March 2020 arXiv papers — page 137

D. S. Agafontsev, S. Randoux, P. Suret

We study numerically the integrable turbulence developing from strongly nonlinear partially coherent waves, in the framework of the focusing one-dimensional nonlinear Schrodinger equation. We find that shortly after the beginning of motion the turbulence enters a state characterized by a very slow evolution of statistics (the quasi-stationary state - QSS), a

Wonjun Ko, Eunjin Jeon, Seungwoo Jeong, Heung-Il Suk

Recent advances in deep learning have had a methodological and practical impact on brain-computer interface research. Among the various deep network architectures, convolutional neural networks have been well suited for spatio-spectral-temporal electroencephalogram signal representation learning. Most of the existing CNN-based methods described in the litera

Olusiji O. Medaiyese, Abbas Syed, Adrian P. Lauf

The emergence of drones has added new dimension to privacy and security issues. There are little or no strict regulations on the people that can purchase or own a drone. For this reason, people can take advantage of these aircraft to intrude into restricted or private areas. A Drone Detection and Identification (DDI) system is one of the ways of detecting an

Vasiliy V. Grigoriev, Oleg Iliev, Petr N. Vabishchevich

This paper discusses an optimization method called Modified Bee Colony algorithm (MBC) based on a particular intelligent behavior of honeybee swarms. The algorithm was checked in a few benchmarks like Shekel, Rozenbroke, Himmelblau and Rastrigin functions, then was applied to parameter identification for reactive flow problems in periodic porous media. The s

Zurab Aghdgomelashvili

The goal of the work is to take on and study one of the fundamental tasks studying Diophantine n-gons (the author of the paper considers an integral n-gon is Diophantine as far as determination of combinatorial properties of each of them requires solution of a certain Diophantine equation (equation sets)).

Cristian Tatino, Nikolaos Pappas, Ilaria Malanchini, Lutz Ewe

Multi-connectivity is emerging as a promising solution to provide reliable communications and seamless connectivity for the millimeter-wave frequency range. Due to the blockage sensitivity at such high frequencies, connectivity with multiple cells can drastically increase the network performance in terms of throughput and reliability. However, an inefficient

Atefeh Hajijamali Arani, M. Mahdi Azari, William Melek, Safieddin Safavi-Naeini

Deployment of unmanned aerial vehicles (UAVs) as aerial base stations can deliver a fast and flexible solution for serving varying traffic demand. In order to adequately benefit of UAVs deployment, their efficient placement is of utmost importance, and requires to intelligently adapt to the environment changes. In this paper, we propose a learning-based mech

David Garofalo

Spin measurement of the 6.5 billion solar mass black hole in M87 from the Event Horizon Telescope image is the latest in a series that span a wide range in values, but that tend to share the feature of co-rotation between the accretion flow and black hole. The spin paradigm for black holes predicts very high black hole spin which in that framework was produc

David Garofalo, Max North, Leanne Belga, Kenzi Waddell

Evidence has accumulated suggesting the clustering of radio loud quasars is greater than for radio quiet quasars. We interpret these results in a context in which the fraction of radio loud quasar formation is less than or equal to that for radio quiet quasars for all environments and redshift. Because we assume that post-merger cold gas onto large black hol

David Jaz Myers

In this paper, we exhibit a "Yoneda"-style embedding of any virtual equipment into the virtual equipment of categories enriched in it. We show that this embedding preserves composition, is full on 2-cells and arrows, and coreflective on proarrows.

A. Amansag, H. Bounit, A. Driouich, S. Hadd

In this paper we show that the concept of maximal $L^p$-regularity is stable under a large class of unbounded perturbations, namely Staffans-Weiss perturbations. To that purpose, we first prove that the analyticity of semigroups is preserved under this class of perturbations, which is a necessary condition for the maximal regularity. In UMD spaces, $\mathcal

Tomohiro Hayashi, Jeong Hee Hong, Sophie Emma Zegers, Wojciech Szymański

The problem of inner vs outer conjugacy of subalgebras of certain graph C*-algebras is investigated. For a large class of finite graphs E, we show that whenever $α$ is a vertex-fixing quasi-free automorphism of the corresponding graph C*-algebra C*(E) such that α(\D_E)\neq\D_E, where \D_E is the canonical MASA in C*(E), then α(\D_E)\neq w\D_E w^* for all uni

E Michoulier, C Toubin, A Simon, J Mascetti

This joint theoretical and experimental study establishes that the adsorption of polycyclic aromatic hydrocarbons (PAHs) onto the amorphous ice surface provokes a broadening and redshift of the "dangling" OH (dOH) ice spectral feature, the redshift increasing with PAH size up to $\sim$ 85~cm$^{-1}$. It also reveals that, in certain interaction config

John Verboom, Seungmo Kim

The 60 GHz band (57-71 GHz) has been attracting considerable research interest thanks to the bandwidth abundance and ruling as an unlicensed band. The 60 GHz Wi-Fi (also known as WiGig) and 5G New Radio Unlicensed (NR-U) are among the key access technologies that will operate in the band. This paper inspects the downlink performance of the two technologies u

Fahimeh Mokhtari, Ernst Roell, Jan Sanders

The normal form for an n-dimensional map with irreducible nilpotent linear part is determined using sl2-representation theory. We sketch by example how the reducible case can also be treated in an algorithmic manner. The construction (and proof) of the sl2-triple from the nilpotent linear part is more complicated than one would hope for, but once the abstrac

Mojtaba Mojahedi, Fereshteh Sady

In this paper, first we study surjective isometries (not necessarily linear) between completely regular subspaces $A$ and $B$ of $C_0(X,E)$ and $C_0(Y,F)$ where $X$ and $Y$ are locally compact Hausdorff spaces and $E$ and $F$ are normed spaces, not assumed to be neither strictly convex nor complete. We show that for a class of normed spaces $F$ satisfying a

M. F. Ghiti, N. Mebarki, H. Aissaoui

The non-commutative Bianchi I curved space-time vierbeins and spin connections are derived. Moreover, the corresponding non-commutative Dirac equation as well as its solutions are presented. As an application within the quantum field theory approach using Bogoliubov transformations, the von Neumann fermion-antifermion pair creation quantum entanglement entro

Vladimir Filinov, Alexander Larkin

Nowadays the term 'sign problem' is used to identify two different problems. The ideas to overcome the first type of the 'sign problem' of strongly oscillating complex valued imtegrand in the Feynman path integrals comes from Picard-Lefschetz theory and a complex version of Morse theory. The main idea is to select Lefschetz thimbles as the cy

Emilio N. M. Cirillo, Matteo Colangeli, Adrian Muntean, T. K. Thoa Thieu

Stochastic particle--based models are useful tools for describing the collective movement of large crowds of pedestrians in crowded confined environments. Using descriptions based on the simple exclusion process, two populations of particles, mimicking pedestrians walking in a built environment, enter a room from two opposite sides. One population is passive

Yan-Fei Li, Yue-Yue Chen, Wei-Min Wang, Hua-Si Hu

The production of a highly-polarized positron beam via nonlinear Breit-Wheeler processes during the interaction of an ultraintense circularly polarized laser pulse with a longitudinally spin-polarized ultrarelativistic electron beam is investigated theoretically. A new Monte Carlo method employing fully spin-resolved quantum probabilities is developed under

Taban Eslami, Joseph S. Raiker, Fahad Saeed

Diagnosing Autism Spectrum Disorder (ASD) is a challenging problem, and is based purely on behavioral descriptions of symptomology (DSM-5/ICD-10), and requires informants to observe children with disorder across different settings (e.g. home, school). Numerous limitations (e.g., informant discrepancies, lack of adherence to assessment guidelines, informant b

N. A. Carella

Let $k\geq 1$ be a small fixed integer. The rational approximations $\left |p/q-π^{k} \right |>1/q^{μ(π^k)}$ of the irrational number $π^{k}$ are bounded away from zero. A general result for the irrationality exponent $μ(π^k)$ will be proved here. The irrationality exponents for the even parameters $2k$ correspond to those for the even zeta constants $ζ(2k)$

Aneta Neumann, Bradley Alexander, Frank Neumann

We present a study demonstrating how random walk algorithms can be used for evolutionary image transition. We design different mutation operators based on uniform and biased random walks and study how their combination with a baseline mutation operator can lead to interesting image transition processes in terms of visual effects and artistic features. Using

Jason P. Bell, Fei Hu, Matthew Satriano

In previous work, the first author, Ghioca, and the third author introduced a broad dynamical framework giving rise to many classical sequences from number theory and algebraic combinatorics. Specifically, these are sequences of the form $f(Φ^n(x))$, where $Φ\colon X\to X$ and $f\colon X\to\mathbb{P}^1$ are rational maps defined over $\overline{\mathbb{Q}}$

Alina Carmen Cojocaru, Matthew Fitzpatrick

Let $E/\mathbb{Q}$ be a non-CM elliptic curve. Assuming GRH, we prove that, for a set of primes $p$ of density $1$, the absolute discriminant of the $\mathbb{F}_p$-endomorphism ring of the reduction of $E$ modulo $p$ is close to maximal.

Efthimia Deligianni, Jutta Kunz, Petya Nedkova

We study the quasi-periodic oscillations from the accretion disk around the distorted Schwarzschild black hole in the framework of the resonant models. We confine ourselves to the case of a quadrupole distortion which can be caused for example by the accreting matter flow in the vicinity of the compact object. For the purpose we examine the linear stability

Weijing Shi, Ragunathan, Rajkumar

In this paper, we propose a graph neural network to detect objects from a LiDAR point cloud. Towards this end, we encode the point cloud efficiently in a fixed radius near-neighbors graph. We design a graph neural network, named Point-GNN, to predict the category and shape of the object that each vertex in the graph belongs to. In Point-GNN, we propose an au

Jason M. Allred, Steven J. Spencer, Gopalakrishnan Srinivasan, Kaushik Roy

Spiking Neural Networks (SNNs) are being explored for their potential energy efficiency resulting from sparse, event-driven computations. Many recent works have demonstrated effective backpropagation for deep Spiking Neural Networks (SNNs) by approximating gradients over discontinuous neuron spikes or firing events. A beneficial side-effect of these surrogat

Jacob Hogan, Haoqi Sun, Luis Paixao, Mike Westmeijer

Objective Brain Age Index (BAI), calculated from sleep electroencephalography (EEG), has been proposed as a biomarker of brain health. This study quantifies night-to-night variability of BAI and establishes probability thresholds for inferring underlying brain pathology based on a patient's BAI. Methods 86 patients with multiple nights of consecutive EEG

Ivan Blum, Sung-Il Baik, Mercouri G. Kanatzidis, David N. Seidman

A method based on the Gibbs' adsorption isotherm is developed to calculate the decrease in interfacial free energy resulting from solute segregation at an internal interface, built on measured concentration profiles. Utilizing atom-probe tomography (APT), we first measure a concentration profile of the relative interfacial excess of solute atoms across a

Christopher H. Betters, Joss Bland-Hawthorn, Salah Sukkarieh, Itandehui Gris-Sanchez

We report on the development of a compact (volume $\approx$ 100\:cm$^3$), multimode diffraction-limited Raman spectrograph and probe designed to be compact as possible. The spectrograph uses `off the shelf' optics, a custom 3D-printed two-part housing and harnesses a multi-core fibre (MCF) photonic lantern (multimode to few-mode converter), which slices

Yutaro Tachibana, Matthew J. Graham, Nobuyuki Kawai, S. G. Djorgovski

Quasars have long been known as intrinsically variable sources, but the physical mechanism underlying the temporal optical/UV variability is still not well understood. We propose a novel nonparametric method for modeling and forecasting the optical variability of quasars utilizing an autoencoder neural network to gain insight into the underlying processes. T

Mohammad Haerinia

Wireless power transmission (WPT) is a critical technology that provides a secure alternative mechanism for wireless power and communication with implantable medical devices. WPT approaches for implantable medical devices have been utilized based on applications. For instance, the inductive coupling tactic is mostly employed for transmission of energy to neu

Andrés Páez

This paper raises three questions regarding the attribution of beliefs, desires, and intentions to robots. The first one is whether humans in fact engage in robot mindreading. If they do, this raises a second question: does robot mindreading foster trust towards robots? Both of these questions are empirical, and I show that the available evidence is insuffic

Youssef Lazar

The aim of this note is to show that given a positive integer $n \geq 5$, the positive integral solutions of the diophantine equation $4/n = 1/x + 1/y+1/z$ cannot have solution such that $x$ and $y$ are coprime with $xy < \sqrt{z/2}$. The proof uses the continued fraction expansion of $4/n$.

Bernard Gottschalk

We measure the length of stretched wire pairs by using them as the delay line pulse shaping element in an avalanche oscillator. The circuitry and method are extremely simple, and insensitive to oscillator supply voltage, to the particular transistor (2N3904) used and to wire tension. Rudimentary tests with simulated broken wires show that these can be detect

Niclas Mattsson, Vilhelm Verendel, Fredrik Hedenus, Lina Reichenberg

Energy system models are increasingly being used to explore scenarios with large shares of variable renewables. This requires input data of high spatial and temporal resolution and places a considerable preprocessing burden on the modeling team. Here we present a new code set with an open source license for automatic generation of input data for large-scale

Qinggang Bu, Sen Zhu

We study in this paper the infinite-dimensional orthogonal Lie algebra $\mathcal{O}_C$ which consists of all bounded linear operators $T$ on a separable, infinite-dimensional, complex Hilbert space $\mathcal{H}$ satisfying $CTC=-T^*$, where $C$ is a conjugation on $\mathcal{H}$. By employing results from the theory of complex symmetric operators and skew-sym

Paul J. Godin, Jacob L. Kloos, Alex Seguin, John E. Moores

A proof of concept for a frost detection imager using reflected starlight is presented; the limitations of this technique are explored experimentally. An ice-covered lunar surface is simulated inside a vacuum chamber, which is then illuminated with a lamp containing UV and visible output to simulate the wavelengths of the background starfield. The simulated

Ricardo Garcia-Rosas, Tianshi Yu, Denny Oetomo, Chris Manzie

In previous work, the authors proposed a data-driven optimisation algorithm for the personalisation of human-prosthetic interfaces, demonstrating the possibility of adapting prosthesis behaviour to its user while the user performs tasks with it. This method requires that the human and the prosthesis personalisation algorithm have same pre-defined objective f

Xiaodong Yang, Hoang-Dung Tran, Weiming Xiang, Taylor Johnson

Deep neural networks have been widely applied as an effective approach to handle complex and practical problems. However, one of the most fundamental open problems is the lack of formal methods to analyze the safety of their behaviors. To address this challenge, we propose a parallelizable technique to compute exact reachable sets of a neural network to an i

Honghao Huang, Chengyang Hu, Minghua Chen, Sigang Yang

Ghost imaging is a fascinating framework which constructs the image of an object by correlating measurements between received beams and reference beams, none of which carries the structure information of the object independently. Recently, by taking into account space-time duality in optics, computational temporal ghost imaging has attracted attentions. Here

Jason D. Hofgartner, Bonnie J. Buratti, Susan D. Benecchi, Ross A. Beyer

On January 1st 2019, the New Horizons spacecraft flew by the classical Kuiper belt object (486958) Arrokoth (provisionally designated 2014 MU69), possibly the most primitive object ever explored by a spacecraft. The I/F of Arrokoth is analyzed and fit with a photometric function that is a linear combination of the Lommel-Seeliger (lunar) and Lambert photomet

Anirudh Chandrashekar, Ashok Handa, Natesh Shivakumar, Pierfrancesco Lapolla

Contrast-enhanced computed tomography angiograms (CTAs) are widely used in cardiovascular imaging to obtain a non-invasive view of arterial structures. However, contrast agents are associated with complications at the injection site as well as renal toxicity leading to contrast-induced nephropathy (CIN) and renal failure. We hypothesised that the raw data ac

Frederik Bous, Luc Ardaillon, Axel Roebel

This article investigates into recently emerging approaches that use deep neural networks for the estimation of glottal closure instants (GCI). We build upon our previous approach that used synthetic speech exclusively to create perfectly annotated training data and that had been shown to compare favourably with other training approaches using electroglottog

Armin Ziaie Tabari, Xinming Ou

With the rapid growth of Internet of Things (IoT) devices, it is imperative to proactively understand the real-world cybersecurity threats posed to them. This paper describes our initial efforts towards building a honeypot ecosystem as a means to gathering and analyzing real attack data against IoT devices. A primary condition for a honeypot to yield useful

Thoria Alghamdi, Gita Alaghband

We present four high performance hybrid sorting methods developed for various parallel platforms: shared memory multiprocessors, distributed multiprocessors, and clusters taking advantage of existence of both shared and distributed memory. Merge sort, known for its stability, is used to design several of our algorithms. We improve its parallel performance by

Sheng Chen, Jie Shen

We present two new classes of orthogonal functions, log orthogonal functions (LOFs) and generalized log orthogonal functions (GLOFs), which are constructed by applying a $\log$ mapping to Laguerre polynomials. We develop basic approximation theory for these new orthogonal functions and apply them to solve several typical fractional differential equations who

Chuanyu Zhang, Xiaofeng Guo, Laurent Royon, Philippe Brunet

Acoustic waves can generate steady streaming within a fluid owing to the generation of viscous boundary layers near walls, of typical thickness $δ$. In microchannels, the acoustic wavelength $λ$ is adjusted to twice the channel width $w$ to ensure a resonance condition, which implies the use of MHz transducers. Recently though, intense acoustic streaming was

Ann E. Nicholson, Kevin B. Korb, Erik P. Nyberg, Michael Wybrow

In many complex, real-world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, human reasoning in these cases is prone to confusion and error. Bayesian networks (BNs) are an artificial intelligence technology that models uncertain situations, supporting probabilistic and causal reasoning and

Mariola Ndrio, Khaled Alshehri, Subhonmesh Bose

We consider a market in which both suppliers and consumers compete for a product via scalar-parameterized supply offers and demand bids. Scalar-parameterized offers/bids are appealing due to their modeling simplicity and desirable mathematical properties with the most prominent being bounded efficiency loss and price markup under strategic interactions. Our

B. Akbari, Mark L. Lewis, J. Mirzajani, A. R. Moghaddamfar

Let $G$ be a finite group. The solubility graph associated with the finite group $G$, denoted by $Γ_{\cal S}(G)$, is a simple graph whose vertices are the non-trivial elements of $G$, and there is an edge between two distinct elements $x$ and $y$ if and only if $\langle x, y\rangle$ is a soluble subgroup of $G$. In this paper, we examine some properties of s

Aosong Feng, Priyadarshini Panda

Deep learning has achieved state-of-the-art accuracies on several computer vision tasks. However, the computational and energy requirements associated with training such deep neural networks can be quite high. In this paper, we propose a cumulative training strategy with Net2Net transformation that achieves training computational efficiency without incurring

Siddhartha V. Jayanti, Robert E. Tarjan

We develop and analyze concurrent algorithms for the disjoint set union (union-find) problem in the shared memory, asynchronous multiprocessor model of computation, with CAS (compare and swap) or DCAS (double compare and swap) as the synchronization primitive. We give a deterministic bounded wait-free algorithm that uses DCAS and has a total work bound of $O

Weixin Wang, Taeyoung Lee

General Stochastic Hybrid Systems (GSHS) have been formulated to represent various types of uncertainties in hybrid dynamical systems. In this paper, we propose computational techniques for Bayesian estimation of GSHS. In particular, the Fokker-Planck equation that describes the evolution of uncertainty distributions along GSHS is solved by spectral techniqu

Anupam Roy, Rik Dey, Tanmoy Pramanik, Amritesh Rai

Chromium selenide thin films were grown epitaxially on Al${_2}$O${_3}$(0001) and Si(111)-(7${\times}$7) substrates using molecular beam epitaxy (MBE). Sharp streaks in reflection high-energy electron diffraction and triangular structures in scanning tunneling microscopy indicate a flat smooth film growth along the c-axis, and is very similar to that from a h

Adrian Di Paolo, Alejandro Gangui

In this paper we discuss the importance of studying the orientation of ancient Christian churches, as a complement to the historical and cultural research of the temples. We present preliminary results of the analysis of the precise spatial orientation of 38 colonial churches located on the Canary Island of La Gomera (Spain). The sample suggests that, althou

Nimish M. Awalgaonkar, Haining Zheng, Christopher S. Gurciullo

When it comes to addressing the safety/security related needs at different production/construction sites, accurate detection of the presence of workers, vehicles, equipment important and formed an integral part of computer vision-based surveillance systems (CVSS). Traditional CVSS systems focus on the use of different computer vision and pattern recognition

Marco Marconati, Silvia Pani, Jan Engmann, Adam Burbidge

The development of novel texture adaptations for the management of swallowing disorders could be accelerated if reliable in vitro tests were made available. This study addresses some of the limitations of swallowing in vitro models, by introducing a soft robotic actuator inspired by the tongue. The wettability of the soft-robotic actuator was engineered to a

Kongtao Chen, Jian Han, David J. Srolovitz

The grain boundary (GB) mobility relates GB velocity to the thermodynamic driving forces and is central to our understanding of microstructure evolution in polycrystals. Recent molecular dynamics (MD) and experimental studies have shown that the temperature-dependence of the GB mobility is much more varied than is commonly thought. GB mobility may increase,

Alexander R. Munoz, Lazar Kish, Kannan Lu, Thomas Heitmann

Magnetic neutron scattering measures spin-spin correlations giving information about the long-range spin order as well as the shape of the spin density in magnetic materials. Similarly, detailed first principles calculations directly compute the spin density in materials. In this work, the authors carefully compare experimentally measured magnetic neutron in

Jingxiu Yao, Martin Shepperd

Context: There is considerable diversity in the range and design of computational experiments to assess classifiers for software defect prediction. This is particularly so, regarding the choice of classifier performance metrics. Unfortunately some widely used metrics are known to be biased, in particular F1. Objective: We want to understand the extent to whi

Stefano Alletto, Shenyang Huang, Vincent Francois-Lavet, Yohei Nakata

Almost all neural architecture search methods are evaluated in terms of performance (i.e. test accuracy) of the model structures that it finds. Should it be the only metric for a good autoML approach? To examine aspects beyond performance, we propose a set of criteria aimed at evaluating the core of autoML problem: the amount of human intervention required t

Anastasiia V Uvarova, Hans Moritz Günther, David A. Principe, P. Christian Schneider

Young stars accrete mass and angular momentum from their circumstellar disks. Some of them also drive outflows, which can be distinguished in optical forbidden emission lines (FELs). We analyze a sample of binary T Tauri stars observed with long-slit spectroscopy by the Hubble Space Telescope (HST), searching for spatially resolved outflows. We detect resolv

Anil Shanbhag, Samuel Madden, Xiangyao Yu

There has been significant amount of excitement and recent work on GPU-based database systems. Previous work has claimed that these systems can perform orders of magnitude better than CPU-based database systems on analytical workloads such as those found in decision support and business intelligence applications. A hardware expert would view these claims wit

Maxime Brunet, Basile Gallet, Pierre-Philippe Cortet

We report on laboratory experiments of wave-driven rotating turbulence. A set of wavemakers produces inertial-wave beams that interact nonlinearly in the central region of a water tank mounted on a rotating platform. The forcing thus injects energy into inertial waves only. For moderate forcing amplitude, part of the energy of the forced inertial waves is tr

Mojtaba Rezaei, Kurosh Javidan, Hamidreza Ramezani, Mehdi Abdi

The main challenge in deterministic quantum state transfer in long-distance quantum communications is the transmission losses in the communication channel. To overcome this limitation, here we use the adiabatic theorem and find a lossless evolution path between two remote mechanical modes. By adiabatic variation of the effective coupling strengths between th

Kathryn Mann

We extend the proof of automatic continuity for homeomorphism groups of manifolds to non-compact manifolds and manifolds with marked points and their mapping class groups. Specifically, we show that, for any manifold $M$ homeomorphic to the interior of a compact manifold, and a set $X \subset M$ homeomorphic to the union of a Cantor set and finite set, the r

A. Riols, B. Roux, H. Latter, G. Lesur

Gravitational instability (GI) controls the dynamics of young massive protoplanetary discs. Apart from facilitating gas accretion on to the central protostar, it must also impact on the process of planet formation: directly through fragmentation, and indirectly through the turbulent concentration of small solids. To understand the latter process, it is essen

Alex J. Lee, Ming Chen, Wenfei Li, Daniel Neuhauser

We apply a stochastic version of an optimally tuned range-separated hybrid functional to provide insight on the electronic properties of P- and B- doped Si nanocrystals of experimentally relevant sizes. We show that we can use the range-separation parameter for undoped systems to calculate accurate results for dopant activation energies. We apply this strate

Chen Jiang, Masood Dehghan, Martin Jagersand

Manipulation tasks in daily life, such as pouring water, unfold intentionally under specialized manipulation contexts. Being able to process contextual knowledge in these Activities of Daily Living (ADLs) over time can help us understand manipulation intentions, which are essential for an intelligent robot to transition smoothly between various manipulation

Antonio J. Muñoz-Montoro, Julio J. Carabias-Orti, Archontis Politis, Konstantinos Drossos

This work addresses the problem of multichannel source separation combining two powerful approaches, multichannel spectral factorization with recent monophonic deep-learning (DL) based spectrum inference. Individual source spectra at different channels are estimated with a Masker-Denoiser Twin Network (MaD TwinNet), able to model long-term temporal patterns

Sichen Li, Yohsuke Matsuzawa

We collect some results on endomorphisms on projective varieties related with the Kawaguchi-Silverman conjecture. We discuss certain condition on automorphism groups of projective varieties and positivity conditions on leading real eigendivisors of self-morphisms. We prove Kawaguchi-Silverman conjecture for endomorphisms on projective bundles on a smooth Fan

Supanat Kamtue

An equivalent definition of entropic Ricci curvature on discrete spaces was given in terms of the global gradient estimate. With a particular choice of the density function $ρ$, we obtain a localized gradient estimate, which in turns allow us to derive a Bonnet-Myers type diameter bound for graphs with positive entropic Ricci curvature. However, the case of

Mengmeng Yang, Zhilong Fang, Philipp Witte, Felix J. Herrmann

Least-squares reverse time migration is well-known for its capability to generate artifact-free true-amplitude subsurface images through fitting observed data in the least-squares sense. However, when applied to realistic imaging problems, this approach is faced with issues related to overfitting and excessive computational costs induced by many wave-equatio

H. Ait Mansour, F-Z. Siyouri, M. Faqir, M. El Baz

We investigate the dynamics of quantum discord and concurrence between two excitonic qubits placed inside two coupled semiconductor quantum dots independently interacting with dephasing reservoirs. We explore their behavior against the dimensionless time and the temperature in both Markovian and non-Markovian environments. Moreover, we analyze the external e

Tapajit Dey, Audris Mockus

Background: Pull Request (PR) Integrators often face challenges in terms of multiple concurrent PRs, so the ability to gauge which of the PRs will get accepted can help them balance their workload. PR creators would benefit from knowing if certain characteristics of their PRs may increase the chances of acceptance. Aim: We modeled the probability that a PR w

Benedetta Flebus, Rembert A. Duine, Hilary M. Hurst

Magnetic systems have been extensively studied both from a fundamental physics perspective and as building blocks for a variety of applications. Their topological properties, in particular those of excitations, remain relatively unexplored due to their inherently dissipative nature. The recent introduction of non-Hermitian topological classifications opens u

Sarika Jalan, Priodyuti Pradhan

Investigation of eigenvector localization properties of complex networks is not only important for gaining insight into fundamental network problems such as network centrality measure, spectral partitioning, development of approximation algorithms, but also is crucial for understanding many real-world phenomena such as disease spreading, criticality in brain

Nataly Brukhim, Xinyi Chen, Elad Hazan, Shay Moran

Boosting is a widely used machine learning approach based on the idea of aggregating weak learning rules. While in statistical learning numerous boosting methods exist both in the realizable and agnostic settings, in online learning they exist only in the realizable case. In this work we provide the first agnostic online boosting algorithm; that is, given a

M. Fernández López, L. A. Zapata, L. F. Rodríguez, M. M. Vazzano

We present new ALMA Band 6 observations including the CO(2-1) line and 1.3 mm continuum emission from the surroundings of the young stellar object DO Tauri. The ALMA CO molecular data show three different series of rings at different radial velocities. These rings have radii around 220 au and 800 au. We make individual fits to the rings and note that their c

Maurício Hippert, David Dobrigkeit Chinellato, Matthew Luzum, Jorge Noronha

We propose a redefinition of the principal component analysis (PCA) of anisotropic flow that makes it more directly connected to fluctuations of the initial geometry of the system. Then, using state-of-the-art hydrodynamic simulations, we make an explicit connection between flow fluctuations and a cumulant expansion of the initial transverse geometry. In par

Yongjie Zou, Stephen M. Goodnick

Dilute-N GaPAsN alloys have great potential for optoelectronics lattice-matched to Si. However, there is a lack of systematic calculation of the optical response of these alloys. The present paper uses the sp^3d^5s^*s_N tight-binding model to calculate the fullband electronic structure of dilute-N GaPAsN, and then calculate the optical response functions con

Ergin Sezgin

The maximally supersymmetric Freund-Rubin vacua for eleven dimensional supergravity, namely $AdS_4 \times S^7$ and $AdS_7 \times S^4$, admit an analytic continuation to $S^4 \times S^7$. From the full harmonic expansions on $S^4 \times S^7$, it is shown that by analytical continuation to either $AdS_4$, or to $AdS_7$, the detailed structure of the Kaluza-Kle

Pieter W. Claeys, Austen Lamacraft

We consider the long-time limit of out-of-time-order correlators (OTOCs) in two classes of quantum lattice models with time evolution governed by local unitary quantum circuits and maximal butterfly velocity $v_{B} = 1$. Using a transfer matrix approach, we present analytic results for the long-time value of the OTOC on and inside the light cone. First, we c

Lucas Kocia, Mohan Sarovar

We show that the cost of strong simulation of quantum circuits using $t$ $T$ gate magic states exhibits non-trivial reductions on its upper bound for $t=1$, $t=2$, $t=3$, and $t=6$ with odd-prime-qudits. This agrees with previous numerical bounds found for qubits. We define simulation cost by the number of terms that require Gaussian elimination of a $t \tim

Umberto D&#39;Alesio, Francesco Murgia, Marco Zaccheddu

We present a thorough phenomenological analysis of the experimental data from Belle Collaboration for the transverse $Λ$ and $\barΛ$ polarisation, measured in $e^+e^-$ annihilation processes, for the case of inclusive (plus a jet) and associated production with a light charged hadron. This allows for the first ever extraction of the quark polarising fragment

Dimitri Veras, Kosuke Kurosawa

Metal pollution in white dwarf photospheres originates from the accretion of some combination of planets, moons, asteroids, comets, boulders, pebbles and dust. When large bodies reside in dynamically stagnant locations -- unable themselves to pollute nor even closely approach the white dwarf -- then smaller reservoirs of impact debris may become a complement

Juan A. Sanchez, Cristina Thomas, Vishnu Reddy, Noah Frere

The surface composition of S-type asteroids can be determined using band parameters extracted from their near-infrared (NIR) spectra (0.7-2.50 $μ$m) along with spectral calibrations derived from laboratory samples. In the past, these empirical equations have been obtained by combining NIR spectra of meteorite samples with information about their composition

E. Laplace, Y. Götberg, S. E. de Mink, S. Justham

Massive binaries that merge as compact objects are the progenitors of gravitational-wave sources. Most of these binaries experience one or more phases of mass transfer, during which one of the stars loses part or all of its outer envelope and becomes a stripped-envelope star. The evolution of the size of these stripped stars is crucial in determining whether

J. M. Diederik Kruijssen, Joel L. Pfeffer, Mélanie Chevance, Ana Bonaca

Globular clusters (GCs) formed when the Milky Way experienced a phase of rapid assembly. We use the wealth of information contained in the Galactic GC population to quantify the properties of the satellite galaxies from which the Milky Way assembled. To achieve this, we train an artificial neural network on the E-MOSAICS cosmological simulations of the co-fo

Albert Liu, Steven T. Cundiff

Vacancy centers in diamond have proven to be a viable solid-state platform for quantum coherent opto-electronic applications. Among the variety of vacancy centers, silicon-vacancy (SiV) centers have recently attracted much attention as an inversion-symmetric system that is less susceptible to electron-phonon interactions. Nevertheless, phonon-mediated proces

Vincenzo Zaccà, Pablo Martinez-Nuevo, Martin Møller, Jorge Martínez

Accurate sound field reproduction in rooms is often limited by the lack of knowledge of the room characteristics. Information about the room shape or nearby reflecting boundaries can, in principle, be used to improve the accuracy of the reproduction. In this paper, we propose a method to infer the location of nearby reflecting boundaries from measurements on

The ILD Collaboration

The ILD detector is proposed for an electron-positron collider with collision centre-of-mass energies from 90~\GeV~to about 1~\TeV. It has been developed over the last 10 years by an international team of scientists with the goal to design and eventually propose a fully integrated detector, primarily for the International Linear Collider, ILC. In this report

Mark van der Wilk, Vincent Dutordoir, ST John, Artem Artemev

One obstacle to the use of Gaussian processes (GPs) in large-scale problems, and as a component in deep learning system, is the need for bespoke derivations and implementations for small variations in the model or inference. In order to improve the utility of GPs we need a modular system that allows rapid implementation and testing, as seen in the neural net

Yu Zhang, Gongbo Liang, Nathan Jacobs, Xiaoqin Wang

Generalization is one of the key challenges in the clinical validation and application of deep learning models to medical images. Studies have shown that such models trained on publicly available datasets often do not work well on real-world clinical data due to the differences in patient population and image device configurations. Also, manually annotating

Erik R. Eisenach, John F. Barry, Michael F. O&#39;Keeffe, Jennifer M. Schloss

Robust, high-fidelity readout is central to quantum device performance. Overcoming poor readout is an increasingly urgent challenge for devices based on solid-state spin defects, particularly given their rapid adoption in quantum sensing, quantum information, and tests of fundamental physics. Spin defects in solids combine the repeatability and precision ava

Shweta Narayan, Davis B. Moravec, Andrew J. Dallas, Cari S. Dutcher

Here, we trap and control the position of droplets to study their dynamics using hydrodynamic forces alone without an external field. The hydrodynamic trap is adapted from a previously implemented Stokes trap by incorporating a drop-on-demand system to generate droplets at a T-junction geometry on the same microfluidic chip. We then study confined droplet dy

C. H. Baldwin, B. J. Bjork, M. Foss-Feig, J. P. Gaebler

To date, the highest fidelity quantum logic gates between two qubits have been achieved with variations on the geometric-phase gate in trapped ions, with the two leading variants being the Molmer-Sorensen gate and the light-shift (LS) gate. Both of these approaches have their respective advantages and challenges. For example, the latter is technically simple

Cristina Flaut, Diana Savin

In this paper we provide some applications of the norm form in some quaternion division algebras over rational field and we give some properties of Fibonacci sequence and Fibonacci sequence in connection with quaternion elements. We define a monoid structure over a fnite set on which we will prove that the defined Fibonacci sequence is stationary, we provide