July 2020 arXiv papers — page 2

Yan Wu, Aoming Liu, Zhiwu Huang, Siwei Zhang

This paper aims at enlarging the problem of Neural Architecture Search (NAS) from Single-Path and Multi-Path Search to automated Mixed-Path Search. In particular, we model the NAS problem as a sparse supernet using a new continuous architecture representation with a mixture of sparsity constraints. The sparse supernet enables us to automatically achieve spar

Masahiro Ibe, Shin Kobayashi, Yuhei Nakayama, Satoshi Shirai

Recently, the XENON1T collaboration reported an excess in the electron recoil energy spectrum. One of the simplest new physics interpretation is a new neutrino-electron interaction mediated by a light vector particle. However, for the parameter region favored by this excess, the constraints from the stellar cooling are severe. Still, there are astrophysical

Amelia Jiménez-Sánchez, Diana Mateus, Sonja Kirchhoff, Chlodwig Kirchhoff

An adequate classification of proximal femur fractures from X-ray images is crucial for the treatment choice and the patients' clinical outcome. We rely on the commonly used AO system, which describes a hierarchical knowledge tree classifying the images into types and subtypes according to the fracture's location and complexity. In this paper, we pro

Nathan B. Clayburn, Trevor H. Wright, Eric B. Norrgard, David DeMille

We report high-precision measurements on the thallium fluoride $\tilde{J} = 1$ hyperfine manifold of the $B^3Π_1$ ($ν= 0$) state. This state is of special interest because it is central to an optical cycling scheme that is envisioned to play an important role in enhancing the sensitivity of the CeNTREX nuclear Schiff-moment experiment presently under constru

Haotian Tang, Zhijian Liu, Shengyu Zhao, Yujun Lin

Self-driving cars need to understand 3D scenes efficiently and accurately in order to drive safely. Given the limited hardware resources, existing 3D perception models are not able to recognize small instances (e.g., pedestrians, cyclists) very well due to the low-resolution voxelization and aggressive downsampling. To this end, we propose Sparse Point-Voxel

Sergei Gninenko, Dmitry Gorbunov

The recent confirmation by FNAL of the $(g-2)_μ$ muon anomaly gives strong evidence for the possible existence of new physics beyond the Standard Model in the muon sector. Thus it is worthy to revisit the existing experimental constraints on models suggesting theoretically consistent explanations of the anomaly. In this work, we point out that accounting for

Marie-Françoise Bidaut-Veron, Marta Garcia-Huidobro, Laurent Veron

We study properties of positive functions satisfying (E) --$Δ$u + u p -- M |$\nabla$u| q = 0 is a domain $Ω$ or in R N + when p > 1 and 1 < q < min{p, 2}. We concentrate our research on the solutions of (E) vanishing on the boundary except at one point. This analysis depends on the existence of separable solutions in R N +. We consruct various types of posit

G. Schoenhense, S. Babenkov, D. Vasilyev, H. -J. Elmers

Photoelectron momentum microscopy is an emerging powerful method for angle-resolved photoelectron spectroscopy (ARPES), especially in combination with imaging spin filters. These instruments record kx-ky images, typically exceeding a full Brillouin zone. As energy filters double-hemispherical or time-of-flight (ToF) devices are in use. Here we present a new

Carlo Mantegazza, Marco Pozzetta

We define the elastic energy of smooth immersed closed curves in $\mathbb{R}^n$ as the sum of the length and the $L^2$-norm of the curvature, with respect to the length measure. We prove that the $L^2$-gradient flow of this energy smoothly converges asymptotically to a critical point. One of our aims was to the present the application of a Lojasiewicz-Simon

Yiming Chen, Victor Gorbenko, Juan Maldacena

We consider two dimensional CFT states that are produced by a gravitational path integral. As a first case, we consider a state produced by Euclidean $AdS_2$ evolution followed by flat space evolution. We use the fine grained entropy formula to explore the nature of the state. We find that the naive hyperbolic space geometry leads to a paradox. This is solve

G. A. Pavliotis, G. Stoltz, U. Vaes

In this paper, we study the diffusive limit of solutions to the generalized Langevin equation (GLE) in a periodic potential. Under the assumption of quasi-Markovianity, we obtain sharp longtime equilibration estimates for the GLE using techniques from the theory of hypocoercivity. We then prove asymptotic results for the effective diffusion coefficient in th

K. S. Babu, Shaikh Saad

The clockwork mechanism, which can naturally explain the origin of small numbers, is implemented in $SO(10)$ grand unified theories to address the origin of hierarchies in fermion masses and mixings. We show that a minimal Yukawa sector involving a $10_H$ and $\overline{126}_H$ of Higgs bosons, extended with two clockwork chains consisting of $16+\overline{1

Roberto Verdel, Markus Schmitt, Yi-Ping Huang, Petr Karpov

Dynamics in correlated quantum matter is a hard problem, as its exact solution generally involves a computational effort that grows exponentially with the number of constituents. While a remarkable progress has been witnessed in recent years for one-dimensional systems, much less has been achieved for interacting quantum models in higher dimensions, since th

Stéphane Ballet, Alexis Bonnecaze, Bastien Pacifico

We propose a Recursive Polynomial Generic Construction (RPGC) of multiplication algorithms in any finite field $\mathbb{F}_{q^n}$ based on the method of D.V. and G.V. Chudnovsky specialized on the projective line. They are usual polynomial interpolation algorithms in small extensions and the Karatsuba algorithm is seen as a particular case of this constructi

Lucia Morotti, Hung P. Tong-Viet

In this paper, we study the proportion of vanishing elements of finite groups. We show that the proportion of vanishing elements of every finite non-abelian group is bounded below by $1/2$ and classify all finite groups whose proportions of vanishing elements attain this bound. For symmetric groups of degree at least $5$, we show that this bound is at least

Marilena Daquino, Ivan Heibi, Silvio Peroni, David Shotton

Semantic Web technologies are widely used for storing RDF data and making them available on the Web through SPARQL endpoints, queryable using the SPARQL query language. While the use of SPARQL endpoints is strongly supported by Semantic Web experts, it hinders broader use of RDF data by common Web users, engineers and developers unfamiliar with Semantic Web

Dora Klindžić, Daphne M. Stam, Frans Snik, H. Jens Hoeijmakers

LOUPE, the Lunar Observatory for Unresolved Polarimetry of the Earth, is a small, robust spectro-polarimeter with a mission to observe the Earth as an exoplanet. Detecting Earth-like planets in stellar habitable zones is one of the key challenges of modern exoplanetary science. Characterising such planets and searching for traces of life requires the direct

Luca Chiaraviglio, Cristian Di Paolo, Nicola Blefari-Melazzi

We target the planning of a 5G cellular network under 5G service and ElectroMagnetic Fields (EMFs) constraints. We initially model the problem with a Mixed Integer Linear Programming (MILP) formulation. The pursued objective is a weighed function of next-generation Node-B (gNB) installation costs and 5G service coverage level from a massive Multiple Input Mu

Angel Ballesteros, Alfonso Blasco, Ivan Gutierrez-Sagredo

The exact analytical solution in closed form of a modified SIR system where recovered individuals are removed from the population is presented. In this dynamical system the populations $S(t)$ and $R(t)$ of susceptible and recovered individuals are found to be generalized logistic functions, while infective ones $I(t)$ are given by a generalized logistic func

S. V. Doronkina, A. E. Myasnikova, A. H. Dzhantemirov, A. V. Lutsenko

Pseudogap in hole-doped cuprate superconductors is acknowledged as a possible key to understanding their ground normal state, however, existing pseudogap models have essential inconsistencies with experiments. In our approach pseudogap emerges due to impact of autolocalized carriers on stationary states of delocalized ones and topology of the 2D hole-like di

P. Elli Stamatopoulou, Vassilios Yannopapas, N. Asger Mortensen, Christos Tserkezis

We examine the far-field optical response, under-plane wave excitation in the presence of a static magnetic field, of core-shell nanoparticles involving a gyroelectric component, either as the inner or the outer layer, through analytic calculations based on appropriately extended Mie theory. We focus on absorption and scattering of light by bismuth-substitut

Antonio Elías, Raúl Jiménez, Joe Yukich

We propose an alternative to $k$-nearest neighbors for functional data whereby the approximating neighboring curves are piecewise functions built from a functional sample. Using a locally defined distance function that satisfies stabilization criteria, we establish pointwise and global approximation results in function spaces when the number of data curves i

Giacomo De Nicola, Marc Schneble, Göran Kauermann, Ursula Berger

Governments around the world continue to act to contain and mitigate the spread of COVID-19. The rapidly evolving situation compels officials and executives to continuously adapt policies and social distancing measures depending on the current state of the spread of the disease. In this context, it is crucial for policymakers to have a firm grasp on what the

Gaoyong Sun, Wen-Long You, Tao Zhou

Motivated by the experiment [St-Jean {\it et al}., Nature Photon. {\bf 11}, 651 (2017)] on topological phases with collective photon modes in a zigzag chain of polariton micropillars, we study spinless $p$-orbital fermions with local interorbital hoppings and repulsive interactions between $p_x$ and $p_y$ bands in zigzag optical lattices. We show that spinle

Effrosyni Simou, Dorina Thanou, Pascal Frossard

In order to perform network analysis tasks, representations that capture the most relevant information in the graph structure are needed. However, existing methods do not learn representations that can be interpreted in a straightforward way and that are robust to perturbations to the graph structure. In this work, we address these two limitations by proposi

Nannan Zou, Honglei Zhang, Francesco Cricri, Hamed R. Tavakoli

In this paper we present an end-to-end meta-learned system for image compression. Traditional machine learning based approaches to image compression train one or more neural network for generalization performance. However, at inference time, the encoder or the latent tensor output by the encoder can be optimized for each test image. This optimization can be

M. J. Calderón, E. Bascones

We calculate the interactions between the Wannier functions of the 8-orbital model for twisted bilayer graphene (TBG). In this model, two orbitals per valley centered at the AA regions, the AA-p orbitals, account for the most part of the spectral weight of the flats bands. Exchange and assisted-hopping terms between these orbitals are found to be small. Ther

Yu. E. Lozovik, I. L. Kurbakov, G. E. Astrakharchik, J. Boronat

We present an analytical method to estimate the condensate fraction $n_0/n$ in strongly correlated systems for which the zero-temperature static structure factor $S({\bf p})$ is known. The advantage of the proposed method is that it allows one to predict the long-range behavior of the one-body density matrix (i) in macroscopic and mesoscopic systems, (ii) in

Francesco Mambretti, Simone Molinelli, Davide Pini, Gianluca Bertaina

Soft matter systems are renowned for being able to display complex emerging phenomena such as clustering phases. Recently, a surprising quantum phase transition has been revealed in a one-dimensional (1D) system composed of bosons interacting via a pairwise soft potential in the continuum. It was shown that the spatial coordinates undergoing two-particle clu

Tong Xu, Wenchuan Wu, Yiwen Hong, Junjie Yu

For active distribution networks (ADNs) integrated with massive inverter-based energy resources, it is impractical to maintain the accurate model and deploy measurements at all nodes due to the large-scale of ADNs. Thus, current models of ADNs are usually involving significant errors or even unknown. Moreover, ADNs are usually partially observable since only

Tiago Andrade, Rafael Kelman, Tainá M. Cunha, Luiz Rodolpho de Albuquerque

Energy storage systems - in particular, Pumped Hydropower Storage (PHS) - will be increasingly important to support the transition of power systems toward zero emissions. The reason is that PHS can mitigate the variability and uncertainty of renewable energy production from solar and wind power to balance electricity demand with supply. In this paper, we pro

Anna Kauch, Paul Worm, Paul Prauhart, Michael Innerberger

We perform time-resolved exact diagonalization of the Hubbard model with time dependent hoppings on small clusters of up to $12$ sites. Here, the time dependence originates from a classic electromagnetic pulse, which mimics the impact of a photon. We investigate the behavior of the double occupation and spectral function after the pulse for different cluster

Joseph Bowles, Flavien Hirsch, Daniel Cavalcanti

Activation of Bell nonlocality refers to the phenomenon that some entangled mixed states that admit a local hidden variable model in the standard Bell scenario nevertheless reveal their nonlocal nature in more exotic measurement scenarios. We present such a scenario that involves broadcasting the local subsystems of a single-copy of a bipartite quantum state

Haowu Wang

The weak Jacobi forms of integral weight and integral index associated to an even positive definite lattice form a bigraded algebra. In this paper we prove a criterion for this type of algebra being free. As an application, we give an automorphic proof of K. Wirthmüller&#39;s theorem which asserts that the bigraded algebra of weak Jacobi forms invariant unde

Pierre-Michel Déjardin, Florian Pabst, Yann Cornaton, Cyril Caliot

An exact integral formula for the Kirkwood correlation factor of isotropic polar fluids $g_K$ is derived from the equilibrium averaged rotational Dean equation, which as compared to previous approaches easily lends itself to further approximations. The static linear permittivity of polar fluids $ε$ is calculated as a function of temperature, density and mole

Henrique N. Lengler

We investigate the applicability of the Method of Regularized Stokeslets (MRS) in the simulation of micro-swimmers at low Reynolds number. The chosen model for the study is the well-known three linked spheres swimmer. We compare our results with the lattice Boltzmann method, multiparticle collision dynamics, a numerical solution of the Oseen tensor equation

L. H. Gallardo, O. Rahavandrainy

We give necessary conditions satisfied by the set of odd prime divisors of binary perfect polynomials. This allows us to get a new characterization of all the known perfect binary polynomials.

Ander Movilla Miangolarra, Aléria Duperray-Susini, Mathieu Coppey, Michele Castellana

Protein aggregation is of particular interest due to its connection with many diseases and disorders. Many factors can alter the dynamics and result of this process, one of them being the diffusivity of the monomers and aggregates in the system. Here, we study experimentally and theoretically an aggregation process in cells, and we identify two distinct phys

Ning-An Lai, Nico Michele Schiavone

We study in this paper the small data Cauchy problem for the semilinear generalized Tricomi equations with a nonlinear term of derivative type $u_{tt}-t^{2m}Δu=|u_t|^p$ for $m\ge0$. Blow-up result and lifespan estimate from above are established for $1<p\le 1+\frac{2}{(m+1)(n-1)-m}$. If $m=0$, our results coincide with those of the semilinear wave equation.

Roberto Emparan, Antonia Micol Frassino, Benson Way

We study a holographic construction of quantum rotating BTZ black holes that incorporates the exact backreaction from strongly coupled quantum conformal fields. It is based on an exact four-dimensional solution for a black hole localized on a brane in AdS$_4$, first discussed some years ago but never fully investigated in this manner. Besides quantum CFT eff

Louis Sharrock, Nikolas Kantas

In this paper, we establish the almost sure convergence of two-timescale stochastic gradient descent algorithms in continuous time under general noise and stability conditions, extending well known results in discrete time. We analyse algorithms with additive noise and those with non-additive noise. In the non-additive case, our analysis is carried out under

Scott Davidson, Amir Fruchtman, Felix Pollock, Erik Gauger

We present a novel, counter-intuitive method, based on dark state protection, for significantly improving exciton transport efficiency through `wires&#39; comprising a chain of molecular sites with an intrinsic energy gradient. Specifically, by introducing `barriers&#39; to the energy landscape at regular intervals along the transport path, we find that unde

Sarah Friedrich, Tim Friede

The usual development cycles are too slow for the development of vaccines, diagnostics and treatments in pandemics such as the ongoing SARS-CoV-2 pandemic. Given the pressure in such a situation, there is a risk that findings of early clinical trials are overinterpreted despite their limitations in terms of size and design. Motivated by a non-randomized open

Jake Langham, Mark J. Woodhouse, Andrew J. Hogg, Jeremy C. Phillips

It is increasingly common for models of shallow-layer overland flows to include equations for the evolution of the underlying bed (morphodynamics) and the motion of an associated sedimentary phase. We investigate the linear stability properties of these systems in considerable generality. Naive formulations of the morphodynamics, featuring exchange of sedime

Nadine Stahl, Nicole Marheineke

In this paper we investigate the performance of projection-based low-rank approximations in Kalman filtering. For large-scale gas pipeline networks structure-preserving model order reduction has turned out to be an advantageous way to compute accurate solutions with much less computational effort. For state estimation we propose to combine these low-rank mod

B. Popescu Braileanu, V. S. Lukin, E. Khomenko, A. de Vicente

Solar prominences are formed by partially ionized plasma with inter-particle collision frequencies generally warranting magnetohydrodynamic treatment. In this work, we explore the dynamical impacts and observable signatures of two-fluid effects in the parameter regimes when ion-neutral collisions do not fully couple the neutral and charged fluids. We perform

Ioannis Kontoyiannis, Yi Heng Lim, Katia Papakonstantinopoulou, Wojtek Szpankowski

For various purposes and, in particular, in the context of data compression, a graph can be examined at three levels. Its structure can be described as the unlabeled version of the graph; then the labeling of its structure can be added; and finally, given then structure and labeling, the contents of the labels can be described. Determining the amount of info

Sean Dewar, Derek Kitson, Anthony Nixon

We present three results which support the conjecture that a graph is minimally rigid in $d$-dimensional $\ell_p$-space, where $p\in (1,\infty)$ and $p\not=2$, if and only if it is $(d,d)$-tight. Firstly, we introduce a graph bracing operation which preserves independence in the generic rigidity matroid when passing from $\ell_p^d$ to $\ell_p^{d+1}$. We then

Laurent Bétermin, Markus Faulhuber

We present two families of lattice theta functions accompanying the family of lattice theta functions studied by Montgomery in [H.~Montgomery. Minimal theta functions. \textit{Glasgow Mathematical Journal}, 30(1):75--85, 1988]. The studied theta functions are generalizations of the Jacobi theta-2 and theta-4 functions. Contrary to Montgomery&#39;s result, we

Madhuri Latha Mannedu, Sai Krishna Charan Dara, Sachin Chaudhari, Neeraj Varshney

In this paper, we propose beamformed energy detection (BFED) spectrum sensing schemes for a single secondary user (SU) or a cognitive radio to detect a primary user (PU) transmission in the presence of an interferer. In the millimeter wave (mmWave) band, due to high attenuation, there are fewer multipaths, and the channel is sparse, giving rise to fewer dire

Naoki Matsui

We consider a mass critical nonlinear Schrödinger equation with a real-valued potential. In this work, we construct a minimal mass solution that blows up at finite time, under weaker assumptions on spatial dimensions and potentials than Banica, Carles, and Duyckaerts (2011). Moreover, we show that the blow-up solution converges to a blow-up profile. Furtherm

Daniela di Serafino, Nataša Krejić, Nataša Krklec Jerinkić, Marco Viola

We develop a line-search second-order algorithmic framework for minimizing finite sums. We do not make any convexity assumptions, but require the terms of the sum to be continuously differentiable and have Lipschitz-continuous gradients. The methods fitting into this framework combine line searches and suitably decaying step lengths. A key issue is a two-ste

Howard Georgi

I discuss the 2-flavor Schwinger model both without and with fermion masses. I argue that the concept of &#34;conformal coalescence,&#34; in unparticle physics in which linear combinations of short distance operators can disappear from the long-distance theory, makes it easy to understand some puzzling features of the model with small fermion masses. In part

Le Zhang, Ryutaro Tanno, Mou-Cheng Xu, Chen Jin

Recent years have seen increasing use of supervised learning methods for segmentation tasks. However, the predictive performance of these algorithms depends on the quality of labels. This problem is particularly pertinent in the medical image domain, where both the annotation cost and inter-observer variability are high. In a typical label acquisition proces

Xiangpeng Wei, Rongxiang Weng, Yue Hu, Luxi Xing

Recent studies have demonstrated the overwhelming advantage of cross-lingual pre-trained models (PTMs), such as multilingual BERT and XLM, on cross-lingual NLP tasks. However, existing approaches essentially capture the co-occurrence among tokens through involving the masked language model (MLM) objective with token-level cross entropy. In this work, we exte

Weitao Xu, Junqing Zhang, Shunqi Huang, Chengwen Luo

Key generation is a promising technique to bootstrap secure communications for the Internet of Things (IoT) devices that have no prior knowledge between each other. In the past few years, a variety of key generation protocols and systems have been proposed. In this survey, we review and categorise recent key generation systems based on a novel taxonomy. Then

Evgeny V. Anikin, Dmitry A. Chermoshentsev, Sergey A. Dyakov, Nikolay A. Gippius

We study Dyakonov surface waveguide modes in a waveguide represented by an interface of two anisotropic media confined between two air half-spaces. We analyze such modes in terms of perturbation theory in the approximation of weak anisotropy. We show that in contrast to conventional Dyakonov surface waves that decay monotonically with distance from the inter

Brian Kenji Iwana, Seiichi Uchida

In recent times, deep artificial neural networks have achieved many successes in pattern recognition. Part of this success can be attributed to the reliance on big data to increase generalization. However, in the field of time series recognition, many datasets are often very small. One method of addressing this problem is through the use of data augmentation

Takayuki Nishiyama, Atsuto Seko, Isao Tanaka

Accurate interatomic potentials are in high demand for large-scale atomistic simulations of materials that are prohibitively expensive by density functional theory (DFT) calculation. In this study, we apply machine learning potentials in a recently constructed repository to the prediction of the grain boundary energy in face-centered-cubic elemental metals,

Purba Mukherjee, Narayan Banerjee

The cosmic deceleration parameter $q$ has been reconstructed in a non-parametric way using various combinations of recent observational datasets. The Pantheon compilation of the Supernova (SN) distance modulus data, the Cosmic Chronometer (CC) measurements of the Hubble parameter including the full systematics and the Baryon Acoustic Oscillation (BAO) data h

David Juher, David Rojas, Joan Saldaña

This paper is concerned with the robustness of the sustained oscillations predicted by an epidemic ODE model defined on contact networks. The model incorporates the spread of awareness among individuals and, moreover, a small inflow of imported cases. These cases prevent stochastic extinctions when we simulate the epidemics and, hence, they allow to check wh

Sergey Brener, Evgeny A. Stepanov, Alexey N. Rubtsov, Mikhail I. Katsnelson

We present a purely diagrammatic derivation of the dual fermion scheme [Phys. Rev. B 77 (2008) 033101]. The derivation makes particularly clear that a similar scheme can be developed for an arbitrary reference system provided it has the same interaction term as the original system. Thereby no restrictions are imposed by the locality of the reference problem

Marina Khismatullina, Michael Vogt

The COVID-19 pandemic is one of the most pressing issues at present. A question which is particularly important for governments and policy makers is the following: Does the virus spread in the same way in different countries? Or are there significant differences in the development of the epidemic? In this paper, we devise new inference methods that allow to

José Lopes, Thomas Lacroix, Ilídio Lopes

Dark matter (DM) capture in stars offers a rich phenomenology that makes it possible to probe a wide variety of particle DM scenarios in diverse astrophysical environments. In spite of decades of improvements to refine predictions of capture-related observables and better quantify astrophysical and particle-physics uncertainties, the actual impact of the Gal

Ziyi Guo, Lars Bathe-Peters, Shaomin Chen, Mourad Chouaki

China Jinping Underground Laboratory (CJPL) is ideal for studying solar-, geo-, and supernova neutrinos. A precise measurement of the cosmic-ray background would play an essential role in proceeding with the R\&D research for these MeV-scale neutrino experiments. Using a 1-ton prototype detector for the Jinping Neutrino Experiment (JNE), we detected 264 high

Jeff M. Phillips, Hasan Pourmahmood-Aghababa

We introduce an orientation-preserving landmark-based distance for continuous curves, which can be viewed as an alternative to the \Frechet or Dynamic Time Warping distances. This measure retains many of the properties of those measures, and we prove some relations, but can be interpreted as a Euclidean distance in a particular vector space. Hence it is sign

Brecht Donvil, Dmitry Golubev, Paolo Muratore-Ginanneschi

Calorimetric measurements are experimentally realizable methods to assess thermodynamics relations in quantum devices. With this motivation in mind, we consider a resonant level coupled to a Fermion reservoir. We consider a transient process, in which the interaction between the level and the reservoir is initially switched on and then switched off again. We

Jeandré Boshoff, Adriana Roux

The localization game is played by two players: a Cop with a team of $k$ cops, and a Robber. The game is initialised by the Robber choosing a vertex $r \in V$, unknown to the Cop. Thereafter, the game proceeds turn based. At the start of each turn, the Cop probes $k$ vertices and in return receives a distance vector. If the Cop can determine the exact locati

Jan Philipp Thoma, Jakob Feldtkeller, Markus Krausz, Tim Güneysu

Recent research has revealed an ever-growing class of microarchitectural attacks that exploit speculative execution, a standard feature in modern processors. Proposed and deployed countermeasures involve a variety of compiler updates, firmware updates, and hardware updates. None of the deployed countermeasures have convincing security arguments, and many of

Noriaki Ikeda, Thomas Strobl

The BFV formulation of a given gauge theory is usually significantly easier to obtain than its BV formulation. Grigoriev and Damgaard introduced simple formulas for obtaining the latter from the former. Since BFV relies on the Hamiltonian version of the gauge theory, however, it does not come as a surprise that in general the resulting BV theory does not exh

Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek

Artificial intelligence (AI) has huge potential to improve the health and well-being of people, but adoption in clinical practice is still limited. Lack of transparency is identified as one of the main barriers to implementation, as clinicians should be confident the AI system can be trusted. Explainable AI has the potential to overcome this issue and can be

F. Mernier, E. Cucchetti, L. Tornatore, V. Biffi

The chemical enrichment of the Universe at all scales is related to stellar winds and explosive supernovae phenomena. Metals produced by stars and later spread at the mega-parsec scale through the intra-cluster medium (ICM) become a fossil record of the chemical enrichment of the Universe and of the dynamical and feedback mechanisms determining their circula

Simone Raponi, Javier Hernandez, Aymen Omri, Gabriele Oligeri

Noise modeling in power line communications has recently drawn the attention of researchers. However, when characterizing the noise process in narrowband communications, previous works have only focused on small-scale phenomena involving fine-grained details. Nevertheless, the communication link&#39;s reliability is also affected by long-term noise phenomena

Samuel Mañas-Valero, Benjamin Huddart, Tom Lancaster, Eugenio Coronado

Quantum materials exhibiting magnetic frustration are connected to diverse phenomena including high-Tc superconductivity, topological order and quantum spin liquids (QSLs). A QSL is a quantum phase (QP) related to a quantum-entangled fluid-like state of matter. Previous experiments on QSL candidate materials are usually interpreted in terms of a single QP, a

François Monard, Richard Nickl, Gabriel P. Paternain

Bayesian inference and uncertainty quantification in a general class of non-linear inverse regression models is considered. Analytic conditions on the regression model $\{\mathscr G(θ): θ\in Θ\}$ and on Gaussian process priors for $θ$ are provided such that semi-parametrically efficient inference is possible for a large class of linear functionals of $θ$. A

Jesús Álvarez López, Peter Gilkey

We introduce a Witten-Novikov type perturbation $\bar\partial_{\barω}$ of the Dolbeault complex of any complex Kähler manifold, defined by a form $ω$ of type $(1,0)$ with $\partialω=0$. We give an explicit description of the associated index density which shows that it exhibits a nontrivial dependence on $ω$. The heat invariants of lower order are shown to b

Ming Xu, Vladimir S. Matveev

For a smooth strongly convex Minkowski norm $F:\mathbb{R}^n \to \mathbb{R}_{\geq0}$, we study isometries of the Hessian metric corresponding to the function $E=\tfrac12F^2$. Under the additional assumption that $F$ is invariant with respect to the standard action of $SO(k)\times SO(n-k)$, we prove a conjecture of Laugwitz stated in 1965. Further, we describe

Yu-Biao Wu, Guang-Can Guo, Zhen Zheng, Xu-Bo Zou

Higher-order topological superfluids have gapped bulk and symmetry-protected Majorana zero modes with various localizations. Motivated by recent advances, we present a proposal for synthesizing multi-order topological superfluids that support various Majorana zero modes in ultracold atomic gases. For this purpose, we use the two-dimensional optical superlatt

Johannes Schmidt-Hieber

There is a longstanding debate whether the Kolmogorov-Arnold representation theorem can explain the use of more than one hidden layer in neural networks. The Kolmogorov-Arnold representation decomposes a multivariate function into an interior and an outer function and therefore has indeed a similar structure as a neural network with two hidden layers. But th

Xu Sun, Huihui Fang, Yehui Yang, Dongwei Zhu

Retinal vessel segmentation is a fundamental step in screening, diagnosis, and treatment of various cardiovascular and ophthalmic diseases. Robustness is one of the most critical requirements for practical utilization, since the test images may be captured using different fundus cameras, or be affected by various pathological changes. We investigate this pro

Pawel Szalachowski

Password-authenticated identities, where users establish username-password pairs with individual servers and use them later on for authentication, is the most widespread user authentication method over the Internet. Although they are simple, user-friendly, and broadly adopted, they offer insecure authentication and position server operators as trusted partie

Zhi-Tao Lu, Han-Yu Jiang, Jun He

Recently, a hint for dibaryon $NΔ(D_{21})$ was observed at WASA-AT-COSY with a mass about $30\pm10$ MeV below the $NΔ$ threshold. It has a relatively small binding energy compared with the $d^*(2380)$ and a width close to the width of the $Δ$ baryon, which suggests that it may be a dibaryon in a molecular state picture. In this work, we study the possible $S

Federico Centrone, Niraj Kumar, Eleni Diamanti, Iordanis Kerenidis

In recent years, many computational tasks have been proposed as candidates for showing a quantum computational advantage, that is an advantage in the time needed to perform the task using a quantum instead of a classical machine. Nevertheless, practical demonstrations of such an advantage remain particularly challenging because of the difficulty in bringing

Volker Mayer, Mariusz Urbanski

This text provides an overview of the (geometric) thermodynamic formalism for transcendental meromorphic and entire functions with particular emphasis on geometric/fractal aspects such as Bowen&#39;s Formula expressing the hyperbolic dimension as a unique zero of a pressure function and the behavior of the latter when the transcendental functions vary in an

Flavio Romano, John Russo, Lukáš Kroc, Petr Šulc

One of the fundamental goals of nanotechnology is to exploit selective and directional interactions between molecules to design particles that self-assemble into desired structures, from capsids, to nano-clusters, to fully formed crystals with target properties (e.g. optical, mechanical, etc.). Here we provide a general framework which transforms the inverse

Hiroyuki Fuji, Kohei Iwaki, Hitoshi Murakami, Yuji Terashima

In this paper, for a Seifert loop (i.e., a knot in a Seifert three-manifold), first we give a family of an explicit function $Φ(q; N)$ whose special values at roots of unity are identified with the Witten-Reshetikhin-Turaev invariants of the Seifert loop for the integral homology sphere. Second, we show that the function $Φ(q; N)$ satisfies a $q$-difference

Jianyuan Yin, Kai Jiang, An-Chang Shi, Pingwen Zhang

Due to structural incommensurability, the emergence of a quasicrystal from a crystalline phase represents a challenge to computational physics. Here the nucleation of quasicrystals is investigated by using an efficient computational method applied to a Landau free-energy functional. Specifically, transition pathways connecting different local minima of the L

Alan F. T. Winfield, Katie Winkle

Risk Assessment is a well known and powerful method for discovering and mitigating risks, and hence improving safety. Ethical Risk Assessment uses the same approach but extends the envelope of risk to cover ethical risks in addition to safety risks. In this paper we outline Ethical Risk Assessment (ERA) and set ERA within the broader framework of Responsible

Niharika Gauraha

High-dimensional state trajectories of state-space models pose challenges for Bayesian inference. Particle Gibbs (PG) methods have been widely used to sample from the posterior of a state space model. Basically, particle Gibbs is a Particle Markov Chain Monte Carlo (PMCMC) algorithm that mimics the Gibbs sampler by drawing model parameters and states from th

Yichen Shen, Zhilu Zhang, Mert R. Sabuncu, Lin Sun

Calibrated estimates of uncertainty are critical for many real-world computer vision applications of deep learning. While there are several widely-used uncertainty estimation methods, dropout inference stands out for its simplicity and efficacy. This technique, however, requires multiple forward passes through the network during inference and therefore can b

Teppei Suzuki, Keisuke Ozawa, Yusuke Sekikawa

PointNet, which is the widely used point-wise embedding method and known as a universal approximator for continuous set functions, can process one million points per second. Nevertheless, real-time inference for the recent development of high-performing sensors is still challenging with existing neural network-based methods, including PointNet. In ordinary c

Daniel Leykam, Ekaterina Smolina, Aleksandra Maluckov, Sergej Flach

We analyze the modulational instability of nonlinear Bloch waves in topological photonic lattices. In the initial phase of the instability development captured by the linear stability analysis, long wavelength instabilities and bifurcations of the nonlinear Bloch waves are sensitive to topological band inversions. At longer timescales, nonlinear wave mixing

Sohaib Ahmad, Christopher Geiger, Benjamin Fuller

Iris recognition systems transform an iris image into a feature vector. The seminal pipeline segments an image into iris and non-iris pixels, normalizes this region into a fixed-dimension rectangle, and extracts features which are stored and called a template (Daugman, 2009). This template is stored on a system. A future reading of an iris can be transformed

Govinda Anantha Padmanabha, Nicholas Zabaras

Inverse modeling for computing a high-dimensional spatially-varying property field from indirect sparse and noisy observations is a challenging problem. This is due to the complex physical system of interest often expressed in the form of multiscale PDEs, the high-dimensionality of the spatial property of interest, and the incomplete and noisy nature of obse

Syed Hasib Akhter Faruqui, Adel Alaeddini, Jing Wang, Carlos A. Jaramillo

Bayesian networks are powerful statistical models to study the probabilistic relationships among set random variables with major applications in disease modeling and prediction. Here, we propose a continuous time Bayesian network with conditional dependencies, represented as Poisson regression, to model the impact of exogenous variables on the conditional de

Masashi Wakaiki

Suppose that a continuous-time linear infinite-dimensional system with a static state-feedback controller is strongly stable. We address the following question: If we convert the continuous-time controller to a sampled-data controller by applying an idealized sampler and a zero-order hold, will the resulting sampled-data system be strongly stable for all suf

Harshal D. Kaushik, Farzad Yousefian

We consider a class of optimization problems with Cartesian variational inequality (CVI) constraints, where the objective function is convex and the CVI is associated with a monotone mapping and a convex Cartesian product set. This mathematical formulation captures a wide range of optimization problems including those complicated by the presence of equilibri

Agustina G. Magnoni, Laura T. Knoll, Miguel A. Larotonda

A promising result from optical quantum metrology is the ability to achieve sub-shot-noise performance in transmission or absorption measurements. This is due to the significantly lower uncertainty in light intensity of quantum beams with respect to their classical counterparts. In this work, we simulate the outcome of an experiment that uses a multiplexed s

Zhao Zhang, Yan Zhang, Mingliang Xu, Li Zhang

The quality of learned features by representation learning determines the performance of learning algorithms and the related application tasks (such as high-dimensional data clustering). As a relatively new paradigm for representation learning, Concept Factorization (CF) has attracted a great deal of interests in the areas of machine learning and data mining

Samuel B. Hopkins, Jerry Li, Fred Zhang

We study the problem of estimating the mean of a distribution in high dimensions when either the samples are adversarially corrupted or the distribution is heavy-tailed. Recent developments in robust statistics have established efficient and (near) optimal procedures for both settings. However, the algorithms developed on each side tend to be sophisticated a