March 2020 arXiv papers — page 134

Wansong Liu, Danyang Luo, Changxu Wu, Minghui Zheng

Currently, studying the vehicle-human interactive behavior in the emergency needs a large amount of datasets in the actual emergent situations that are almost unavailable. Existing public data sources on autonomous vehicles (AVs) mainly focus either on the normal driving scenarios or on emergency situations without human involvement. To fill this gap and fac

Matt Jordan, Alexandros G. Dimakis

The local Lipschitz constant of a neural network is a useful metric with applications in robustness, generalization, and fairness evaluation. We provide novel analytic results relating the local Lipschitz constant of nonsmooth vector-valued functions to a maximization over the norm of the generalized Jacobian. We present a sufficient condition for which back

Yuhua Chen, Anthony G. Christodoulou, Zhengwei Zhou, Feng Shi

High-resolution (HR) magnetic resonance imaging (MRI) provides detailed anatomical information that is critical for diagnosis in the clinical application. However, HR MRI typically comes at the cost of long scan time, small spatial coverage, and low signal-to-noise ratio (SNR). Recent studies showed that with a deep convolutional neural network (CNN), HR gen

Yue Li, Xuan Li, Minchen Li, Yixin Zhu

In this paper, a hybrid Lagrangian-Eulerian topology optimization (LETO) method is proposed to solve the elastic force equilibrium with the Material Point Method (MPM). LETO transfers density information from freely movable Lagrangian carrier particles to a fixed set of Eulerian quadrature points. This transfer is based on a smooth radial kernel involved in

Subodh Mishra, Gaurav Pandey, Srikanth Saripalli

This work presents an extrinsic parameter estimation algorithm between a 3D LIDAR and a Projective Camera using a marker-less planar target, by exploiting Planar Surface Point to Plane and Planar Edge Point to back-projected Plane geometric constraints. The proposed method uses the data collected by placing the planar board at different poses in the common f

Walaa I. Eshraim

The Hamilton-Jacobi formalism of constrained systems is used to study superstring. That obtained the equations of motion for a singular system as total differential equations in many variables. These equations of motion are in exact agreement with those equations obtained using Dirac's method. Moreover, the Hamilton-Jacobi quantization of a constrained s

Danis I. Badrtdinov, Alexander A. Tsirlin, Vladimir V. Mazurenko, Frédéric Mila

Using density-functional theory (DFT) band-structure calculations, we study the crystal structure, the lattice dynamics, and the magnetic interactions in the Shastry-Sutherland magnet SrCu$_2$(BO$_3$)$_2$ under pressure, concentrating on experimentally relevant pressures up to 4 GPa. All tendencies inside the candidate intermediate phases are thoroughly work

Sami H. Assaf

Kohnert proposed the first monomial positive formula for Schubert polynomials as the generating polynomial for certain unit cell diagrams obtained from the Rothe diagram of a permutation. Billey, Jockusch and Stanley gave the first proven formula for Schubert polynomials as the generating polynomial for compatible sequences of reduced words of a permutation.

Ángel Arroyo, José G. Llorente

Let $Ω\subset\mathbb{R}^n$ be a bounded domain satisfying the uniform exterior cone condition. We establish existence and uniqueness of continuous solutions of the Dirichlet Problem associated to certain intrinsic nonlinear mean value properties in $Ω$. Furthermore we show that, when properly normalized, such functions converge to the $p$-harmonic solution o

Tapajit Dey, Sara Mousavi, Eduardo Ponce, Tanner Fry

Background: Some developer activity traditionally performed manually, such as making code commits, opening, managing, or closing issues is increasingly subject to automation in many OSS projects. Specifically, such activity is often performed by tools that react to events or run at specific times. We refer to such automation tools as bots and, in many softwa

Mohammad Arani, Mousaalreza Dastmard, Zhila Dehdari Ebrahimi, Mohsen Momenitabar

Today, a competitive manufacturing environment imposes further production cost reduction on modern companies. Seeking proper recommendations in production and maintenance planning are the two essential cornerstones of effective production organizations. In the current research, we have considered the problem of integrated multi-product process and maintenanc

Y. Ageeva, O. Evseev, O. Melichev, V. Rubakov

It is of interest to understand whether or not one can construct a classical field theory description of early cosmology which would be free of the initial singularity and stable throughout the whole evolution. One of the known possibilities is genesis within the Horndeski theory, which is thought to be an alternative to or a possible completion of the infla

Wansong Liu, Zhu Chen, Minghui Zheng

Quadrotor unmanned aerial vehicles (UAVs) have been developed and applied into several types of workplaces, such as warehouses, which usually involve human workers. The co-existence of human and UAVs brings new challenges to UAVs: potential failure of UAVs may cause risk and danger to surrounding human. Effective and efficient detection of such failure may p

Charles Lu, Julia Strout, Romane Gauriau, Brad Wright

Healthcare is one of the most promising areas for machine learning models to make a positive impact. However, successful adoption of AI-based systems in healthcare depends on engaging and educating stakeholders from diverse backgrounds about the development process of AI models. We present a broadly accessible overview of the development life cycle of clinic

Amirsina Torfi, Rouzbeh A. Shirvani, Yaser Keneshloo, Nader Tavaf

Natural Language Processing (NLP) helps empower intelligent machines by enhancing a better understanding of the human language for linguistic-based human-computer communication. Recent developments in computational power and the advent of large amounts of linguistic data have heightened the need and demand for automating semantic analysis using data-driven a

Wenhao Ding, Baiming Chen, Minjun Xu, Ding Zhao

Long-tail and rare event problems become crucial when autonomous driving algorithms are applied in the real world. For the purpose of evaluating systems in challenging settings, we propose a generative framework to create safety-critical scenarios for evaluating specific task algorithms. We first represent the traffic scenarios with a series of autoregressiv

Srilakshmi Pattabiraman, Ryan Gabrys, Olgica Milenkovic

Motivated by polymer-based data-storage platforms that use chains of binary synthetic polymers as the recording media and read the content via tandem mass spectrometers, we propose a new family of codes that allows for both unique string reconstruction and correction of multiple mass errors. We consider two approaches: The first approach pertains to asymmetr

Michal Gnacik, Marcin Guzik, Tomasz Kania

Kalton and Roberts [Trans. Amer. Math. Soc., 278 (1983), 803--816] proved that there exists a universal constant $K\leqslant 44.5$ such that for every set algebra $\mathcal{F}$ and every 1-additive function $f\colon \mathcal{F}\to \mathbb R$ there exists a finitely-additive signed measure $μ$ defined on $\mathcal{F}$ such that $|f(A)-μ(A)|\leqslant K$ for an

Frank Aurzada, Sumit Mukherjee

With $\{ξ_i\}_{i\ge 0}$ being a centered stationary Gaussian sequence with non-negative correlation function $ρ(i):=\mathbb{E}[ ξ_0ξ_i]$ and $\{σ(i)\}_{i\ge 1}$ a sequence of positive reals, we study the asymptotics of the persistence probability of the weighted sum $\sum_{i=1}^\ell σ(i) ξ_i$, $\ell\ge 1$. For summable correlations $ρ$, we show that the pers

Marija Jegorova, Joshua Smith, Michael Mistry, Timothy Hospedales

Dynamic System Identification approaches usually heavily rely on the evolutionary and gradient-based optimisation techniques to produce optimal excitation trajectories for determining the physical parameters of robot platforms. Current optimisation techniques tend to generate single trajectories. This is expensive, and intractable for longer trajectories, th

Polona Durcik, Vjekoslav Kovač

We investigate gaps of $n$-term arithmetic progressions $x, x+y, \ldots, x+(n-1)y$ inside a positive measure subset $A$ of the unit cube $[0,1]^d$. If lengths of their gaps $y$ are evaluated in the $\ell^p$-norm for any $p$ other than $1, 2, \ldots, n-1$, and $\infty$, and if the dimension $d$ is large enough, then we show that the numbers $\|y\|_{\ell^p}$ a

R. A. Konoplya, A. F. Zinhailo

Recently a $D$-dimensional regularization approach leading to the non-trivial $(3+1)$-dimensional Einstein-Gauss-Bonnet (EGB) effective description of gravity was formulated which was claimed to bypass the Lovelock's theorem and avoid Ostrogradsky instability. Later it was shown that the regularization is possible only for some broad, but limited, class

William J. Roper, Peter A. Thomas, Chaichalit Srisawat

When following the growth of structure in the Universe, we propose replacing merger trees with merger graphs, in which haloes can both merge and split into separate pieces. We show that this leads to smoother mass growth and eliminates catastrophic failures in which massive haloes have no progenitors or descendants. For those who prefer to stick with merger

Konstantinos Filippou, Christos G. Tsagas

We employ a perturbative analysis to study the evolution of large-scale peculiar velocity fields within the framework of Newtonian gravity and then compare our results to those of the corresponding relativistic treatment. In so doing, we use the same mathematical formalism and apply the same physical approach. This facilitates a direct and transparent compar

Fei Xue, Fengcheng Wu, Allan H. MacDonald

Higgs modes in condensed matter physics have drawn attention because of analogies to the Higgs bosons of particle physics. Here we use a microscopic time-dependent mean-field theory to study the collective mode spectra of two-dimensional spatially indirect exciton (electron-hole pair) condensates, focusing on the Higgs modes, i.e., those that have a large we

Kyongmin Yeo, Dylan E. C. Grullon, Fan-Keng Sun, Duane S. Boning

We propose a recurrent neural network for a "model-free" simulation of a dynamical system with unknown parameters without prior knowledge. The deep learning model aims to jointly learn the nonlinear time marching operator and the effects of the unknown parameters from a time series dataset. We assume that the time series data set consists of an ensem

Luca Mazzola, Alexander Denzler, Ramon Christen

This work focuses on the electric power market, comparing the status quo with the recent trend towards the increase in distributed self-generation capabilities by prosumers. Starting from the existing tension between the intrinsically hierarchical current structure of the electricity distribution network and the substantially distributed and self-organising

Chirag Nagpal, Xinyu Rachel Li, Artur Dubrawski

We describe a new approach to estimating relative risks in time-to-event prediction problems with censored data in a fully parametric manner. Our approach does not require making strong assumptions of constant proportional hazard of the underlying survival distribution, as required by the Cox-proportional hazard model. By jointly learning deep nonlinear repr

Peng Jiang, Srikanth Saripalli

We present a boundary-aware domain adaptation model for LiDAR scan full-scene semantic segmentation (LiDARNet). Our model can extract both the domain private features and the domain shared features with a two-branch structure. We embedded Gated-SCNN into the segmentor component of LiDARNet to learn boundary information while learning to predict full-scene se

Brian Allen, Raquel Perales, Christina Sormani

Given a pair of metric tensors $g_1 \ge g_0$ on a Riemannian manifold, $M$, it is well known that $\operatorname{Vol}_1(M) \ge \operatorname{Vol}_0(M)$. Furthermore one has rigidity: the volumes are equal if and only if the metric tensors are the same $g_1=g_0$. Here we prove that if $g_j \ge g_0$ and $\operatorname{Vol}_1(M)\to \operatorname{Vol}_0(M)$ then

Christian Noack, Philippe Sosoe

Seppäläinen and Valkó showed in \cite{SV} that for a suitable choice of parameters, the variance growth of the free energy of the stationary O'Connell-Yor polymer is governed by the exponent $2/3$, characteristic of models in the KPZ universality class. We develop exact formulas based on Gaussian integration by parts to relate the cumulants of the free e

Alexander Moreno, Zhenke Wu, Jamie Yap, David Wetter

Panel count data describes aggregated counts of recurrent events observed at discrete time points. To understand dynamics of health behaviors, the field of quantitative behavioral research has evolved to increasingly rely upon panel count data collected via multiple self reports, for example, about frequencies of smoking using in-the-moment surveys on mobile

Erin M. Schliep, Alan E. Gelfand, Jesus Abaurrea, Jesus Asin

There is increasing evidence that global warming manifests itself in more frequent warm days and that heat waves will become more frequent. Presently, a formal definition of a heat wave is not agreed upon in the literature. To avoid this debate, we consider extreme heat events, which, at a given location, are well-defined as a run of consecutive days above a

J. O. de Almeida, J. Kołodyński, C. Hirche, M. Lewenstein

Spatially resolving two incoherent point sources whose separation is well below the diffraction limit dictated by classical optics has recently been shown possible using techniques that decompose the incoming radiation into orthogonal transverse modes. Such a demultiplexing procedure, however, must be perfectly calibrated to the transverse profile of the inc

Marc Pegon

This paper is concerned with volume-constrained minimization problems derived from Gamow's liquid drop model for the atomic nucleus, involving the competition of a perimeter term and repulsive nonlocal potentials. We consider a large class of potentials, given by general radial nonnegative kernels which are integrable on $\mathbb{R}^n$, such as Bessel po

Guangzhi Tang, Neelesh Kumar, Konstantinos P. Michmizos

Energy-efficient mapless navigation is crucial for mobile robots as they explore unknown environments with limited on-board resources. Although the recent deep reinforcement learning (DRL) approaches have been successfully applied to navigation, their high energy consumption limits their use in several robotic applications. Here, we propose a neuromorphic ap

Ali Shafti, Jonas Tjomsland, William Dudley, A. Aldo Faisal

The intuitive collaboration of humans and intelligent robots (embodied AI) in the real-world is an essential objective for many desirable applications of robotics. Whilst there is much research regarding explicit communication, we focus on how humans and robots interact implicitly, on motor adaptation level. We present a real-world setup of a human-robot col

Hermann Kaindl, Stefan Kramer

Machine learning (ML) has recently created many new success stories. Hence, there is a strong motivation to use ML technology in software-intensive systems, including safety-critical systems. This raises the issue of safety verification of MLbased systems, which is currently thought to be infeasible or, at least, very hard. We think that it requires taking i

Charles Carlson, Ewan Davies, Alexandra Kolla

An emerging trend in approximate counting is to show that certain `low-temperature' problems are easy on typical instances, despite worst-case hardness results. For the class of regular graphs one usually shows that expansion can be exploited algorithmically, and since random regular graphs are good expanders with high probability the problem is typically tr

Piotr Franciszek Orzechowski, Christoph Burger, Martin Lauer

Behavior planning and decision-making are some of the biggest challenges for highly automated systems. A fully automated vehicle (AV) is confronted with numerous tactical and strategical choices. Most state-of-the-art AV platforms implement tactical and strategical behavior generation using finite state machines. However, these usually result in poor explain

Roberto Frigerio, Alessandro Sisto

It was shown by Gersten that a central extension of a finitely generated group is quasi-isometrically trivial provided that its Euler class is bounded. We say that a finitely generated group $G$ satisfies Property QITB (quasi-isometrically trivial implies bounded) if the Euler class of any quasi-isometrically trivial central extension of $G$ is bounded. We e

Philippe Meyer

The aim of this paper is to define cubic Dirac operators for colour Lie algebras. We give a necessary and sufficient condition to construct a colour Lie algebra from an $\epsilon$-orthogonal representation of an $\epsilon$-quadratic colour Lie algebra. This is used to prove a strange Freudenthal-de Vries formula for basic colour Lie algebras as well as a Par

Luka Trifunovic, Piet W. Brouwer

The interplay of topology and symmetry in a material's band structure may result in various patterns of topological states of different dimensionality on the boundary of a crystal. The protection of these "higher-order" boundary states comes from topology, with constraints imposed by symmetry. We review the bulk-boundary correspondence of topolog

A. Nietner, B. Vanhecke, F. Verstraete, J. Eisert

Tensor network states provide an efficient class of states that faithfully capture strongly correlated quantum models and systems in classical statistical mechanics. While tensor networks can now be seen as becoming standard tools in the description of such complex many-body systems, close to optimal variational principles based on such states are less obvio

Scott Tremaine

Some quadruple star systems in the hierarchical 2+2 configuration exhibit orbit-orbit resonances between the two compact binaries. We show that the most important resonances occur at period ratios of 1:1, 3:2 and 2:1. We describe the conditions required for capture and show that they can be satisfied at the 3:2 and 2:1 resonances in binaries that migrate sig

G. Nowak, R. Luque, H. Parviainen, E. Pallé

We present the discovery and characterisation of two transiting planets observed by the Transiting Exoplanet Survey Satellite (TESS) orbiting the nearby (d ~ 22 pc), bright (J ~ 9 mag) M3.5 dwarf LTT 3780 (TOI-732). We confirm both planets and their association with LTT 3780 via ground-based photometry and determine their masses using precise radial velociti

Thi Thu Phùng, Robert Peters, Andreas Honecker, Guy Trambly de Laissardière

We investigate the spin-dependent thermoelectric effect of graphene flakes with magnetic edges in the ballistic regime. Employing static, respectively, dynamic mean-field theory we first show that magnetism appears at the zigzag edges for a window of Coulomb interactions that increases significantly with increasing flake size. We then use the Landauer formal

Javier Lopez-Piqueres, Brayden Ware, Romain Vasseur

Entanglement phase transitions in quantum chaotic systems subject to projective measurements and in random tensor networks have emerged as a new class of critical points separating phases with different entanglement scaling. We propose a mean-field theory of such transitions by studying the entanglement properties of random tree tensor networks. As a functio

Misaki Mizumoto, Mariko Nomura, Chris Done, Ken Ohsuga

UltraFast Outflows (UFO) are observed in some active galactic nuclei (AGN), with blueshifted and highly ionised Fe-K absorption features. AGN typically have a UV bright accretion flow, so UV line driving is an obvious candidate for launching these winds. However this mechanism requires material with UV opacity, in apparent conflict with the observed high ion

Ryan Cloutier, Jason D. Eastman, Joseph E. Rodriguez, Nicola Astudillo-Defru

We present the confirmation of two new planets transiting the nearby mid-M dwarf LTT 3780 (TIC 36724087, TOI-732, $V=13.07$, $K_s=8.204$, $R_s$=0.374 R$_{\odot}$, $M_s$=0.401 M$_{\odot}$, d=22 pc). The two planet candidates are identified in a single TESS sector and are validated with reconnaissance spectroscopy, ground-based photometric follow-up, and high-

A. E. Cárcamo Hernández, Ivo de Medeiros Varzielas

We propose a simple framework based on $Δ(27)$ that leads to the successful cobimaximal lepton mixing ansatz, thus providing a predictive explanation for leptonic mixing observables. We explore first the effective neutrino mass operators, then present a specific model realization based on type I seesaw, and also propose a model with radiative 1-loop seesaw w

Anna-Christina Eilers, David W. Hogg, Hans-Walter Rix, Neige Frankel

The mean Galactocentric radial velocities $\langle v_{R}\rangle(R,φ)$ of luminous red giant stars within the mid-plane of the Milky Way reveal a spiral signature, which could plausibly reflect the response to a non-axisymmetric perturbation of the gravitational potential in the Galactic disk. We apply a simple steady-state toy model of a logarithmic spiral t

Jose Utreras, Guillermo A. Blanc, Andres Escala, Sharon Meidt

In galactic disks, galactic rotation sets the bulk motion of gas, and its energy and momentum can be transferred toward small scales. Additionally, in the interstellar medium, random and noncircular motions arise from stellar feedback, cloud-cloud interactions, and instabilities, among other processes. Our aim is to comprehend to which extent small-scale gas

Paz Beniamini, Kenta Hotokezaka

We study turbulent gas diffusion affects on $r$-process abundances in Milky Way stars, by a combination of an analytical approach and a Monte Carlo simulation. Higher $r$-process event rates and faster diffusion, lead to more efficient mixing corresponding to a reduced scatter of $r$-process abundances and causing $r$-process enriched stars to start appearin

P. Mroz, R. Poleski, C. Han, A. Udalski

High-cadence observations of the Galactic bulge by the microlensing surveys led to the discovery of a handful of extremely short-timescale microlensing events that can be attributed to free-floating or wide-orbit planets. Here, we report the discovery of another strong free-floating planet candidate, which was found from the analysis of the gravitational mic

Mark R. Lovell

Studies of flux anomalies statistics and perturbations in stellar streams have the potential to constrain models of warm dark matter (WDM), including sterile neutrinos. Producing these constraints requires a parametrization of the WDM mass function relative to that of the cold dark matter (CDM) equivalent. We use five WDM models with half-mode masses, $M_\ma

Morgan MacLeod, Abraham Loeb

Binary systems undergoing unstable Roche Lobe overflow spill gas into their circumbinary environment as their orbits decay toward coalescence. In this paper, we use a suite of hydrodynamic models of coalescing binaries involving an extended donor and a more compact accretor. We focus on the period of unstable Roche Lobe overflow that ends as the accretor plu

Jyothish Pari, Joseph L. Hora

The field of computer vision has greatly matured in the past decade, and many of the methods and techniques can be useful for astronomical applications. One example is in searching large imaging surveys for objects of interest, especially when it is difficult to specify the characteristics of the objects being searched for. We have developed a method using c

A. V. Belitsky, G. P. Korchemsky

We study a special class of four-point correlation functions of infinitely heavy half-BPS operators in planar N=4 SYM which admit factorization into a product of two octagon form factors. We demonstrate that these functions satisfy a system of nonlinear integro-differential equations which are powerful enough to fully determine their dependence on the 't

Matthew Habermann

In this paper, we give a proof of homological mirror symmetry for two variable invertible polynomials, where the symmetry group on the $B$-side is taken to be maximal. The proof involves an explicit gluing construction of the Milnor fibres, and as an application, we prove derived equivalences between certain nodal stacky curves, some of whose irreducible com

Nabarun Chakrabarty, Indrani Chakraborty, Dilip Kumar Ghosh

Color-octet scalars arise in various Grand Unification scenarios and also in other models of new physics. They are also postulated for minimal flavour violation. Purely phenomenological imprints of such scalars are therefore worth looking at. Motivated by this, we perform a complete one-loop calculation of the $H^+ \to W^+ Z (\g)$ decay in a two Higgs double

V. N. Smolyaninova, J. Cartelli, B. Augstein, S. Spickard

Recently it was proposed that extraordinary light waves in hyperbolic metamaterials exhibit two times physics behavior (Phys. Rev. Lett. 105, 067402, 2010). We report experimental observation of this effect via investigation of gravity-like nonlinear optics of iron/cobalt-based ferrofluid hyperbolic metamaterials. In addition to conventional temporal coordin

Luca Di Luzio, Maurizio Giannotti, Enrico Nardi, Luca Visinelli

We review the landscape of QCD axion models. Theoretical constructions that extend the window for the axion mass and couplings beyond conventional regions are highlighted and classified. Bounds from cosmology, astrophysics and experimental searches are reexamined and updated.

H. V. Ragavendra, Debika Chowdhury, L. Sriramkumar

[Abridged] A sharp cut-off in the primordial scalar power spectrum on large scales has been known to improve the fit to the cosmic microwave background (CMB) data when compared to the more standard, nearly scale invariant power spectrum that arises in slow roll inflation. In an earlier work, we had numerically investigated the characteristics of the scalar b

Zahra Zahedi, Alireza Khayatian, Mohammad Mehdi Arefi, Shen Yin

This paper aims at investigating the problem of fast convergence to the Nash equilibrium (NE) for N-Player noncooperative differential games. The proposed method is such that the players attain their NE point without steady-state oscillation (SSO) by measuring only their payoff values with no information about payoff functions, the model and also the actions

Mehdi Assanioussi, Isha Kotecha

The condensate cosmology programme of group field theory has produced several interesting results. The key idea is in the suggestion that a macroscopic homogeneous spacetime can be approximated by a dynamical condensate phase of the underlying microscopic system of an arbitrarily large number of candidate quanta of geometry. In this work, we extend the stand

James McInerney, Bryan Gin-ge Chen, Louis Theran, Christian Santangelo

We consider the zero-energy deformations of periodic origami sheets with generic crease patterns. Using a mapping from the linear folding motions of such sheets to force-bearing modes in conjunction with the Maxwell-Calladine index theorem we derive a relation between the number of linear folding motions and the number of rigid body modes that depends only o

Hardy Chan, María del Mar González, Yanghong Huang, Edoardo Mainini

We establish uniqueness of vanishing radially decreasing entire solutions, which we call ground states, to some semilinear fractional elliptic equations. In particular, we treat the fractional plasma equation and the supercritical power nonlinearity. As an application, we deduce uniqueness of radial steady states for nonlocal aggregation-diffusion equations

Ahmadreza Jeddi, Mohammad Javad Shafiee, Michelle Karg, Christian Scharfenberger

While deep neural networks have been achieving state-of-the-art performance across a wide variety of applications, their vulnerability to adversarial attacks limits their widespread deployment for safety-critical applications. Alongside other adversarial defense approaches being investigated, there has been a very recent interest in improving adversarial rob

Sen Wang, Jiaqi Chen, Xuanliang Deng, Seth Hutchinson

Chinese calligraphy is a unique art form with great artistic value but difficult to master. In this paper, we formulate the calligraphy writing problem as a trajectory optimization problem, and propose an improved virtual brush model for simulating the real writing process. Our approach is inspired by pseudospectral optimal control in that we parameterize th

Suat Gumussoy, Hitay Ozbay

A state space based design method is given to find strongly stabilizing controllers for multiple-input-multiple-output plants (MIMO). A sufficient condition is derived for the existence of suboptimal stable H-infinity controller in terms of linear matrix inequalities (LMIs) and the controller order is twice that of the plant. A new parameterization of strong

E. Varga, V. Vadakkumbatt, A. J. Shook, P. H. Kim

Turbulent flow restricted to two dimensions can spontaneously develop order on large scales, defying entropy expectations and in sharp contrast with turbulence in three dimensions where nonlinear turbulent processes act to destroy large-scale order. In this work we report the observation of unusual turbulent behavior in steady-state flow of superfluid \4He--

Raza Sabbir Sufian, Tianbo Liu, Andrei Alexandru, Stanley J. Brodsky

We present the first lattice QCD calculation of the charm quark contribution to the nucleon electromagnetic form factors $G^c_{E,M}(Q^2)$ in the momentum transfer range $0\leq Q^2 \leq 1.4$ $\rm GeV^2$. The quark mass dependence, finite lattice spacing and volume corrections are taken into account simultaneously based on the calculation on three gauge ensemb

Claudia Artiaco, Federico Balducci, Giorgio Parisi, Antonello Scardicchio

In this Letter, we analyze the quantum dynamics of the perceptron model: a particle is constrained on a $N$-dimensional sphere, with $N\to \infty$, and subjected to a set of randomly placed hard-wall potentials. This model has several applications, ranging from learning protocols to the effective description of the dynamics of an ensemble of infinite-dimensi

I. Giomataris, M. Gros, I. Katsioulas, P. Knights

The spherical proportional counter is a gaseous detector used in a variety of applications, including direct dark matter and neutrino-less double beta decay searches. The ACHINOS multianode structure is a read-out technology that overcomes the limitations of single-anode read-out structures for large-size detectors and operation under high pressure. A resist

Venkatraman Narayanan, Bala Murali Manoghar, Vishnu Sashank Dorbala, Dinesh Manocha

We present ProxEmo, a novel end-to-end emotion prediction algorithm for socially aware robot navigation among pedestrians. Our approach predicts the perceived emotions of a pedestrian from walking gaits, which is then used for emotion-guided navigation taking into account social and proxemic constraints. To classify emotions, we propose a multi-view skeleton

Nan Yang, Lukas von Stumberg, Rui Wang, Daniel Cremers

We propose D3VO as a novel framework for monocular visual odometry that exploits deep networks on three levels -- deep depth, pose and uncertainty estimation. We first propose a novel self-supervised monocular depth estimation network trained on stereo videos without any external supervision. In particular, it aligns the training image pairs into similar lig

Rob Rahm

For any operator $T$ whose bilinear form can be dominated by a sparse bilinear form, we prove that $T$ is bounded as a map from $L^1(\widetilde{M}w)$ into weak--$L^1(w)$. Our main innovation is that $\widetilde{M}$ is a maximal function defined by directly using the local $A_\infty$ characteristic of the weight (rather than Orlicz norms). Prior results are d

Rolf Schimmrigk

Geometric modularity has recently been conjectured to be a characteristic feature for flux vacua with $W=0$. This paper provides support for the conjecture by computing motivic modular forms in a direct way for several string compactifications for which such vacua are known to exist. The analysis of some Calabi-Yau manifolds which do not admit supersymmetric

C. Armendariz-Picon

In previous work we argued that the correct procedure to predict the gravitational wave signal from preheating after inflation rests on the in-in formalism. We extend here our previous analysis to include the backreaction of the produced matter on the motion of the inflaton and the expansion of the universe, and study how the latter affect the spectrum of th

Gianluca Cassese

We investigate the possibility of completing financial markets in a model with no exogenous probability measure and market imperfections. A necessary and sufficient condition is obtained for such extension to be possible.

Stéphane d'Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala

Deep neural networks can achieve remarkable generalization performances while interpolating the training data perfectly. Rather than the U-curve emblematic of the bias-variance trade-off, their test error often follows a "double descent" - a mark of the beneficial role of overparametrization. In this work, we develop a quantitative theory for this ph

Pavel Chebotarev, Dmitry Gubanov

Centrality metrics play a crucial role in network analysis, while the choice of specific measures significantly influences the accuracy of conclusions as each measure represents a unique concept of node importance. Among over 400 proposed indices, selecting the most suitable ones for specific applications remains a challenge. Existing approaches -- model-bas

Alexander S. Kuznetsov, Diego H. O. Machado, Klaus Biermann, Paulo V. Santos

Polaritons enable the resonant coupling of excitons and photons to vibrations in the application-relevant super high frequency (SHF, 3-30 GHz) domain. We introduce a novel platform for coherent optomechanics based on the coupling of exciton-polaritons and electrically driven SHF longitudinal acoustic phonons confined within the spacer region of a planar Brag

C. A. Downing, J. C. López Carreño, A. I. Fernández-Domínguez, E. del Valle

We study a prototypical model of two coupled two-level systems, where the competition between coherent and dissipative coupling gives rise to a rich phenomenology. In particular, we analyze the case of asymmetric coupling, as well as the limiting case of chiral (or one-way) coupling. We investigate various quantum optical properties of the system, including

Tiep M. Hoang, Trung Q. Duong, Hoang Duong Tuan, Sangarapillai Lambotharan

This paper presents a framework for converting wireless signals into structured datasets, which can be fed into machine learning algorithms for the detection of active eavesdropping attacks at the physical layer. More specifically, a wireless communication system, which consists of K legal users, one access point (AP) and one active eavesdropper, is consider

E. Gaztanaga, S. J. Schmidt, M. D. Schneider, J. A. Tyson

We test the impact of some systematic errors in weak lensing magnification measurements with the COSMOS 30-band photo-$z$ Survey flux limited to $I_{auto}<25.0$ using correlations of both source galaxy counts and magnitudes. Systematic obscuration effects are measured by comparing counts and magnification correlations. We use the ACS-HST catalogs to identify

EDELWEISS Collaboration, Q. Arnaud, E. Armengaud, C. Augier

The EDELWEISS collaboration has performed a search for Dark Matter (DM) particles interacting with electrons using a 33.4 g Ge cryogenic detector operated underground at the LSM. A charge resolution of 0.53 electron-hole pairs (RMS) has been achieved using the Neganov-Trofimov-Luke amplification with a bias of 78 V. We set the first Ge-based constraints on s

Pedro G. S. Fernandes

Recently, spontaneous scalarization of charged black holes has attracted a great deal of attention and motivated several studies of Einstein-Maxwell-scalar models. These studies have, however, only considered a massless and non-self-interacting scalar field. In this work a more realistic treatment of the problem is considered by studying the effects of scala

Andrew D. Kercher, Andrew Corrigan

A least-squares formulation of the Moving Discontinuous Galerkin Finite Element Method with Interface Condition Enforcement (LS-MDG-ICE) is presented. This method combines MDG-ICE, which uses a weak formulation that separately enforces a conservation law and the corresponding interface condition and treats the discrete geometry as a variable, with the Discon

Amit Das, Srikanth Sastry, Dapeng Bi

Cell neighbor exchanges are integral to tissue rearrangements in biology, including development and repair. Often these processes occur via topological T1 transitions analogous to those observed in foams, grains and colloids. However, in contrast to in non-living materials the T1 transitions in biological tissues are rate-limited and cannot occur instantaneo

E. M. M. B. Ekanayake, H. M. H. K. Weerasooriya, D. Y. L. Ranasinghe, S. Herath

Hyperspectral unmixing (HU) has become an important technique in exploiting hyperspectral data since it decomposes a mixed pixel into a collection of endmembers weighted by fractional abundances. The endmembers of a hyperspectral image (HSI) are more likely to be generated by independent sources and be mixed in a macroscopic degree before arriving at the sen

Chuangchuang Sun, Macheng Shen, Jonathan P. How

The complexity of multiagent reinforcement learning (MARL) in multiagent systems increases exponentially with respect to the agent number. This scalability issue prevents MARL from being applied in large-scale multiagent systems. However, one critical feature in MARL that is often neglected is that the interactions between agents are quite sparse. Without ex

Angela Vasanelli, Simon Huppert, Andrew Haky, Thibault Laurent

We investigate the frontier between classical and quantum plasmonics in highly doped semiconductor layers. The choice of a semiconductor platform instead of metals for our study permits an accurate description of the quantum nature of the electrons constituting the plasmonic response, which is a crucial requirement for quantum plasmonics. Our quantum model a

Jacob Miller, Guillaume Rabusseau, John Terilla

Tensor networks are a powerful modeling framework developed for computational many-body physics, which have only recently been applied within machine learning. In this work we utilize a uniform matrix product state (u-MPS) model for probabilistic modeling of sequence data. We first show that u-MPS enable sequence-level parallelism, with length-n sequences ab

Vincent Lostanlen, Alice Cohen-Hadria, Juan Pablo Bello

With the aim of constructing a biologically plausible model of machine listening, we study the representation of a multicomponent stationary signal by a wavelet scattering network. First, we show that renormalizing second-order nodes by their first-order parents gives a simple numerical criterion to assess whether two neighboring components will interfere ps

Daniel Meljanac, Stjepan Meljanac, Zoran Škoda, Rina Štrajn

We consider two families of Drinfeld twists generated from a simple Jordanian twist further twisted with 1-cochains. Using combinatorial identities, they are presented as a series expansion in the dilatation and momentum generators. These twists interpolate between two simple Jordanian twists. For an expansion of a family of twists $\mathcal{F}_{L,u}$, we al

Marko Medenjak, Tomaz Prosen, Lenart Zadnik

Dynamical response functions are standard tools for probing local physics near the equilibrium. They provide information about relaxation properties after the equilibrium state is weakly perturbed. In this paper we focus on systems which break the assumption of thermalization by exhibiting persistent temporal oscillations. We provide rigorous bounds on the F

Ignacio Abadia, Francisco Naveros, Jesus A. Garrido, Eduardo Ros

The work presented here is a novel biological approach for the compliant control of a robotic arm in real time (RT). We integrate a spiking cerebellar network at the core of a feedback control loop performing torque-driven control. The spiking cerebellar controller provides torque commands allowing for accurate and coordinated arm movements. To compute these

Nikolai Miklin, Michał Oszmaniec

We consider the problem of certification of arbitrary ensembles of pure states and projective measurements solely from the experimental statistics in the prepare-and-measure scenario assuming the upper bound on the dimension of the Hilbert space. To this aim, we propose a universal and intuitive scheme based on establishing perfect correlations between targe