March 2020 arXiv papers — page 71

Vivek Sahai, Ashish Verma

In this paper we derive the infinite summation formulas of Srivastava's general triple hypergeometric function. Certain particular cases leading to infinite summation formulas for fourteen Lauricella and three Srivastavaś triple hypergeometric functions are also presented.

Hamid Hosseinianfar, Maite Brandt-Pearce

Visible light communication (VLC) systems are promising candidates for future indoor access and peer-to-peer networks. The performance of these systems, however, is vulnerable to the line of sight (LOS) link blockage due to objects inside the room. In this paper, we develop a probabilistic object detection method that takes advantage of the blockage status o

Rachel Gehlhar, Yuxiao Chen, Aaron D. Ames

This paper proposes a data-driven method for powered prosthesis control that achieves stable walking without the need for additional sensors on the human. The key idea is to extract the nominal gait and the human interaction information from motion capture data, and reconstruct the walking behavior with a dynamic model of the human-prosthesis system. The wal

Shruthi Chari, Daniel M. Gruen, Oshani Seneviratne, Deborah L. McGuinness

Interest in the field of Explainable Artificial Intelligence has been growing for decades and has accelerated recently. As Artificial Intelligence models have become more complex, and often more opaque, with the incorporation of complex machine learning techniques, explainability has become more critical. Recently, researchers have been investigating and tac

Vivek Sahai, Ashish Verma

Special matrix functions have recently been investigated for regions of convergence, integral representations and the systems of matrix differential equation that these functions satisfy. In this paper, we find the recursion formulas for the Gauss hypergeometric matrix function. We also give the recursion formulas for the two variable Appell matrix functions

Shruthi Chari, Daniel M. Gruen, Oshani Seneviratne, Deborah L. McGuinness

Explainability has been an important goal since the early days of Artificial Intelligence. Several approaches for producing explanations have been developed. However, many of these approaches were tightly coupled with the capabilities of the artificial intelligence systems at the time. With the proliferation of AI-enabled systems in sometimes critical settin

Xing Yang

The lifetime effects of the electron pairs are supposed to be responsible for the atypical behavior of the single electron transistors manufactured at the strontium titanate/ lanthanum aluminate (STO/LAO) interface. In addition, as shown in Richter's experiments, the energy gap $Δ$ should persist above the superconducting transition temperature $T_c$. In

Luanxuan Hou, Jie Cao, Yuan Zhao, Haifeng Shen

The target of human pose estimation is to determine body part or joint locations of each person from an image. This is a challenging problems with wide applications. To address this issue, this paper proposes an augmented parallel-pyramid net with attention partial module and differentiable auto-data augmentation. Technically, a parallel pyramid structure is

Minjie Shan, Baoxiang Wang, Liqun Zhang

The Cauchy problem for Zakharov-Kuznetsov equation on $\mathbb{R}^2$ is shown to be global well-posed for the initial date in $H^{s}$ provided $s>-\frac{1}{13}$. As conservation laws are invalid in Sobolev spaces below $L^2$, we construct an almost conserved quantity using multilinear correction term following the $I$-method introduced by Colliander, Keel, S

Jongmin Yu, Yongsang Yoon, Moongu Jeon

In skeleton-based action recognition, graph convolutional networks (GCNs), which model human body skeletons using graphical components such as nodes and connections, have achieved remarkable performance recently. However, current state-of-the-art methods for skeleton-based action recognition usually work on the assumption that the completely observed skeleto

Yong Moo Chung ad Kenichiro Yamamoto

For $0\le α<1$ and $β>2$, we consider a linear mod 1 transformation on a unit interval; $x\mapstoβx+α$ (${\rm mod}\ 1$), and prove that it satisfies the level-2 large deviation principle with the unique measure of maximal entropy. For the proof, we use the density of periodic measures and Hofbauer&#39;s Markov Diagram.

Meng-Yue Cao, Jack H, Koolen, Yen-Chi Roger Lin

In this paper we show that the conjecture of Lemmens and Seidel of 1973 for systems of equiangular lines with common angle $\arccos (1/5)$ is true. Our main tool is forbidden subgraphs for smallest Seidel eigenvalue $-5$.

S. M. Zhang, X. Z. Zhang, L. Jin, Z. Song

We employ the intertwining operator technique to synthesize a supersymmetric (SUSY) array of arbitrary size $N$. The synthesized SUSY system is equivalent to a spin-$(N-1)/2$ under an effective magnetic field. By considering an additional imaginary magnetic field, we obtain a generalized parity-time-symmetric non-Hermitian Hamiltonian that describes a SUSY a

A. K. Bhavani Singh, Mounika Guntu, Ananth Reddy Bhimireddy, Judy W. Gichoya

In the United States, 25% or greater than 200 billion dollars of hospital spending accounts for administrative costs that involve services for medical coding and billing. With the increasing number of patient records, manual assignment of the codes performed is overwhelming, time-consuming and error-prone, causing billing errors. Natural language processing

Amir Hossein Alikhah Mishamandani

The Attitude Determination and Control System is one of the critical boards of any satellite, specially the micro-satellites. The ADCS is the bridge linking sensors data to actuators by several computationally complex algorithms such as Extended Kalman Filter, Detumbling and Tumbling controller and so on. In this thesis, I will focus on the implementation of

Md Amiruzzaman, Rizal Mohd Nor

In this paper, a new steganographic method is presented that provides minimum distortion in the stego image. The proposed encoding algorithm focuses on DCT rounding error and optimizes that in a way to reduce distortion in the stego image, and the proposed algorithm produces less distortion than existing methods (e.g., F5 algorithm). The proposed method is b

Jie Jiang, Yunjiao Gao

Recently, Li and Bambi proposed a hypothesis that the event horizon of a regular black hole can be destroyed because these objects have no gravitational singularity and therefore they are not protected by the weak cosmic censorship conjecture (WCCC). In this paper, to test their hypothesis, we perform the new version of the gedanken experiments proposed by S

Jie Song, Yixin Chen, Jingwen Ye, Xinchao Wang

Exploring the intrinsic interconnections between the knowledge encoded in PRe-trained Deep Neural Networks (PR-DNNs) of heterogeneous tasks sheds light on their mutual transferability, and consequently enables knowledge transfer from one task to another so as to reduce the training effort of the latter. In this paper, we propose the DEeP Attribution gRAph (D

Bowen Liu, Siwei Sun, Pawel Szalachowski

Although blockchain-based smart contracts promise a ``trustless&#39;&#39; way of enforcing agreements even with monetary consequences, they suffer from multiple security issues. Many of these issues could be mitigated via an effective access control system, however, its realization is challenging due to the properties of current blockchain platforms (like la

Mohammad Arif Ul Alam, Nirmalya Roy, Sarah Holmes, Aryya Gangopadhyay

Cognitive impairment has become epidemic in older adult population. The recent advent of tiny wearable and ambient devices, a.k.a Internet of Things (IoT) provides ample platforms for continuous functional and cognitive health assessment of older adults. In this paper, we design, implement and evaluate AutoCogniSys, a context-aware automated cognitive health

Ke Dong, Karime Pereida, Florian Shkurti, Angela P. Schoellig

Mobile manipulators consist of a mobile platform equipped with one or more robot arms and are of interest for a wide array of challenging tasks because of their extended workspace and dexterity. Typically, mobile manipulators are deployed in slow-motion collaborative robot scenarios. In this paper, we consider scenarios where accurate high-speed motions are

Guofeng Deng, Ezzeddine El Sai, Trevor Manders, Peter Mayr

Promise Constraint Satisfaction Problems (PCSP) were proposed recently by Brakensiek and Guruswami arXiv:1704.01937 as a framework to study approximations for Constraint Satisfaction Problems (CSP). Informally a PCSP asks to distinguish between whether a given instance of a CSP has a solution or not even a specified relaxation can be satisfied. All currently

Mingjian He, Hong Qi, Yatao Ren, Yijun Zhao

In this letter, active control of near-field radiative heat transfer (NFRHT) between two isotropic materials is realized by a coating-twisting method. The two slabs are coated with graphene gratings, and then the NFRHT can be not only enhanced, but also weakened, by tuning the twisted angle between the two gratings. The physical mechanism is attributed to th

Leonardo J. Colombo, Maria Emma Eyrea Irazú, Eduardo García-Toraño Andrés

This note discusses Routh reduction for hybrid time-dependent mechanical systems. We give general conditions on whether it is possible to reduce by symmetries a hybrid time-dependent Lagrangian system extending and unifying previous results for continuous-time systems. We illustrate the applicability of the method using the example of a billiard with moving

Jinyu Li, Rui Zhao, Eric Sun, Jeremy H. M. Wong

While the community keeps promoting end-to-end models over conventional hybrid models, which usually are long short-term memory (LSTM) models trained with a cross entropy criterion followed by a sequence discriminative training criterion, we argue that such conventional hybrid models can still be significantly improved. In this paper, we detail our recent ef

Letian Chen

We show that an $n$-dimensional surface whose entropy is close to that of an $n$-dimensional plane is close in Hausdorff distance to some $n$-dimensional plane at every scale. Moreover we show that self-expanders of low entropy converge in the Hausdorff sense to their asymptotic cones.

Elie Aljalbout, Florian Walter, Florian Röhrbein, Alois Knoll

Legged locomotion is a challenging task in the field of robotics but a rather simple one in nature. This motivates the use of biological methodologies as solutions to this problem. Central pattern generators are neural networks that are thought to be responsible for locomotion in humans and some animal species. As for robotics, many attempts were made to rep

Bernard S. Kay

We provide a theoretical foundation for the notion of the quantum coherent state of the electrostatic field of a static external charge distribution introduced in a 1998 paper and rederive formulae there for the inner products of a pair of such states. Contrary to what one might expect, these inner products are non-zero whenever the total charges of the two

Yoshiharu Asaki, Luke T. Maud, Edward B. Fomalont, Neil M. Phillips

In 2017, an Atacama Large Millimeter/submillimeter Array (ALMA) high-frequency long baseline campaign was organized to test image capabilities with baselines up to 16 km at submillimeter (submm) wavelengths. We investigated image qualities using ALMA receiver Bands 7, 8, 9, and 10 (285-875 GHz) by adopting band-to-band (B2B) phase referencing in which a phas

Carlos Damián Rodríguez Fernández, Yago Arosa, Bilal Algnamat, Elena López Lago

The material dispersion of the [Ckmim][BF4] (k = 2,3,4,6,7,8,10) family of ionic liquids is measured at several temperatures over a broad spectral range from 300 nm to 1550 nm. The experimental curves are fitted to a modified three-resonance Sellmeier model to understand the effect of temperature and alkyl chain length in the dispersion. From the parameters

G. B. Xu, D. H. Jiang

Nonlocal sets of orthogonal product states (OPSs) are widely used in quantum protocols owing to their good property. Thus a lot of attention are paid to how to construct a nonlocal set of orthogonal product states though it is a difficult problem. In this paper, we propose a novel general method to construct a nonlocal set of orthogonal product states in $\m

Jiaxiong Qiu, Cai Chen, Shuaicheng Liu, Bing Zeng

The channel redundancy in feature maps of convolutional neural networks (CNNs) results in the large consumption of memories and computational resources. In this work, we design a novel Slim Convolution (SlimConv) module to boost the performance of CNNs by reducing channel redundancies. Our SlimConv consists of three main steps: Reconstruct, Transform and Fus

Gregor Thiele, Arne Fey, David Sommer, Jörg Krüger

Hysteresis-controlled devices are widely used in industrial applications. For example, cooling devices usually contain a two-point controller, resulting in a nonlinear hybrid system with two discrete states. Dynamic models of systems are essential for optimizing such industrial supply technology. However, conventional system identification approaches can har

Conrad James Foley, Sagar Vaze, Mohamed El Amine Seddiq, Alexey Unagaev

Soil moisture is critical component of crop health and monitoring it can enable further actions for increasing yield or preventing catastrophic die off. As climate change increases the likelihood of extreme weather events and reduces the predictability of weather, and non-optimal soil moistures for crops may become more likely. In this work, we a series of L

Marek Żukowski, Marcin Markiewicz

"The unambiguous account of proper quantum phenomena must, in principle, include a description of all relevant features of experimental arrangement" (Bohr). The measurement process is composed of pre-measurement (quantum correlation of the system with the pointer variable), and an irreversible decoherence via interaction with an environment. The system ends

Francisco Cabral, Francisco S. N. Lobo, Diego Rubiera-Garcia

Einstein-Cartan theory is an extension of the standard formulation of General Relativity characterized by a non-vanishing torsion. The latter is sourced by the matter fields via the spin tensor, and its effects are expected to be important at very high spin densities. In this work we analyze in detail the physics of Einstein-Cartan theory with Dirac and Maxw

Benjamin A. Frandsen, Stella D. Nickerson, Austin D. Clark, Andrew Solano

The structure of the molten salt (LiF)$_{0.465}$(NaF)$_{0.115}$(KF)$_{0.42}$ (FLiNaK), a potential coolant for molten salt nuclear reactors, has been studied by ab initio molecular dynamics simulations and neutron total scattering experiments. We find that the salt retains well-defined short-range structural correlations out to approximately 9 Angstroms at t

Zeses Pitenis, Marcos Zampieri, Tharindu Ranasinghe

As offensive language has become a rising issue for online communities and social media platforms, researchers have been investigating ways of coping with abusive content and developing systems to detect its different types: cyberbullying, hate speech, aggression, etc. With a few notable exceptions, most research on this topic so far has dealt with English.

Maciej Łebek, Paweł Jakubczyk

We consider the Bose gas on a $d$-dimensional anisotropic lattice employing the imperfect (mean-field) gas as a prototype example. We study the dimensional crossover arising as a result of varying the dispersion relation at finite temperature $T$. We analyze in particular situations where one of the relevant effective dimensionalities is located at or below

Zijia Zhong, Earl E. Lee, Mark Nejad, Joyoung Lee

Being one of the most promising applications enabled by connected and automated vehicles (CAV) technology, Cooperative Adaptive Cruise Control (CACC) is expected to be deployed in the near term on public roads.} Thus far, the majority of the CACC studies have been focusing on the overall network performance with limited insights on the potential impacts of C

Abhinav Dronamraju, Songyan Li, Qirui Li, Yuting Li

What has become known as Stahl&#39;s Theorem in power-engineering circles has been used to justify a convergence guarantee of the Holomorphic Embedding Method (HEM) as it applies to the power-flow problem. In this, the second part of a two-part paper, we examine implications to numerical convergence of HEM and the numerical properties of a Padé approximant a

Virginia Cuomo, J. Alfonso L. Aguerri, Enrico Maria Corsini, Victor P. Debattista

We investigate the relations between the properties of bars and their host galaxies in a sample of 77 nearby barred galaxies, spanning a wide range of morphological types and luminosities, with 34 SB0-SBa and 43 SBab-SBc galaxies. The sample includes all the galaxies with reliable direct measurement of their bar pattern speed based on long-slit or integral-f

Aleksandr Kurov, Frank Saueressig

The asymptotic safety program builds on a high-energy completion of gravity based on the Reuter fixed point, a non-trivial fixed point of the gravitational renormalization group flow. At this fixed point the canonical mass-dimension of coupling constants is balanced by anomalous dimensions induced by quantum fluctuations such that the theory enjoys quantum s

Manvir Grewal, Zhong-Bo Kang, Jian-Wei Qiu, Andrea Signori

We investigate the predictive power of transverse-momentum-dependent (TMD) distributions as a function of the light-cone momentum fraction $x$ and the hard scale $Q$ defined by the process. We apply the saddle point approximation to the unpolarized quark and gluon transverse momentum distributions and evaluate the position of the saddle point as a function o

Ovidiu Costin, Gerald V. Dunne

Expansions of physical functions are controlled by their singularities, which have special structure because they themselves are physical, corresponding to instantons, caustics or saddle configurations. Resurgent asymptotics formalizes this idea mathematically, and leads to significantly more powerful extrapolation methods to extract physical information fro

Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang

Variants of Graph Neural Networks (GNNs) for representation learning have been proposed recently and achieved fruitful results in various fields. Among them, Graph Attention Network (GAT) first employs a self-attention strategy to learn attention weights for each edge in the spatial domain. However, learning the attentions over edges can only focus on the lo

Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R Devon Hjelm

Despite recent impressive results on single-object and single-domain image generation, the generation of complex scenes with multiple objects remains challenging. In this paper, we start with the idea that a model must be able to understand individual objects and relationships between objects in order to generate complex scenes well. Our layout-to-image-gene

Mohammad Altimania, Mohamad Saleh Sanjari Nia, Mehdi Ferdowsi, Pourya Shamsi

This paper proposes a new topology of a non-isolated two-phase interleaved boost DC-DC converters with modified Greinacher voltage multiplier cells (VMCs) in continuous conduction mode (CCM). The proposed topology can quickly achieve a high gain with low stress on components and proper duty cycle. Moreover, this topology requires a small inductance size in C

Jonathan C. McDowell

I discuss the current low Earth orbit artificial satellite population and show that the proposed `megaconstellation&#39; of circa 12,000 Starlink internet satellites would dominate the lower part of Earth orbit, below 600 km, with a latitude-dependent areal number density of between 0.005 and 0.01 objects per square degree at airmass < 2. Such large, low alt

Zhuohao Chen, Singla Karan, David C. Atkins, Zac E Imel

Many text classification tasks are domain-dependent, and various domain adaptation approaches have been proposed to predict unlabeled data in a new domain. Domain-adversarial neural networks (DANN) and their variants have been used widely recently and have achieved promising results for this problem. However, most of these approaches assume that the label pr

Mateus Roder, Gustavo Henrique de Rosa, João Paulo Papa

Throughout the last years, machine learning techniques have been broadly encouraged in the context of deep learning architectures. An exciting algorithm denoted as Restricted Boltzmann Machine relies on energy- and probabilistic-based nature to tackle the most diverse applications, such as classification, reconstruction, and generation of images and signals.

Gustav Grund Pihlgren, Fredrik Sandin, Marcus Liwicki

This work investigates three methods for calculating loss for autoencoder-based pretraining of image encoders: The commonly used reconstruction loss, the more recently introduced deep perceptual similarity loss, and a feature prediction loss proposed here; the latter turning out to be the most efficient choice. Standard auto-encoder pretraining for deep lear

H. R. Reiss

It was shown recently that unambiguous description of electromagnetic environments requires electromagnetic potentials; knowledge only of electric and magnetic fields is insufficient and can lead to error. Consequences of that demonstration are here applied to propagating fields, such as laser fields. Gauge invariance is replaced by symmetry preservation. Th

Luca Ballotta, Luca Schenato, Luca Carlone

This paper investigates the use of a networked system ($e.g.$, swarm of robots, smart grid, sensor network) to monitor a time-varying phenomenon of interest in the presence of communication and computation latency. Recent advances in edge computing have enabled processing to be spread across the network, hence we investigate the fundamental computation-commu

Mudabbir Kaleem, Anastasia Mavridou, Aron Laszka

Vyper has been proposed as a new high-level language for Ethereum smart contract development due to numerous security vulnerabilities and attacks witnessed on contracts written in Solidity since the system&#39;s inception. Vyper aims to address these vulnerabilities by providing a language that focuses on simplicity, auditability and security. We present a s

Halgurd S. Maghdid, Kayhan Zrar Ghafoor, Ali Safaa Sadiq, Kevin Curran

Coronaviruses are a famous family of viruses that cause illness in both humans and animals. The new type of coronavirus COVID-19 was firstly discovered in Wuhan, China. However, recently, the virus has widely spread in most of the world and causing a pandemic according to the World Health Organization (WHO). Further, nowadays, all the world countries are str

Mohammad Arif Ul Alam, Dhawal Kapadia

Veteran mental health is a significant national problem as large number of veterans are returning from the recent war in Iraq and continued military presence in Afghanistan. While significant existing works have investigated twitter posts-based Post Traumatic Stress Disorder (PTSD) assessment using blackbox machine learning techniques, these frameworks canno

Michael A. Georgiou, Aristodemos Paphitis, Michael Sirivianos, Herodotos Herodotou

With the advent of the Internet and Internet-connected devices, modern business applications can experience rapid increases as well as variability in transactional workloads. Database replication has been employed to scale performance and improve availability of relational databases but past approaches have suffered from various issues including limited scal

Israel Quiros, Tame Gonzalez, Roberto De Arcia, Ricardo García-Salcedo

In this paper we investigate the asymptotic dynamics of inflationary cosmological models that are based in scalar-tensor theories of gravity. Our main aim is to explore the global structure of the phase space in the framework of single-field inflation models. For this purpose we make emphasis in the adequate choice of the variables of the phase space. Our re

Daewa Kim, Annalisa Quaini

The goal of this work is to study an infectious disease spreading in a medium size population occupying a confined environment. For this purpose, we consider a kinetic theory approach to model crowd dynamics in bounded domains and couple it to a kinetic equation to model contagion. The interactions of a person with other pedestrians and the environment are m

Robert A. Jarrow, Rinald Murataj, Martin T. Wells, Liao Zhu

The paper provides a new explanation of the low-volatility anomaly. We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find those basis assets significantly related to low and high volatility portfolios. These two portfolios load on very different factors, indicating that volatility is no

Yuval Efron, Ofer Grossman, Seri Khoury

By far the most fruitful technique for showing lower bounds for the CONGEST model is reductions to two-party communication complexity. This technique has yielded nearly tight results for various fundamental problems such as distance computations, minimum spanning tree, minimum vertex cover, and more. In this work, we take this technique a step further, and w

Hossein Ghaffarnejad

This paper has three parts. In first step we use modified scalar tensor vector Brans Dicke gravity \cite{GH0} to obtain metric solution of a spherically symmetric static black hole via perturbation method which asymptotically behaves as modified Schwarzschild de Sitter black hole in weak field limits. Corrections on the line element with respect to the point

Zachary McGuirk, Byungdo Park

We prove that any contravariant functor from the homotopy category of finite directed graphs to abelian groups satisfying the additivity axiom and the Mayer-Vietoris axiom is representable.

Lenz Furrer, Joseph Cornelius, Fabio Rinaldi

Background: Named Entity Recognition (NER) and Normalisation (NEN) are core components of any text-mining system for biomedical texts. In a traditional concept-recognition pipeline, these tasks are combined in a serial way, which is inherently prone to error propagation from NER to NEN. We propose a parallel architecture, where both NER and NEN are modeled a

Piotr Zielinski, Shankar Krishnan, Satrajit Chatterjee

Coherent Gradients (CGH) is a recently proposed hypothesis to explain why over-parameterized neural networks trained with gradient descent generalize well even though they have sufficient capacity to memorize the training set. The key insight of CGH is that, since the overall gradient for a single step of SGD is the sum of the per-example gradients, it is st

Matteo M. Wauters, Glen Bigan Mbeng, Giuseppe E. Santoro

We show that the quantum approximate optimization algorithm (QAOA) can construct with polynomially scaling resources the ground state of the fully-connected p-spin Ising ferromagnet, a problem that notoriously poses severe difficulties to a Quantum Annealing (QA) approach, due to the exponentially small gaps encountered at first-order phase transition for ${

I. M. Dremin

Large-distance ultraperipheral collisions of two relativistic ions are considered. The clouds of photons surrounding the ions are responsible for their distant electromagnetic interaction. The perturbative approach and the method of equivalent photons are described. It is shown that the total cross section of these collisions increases rapidly with increasin

Stephen McKean

The classical version of B\'ezout's Theorem gives an integer-valued count of the intersection points of hypersurfaces in projective space over an algebraically closed field. Using work of Kass and Wickelgren, we prove a version of B\'ezout's Theorem over any perfect field by giving a bilinear form-valued count of the intersection points of hypersurfaces in p

Sang-Hyeon Lee, Kirsten Harth, Maaike Rump, Minwoo Kim

When a liquid drop impacts on a heated substrate, it can remain deposited, or violently boil in contact, or lift off with or without ever touching the surface. The latter is known as the Leidenfrost effect. The duration and area of the liquid--substrate contact is highly relevant for the heat transfer, as well as other effects such as corrosion. However, mos

Flavio Del Santo

A tradition handed down among physicists maintains that classical physics is a perfectly deterministic theory capable of predicting the future with absolute certainty, independently of any interpretations. It also tells that it was quantum mechanics that introduced fundamental indeterminacy into physics. We show that there exist alternative stories to be tol

Manuel Arca Sedda, Michela Mapelli, Mario Spera, Matthew Benacquista

Binary black holes (BBHs) are thought to form in different environments, including the galactic field and (globular, nuclear, young and open) star clusters. Here, we propose a method to estimate the fingerprints of the main BBH formation channels associated with these different environments. We show that the metallicity distribution of galaxies in the local

Hashim A Hashim, Frank L Lewis

Two novel robust nonlinear stochastic full pose (i.e, attitude and position) estimators on the Special Euclidean Group SE(3) are proposed using the available uncertain measurements. The resulting estimators utilize the basic structure of the deterministic pose estimators adopting it to the stochastic sense. The proposed estimators for six degrees of freedom

Driss Kiouach, Yassine Sabbar

Recently, emerging epidemics like COVID-19 and its variants require predictive mathematical models to implement suitable responses in order to limit their negative and profound impact on society. The SIR (Susceptible-InfectedRemoved) system is a straightforward mathematical formulation to model the dissemination of many infectious diseases. The present paper

Tharindu Cyril Weerasooriya, Tong Liu, Christopher M. Homan

Supervised machine learning often requires human-annotated data. While annotator disagreement is typically interpreted as evidence of noise, population-level label distribution learning (PLDL) treats the collection of annotations for each data item as a sample of the opinions of a population of human annotators, among whom disagreement may be proper and expe

Yuzhen Qin, Ming Cao, Brian D. O. Anderson, Danielle S. Bassett

Cortical regions without direct neuronal connections have been observed to exhibit synchronized dynamics. A recent empirical study has further revealed that such regions that share more common neighbors are more likely to behave coherently. To analytically investigate the underlying mechanisms, we consider that a set of n oscillators, which have no direct co

Victor Nijimbere

The indefinite integral $$ \int x^αe^{ηx^β}\,_pF_q (a_1, a_2, \cdot\cdot\cdot a_p; b_1, b_2, \cdot\cdot\cdot, b_q; λx^γ)dx, $$ where $α, η, β, λ, γ\ne0$ are real or complex constants and $_pF_q$ is the generalized hypergeometric function, is evaluated in terms of an infinite series involving the generalized hypergeometric function. Related integrals in which

Hashim A. Hashim

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group \mathbb{SO}\left(3\right) with the tracking error of the normalized Euclidean distance meeting predefined transient and steady-state characteristics. The tracking error is confined to initially start within a predetermined large set such that th

Gautam Sharma, K. C. Bhamu

We present thermoelectric properties of Be$_2$C monolayer based on density functional theory and semi-classical Boltzmann transport theory. Electronic structure calculations predict this material as a semiconductor with a direct bandgap of 2.0 eV computed using Gaussian-attenuating Perdew-Burke-Ernzerhof (Gau-PBE) hybrid functional. The Gau-PBE band structur

Alexander Lidiak, Zhexuan Gong

Experimental quantum simulators have become large and complex enough that discovering new physics from the huge amount of measurement data can be quite challenging, especially when little theoretical understanding of the simulated model is available. Unsupervised machine learning methods are particularly promising in overcoming this challenge. For the specif

Marco D'Alessandro, Stefan T. Radev, Andreas Voss, Luigi Lombardi

Adaptive behavior emerges through a dynamic interaction between cognitive agents and changing environmental demands. The investigation of information processing underlying adaptive behavior relies on controlled experimental settings in which individuals are asked to accomplish demanding tasks whereby a hidden state or an abstract rule has to be learned dynam

Apurba Das

In this paper, we consider Leibniz algebras with derivations. A pair consisting of a Leibniz algebra and a distinguished derivation is called a LeibDer pair. We define a cohomology theory for LeibDer pair with coefficients in a representation. We study central extensions and abelian extensions of a LeibDer pair. In the next, we generalize the formal deformat

Julián Haddad, Carlos Hugo Jiménez, Marcos Montenegro

Given a bounded open subset $\Omega$ of $\mathbb R^n$, we establish the weak closure of the affine ball $B^{\mathcal A}_p(\Omega) = \{f \in W^{1,p}_0(\Omega):\ \mathcal E_p f \leq 1\}$ with respect to the affine functional $\mathcal E_pf$ introduced by Lutwak, Yang and Zhang in [43] as well as its compactness in $L^p(\Omega)$ for any $p \geq 1$. These points

Paul Hamacher, Wansu Kim

In this paper we classify isogeny classes of global $\mathsf{G}$-shtukas over a smooth projective curve $C/\mathbb{F}_q$ (or equivalently $\sigma$-conjugacy classes in $\mathsf{G}(\mathsf{F} \otimes_{\mathbb{F}_q} \overline{\mathbb{F}_q})$ where $\mathsf{F}$ is the field of rational functions of $C$) by two invariants $\bar\kappa,\bar\nu$ extending previous

Christian Partmann, Christian Fidler, Cornelius Rampf, Oliver Hahn

Accurate cosmological simulations that include the effect of non-linear matter clustering as well as of massive neutrinos are essential for measuring the neutrino mass scale from upcoming galaxy surveys. Typically, Newtonian simulations are employed and the neutrino distribution is sampled with a large number of particles in order to beat down the shot noise

Damianos Iosifidis

We develop a novel model for Cosmological Hyperfluids, that is fluids with intrinsic hypermomentum that induce spacetime torsion and non-metricity. Imposing the Cosmological Principle to Metric-Affine Spaces, we present the most general covariant form of the hypermomentum tensor in an FLRW Universe along with its conservation laws and therefore construct a n

Antonio Macchia, Amy Wiebe

Recently Gouveia, Thomas and the authors introduced the slack realization space, a new model for the realization space of a polytope. It represents each polytope by its slack matrix, the matrix obtained by evaluating each facet inequality at each vertex. Unlike the classical model, the slack model naturally mods out projective transformations. It is inherent

Jun-Han Huang, Guang-Ming Zhang, Dao-Xin Yao

We study the dynamical spin excitations of the one-dimensional $S=1$ Heisenberg antiferromagnetic chain with single-ion anisotropy by using quantum Monte Carlo simulations and stochastic analytic continuation of imaginary-time correlation function. Using the transverse dynamic spin structure factor, we observe the quantum phase transition with a critical poi

Vladimir Rosenhaus

A number of studies have shown that chaos occurs in scattering: the outgoing deflection angle is seen to be an erratic function of the impact parameter. We propose to extend this to quantum field theory, and to use erratic behavior of the many-particle $S$-matrix as a probe of chaos.

Ankit Dhanuka, Kinjalk Lochan

Semiclassical Physics in gravitational scenario, in its first approximation (1st order) cares only for the expectation value of stress energy tensor and ignores the inherent quantum fluctuations thereof. In the approach of stochastic gravity, on the other hand, these matter fluctuations are supposed to work as the source of geometry fluctuations and have the

Rahul Kashyap

In this paper, we use large reaction networks to find ignition conditions of single-zone nuclear fuel with compositions typical of white dwarf (WD) matter. The necessary but, possibly not sufficient condition for initiation of detonation is that the nuclear burning proceeds on smaller timescale than the sound-crossing timescale. Under typical white dwarf the

F. Tonielli, N. Chakraborty, F. Grusdt, J. Marino

We introduce a Ramsey pulse scheme which extracts the non-Hermitian Hamiltonian associated to an arbitrary Lindblad dynamics. We propose a realted protocol to measure via interferometry a generalised Loschmidt echo of a generic state evolving in time with the non-Hermitian Hamiltonian itself, and we apply the scheme to a one-dimensional weakly interacting Bo

Valentina Cesare, Antonaldo Diaferio, Titos Matsakos, Garry Angus

We test if Refracted Gravity (RG) can describe the dynamics of disk galaxies without resorting to dark matter. RG is a classical theory of gravity where the standard Poisson equation is modified by the gravitational permittivity, $\epsilon$, a universal monotonic function of the local mass density. We use the rotation curves and the vertical velocity dispers

Robin Huber, Ming-Hao Liu, Szu-Chao Chen, Martin Drienovsky

We report an efficient technique to induce gate-tunable two-dimensional superlattices in graphene by the combined action of a back gate and a few-layer graphene patterned bottom gate complementary to existing methods. The patterned gates in our approach can be easily fabricated and implemented in van der Waals stacking procedures allowing flexible use of sup

Peter T. H. Pang, Rico K. L. Lo, Isaac C. F. Wong, Tjonnie G. F. Li

The detection of gravitational wave signals by Advanced LIGO and Advanced Virgo enables us to probe the polarization content of gravitational waves. In general relativity, only tensor modes are present, while in a variety of alternative theories one can also have vector or scalar modes. Recently test were performed which compared Bayesian evidences for the h

Steven Abel, Nicholas Chancellor, Michael Spannowsky

We demonstrate how quantum field theory problems can be embedded on quantum annealers. The general method we use is a discretisation of the field theory problem into a general Ising model, with the continuous field values being encoded into Ising spin chains. To illustrate the method, and as a simple proof of principle, we use a (hybrid) quantum annealer to

Emily Chen, Kristina Lerman, Emilio Ferrara

At the time of this writing, the novel coronavirus (COVID-19) pandemic outbreak has already put tremendous strain on many countries&#39; citizens, resources and economies around the world. Social distancing measures, travel bans, self-quarantines, and business closures are changing the very fabric of societies worldwide. With people forced out of public spac

Doojin Kim, Pedro A. N. Machado, Jong-Chul Park, Seodong Shin

Neutrino and dark matter experiments with large-volume ($\gtrsim 1$ ton) detectors can provide excellent sensitivity to signals induced by energetic light dark matter coming from the present universe. Taking boosted dark matter as a concrete example of energetic light dark matter, we scrutinize two representative search channels, electron scattering and prot

Michal P. Heller, Ro Jefferson, Michał Spaliński, Viktor Svensson

Hydrodynamic attractors have recently gained prominence in the context of early stages of ultra-relativistic heavy-ion collisions at the RHIC and LHC. We critically examine the existing ideas on this subject from a phase space point of view. In this picture the hydrodynamic attractor can be seen as a special case of the more general phenomenon of dynamical d

Marco Chianese, Bowen Fu, Stephen F. King

In the so-called Planckian Interacting Dark Matter (PIDM) scenario, superheavy dark matter particles are produced after inflation by gravity-mediated interactions through the freeze-in mechanism. In the minimal PIDM model, the absence of any additional direct coupling with Standard Model particles is assumed. However, for scalar dark matter particles there i