. In the context of the Fourth Fermi Large Area Telescope Source Catalog (4FGL), the associations rely mainly on parameters as apparent magnitude, integrated flux, and angular separation between the gamma-ray source and its low-energy ca

Kyung Soo Rim, U Jin Choi

We introduce probabilistic neural networks that describe unsupervised synchronous learning on an atomic Hardy space and space of bounded real analytic functions, respectively. For a stationary ergodic vector process, we prove that the probabilistic neural network yields a unique collection of neurons in global optimization without initialization and back-pro

Juliette Alimena, Yutaro Iiyama, Jan Kieseler

We present a first proof of concept to directly use neural network based pattern recognition to trigger on distinct calorimeter signatures from displaced particles, such as those that arise from the decays of exotic long-lived particles. The study is performed for a high granularity forward calorimeter similar to the planned high granularity calorimeter for

Yuichiro Nakai, Ryo Namba, Ziwei Wang

We discuss the possibility of producing a light dark photon dark matter through a coupling between the dark photon field and the inflaton. The dark photon with a large wavelength is efficiently produced due to the inflaton motion during inflation and becomes non-relativistic before the time of matter-radiation equality. We compute the amount of production an

Semin Yoo

We study graphs coming from quadratic spaces over finite fields via orthogonality which generalize a recent result given by Bishnoi, Ihringer, and Pepe (2019). More precisely, we study the graph $\Gamma^{\square}(n,k,q)$ as follows: the vertex set is the set of $k$-dimensional quadratic subspaces of a fixed Lorentzian quadratic space $(\mathbb{F}_{q}^{n},x_{

James Hefford, Vincent Wang, Matthew Wilson

Modelling concept representation is a foundational problem in the study of cognition and linguistics. This work builds on the confluence of conceptual tools from G\"ardenfors semantic spaces, categorical compositional linguistics, and applied category theory to present a domain-independent and categorical formalism of 'concept'.

Kiyoshi Igusa, Job D. Rock, Gordana Todorov

We continue the work started in parts (I) and (II). In this part we classify which continuous type A quivers are derived equivalent and introduce the new continuous cluster category with E-clusters, which are a generalization of clusters. In the middle we provide a rigorous connection between the previous construction of the continuous cluster category and t

Jérémy Blanc, Pierre-Marie Poloni

We study a family of polynomials introduced by Daigle and Freudenburg, which contains the famous V\'en\'ereau polynomials and defines $\mathbb{A}^2$-fibrations over $\mathbb{A}^2$. According to the Dolgachev-Weisfeiler conjecture, every such fibration should have the structure of a locally trivial $\mathbb{A}^2$-bundle over $\mathbb{A}^2$. We follow an idea

Suvendu Mandal, Lukas Schrack, Hartmut Löwen, Matthias Sperl

Transport properties of a hard-sphere colloidal fluid are investigated by Brownian dynamics simulations. We implement a novel algorithm for the time-dependent velocity-autocorrelation function (VACF) essentially eliminating the noise of the bare random motion. The measured VACF reveals persistent anti-correlations manifested by a negative algebraic power-law

Shirshendu Ganguly, Reza Gheissari

Consider the Ising model at low-temperatures and positive external field $\lambda$ on an $N\times N$ box with Dobrushin boundary conditions that are plus on the north, east, and west boundaries and minus on the south boundary. If $\lambda = 0$, the interface separating the plus and minus phases is diffusive, having $O(\sqrt N)$ height fluctuations, and the m

L. M. Abreu, F. M. da Costa Júnior, A. G. Favero

This work is devoted to the discussion and characterization of the tensor $2^{-(-)}$ meson spectrum, by making use of the Coulomb gauge Hamiltonian approach to QCD, with the interactions being given by an improved confining potential and a transverse hyperfine interaction, whose kernel is a Yukawa-type potential. Our aim is to study the basic features of $2^

K. Burdonov, G. Revet, R. Bonito, C. Argiroffi

Investigating in the laboratory the process of matter accretion onto forming stars through scaled experiments is important in order to better understand star and planetary systems formation and evolution. Such experiments can indeed complement observations by providing access to the processes with spatial and temporal resolution. A first step has been made i

Michael W. Liemohn, Abigail R. Azari, Natalia Ganushkina, Lutz Rastaetter

A new model validation and performance assessment tool is introduced, the sliding threshold of observation for numeric evaluation (STONE) curve. It is based on the relative operating characteristic (ROC) curve technique, but instead of sorting all observations in a categorical classification, the STONE tool uses the continuous nature of the observations. Rat

Ahmad B Qasim, Ivan Ezhov, Suprosanna Shit, Oliver Schoppe

Exploiting learning algorithms under scarce data regimes is a limitation and a reality of the medical imaging field. In an attempt to mitigate the problem, we propose a data augmentation protocol based on generative adversarial networks. We condition the networks at a pixel-level (segmentation mask) and at a global-level information (acquisition environment

Gil Triginer Garces, Helen M. Chrzanowski, Shakib Daryanoosh, Valerian Thiel

Nonlinear optical microscopy techniques have emerged as a set of successful tools for biological imaging. Stimulated emission microscopy belongs to a small subset of pump-probe techniques which can image non-fluorescent samples without requiring fluorescent labelling. However, its sensitivity has been shown to be ultimately limited by the quantum fluctuation

Vurukonda Sathish, Siuli Mukhopadhyay, Rashmi Tiwari

Zero inflation is a common nuisance while monitoring disease progression over time. This article proposes a new observation driven model for zero inflated and over-dispersed count time series. The counts given the past history of the process and available information on covariates is assumed to be distributed as a mixture of a Poisson distribution and a dist

Ibrahim Shaer, Anwar Haque, Abdallah Shami

Vehicle-to-everything (V2X) services are attracting a lot of attention in the research and industry communities due to their applicability in the landscape of connected and autonomous vehicles. Such applications have stringent performance requirements in terms of complex data processing and low latency communications which are utilized to ensure road safety

Nathan D. Bamberger, Jeffrey A. Ivie, Keshaba N. Parida, Dominic V. McGrath

Improved understanding of charge-transport in single molecules is essential for harnessing the potential of molecules e.g. as circuit components at the ultimate size limit. However, interpretation and analysis of the large, stochastic datasets produced by most quantum transport experiments remains an ongoing challenge to discovering much-needed structure-pro

Athanasios Chatzistavrakidis, Georgios Karagiannis, Peter Schupp

We review the construction of Lagrangians for higher spin fields of mixed symmetry in the framework of graded geometry. The main advantage of the graded formalism in this context is that it provides universal expressions, in the sense that a given Lagrangian describes the dynamics of any type of bosonic tensor field even though the corresponding explicit exp

M. Khuili, N. Fazouan, H. Abou El Makarim, E. H. Atmani

A comparative study of wurtzite ZnO doped by rare earth elements (Tm, Yb, Ce) have been investigated using density functional theory (DFT) based on the full-potential linearized augmented plane wave orbital (FP-LAPW) method, as implemented in Wien2K code. The structural parameters were calculated by PBEsol functional and in good agreement with the experiment

Jamol Pender, Shuang Tao, Anders Wikum

Electric scooters are becoming immensely popular across the world as a means of reliable transportation around many cities. As these e-scooters rely on batteries, it is important to understand how many of these e-scooters have enough battery life to transport riders and when these e-scooters might require a battery replacement. To this end, we develop the fi

Giorgio Zicari, Matteo Brunelli, Mauro Paternostro

Entropy production provides a general way to state the second law of thermodynamics for non-equilibrium scenarios. In open quantum system dynamics, it also serves as a useful quantifier of the degree of irreversibility. In this work we shed light on the relation between correlations, initial preparation of the system and non-Markovianity by studying a system

Takato Yasuno, Nakajima Michihiro, Noda Kazuhiro

Efficient inspection and accurate diagnosis are required for civil infrastructures with 50 years since completion. Especially in municipalities, the shortage of technical staff and budget constraints on repair expenses have become a critical problem. If we can detect damaged photos automatically per-pixels from the record of the inspection record in addition

Shi Yu

When applying eigenvalue decomposition on the quadratic term matrix in a type of linear equally constrained quadratic programming (EQP), there exists a linear mapping to project optimal solutions between the new EQP formulation where $Q$ is diagonalized and the original formulation. Although such a mapping requires a particular type of equality constraints,

Davide Fioravanti, Marco Rossi, Hongfei Shu

We provide the two fundamental sets of functional relations which describe the strong coupling limit of scattering amplitudes in $\mathcal{N} = 4$ SYM dual to Wilson loops in $AdS_3$: the basic $QQ$-system and the derived $TQ$-system. We use the $TQ$ relations and the knowledge of the main properties of the $Q$-function (eigenvalue of some $Q$-operator) to w

Xavier Tolsa

Let $\Omega\subset\mathbb R^n$ be a $C^1$ domain, or more generally, a Lipschitz domain with small local Lipschitz constant. In this paper it is shown that if $u$ is a function harmonic in $\Omega$ and continuous in $\overline \Omega$ which vanishes in a relatively open subset $\Sigma\subset\partial\Omega$ and moreover the normal derivative $\partial_\nu u$

Alistair Bentley, V. J. Ervin

In this article we consider the linear elasticity problem in an axisymmetric three dimensional domain, with data which are axisymmetric and have zero angular component. The weak formulation of the the three dimensional problem reduces to a two dimensional problem on the meridian domain, involving weighted integrals. The problem is formulated in a mixed metho

Hariom Sharma, R. K. Sharma

Let $F=\mathbb{F}_{q^m}$, $m>6$, $n$ a positive integer, and $f=p/q$ with $p$, $q$ co-prime irreducible polynomials in $F[x]$ and deg$(p)$ $+$ deg$(q)= n$. A sufficient condition has been obtained for the existence of primitive pairs $(\alpha, f(\alpha))$ in $F$ such that for any prescribed $a, b$ in $E=\mathbb{F}_q$, Tr$F/E (\alpha) = a$ and Tr$F/E (\alpha^

Hao Tian, Peng Tao

Molecular dynamics (MD) simulations have been widely applied to study macromolecules including proteins. However, high-dimensionality of the datasets produced by simulations makes it difficult for thorough analysis, and further hinders a deeper understanding of biomacromolecules. To gain more insights into the protein structure-function relations, appropriat

Masaru Nagisa, Yasuo Watatani

We study several classes of general non-linear positive maps between C*-algebras, which are not necessary completely positive maps. We characterize the class of the compositions of *-multiplicative maps and positive linear mapsas the class of non-linear maps of boundedly positive type abstractly. We consider three classes of non-linear positive maps defined

James Bonifacio, Kurt Hinterbichler, Laura A. Johnson

It has recently been argued that there may be a nontrivial four-dimensional limit of the higher-dimensional Gauss--Bonnet and Lovelock interactions and that this might provide a loophole allowing for new four-dimensional gravitational theories, possibly without a standard Lagrangian. We investigate this claim by studying tree-level graviton scattering amplit

Anu Jagannath, Jithin Jagannath, Tommaso Melodia

The year 2019 witnessed the rollout of the 5G standard, which promises to offer significant data rate improvement over 4G. While 5G is still in its infancy, there has been an increased shift in the research community for communication technologies beyond 5G. The recent emergence of machine learning approaches for enhancing wireless communications and empower

Shan Wang, Li-Jen Chen, Naoki Bessho, Michael Hesse

We investigate electric current structures in Short Large-Amplitude Magnetic Structures (SLAMS) in the terrestrial ion foreshock region observed by the Magnetospheric Multiscale mission. The structures with intense currents (|J|~1 {\mu}A/m^2) have scale lengths comparable to the local ion inertial length (di). One current structure type is a current sheet du

Rakotobe Michaël, Ramalingom Delphine, Cocquet Pierre-Henri, Bastide Alain

The objective of this study is to highlight the effect of porosity variation in a topology optimization process in the field of fluid dynamics. Usually a penalization term added to momentum equation provides to get material distribution. Every time material is added inside the computational domain, there is creation of new fluid-solid interfaces and appariti

Igor Bandos, Stefano Lanza, Dmitri Sorokin

We review main features of the pure $\mathcal N=1$, $D=4$ SYM and its effective description by the Veneziano-Yankielowicz generalized sigma-model. We then indicate that the construction of BPS domain walls interpolating between different SYM vacua requires the presence of a dynamical membrane source. We will show how such a membrane is coupled to the SYM and

João Caldeira, Brian Nord

We present a comparison of methods for uncertainty quantification (UQ) in deep learning algorithms in the context of a simple physical system. Three of the most common uncertainty quantification methods - Bayesian Neural Networks (BNN), Concrete Dropout (CD), and Deep Ensembles (DE) - are compared to the standard analytic error propagation. We discuss this c

Karthik Ramanathan, Noah Kurinsky

The development of single charge resolving, macroscopic silicon detectors has opened a window into rare processes at the O(eV) scale. In order to reconstruct the energy of a given event, or model the charge signal obtained for a given amount of energy absorbed by the electrons in a detector, an accurate charge yield model is needed. In this paper we review e

Vishal Katariya, Mark M. Wilde

Quantum channel estimation and discrimination are fundamentally related information processing tasks of interest in quantum information science. In this paper, we analyze these tasks by employing the right logarithmic derivative Fisher information and the geometric R\'enyi relative entropy, respectively, and we also identify connections between these disting

Lucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, Russell Reas

The COVID-19 Open Research Dataset (CORD-19) is a growing resource of scientific papers on COVID-19 and related historical coronavirus research. CORD-19 is designed to facilitate the development of text mining and information retrieval systems over its rich collection of metadata and structured full text papers. Since its release, CORD-19 has been downloaded

Erwin H. Tanin, Tommi Tenkanen

Gravitational waves (GW) produced in the early Universe contribute to the number of relativistic degrees of freedom, $N_{\rm eff}$, during Big Bang Nucleosynthesis (BBN). By using the constraints on $N_{\rm eff}$, we present a new bound on how much the Universe could have expanded between horizon exit of the largest observable scales today and the end of inf

John Ramírez-Figueroa, Carlos Martín-Barreiro, Ana B. Nieto-Librero, Victor Leiva-Sánchez

In this paper, we propose an alternative method to the disjoint principal component analysis. The method consists of a principal component analysis with constraints, which allows us to determine disjoint components that are linear combinations of disjoint subsets of the original variables. The proposed method is named constrained binary optimization by parti

Netanel Raviv, Siddharth Jain, Pulakesh Upadhyaya, Jehoshua Bruck

Deep Neural Networks (DNNs) are a revolutionary force in the ongoing information revolution, and yet their intrinsic properties remain a mystery. In particular, it is widely known that DNNs are highly sensitive to noise, whether adversarial or random. This poses a fundamental challenge for hardware implementations of DNNs, and for their deployment in critica

J. A. Niskanen

Recently it has been pointed out that in the two-baryon $N\Delta$ or $\Delta\Delta$ system the width of the state is greatly diminished due to the relative kinetic energy of the two baryons, since the internal energy of the particles, available for pionic decay, is smaller. For nonzero orbital angular momenta this effect becomes state dependent. Also the rea

Keting Lu, Shiqi Zhang, Xiaoping Chen

Deep reinforcement learning (RL) algorithms frequently require prohibitive interaction experience to ensure the quality of learned policies. The limitation is partly because the agent cannot learn much from the many low-quality trials in early learning phase, which results in low learning rate. Focusing on addressing this limitation, this paper makes a twofo

Stefan Gerhold, Friedrich Hubalek, Richard B. Paris

We derive tail asymptotics for the running maximum of the Cox-Ingersoll-Ross process. The main result is proved by the saddle point method, where the tail estimate uses a new monotonicity property of the Kummer function. This auxiliary result is established by a computer algebra assisted proof. Moreover, we analyse the coefficients of the eigenfunction expan

Demetris Marnerides, Thomas Bashford-Rogers, Kurt Debattista

Convolutional Neural Networks (CNNs) are the current de-facto models used for many imaging tasks due to their high learning capacity as well as their architectural qualities. The ubiquitous UNet architecture provides an efficient and multi-scale solution that combines local and global information. Despite the success of UNet architectures, the use of upsampl

Mingye Xiong, Michael Graf, Nagendra Athreya, Aleksandra Radenovic

A microscopic physical analysis of the various resistive effects involved in the electronic detection of single biomolecules in a nanopore of a MoS2 nanoribbon is presented. The analysis relies on a combined experimental-theoretical approach, where the variations of the transverse electronic current along the two-dimensional (2D) membrane due to the transloc

Yikang Zhang, Jian Zhang, Qiang Wang, Zhao Zhong

Convolution operator is the core of convolutional neural networks (CNNs) and occupies the most computation cost. To make CNNs more efficient, many methods have been proposed to either design lightweight networks or compress models. Although some efficient network structures have been proposed, such as MobileNet or ShuffleNet, we find that there still exists

Santanu Pakhira, N. S. Sangeetha, V. Smetana, A. -V. Mudring

Single crystals of Ca[Co_(2-x)Ir_(x)]_(2-y)As2 with 0 <= x <= 0.35 and 0.10 <= y <= 0.14 have been grown using the self-flux technique and characterized by single-crystal x-ray diffraction (XRD), energy-dispersive x-ray spectroscopy, magnetization M and magnetic susceptibility chi measurements versus temperature T, magnetic field H, and time t, and heat capa

Thomas Gerard, Christophe Sabot, Xiaolin Zeng

A classic result on the 1-dimensional Brownian motion shows that conditionally on its first hitting time of 0, it has the distribution of a 3-dimensional Bessel bridge. By applying a certain time-change to this result, Matsumoto and Yor showed a theorem giving a relation between Brownian motions with opposite drifts. The relevant time change is the one appea

Aziz Elbour

In this paper, we investigate more about relationship between $uaw$ -convergence (resp. $un$-convergence) and the weak convergence. More precisely, we characterize Banach lattices on which every weak null sequence is $uaw$-null. Also, we characterize order continuous Banach lattices under which every norm bounded $un$-null net (resp. sequence) is weakly null

Mohammad Bilal Khan

The critical assessment presented within this paper explores existing research pertaining to the Advanced Persistent Threat (APT) branch of cyber security, applying the knowledge extracted from this research to discuss, evaluate and opinionate upon the areas of discussion as well as involving personal experiences and knowledge within this field. The synthesi

Ravi Anand, Arpita Maitra, Sourav Mukhopadhyay

For any symmetric key cryptosystem with $n$-bit secret key, the key can be recovered in $O(2^{n/2})$ exploiting Grover search algorithm, resulting in the effective key length to be half. In this direction, subsequent work has been done on AES and some other block ciphers. On the other hand, lightweight ciphers like SIMON was left unexplored. In this backdrop

Dániel Korándi, Alexander Roberts, Alex Scott

Tur\'an's Theorem says that an extremal $K_{r+1}$-free graph is $r$-partite. The Stability Theorem of Erd\H{o}s and Simonovits shows that if a $K_{r+1}$-free graph with $n$ vertices has close to the maximal $t_r(n)$ edges, then it is close to being $r$-partite. In this paper we determine exactly the $K_{r+1}$-free graphs with at least $m$ edges that are fart

Abhay Ashtekar, Alejandro Corichi, Aruna Kesavan

We investigate three issues that have been discussed in the context of inflation: Fading of the importance of quantum non-commutativity; the phenomenon of quantum squeezing; and the ability to approximate the quantum state by a distribution function on the classical phase space. In the standard treatments, these features arise from properties of mode functio

Shao-Feng Ge, Hong-Jian He, Yu-Chen Wang, Qiang Yuan

Measuring high energy cosmic ray electrons/positrons (CRE) provides important means for the dark matter (DM) indirect detection and for probing the nearby galactic sources. In this work, we perform a systematic analysis of the flavor structure of DM annihilations into charged leptons based on the cosmic ray CRE spectra measured by DAMPE, Fermi-LAT, AMS-02, a

Giona Veronelli

A basilar property and a useful tool in the theory of Sobolev spaces is the density of smooth compactly supported functions in the space $W^{k,p}(\R^n)$ (i.e. the functions with weak derivatives of orders $0$ to $k$ in $L^p$). On Riemannian manifolds, it is well known that the same property remains valid under suitable geometric assumptions. However, on a co

Lokender Tiwari, Pan Ji, Quoc-Huy Tran, Bingbing Zhuang

Classical monocular Simultaneous Localization And Mapping (SLAM) and the recently emerging convolutional neural networks (CNNs) for monocular depth prediction represent two largely disjoint approaches towards building a 3D map of the surrounding environment. In this paper, we demonstrate that the coupling of these two by leveraging the strengths of each miti

Milutin Obradović, Nikola Tuneski

In this paper we improve the upper bound of the third order Hankel determinant for the class of Ozaki close-to-convex functions. The sharp bound is conjectured.

Julio Backhoff-Veraguas, Joaquín Fontbona

We consider the problem of minimizing a generalized relative entropy, with respect to a reference diffusion law, over the set of path-measures with fully prescribed marginal distributions. When dealing with the actual relative entropy, problems of this kind have appeared in the stochastic mechanics literature, and minimizers go under the name of Nelson Proce

L. M. Abreu, E. B. S. Corrêa, E. S. Nery

In this work we investigate the finite-size effects on the phase structure of a two-flavor four-fermion interaction model with a flavor-mixing four-body interaction and in the presence of a magnetic background, taking into account different boundary conditions. We employ mean-field approximation and Schwinger's proper-time method in a toroidal topology with

J. -B. Delisle, N. Hara, D. Ségransan

Correlated noise affects most astronomical datasets and to neglect accounting for it can lead to spurious signal detections, especially in low signal-to-noise conditions, which is often the context in which new discoveries are pursued. For instance, in the realm of exoplanet detection with radial velocity time series, stellar variability can induce false det

Philipp Staudinger, Svenja Mauthe, Noelia Vico Triviño, Steffen Reidt

Metastable wurtzite crystal phases of semiconductors comprise enormous potential for high-performance electro-optical devices, owed to their extended tunable direct band gap range. However, synthesizing these materials in good quality and beyond nanowire size constraints has remained elusive. In this work, the epitaxy of wurtzite InP microdisks and related g

Zachary P Kilpatrick, Jacob D Davidson, Ahmed El Hady

Foraging is a fundamental behavior as animals' search for food is crucial for their survival. Patch leaving is a canonical foraging behavior, but classic theoretical conceptions of patch leaving decisions lack some key naturalistic details. Optimal foraging theory provides general rules for when an animal should leave a patch, but does not provide mechanisti

Shulai Zhang, Xiaoli Ma

Designing an efficient difficulty control algorithm is an essential problem in Proof-of-Work (PoW) based blockchains because the network hash rate is randomly changing. This paper proposes a general difficulty control algorithm and provides insights for difficulty adjustment rules for PoW based blockchains. The proposed algorithm consists a two-layer neural

Kaïs Ammari, Fathi Hassine, Luc Robbiano

We study the problem of stabilization for the acoustic system with a spatially distributed damping. Without imposing any hypotheses on the structural properties of the damping term, we identify logarithmic decay of solutions with growing time. Logarithmic decay rate is shown by using a frequency domain method and combines a contradiction argument with the mu

Emanuele Congiu, Abdellahi Sow, Thanh Nguyen, Saoud Baouche

A multi-beam ultra-high vacuum apparatus is presented. In this article we describe the design and construction of a new laboratory astrophysics experiment -- VErs de NoUvelles Synth\`eses (VENUS) -- that recreates the solid-state non-energetic formation conditions of complex organic molecules in dark clouds and circumstellar environments. The novel implement

G. Novara, P. Esposito, A. Tiengo, G. Vianello

During a search for X-ray transients in the XMM-Newton archive within the EXTraS project, we discovered a new X-ray source that is detected only during a ~5 min interval of a ~21 h-long observation performed on 2011 June 21 (EXMM 023135.0-603743, probability of a random Poissonian fluctuation: ~$1.4\times10^{-27}$). With dedicated follow-up observations, we

Tongxue Zhou, Su Ruan, Stéphane Canu

Multi-modality is widely used in medical imaging, because it can provide multiinformation about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing multi-information to improve the segmentation. Recently, deep learning-based approaches have presented the state-of-the-art performance in image classification, segmentation, ob

Dingmin Wang, Chenghua Lin, Qi Liu, Kam-Fai Wong

We present a fast and scalable architecture called Explicit Modular Decomposition (EMD), in which we incorporate both classification-based and extraction-based methods and design four modules (for classification and sequence labelling) to jointly extract dialogue states. Experimental results based on the MultiWoz 2.0 dataset validates the superiority of our

Chiara Esposito, Andreas Kraft, Jonas Schnitzer

In this paper we propose a reduction scheme for multivector fields phrased in terms of $L_\infty$-morphisms. Using well-know geometric properties of the reduced manifolds we perform a Taylor expansion of multivector fields, which allows us to built up a suitable deformation retract of DGLA's. We first obtained an explicit formula for the $L_\infty$-Projectio

Hai Dong, Yaoxiong Wen

In this paper, we prove a class of nontrivial q-Pochhammer symbol identities with extra parameters by iterated residue method. Then we use these identities to find relations of the quasi-map $K$-theoretical $I$-functions with level structure between Grassmannian and its dual Grassmannian. Here we find an interval of levels within which two $I$-functions are

Priyadarshini Panda

Deep Neural Networks (DNNs) have been shown to be vulnerable to adversarial attacks, wherein, a model gets fooled by applying slight perturbations on the input. With the advent of Internet-of-Things and the necessity to enable intelligence in embedded devices, low-power and secure hardware implementation of DNNs is vital. In this paper, we investigate the us

Agustinus Andriyanto, Robin Doss

Lack of resources is a challenge for small and medium enterprises (SMEs) in implementing an IT-based system to facilitate more efficient business decisions and expanding the market. A community system based on service-oriented architecture (SOA) can help SMEs alleviate this problem. This paper explores and analyses the frameworks proposed by previous studies

Changming Wu, Heshan Yu, Seokhyeong Lee, Ruoming Peng

Neuromorphic photonics has recently emerged as a promising hardware accelerator, with significant potential speed and energy advantages over digital electronics, for machine learning algorithms such as neural networks of various types. Integrated photonic networks are particularly powerful in performing analog computing of matrix-vector multiplication (MVM)

Olga Polverino, Giovanni Zini, Ferdinando Zullo

Let $f$ be the $\mathbb{F}_q$-linear map over $\mathbb{F}_{q^{2n}}$ defined by $x\mapsto x+ax^{q^s}+bx^{q^{n+s}}$ with $\gcd(n,s)=1$. It is known that the kernel of $f$ has dimension at most $2$, as proved by Csajb\'ok et al. in "A new family of MRD-codes" (2018). For $n$ big enough, e.g. $n\geq5$ when $s=1$, we classify the values of $b/a$ such that the ker

Rafael Chiclana, Miguel Martin

We study the stability behavior of the Bishop-Phelps-Bollob\'as property for Lipschitz maps (Lip-BPB property). This property is a Lipschitz version of the classical Bishop-Phelps-Bollob\'as property and deals with the possibility of approximating a Lipschitz map that almost attains its (Lipschitz) norm at a pair of distinct points by a Lipschitz map attaini

T. Lin, L. Y. Shi, Z. X. Wang, S. J. Zhang

The parkerite-type ternary chalcogenide Bi$_2$Rh$_3$Se$_2$ was discovered to be a charge density wave (CDW) superconductor. However, there was a debate on whether the observed phase transition at 240 K could be attributed to the formation of CDW order. To address the issue, we performed optical spectroscopy and ultrafast pump-probe measurements on single cry

A. Belhaj, A. El Balali, W. El Hadri, Y. Hassouni

We study $d$-dimensional $AdS$ black holes surrounded by Dark Energy (DE), embedded in $D$-dimensional M-theory/superstring inspired models having $AdS_d \times \mathbb{S}^{d+k}$ space-time with $D=2d+k$. We focus on the thermodynamic Hawking-Page phase transitions of quintessential DE black hole solutions, whose microscopical origin is linked to $N$ coincid

O. R. Rubinas, V. V. Soshenko, S. V. Bolshedvorskii, A. I. Zeleneev

The sensitivity of the nitrogen-vacancy (NV) color centers in diamond-based magnetometers strongly depends on the number of NV centers involved in the measurement. Unfortunately, an increasing concentration of NV centers leads to decreases of their dephasing and coherence time if the nitrogen content exceeds a certain threshold level (approximately ${10^{17}

Sewon Min, Julian Michael, Hannaneh Hajishirzi, Luke Zettlemoyer

Ambiguity is inherent to open-domain question answering; especially when exploring new topics, it can be difficult to ask questions that have a single, unambiguous answer. In this paper, we introduce AmbigQA, a new open-domain question answering task which involves finding every plausible answer, and then rewriting the question for each one to resolve the am

Matthew A. Malkan, Sean T. Scully, Floyd W. Stecker

Motivated by the discovery of the ultra-strong emission line starburst galaxies (EELGs) known as "green pea galaxies", we consider here their contribution to the intergalactic flux of ionizing UV at high redshifts. Most galaxies that have been observed show a precipitous drop in their flux blueward of the Lyman limit. However, recent observations of EELGs ha

Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, Jan Hajič

Universal Dependencies is an open community effort to create cross-linguistically consistent treebank annotation for many languages within a dependency-based lexicalist framework. The annotation consists in a linguistically motivated word segmentation; a morphological layer comprising lemmas, universal part-of-speech tags, and standardized morphological feat

Annika Hagemann, Jens Wilting, Bita Samimizad, Florian Mormann

Epileptic seizures are characterized by abnormal and excessive neural activity, where cortical network dynamics seem to become unstable. However, most of the time, during seizure-free periods, cortex of epilepsy patients shows perfectly stable dynamics. This raises the question of how recurring instability can arise in the light of this stable default state.

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassasni, Michal J. Wesolowski, Kevin A. Schneider

The newly identified Coronavirus pneumonia, subsequently termed COVID-19, is highly transmittable and pathogenic with no clinically approved antiviral drug or vaccine available for treatment. The most common symptoms of COVID-19 are dry cough, sore throat, and fever. Symptoms can progress to a severe form of pneumonia with critical complications, including s

Genet Asefa Gesese, Mehwish Alam, Harald Sack

Most Knowledge Graphs (KGs) contain textual descriptions of entities in various natural languages. These descriptions of entities provide valuable information that may not be explicitly represented in the structured part of the KG. Based on this fact, some link prediction methods which make use of the information presented in the textual descriptions of enti

N. A. Lopez, I. Y. Dodin

Geometrical optics (GO) is often used to model wave propagation in weakly inhomogeneous media and quantum-particle motion in the semiclassical limit. However, GO predicts spurious singularities of the wavefield near reflection points and, more generally, at caustics. We present a new formulation of GO, called metaplectic geometrical optics (MGO), that is fre

Olga Petrova, Karel Durkota, Galina Alperovich, Karel Horak

Anomaly detection is a method for discovering unusual and suspicious behavior. In many real-world scenarios, the examined events can be directly linked to the actions of an adversary, such as attacks on computer networks or frauds in financial operations. While the defender wants to discover such malicious behavior, the attacker seeks to accomplish their goa

Akihide Nobuhiro, Yusuke Hirahara, Kensuke Homma, Yuri Kirita

Resonance states of axion-like particles were searched for via four-wave mixing by focusing two-color pulsed lasers into a quasi-vacuum. A quasi-parallel collision system that allows probing of the sub-eV mass range was realized by focusing the combined laser fields with an off-axis parabolic mirror. A 0.10 mJ/34 fs Ti:Sapphire laser pulse and a 0.14 mJ/9 ns

D. Flavián, S. Hayashida, L. Huberich, D. Blosser

A single-crystal sample of the frustrated quasi one-dimensional quantum magnet Cs$_{2}$Cu$_{2}$Mo$_{3}$O$_{12}$ is investigated by magnetic and thermodynamic measurements.A combination of specific heat and magnetic torque measurements maps out the entire $H$-$T$ phase diagram for three orientations.Remarkably, a new phase emerges below the saturation field,