December 2020 arXiv papers — page 145

Arpan Das, Dominik R. G. Schleicher, Nathan W. C. Leigh, Tjarda C. N. Boekholt

More than two hundred supermassive black holes (SMBHs) of masses $\gtrsim 10^9\,\mathrm{M_{\odot}}$ have been discovered at $z \gtrsim 6$. One promising pathway for the formation of SMBHs is through the collapse of supermassive stars (SMSs) with masses $\sim 10^{3-5}\,\mathrm{M_{\odot}}$ into seed black holes which could grow upto few times $10^9\,\mathrm{M_

David Oriola, Miquel Marin-Riera, Kerim Anlas, Nicola Gritti

Multicellular aggregates are known to exhibit liquid-like properties. The fusion process of two cell aggregates is commonly studied as the coalescence of two viscous drops. However, tissues are complex materials and can exhibit viscoelastic behaviour. It is known that elastic effects can prevent the complete fusion of two drops, a phenomenon known as arreste

Łukasz G. Gajewski, Julian Sienkiewicz, Janusz A. Hołyst

Finding hidden layers in complex networks is an important and a non-trivial problem in modern science. We explore the framework of quantum graphs to determine whether concealed parts of a multi-layer system exist and if so then what is their extent, i.e., how many unknown layers there are. Assuming that all information available is the time evolution of a wa

Ramis Movassagh, Yingkai Ouyang

Implementing robust quantum error correction (QEC) is imperative for harnessing the promise of quantum technologies. We introduce a framework that takes {\it any} classical code and explicitly constructs the corresponding QEC code. Our framework can be seen to generalize the CSS codes, and goes beyond the stabilizer formalism~(Fig.~1). A concrete advantage i

Kazutaka Kimura, Takashi Hosokawa, Kazuyuki Sugimura

Recent high-resolution simulations demonstrate that disks around primordial protostars easily fragment in the accretion phase before the protostars accrete less than a solar mass. To understand why the gravitational instability generally causes the fragmentation so early, we develop a one-dimensional (1D) non-steady model of the circumstellar disk that takes

Francesco D'Eramo, Alessandro Lenoci

Feebly Interacting Massive Particles (FIMPs) are dark matter candidates that never thermalize in the early universe and whose production takes place via decays and/or scatterings of thermal bath particles. If FIMPs interactions with the thermal bath are renormalizable, a scenario which is known as freeze-in, production is most efficient at temperatures aroun

Bob Knighton

It was recently shown in arXiv:2009.11306 that tree-level correlation functions in tensionless string theory on $\rm{AdS}_3\times\rm{S}^3\times\mathbb{T}^4$ match the expected form of correlation functions in the symmetric orbifold CFT on $\mathbb{T}^4$ in the large $N$ limit. This analysis utilized the free-field realization of the $\mathfrak{psu}(1,1|2)_1$

Marcin Raczkowski, Fakher F. Assaad, Masatoshi Imada

Using a cluster extension of the dynamical mean-field theory (CDMFT) we map out the magnetic phase diagram of the anisotropic square lattice Hubbard model with nearest-neighbor intrachain $t$ and interchain $t_{\perp}$ hopping amplitudes at half-filling. A fixed value of the next-nearest-neighbor hopping $t'=-t_{\perp}/2$ removes the nesting property of

Zackaria Chacko, Patrick J. Fox, Roni Harnik, Zhen Liu

We consider a class of models in which the neutrinos acquire Majorana masses through mixing with singlet neutrinos that emerge as composite states of a strongly coupled hidden sector. In this framework, the light neutrinos are partially composite particles that obtain their masses through the inverse seesaw mechanism. We focus on the scenario in which the st

Matija Medvidovic, Juan Carrasquilla, Lauren E. Hayward, Bohdan Kulchytskyy

We explore a self-learning Markov chain Monte Carlo method based on the Adversarial Non-linear Independent Components Estimation Monte Carlo, which utilizes generative models and artificial neural networks. We apply this method to the scalar $φ^4$ lattice field theory in the weak-coupling regime and, in doing so, greatly increase the system sizes explored to

Thomas D. Galley, Flaminia Giacomini, John H. Selby

Recently, table-top experiments involving massive quantum systems have been proposed to test the interface of quantum theory and gravity. In particular, the crucial point of the debate is whether it is possible to conclude anything on the quantum nature of the gravitational field, provided that two quantum systems become entangled solely due to the gravitati

Paul Archer-Smith, Daniel Stolarski, Roberto Vega-Morales

We explore models of new physics that can give rise to large (100% or more) enhancements to the rate of Higgs decay to $Zγ$ while still being consistent with other measurements. We show that this is impossible in simple models with one additional multiplet and also in well motivated models such as the MSSM and folded SUSY. We do find models with several mult

Yang-Zhi Chou, Rahul M. Nandkishore

We demonstrate that the one-dimensional helical Majorana edges of two-dimensional time-reversal symmetric topological superconductors (class DIII) can become gapless and insulating by a combination of random edge velocity and interaction. Such a gapless insulating edge breaks time-reversal symmetry inhomogeneously, and the local symmetry broken regions can b

Sihao Huang, Benjamin Lienhard, Greg Calusine, Antti Vepsäläinen

Solid-state qubits with transition frequencies in the microwave regime, such as superconducting qubits, are at the forefront of quantum information processing. However, high-fidelity, simultaneous control of superconducting qubits at even a moderate scale remains a challenge, partly due to the complexities of packaging these devices. Here, we present an appr

Michael Winer, Brian Swingle

One manifestation of quantum chaos is a random-matrix-like fine-grained energy spectrum. Prior to the inverse level spacing time, random matrix theory predicts a `ramp' of increasing variance in the connected part of the spectral form factor. However, in realistic quantum chaotic systems, the finite time dynamics of the spectral form factor is much riche

Andrea Caputo, Angelo Esposito, Fulvio Piccinini, Antonio D. Polosa

We present the analysis of a new signature for light dark matter detection with superfluid $^4$He: the emission of three phonons. We show that, in a region of mass below the MeV, the kinematics of this process can offer a way to reconstruct the dark matter interaction vertex, while providing background rejection via coincidence requirements and directionalit

David S. Aguado, Vasily Belokurov, G. C. Myeong, N. Wyn Evans

The Gaia Sausage (GS) and the Sequoia represent the major accretion events that formed the stellar halo of the Milky Way. A detailed chemical study of these main building blocks provides a pristine view of the early steps of the Galaxy's assembly. We present the results of the analysis of the UVES high-resolution spectroscopic observations at the 8.2m VL

Chi-Ming Chang, Ying-Hsuan Lin

We investigate the emergence of topological defect lines in the conformal Regge limit of two-dimensional conformal field theory. We explain how a local operator can be factorized into a holomorphic and an anti-holomorphic defect operator connected through a topological defect line, and discuss implications on Lorentzian dynamics including aspects of chaos. W

Vadim A. Semenov, Andrey V. Kravtsov, Damiano Caprioli

Observations of the $γ$-ray emission around star clusters, isolated supernova remnants, and pulsar wind nebulae indicate that the cosmic-ray (CR) diffusion coefficient near acceleration sites can be suppressed by a large factor compared to the Galaxy average. We explore the effects of such local suppression of CR diffusion on galaxy evolution using simulatio

Matthew J. Temple, Manda Banerji, Paul C. Hewett, Amy L. Rankine

Using data from SDSS, UKIDSS and WISE, we investigate the properties of the high-frequency cutoff to the infrared emission in $\simeq$5000 carefully selected luminous ($L_{bol} \simeq 10^{47}$) type 1 quasars. The strength of $\simeq$2 $μ$m emission, corresponding to emission from the hottest (T>1200K) dust in the sublimation zone surrounding the central con

Domenico Cantone, Carmelo Fabio Longo, Marianna Nicolosi-Asmundo, Daniele Francesco Santamaria

In this contribution we extend an ontology for modelling agents and their interactions, called Ontology for Agents, Systems, and Integration of Services (in short, OASIS), with conditionals and ontological smart contracts (in short, OSCs). OSCs are ontological representations of smart contracts that allow to establish responsibilities and authorizations amon

Riccardo Gonzo, Andrzej Pokraka

Light-ray operators naturally arise from integrating Einstein equations at null infinity along the light-cone time. We associate light-ray operators to physical detectors on the celestial sphere and we provide explicit expressions in perturbation theory for their hard modes using the steepest descent technique. We then study their algebra in generic 4-dimens

Long Zhao, Yuxiao Wang, Jiaping Zhao, Liangzhe Yuan

We introduce a novel representation learning method to disentangle pose-dependent as well as view-dependent factors from 2D human poses. The method trains a network using cross-view mutual information maximization (CV-MIM) which maximizes mutual information of the same pose performed from different viewpoints in a contrastive learning manner. We further prop

Minke Xiu, Ellis E. Eghan, Zhen Ming, Jiang

Recent advances in Artificial Intelligence (AI), especially in Machine Learning (ML), have introduced various practical applications (e.g., virtual personal assistants and autonomous cars) that enhance the experience of everyday users. However, modern ML technologies like Deep Learning require considerable technical expertise and resources to develop, train

Carl-Fredrik Nyberg-Brodda

We study the language-theoretic properties of the word problem, in the sense of Duncan & Gilman, of weakly compressible monoids, as defined by Adian & Oganesian. We show that if $\mathcal{C}$ is a reversal-closed super-$\operatorname{AFL}$, as defined by Greibach, then $M$ has word problem in $\mathcal{C}$ if and only if its compressed left monoid $L(M)$ has

Christophe Garban, Avelio Sepúlveda

In this paper, we study the influence of the vortices on the fluctuations of $2d$ systems such as the Coulomb gas, the Villain model or the integer-valued Gaussian free field. In the case of the $2d$ Villain model, we prove that the fluctuations induced by the vortices are at least of the same order of magnitude as the ones produced by the spin-wave. We obta

J. Settino, C. A. Perroni, F. Romeo, V. Cataudella

Linear and non-linear transport properties through an atomic-size point contact based on oxides two-dimensional electron gas is examined using the tight-binding method and the $\mathbf{k\cdot p}$ approach. The ballistic transport is analyzed in contacts realized at the (001) interface between band insulators $LaAlO_3$ and $SrTiO_3$ by using the Landauer-B\"u

David N. Hosking, Alexander A. Schekochihin

We present a new theoretical picture of magnetically dominated, decaying turbulence in the absence of a mean magnetic field. We demonstrate that such turbulence is governed by the reconnection of magnetic structures, and not by ideal dynamics, as has previously been assumed. We obtain predictions for the magnetic-energy decay laws by proposing that turbulenc

Richard Rimanyi, Alexander Varchenko

We prove an $\mathbb F_p$-Selberg integral formula of type $A_n$, in which the $\mathbb F_p$-Selberg integral is an element of the finite field $\mathbb F_p$ with odd prime number $p$ of elements. The formula is motivated by analogy between multidimensional hypergeometric solutions of the KZ equations and polynomial solutions of the same equations reduced mo

Yang Liu, Yu Weng, Rufan Yang, Quoc-Tuan Tran

Bilevel optimization problems can be used to represent the collaborative interaction between a power system and grid-connected entities, called the followers, such as data centers. Most existing approaches assume that such followers' response behaviors are made available to the power system in the operation decision-making, which may be untenable in real

Reinhold Kleiner, Xianjing Zhou, Eric Dorsch, Xufeng Zhang

We theoretically demonstrate that the high-critical-temperature superconductor Bi$_2$Sr$_2$CaCu$_2$O$_{8+x}$ (BSCCO) is a natural candidate for the recently envisioned classical space-time crystal. BSCCO intrinsically forms a stack of Josephson junctions. Under a periodic parametric modulation of the Josephson critical current density, the Josephson currents

Oscar King, Geoffrey Goodell

Digitisation is often viewed as beneficial to a user. Whereas traditionally, people would physically have to identify to a service, pay for a ticket in cash, or go into a library to access a book, people can now achieve all of this through a click of a button. Such actions may seem functionally identical to their analogue counterparts, but in the digital cas

Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava

While Graph Neural Networks (GNNs) are powerful models for learning representations on graphs, most state-of-the-art models do not have significant accuracy gain beyond two to three layers. Deep GNNs fundamentally need to address: 1). expressivity challenge due to oversmoothing, and 2). computation challenge due to neighborhood explosion. We propose a simple

Cenk Tüysüz, Kristiane Novotny, Carla Rieger, Federico Carminati

The Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN) will be upgraded to further increase the instantaneous rate of particle collisions (luminosity) and become the High Luminosity LHC. This increase in luminosity, will yield many more detector hits (occupancy), and thus measurements will pose a challenge to track reconstru

Nancy Scherich, Yvon Verberne

Using totally symmetric sets, Chudnovsky, Kordek, Li, and Partin gave a superexponential lower bound on the cardinality of non-abelian finite quotients of the braid group. In this paper, we develop new techniques using multiple totally symmetric sets to count elements in non-abelian finite quotients of the braid group. Using these techniques, we improve the

Mihai Dusmanu, Ondrej Miksik, Johannes L. Schönberger, Marc Pollefeys

Visual localization and mapping is the key technology underlying the majority of mixed reality and robotics systems. Most state-of-the-art approaches rely on local features to establish correspondences between images. In this paper, we present three novel scenarios for localization and mapping which require the continuous update of feature representations an

Sheng Lei, Alexander Flueck

Obreshkov-like numerical integrators have been widely applied to power system transient simulation. Misuse of the numerical integrators as numerical differentiators may lead to numerical oscillation or bias. Criteria for Obreshkov-like numerical integrators to be used as numerical differentiators are proposed in this paper to avoid these misleading phenomena

Ian Lowe, Peter A. R. Ade, Peter C. Ashton, Jason E. Austermann

The Next Generation Balloon-borne Large Aperture Submillimeter Telescope (BLAST-TNG) is a submillimeter polarimeter designed to map interstellar dust and galactic foregrounds at 250, 350, and 500 microns during a 24-day Antarctic flight. The BLAST-TNG detector arrays are comprised of 918, 469, and 272 MKID pixels, respectively. The pixels are formed from two

John T. Stefan, Alexander G. Kosovichev, Andrey M. Stejko

A time-distance helioseismic technique, similar to the one used by Ilonidis et al (2011), is applied to two independent numerical models of subsurface sound-speed perturbations to determine the spatial resolution and accuracy of phase travel time shift measurements. The technique is also used to examine pre-emergence signatures of several active regions obse

Christian Baer, Alexander Strohmaier

Index theory for Lorentzian Dirac operators is a young subject with significant differences to elliptic index theory. It is based on microlocal analysis instead of standard elliptic theory and one of the main features is that a nontrivial index is caused by topologically nontrivial dynamics rather than nontrivial topology of the base manifold. In this paper

Giuseppe Bevilacqua, Huan-Yu Bi, Heribertus Bayu Hartanto, Manfred Kraus

Recent discrepancies between theoretical predictions and experimental data in multi-lepton plus $b$-jets analyses for the $t\bar{t}W^\pm$ process, as reported by the ATLAS collaboration, have indicated that more accurate theoretical predictions and high precision observables are needed to constrain numerous new physics scenarios in this channel. To this end

Li Yang, Adnan Siraj Rakin, Deliang Fan

Nowadays, one practical limitation of deep neural network (DNN) is its high degree of specialization to a single task or domain (e.g., one visual domain). It motivates researchers to develop algorithms that can adapt DNN model to multiple domains sequentially, while still performing well on the past domains, which is known as multi-domain learning. Almost al

Frank Kutzschebauch, Gerald W. Schwarz

Let $G$ be a reductive complex Lie group acting holomorphically on $X=\mathbb{C}^n$. The (holomorphic) Linearization Problem asks if there is a holomorphic change of coordinates on $\mathbb{C}^n$ such that the $G$-action becomes linear. Equivalently, is there a $G$-equivariant biholomorphism $Φ\colon X\to V$ where $V$ is a $G$-module? There is an intrinsic s

Fengwen Wang, Ole Sigmund

This paper presents a class of 3D single-scale isotropic materials with tunable stiffness and buckling strength obtained via topology optimization and subsequent shape optimization. Compared to stiffness-optimal closed-cell plate material, the material class reduces the Young's modulus to a range from 79% to 58%, but improves the uniaxial buckling streng

Patricio Almirón, Julio José Moyano-Fernández

The aim of this paper is to propose an extension of the Wilf conjecture to semimodules over a numerical semigroup through a new approach toward the solution of the Wilf conjecture on numerical semigroups. The key point is the introduction of a new invariant that we call Wilf function of a semigroup that can be also defined for a semimodule over the semigroup

Jaykumar Vaidya, Mohammad Khairul Bashar, Nikhil Shukla

Noise is expected to play an important role in the dynamics of analog systems such as coupled oscillators which have recently been explored as a hardware platform for application in computing. In this work, we experimentally investigate the effect of noise on the synchronization of relaxation oscillators and their computational properties. Specifically, in c

Yiming Gan, Bo Yu, Boyuan Tian, Leimeng Xu

We develop and commercialize autonomous machines, such as logistic robots and self-driving cars, around the globe. A critical challenge to our -- and any -- autonomous machine is accurate and efficient localization under resource constraints, which has fueled specialized localization accelerators recently. Prior acceleration efforts are point solutions in th

Soichiro Isoyama, Riccardo Sturani, Hiroyuki Nakano

To enable detection and maximise the physics output of gravitational wave observations from compact binary systems, it is crucial the availability of accurate waveform models. The present work aims at giving an overview for non-experts of the (inspiral) waveforms used in the gravitational wave data analysis for compact binary coalescence. We first provide th

Abhinav Prakash, Rui Tuo, Yu Ding

This paper is concerned with a nonparametric regression problem in which the input variables and the errors are autocorrelated in time. The motivation for the research stems from modeling wind power curves. Using existing model selection methods, like cross validation, results in model overfitting in presence of temporal autocorrelation. This phenomenon is r

Ricardo Guerrero, Hai Xuan Pham, Vladimir Pavlovic

Computational food analysis (CFA) naturally requires multi-modal evidence of a particular food, e.g., images, recipe text, etc. A key to making CFA possible is multi-modal shared representation learning, which aims to create a joint representation of the multiple views (text and image) of the data. In this work we propose a method for food domain cross-modal

Matteo Mancinelli, Vincent Jaunet, Peter Jordan, Aaron Towne

We model the resonance mechanism underpinning generation of A1 and A2 screech tones in an under-expanded supersonic jet. Starting from the resonance model recently proposed by \cite{mancinelli2019screech}, where the upstream-travelling wave is a neutrally-stable guided jet mode, we here present a more complete linear-stability-based model for screech predict

Tobias Schlagenhauf, Faruk Yildirim, Benedikt Brückner

Training deep learning models in technical domains is often accompanied by the challenge that although the task is clear, insufficient data for training is available. In this work, we propose a novel approach based on the combination of Siamese networks and radial basis function networks to perform data-efficient classification without pretraining by measuri

Veronika Ertl, Timo Keller, Yanshuai Qin

For an abelian variety $A$ over a finitely generated field $K$ of characteristic $p > 0$, we prove that the algebraic rank of $A$ is at most a suitably defined analytic rank. Moreover, we prove that equality, i.e., the BSD rank conjecture, holds for $A/K$ if and only if a suitably defined Tate--Shafarevich group of $A/K$ (1) has finite $\ell$-primary compone

O. Contigiani, Y. M. Bahé, H. Hoekstra

The outskirts of accreting dark matter haloes exhibit a sudden drop in density delimiting their multi-stream region. Due to the dynamics of accretion, the location of this physically motivated edge strongly correlates with the halo growth rate. Using hydrodynamical zoom-in simulations of high-mass clusters, we explore this definition in realistic simulations

Valery E. Lyubovitskij, Ivan Schmidt

We study the gluon parton densities [parton distribution functions (PDFs), transverse momentum distributions (TMDs), generalized parton distributions (GPDs)] and form factors in soft-wall AdS/QCD. We show that the power behavior of gluon parton distributions and form factors at large values of the light-cone variable and large values of square momentum is co

Olga Korotkova, Greg Gbur

A matrix representation is introduced for stationary beam-like light fields that allows for simultaneous treatment of the orbital angular momentum (OAM) and the second-order state of spatial coherence. This Coherence-OAM matrix is a counterpart of the 2 x 2 beam Coherence-polarization matrix in a Cartesian polarization basis or Coherence-spin angular momentu

Theophilus Agama, Berndt Gensel

In this paper, we introduce and develop the circle embedding method. This method hinges essentially on a combinatorial-geometric structure which we choose to call circles of partition. We provide applications in the context of problems that relates to deciding on the feasibility of partitioning numbers into certain subset of integers. In particular, our meth

Justin Jude, Matthias H. Hennig

Can neural networks learn goal-directed behaviour using similar strategies to the brain, by combining the relationships between the current state of the organism and the consequences of future actions? Recent work has shown that recurrent neural networks trained on goal based tasks can develop representations resembling those found in the brain, entorhinal c

Shahriar Nahian, Shahriar Muhammad Nahid, Mohammad Motalab, Pritom Bose

Combined gold and silicon nano-system has spurred tremendous interest in the scientific community due to its application in different metal-semiconductor electronic devices and solar driven water splitting cells. Silicon, fabricated on gold layer, is prone to gold atom diffusion at its surface. In this study, detailed analysis of mechanical properties of gol

Navod Neranjan Thilakarathne, Mohan Krishna Kagita, W. D Madhuka Priyashan

The Internet of Things (IoT) is seen as a novel technical paradigm aimed at enabling connectivity between billions of interconnected devices all around the world. This IoT is being served in various domains, such as smart healthcare, traffic surveillance, smart homes, smart cities, and various industries. IoT's main functionality includes sensing the sur

Yanshuai Qin

Let $\mathcal{X}\rightarrow C$ be a dominant morphism between smooth irreducible varieties over a finitely generated field $k$ such that the generic fiber $X$ is smooth, projective and geometrically connected. Assuming that $C$ is a curve with function field $K$, we build a relation between the Tate-Shafarevich group for $\mathrm{Pic}^0_{X/K}$ and the geomet

Johannes K. Fichte, Markus Hecher, Florim Hamiti

Many computational problems in modern society account to probabilistic reasoning, statistics, and combinatorics. A variety of these real-world questions can be solved by representing the question in (Boolean) formulas and associating the number of models of the formula directly with the answer to the question. Since there has been an increasing interest in p

Jonas Mielke, Jason R. Petta, Guido Burkard

Nuclear spins show long coherence times and are well isolated from the environment, which are properties making them promising for quantum information applications. Here, we present a method for nuclear spin readout by probing the transmission of a microwave resonator. We consider a single electron in a silicon quantum dot-donor device interacting with a mic

Korranat Naruenatthanaset, Thanarat H. Chalidabhongse, Duangdao Palasuwan, Nantheera Anantrasirichai

Automated red blood cell (RBC) classification on blood smear images helps hematologists to analyze RBC lab results in a reduced time and cost. However, overlapping cells can cause incorrect predicted results, and so they have to be separated into multiple single RBCs before classifying. To classify multiple classes with deep learning, imbalance problems are

Rui Xu, Yong Gao, Lijing Shao

The Standard-Model Extension (SME) is an effective-field-theoretic framework that catalogs all Lorentz-violating field operators. The anisotropic correction from the minimal gravitational SME to Newtonian gravitational energy for spheroids is studied, and the rotation of rigid spheroids is solved with perturbation method and numerical approach. The well-know

Colm Talbot, Eric Thrane

Many astronomical surveys are limited by the brightness of the sources, and gravitational-wave searches are no exception. The detectability of gravitational waves from merging binaries is affected by the mass and spin of the constituent compact objects. To perform unbiased inference on the distribution of compact binaries, it is necessary to account for this

Yilun Du, Shuang Li, Joshua Tenenbaum, Igor Mordatch

Contrastive divergence is a popular method of training energy-based models, but is known to have difficulties with training stability. We propose an adaptation to improve contrastive divergence training by scrutinizing a gradient term that is difficult to calculate and is often left out for convenience. We show that this gradient term is numerically signific

Elena Kozlikin, Robert Lilow, Felix Fabis, Matthias Bartelmann

We present a detailed comparison of the newly developed particle-based Kinetic Field Theory framework for cosmic large-scale structure formation with the established formalism of Eulerian Standard Perturbation Theory. We highlight the qualitative differences of both approaches by a comparative analysis of the respective equations of motion and implementation

Joshua F. Robinson, Ioatzin Rios de Anda, Fergus J. Moore, Florence K. A. Gregson

In the COVID-19 pandemic, billions are wearing face masks, in both health care settings and in public. Which type of mask we should wear in what situation, is therefore important. There are three basic types: cotton, surgical, and respirators (e.g. FFP2, N95 and similar). All are essentially air filters worn on the face. Air filtration is relatively well und

Ehsan Reyhanian, Benedikt Dorschner, Ilya Karlin

We investigate a kinetic model for compressible non-ideal fluids [DOI:10.1103/PhysRevE.102.020103]. The model imposes the local thermodynamic pressure through a rescaling of the particles velocities, which accounts for both long- and short-range effects and hence full thermodynamic consistency. The model is fully Galilean invariant and treats mass, momentum

V. K. Oikonomou

We consider a class of exponential models of $f(R)$ gravity, in the presence of a canonical scalar field, for which at early times the effective Lagrangian of the theory becomes that of a rescaled canonical scalar field with the Einstein-Hilbert term becoming $\sim αR$, with $α$ a dimensionless constant. This rescaled Einstein-Hilbert scalar field theory at

Zhipeng Li, Yong Long, Il Yong Chun

Dual-energy computed tomography (DECT) has been widely used in many applications that need material decomposition. Image-domain methods directly decompose material images from high- and low-energy attenuation images, and thus, are susceptible to noise and artifacts on attenuation images. The purpose of this study is to develop an improved iterative neural ne

Philip Dittmann, Florian Pop

We resolve the strong Elementary Equivalence versus Isomorphism Problem for finitely generated fields. That is, we show that for every field in this class there is a first-order sentence which characterizes this field within the class up to isomorphism. Our solution is conditional on resolution of singularities in characteristic two and unconditional in all

Jun Zhang, Yuan Sun

We study the sparsity of Hawking radiation from nonrotating singularity-free black holes in conformal gravity. We give a rigorous bound on the greybody factor for massless scalar field and calculate the sparsity of Hawking radiation from the black hole. Besides, we investigate the dependence of the greybody factor and the sparsity of Hawking radiation on the

Filipe S. Pereira, Fernando Grinstein, Daniel M. Israel, Rick Rauenzahn

The PANS equations model is used to predict the transitional Taylor-Green vortex (TGV) flow at Re=3000. A new form of the closure is proposed, in which the PANS procedure is applied to a variant of the BHR turbulence model. The TGV is a benchmark case for transitional flows in which the onset of turbulence is driven by vortex-stretching and reconnection mech

Valentin Iovene, Gaston Zanitti, Demian Wassermann

With the growing number of published functional magnetic resonance imaging (fMRI) studies, meta-analysis databases and models have become an integral part of brain mapping research. Coordinate-based meta-analysis (CBMA) databases are built by automatically extracting both coordinates of reported peak activations and term associations using natural language p

Shi-Yuan Hu, Jun-Jun Chu, Michael J. Shelley, Jun Zhang

In cellular vortical flows, namely arrays of counter-rotating vortices, short but flexible filaments can show simple random walks through their stretch-coil interactions with flow stagnation points. Here, we study the dynamics of semi-rigid filaments long enough to broadly sample the vortical field. Using simulation, we find a surprising variety of long-time

M. A. Alcoforado, R. F. Aranha, W. O. Barreto, H. P. de Oliveira

We follow the strategy initiated in Ref. [1] and proceed with the implementation of the Galerkin-Collocation domain decomposition (GCDD) applied to the dynamics of a spherical self-gravitating scalar field with the field equation in the Cauchy formulation. We have adopted the areal slicing gauge. We have presented a detailed implementation for an arbitrary n

SBND Collaboration, R. Acciarri, C. Adams, C. Andreopoulos

In liquid argon time projection chambers exposed to neutrino beams and running on or near surface levels, cosmic muons and other cosmic particles are incident on the detectors while a single neutrino-induced event is being recorded. In practice, this means that data from surface liquid argon time projection chambers will be dominated by cosmic particles, bot

Erik Aumayr, Saman Feghhi, Filippo Vannella, Ezeddin Al Hakim

Safe interaction with the environment is one of the most challenging aspects of Reinforcement Learning (RL) when applied to real-world problems. This is particularly important when unsafe actions have a high or irreversible negative impact on the environment. In the context of network management operations, Remote Electrical Tilt (RET) optimisation is a safe

Jann Michael Weinand, Kenneth Sörensen, Pablo San Segundo, Max Kleinebrahm

Real-world problems are becoming highly complex and, therefore, have to be solved with combinatorial optimisation (CO) techniques. Motivated by the strong increase of publications on CO, 8,393 articles from this research field are subjected to a bibliometric analysis. The corpus of literature is examined using mathematical methods and a novel algorithm for k

Javier Faba, Vicente Martín, Luis Robledo

A simple expression to compute the quantum discord between two orbitals in fermion systems is derived using the parity superselection rule. As the correlation between orbitals depends on the basis chosen, we discuss a special orbital basis, the natural one. We show that quantum correlations between natural orbital pairs disappear when the pairing tensor is z

Toru Masuda, Hiroaki Matsunaga, Toshifumi Noumi

We study relation between the gauge invariant quantity obtained in [arXiv:1908.09784] and the Feynman diagrams in the dressed $ \mathcal B_0 $ gauge in the open cubic string field theory. We derive a set of recurrence relations that hold among the terms of this gauge invariant quantity. By using these relations, we prove that this gauge invariant quantity eq

Andrés Anabalón, Dumitru Astefanesei, David Choque, Antonio Gallerati

We present a family of exact planar hairy neutral black hole solutions in extended supergravity with Fayet-Iliopoulos (FI) terms. We consider a model where the magnetic part of FI sector vanishes and obtain the superpotential at finite temperature in analytic form. Then, we discuss the thermodynamics and some holographic properties of these solutions. We reg

Shenghuan Yang, Md Tariqul Islam

In this paper, we analyzed the dataset IBM Employee Attrition to find the main reasons why employees choose to resign. Firstly, we utilized the correlation matrix to see some features that were not significantly correlated with other attributes and removed them from our dataset. Secondly, we selected important features by exploiting Random Forest, finding mo

Jakob Prange, Nathan Schneider, Vivek Srikumar

Although current CCG supertaggers achieve high accuracy on the standard WSJ test set, few systems make use of the categories' internal structure that will drive the syntactic derivation during parsing. The tagset is traditionally truncated, discarding the many rare and complex category types in the long tail. However, supertags are themselves trees. Rath

Hassan Azad, Indranil Biswas, Fazal M. Mahomed, Said Waqas Shah

A brief proof of Lie's classification of solvable algebras of vector fields on the plane is given. The proof uses basic representation theory and PDEs.

Gang Zhao, Yuqin Chen

We search for metal-rich Sausage-kinematic (MRSK) stars with [Fe/H]> -0.8 and -100<Vphi<50 km/s in LAMOST DR5 in order to investigate the influence of the Gaia-Sausage-Enceladus (GSE) merger event on the Galactic disk. For the first time, we find a group of low-alpha MRSK stars, and classify it as a metal-rich tail of the GSE galaxy based on the chemical and

Johannes Zeiher, Julian Wolf, Joshua A. Isaacs, Jonathan Kohler

The fluctuations in thermodynamic and transport properties in many-body systems gain importance as the number of constituent particles is reduced. Ultracold atomic gases provide a clean setting for the study of mesoscopic systems; however, the detection of temporal fluctuations is hindered by the typically destructive detection, precluding repeated precise m

Ronald Drimmel, Alessandro Sozzetti, Klaus-Peter Schroeder, Ulrich Bastian

We present a spectroscopic characterisation and a new orbital solution for the binary system beta Cyg Aa/Ac (MCA 55), the primary component (beta Cyg A) of the well-known wide double star Albireo. By matching evolutionary tracks to the physical parameters of all three Albireo stars (beta Cyg Aa, Ac and B) as obtained from a spectroscopic analysis of TIGRE an

Noel T. Anderson, Jay-U Chung, Shelby Kimmel

Quantum span program algorithms for function evaluation commonly have reduced query complexity when promised that the input has a certain structure. We design a modified span program algorithm to show these speed-ups persist even without having a promise ahead of time, and we extend this approach to the more general problem of state conversion. For example,

Léo Brunswic

A classical Theorem of Alexandrov states that the map associating its boundary to a convex polyhdedron of the 3-dimensional Euclidean space is a bijection from the set of convex polyhdedron up to congruence to the set of isometry classes of locally Euclidean metric on the 2-sphere with conical singularities smaller that $2\pi$. Fillastre proved a similar sta

Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm

Predictions of certifiably robust classifiers remain constant in a neighborhood of a point, making them resilient to test-time attacks with a guarantee. In this work, we present a previously unrecognized threat to robust machine learning models that highlights the importance of training-data quality in achieving high certified adversarial robustness. Specifi

Haojie Pan, Chengyu Wang, Minghui Qiu, Yichang Zhang

Pre-trained language models have been applied to various NLP tasks with considerable performance gains. However, the large model sizes, together with the long inference time, limit the deployment of such models in real-time applications. One line of model compression approaches considers knowledge distillation to distill large teacher models into small stude

Francesco Picciolo, Franco Ruzzenenti, Petter Holme, Rossana Mastrandrea

Over the last two decades, network theory has shown to be a fruitful paradigm in understanding the organization and functioning of real-world complex systems. One technique helpful to this endeavor is identifying functionally influential subgraphs, shedding light on underlying evolutionary processes. Such overrepresented subgraphs, &#34;motifs&#34;, have rec

Kousuke Nakano, Tommaso Morresi, Michele Casula, Ryo Maezono

We report the first successful application of the {\it ab initio} quantum Monte Carlo (QMC) framework to a phonon dispersion calculation. A full phonon dispersion of diamond is successfully calculated at the variational Monte Carlo (VMC) level, based on the frozen-phonon technique. The VMC-phonon dispersion is in good agreement with the experimental results,

Leonardo Bonati, Salvatore D&#39;Oro, Michele Polese, Stefano Basagni

Next Generation (NextG) cellular networks will be natively cloud-based and built upon programmable, virtualized, and disaggregated architectures. The separation of control functions from the hardware fabric and the introduction of standardized control interfaces will enable the definition of custom closed-control loops, which will ultimately enable embedded

Paolo Rinaldi, Federico Sclavi

The reconstruction theorem is a cornerstone of the theory of regularity structures [Hai14]. In [CZ20] the authors formulate and prove this result in the language of distributions theory on the Euclidean space $\mathbb{R}^d$, without any reference to the original framework. In this paper we generalize their constructions to the case of distributions over a ge

Petri J. Käpylä

(abridged) Context: Main-sequence late-type stars with masses less than $0.35 M_\odot$ are fully convective. Aims: The goal is to study convection, differential rotation, and dynamos as functions of rotation in fully convective stars. Methods: Three-dimensional hydrodynamic and magnetohydrodynamic numerical simulations with a star-in-a-box model, where a sph

Yuri Kifer

We obtain error estimates for strong approximations of a diffusion with a diffusion matrix $σ$ and a drift b by the discrete time process defined recursively X_N((n+1)/N) = X_N(n/N)+N^{1/2}σ(X_N(n/N))ξ(n+1)+N^{-1}b(XN(n/N)); where ξ(n); n\geq 1 are i.i.d. random vectors, and apply this in order to approximate the fair price of a game option with a diffusion