June 2019 arXiv papers — page 41

Francesco Capozzi, Georg Raffelt, Tobias Stirner

In an interacting neutrino gas, flavor coherence becomes dynamical and can propagate as a collective mode. In particular, tachyonic instabilities can appear, leading to "fast flavor conversion" that is independent of neutrino masses and mixing angles. On the other hand, without neutrino-neutrino interaction, a prepared wave packet of flavor coherence

Sergei O. Ivanov, Roman Mikhailov, Fedor Pavutnitskiy

For a strongly connected category $\mathcal C$ with pair-wise coproducts, we introduce a cosimplicial object, which serves as a sort of resolution for computing higher derived functors of ${\sf lim} : \mathrm{Ab}^{\mathcal C}\to \mathrm{Ab}$. Applications involve K\"unneth theorem for higher limits and ${\sf lim}$-finiteness of ${\bf fr}$-codes. A dictionary

Trung Dac Nguyen, Monica Olvera de la Cruz

We demonstrate that a highly charged polyelectrolyte confined in a spherical cavity undergoes reversible transformations between amorphous conformations to a four-fold symmetry morphology as a function of dielectric mismatch between the media inside and outside the cavity. Surface polarization due to dielectric mismatch exhibits an extra "confinement&#34

Antonio Michele Miti, Leonid Ryvkin

We investigate the existence of homotopy comoment maps (comoments) for high-dimensional spheres seen as multisymplectic manifolds. Especially, we solve the existence problem for compact effective group actions on spheres and provide explicit constructions for such comoments in interesting particular cases.

Maria Okounkova, Leo C. Stein, Mark A. Scheel, Saul A. Teukolsky

We produce the first numerical relativity binary black hole gravitational waveforms in a higher-curvature theory beyond general relativity. In particular, we study head-on collisions of binary black holes in order-reduced dynamical Chern-Simons gravity. This is a precursor to producing beyond-general-relativity waveforms for inspiraling binary black hole sys

David Vartanyan, Adam Burrows, David Radice

We provide the time series and angular distributions of the neutrino and gravitational-wave emissions of eleven state-of-the-art three-dimensional non-rotating core-collapse supernova models and explore correlations between these signatures and the real-time dynamics of the shock and the proto-neutron-star core. The neutrino emissions are roughly isotropic o

Kyle Aitken, Andrew Baumgartner, Changha Choi, Andreas Karch

We extend the recently proposed symmetry breaking scenario of QCD$_3$ to the so-called "master" $(2+1)$d bosonization duality, which has bosonic and fermionic matter on both ends. Using anomaly arguments, a phase diagram emerges with several novel regions. We then construct $2+1$ dimensional dualities for flavored quivers using node-by-node dualization. Such

Matthew C. Chan, John P. Stott

We introduce Deep-CEE (Deep Learning for Galaxy Cluster Extraction and Evaluation), a proof of concept for a novel deep learning technique, applied directly to wide-field colour imaging to search for galaxy clusters, without the need for photometric catalogues. This technique is complementary to traditional methods and could also be used in combination with

Xizhi Han, Sean A. Hartnoll

We employ machine learning techniques to provide accurate variational wavefunctions for matrix quantum mechanics, with multiple bosonic and fermionic matrices. Variational quantum Monte Carlo is implemented with deep generative flows to search for gauge invariant low energy states. The ground state, and also long-lived metastable states, of an $\mathrm{SU}(N

Tassadaq Nawaz, Marco Seminara, Stefano Caputo, Lorenzo Mucchi

The integration of Visible-Light Communications technology (VLC) in Intelligent Transportation Systems (ITS) is a very promising platform for a cost-effective implementation of revolutionary ITS and cooperative ITS protocols. In this paper, we propose an infrastructure-to-vehicle-to-vehicle (I2V2V) VLC system for ITS, implementing it through a regular LED tr

Pere Giménez-Febrer, Alba Pagès-Zamora, Georgios B. Giannakis

Prior information can be incorporated in matrix completion to improve estimation accuracy and extrapolate the missing entries. Reproducing kernel Hilbert spaces provide tools to leverage the said prior information, and derive more reliable algorithms. This paper analyzes the generalization error of such approaches, and presents numerical tests confirming the

Callum R. Brodie, Andrei Constantin, Rehan Deen, Andre Lukas

We conjecture and prove closed-form index expressions for the cohomology dimensions of line bundles on del Pezzo and Hirzebruch surfaces. Further, for all compact toric surfaces we provide a simple algorithm which allows expression of any line bundle cohomology in terms of an index. These formulae follow from general theorems we prove for a wider class of su

Motoi Endo, Wen Yin

We propose a SUSY scenario to explain the current electron and muon $g-2$ discrepancies without introducing lepton flavor mixings. Threshold corrections to the Yukawa couplings can enhance the electron $g-2$ and flip the sign of the SUSY contributions. The mechanism predicts a flavor-dependent slepton mass spectrum. We show that it is compatible with the Hig

Thomas E. Gartmann, Loren Ban, Bruce L. Yoder, Sebastian Hartweg

We have investigated the solvation dynamics and the genuine binding energy and photoemission anisotropy of the solvated electron in neutral water clusters with a combination of time-resolved photoelectron velocity map imaging and electron scattering simulations. The dynamics was probed with a UV probe pulse following above-band-gap excitation with a EUV pump

Cesar Damian, Oscar Loaiza-Brito

In this note, we present a scenario in which the existence of dS vacua is jeopardized by topological transitions between non-BPS branes and fluxes in type IIB toroidal compactifications. We focus our study on a six-dimensional torus compactification modded out by an orientifold three-plane. In particular, we consider the presence of non-BPS five branes, whic

Qiuxia Lai, Salman Khan, Yongwei Nie, Jianbing Shen

Human visual system can selectively attend to parts of a scene for quick perception, a biological mechanism known as Human attention. Inspired by this, recent deep learning models encode attention mechanisms to focus on the most task-relevant parts of the input signal for further processing, which is called Machine/Neural/Artificial attention. Understanding

Rihuan Ke, Aurélie Bugeau, Nicolas Papadakis, Peter Schuetz

The need for labour intensive pixel-wise annotation is a major limitation of many fully supervised learning methods for segmenting bioimages that can contain numerous object instances with thin separations. In this paper, we introduce a deep convolutional neural network for microscopy image segmentation. Annotation issues are circumvented by letting the netw

Gauri Jagatap, Chinmay Hegde

Deep neural networks as image priors have been recently introduced for problems such as denoising, super-resolution and inpainting with promising performance gains over hand-crafted image priors such as sparsity and low-rank. Unlike learned generative priors they do not require any training over large datasets. However, few theoretical guarantees exist in th

Emanuel Gallo, Thomas Mädler

We discuss a recently presented boosted Kerr black hole solution which had already been used by other authors. This boosted metric is based on wrong assumptions regarding asymptotic inertial observers and moreover the performed boost is not a proper Lorentz transformation. This note aims to clarify some of the issues when boosting black holes and the necessa

Giulio Fabbian, Antony Lewis, Dominic Beck

The cross-correlation between cosmic microwave background (CMB) gravitational lensing and large-scale structure tracers will be an important cosmological probe in the coming years. Quadratic estimators provide a simple and powerful (if suboptimal) way to reconstruct the CMB lensing potential and are widely used. For Gaussian fields, the cross-correlation of

Florian Beutler, Matteo Biagetti, Daniel Green, Anže Slosar

Sharp features in the primordial power spectrum are a powerful window into the inflationary epoch. To date, the cosmic microwave background (CMB) has offered the most sensitive avenue to search for these signatures. In this paper, we demonstrate the power of large-scale structure observations to surpass the CMB as a probe of primordial features. We show that

Ruben J Tomlin, Radu Cimpeanu, Demetrios T Papageorgiou

We consider the gravity-driven flow of a perfect dielectric, viscous, thin liquid film, wetting a flat substrate inclined at a non-zero angle to the horizontal. The dynamics of the thin film is influenced by an electric field which is set up parallel to the substrate surface - this nonlocal physical mechanism has a linearly stabilizing effect on the interfac

C van Zyl, F Lombard

We develop Shiryaev-Roberts schemes based on signed sequential ranks to detect a persistent change in location of a continuous symmetric distribution with known median. The in-control properties of these schemes are distribution free, hence they do not require a parametric specification of an underlying density function or the existence of any moments. Table

Ferdia Sherry, Martin Benning, Juan Carlos De los Reyes, Martin J. Graves

The discovery of the theory of compressed sensing brought the realisation that many inverse problems can be solved even when measurements are "incomplete". This is particularly interesting in magnetic resonance imaging (MRI), where long acquisition times can limit its use. In this work, we consider the problem of learning a sparse sampling pattern that can b

Matthias Schötz

The classical Gelfand--Naimark theorems provide important insight into the structure of general and of commutative C*-algebras. It is shown that these can be generalized to certain ordered *-algebras. More precisely, for $\sigma$-bounded closed ordered *-algebras a faithful representation as operators is constructed. Similarly, for commutative such algebras,

Netan Dogra, Samuel Le Fourn

In this paper, we provide refined sufficient conditions for the quadratic Chabauty method to produce a finite set of points, with the conditions on the rank of the Jacobian replaced by conditions on the rank of a quotient of the Jacobian plus an associated space of Chow-Heegner points. We then apply this condition to prove the finiteness of this set for any

Ye Li, Bing Zhang, Kentaro Nagamine, Jingjing Shi

We search for host galaxy candidates of nearby fast radio bursts (FRBs), FRB 180729.J1316+55, FRB 171020, FRB 171213, FRB 180810.J1159+83, and FRB 180814.J0422+73 (the second repeating FRB). We compare the absolute magnitudes and the expected host dispersion measure $\rm DM_{host}$ of these candidates with that of the first repeating FRB, FRB 121102, as well

Cristian Barrera-Hinojosa, Domenico Sapone

We study the imprints of an effective dark energy fluid in the large scale structure of the universe through the observed angular power spectrum of galaxies in the relativistic regime. We adopt the phenomenological approach that introduces two parameters $\{Q,\eta\}$ at the level of linear perturbations and allow to take into account the modified clustering

Le Thanh Nguyen-Meidine, Eric Granger, Madhu Kiran, Louis-Antoine Blais-Morin

Although deep neural networks (NNs) have achievedstate-of-the-art accuracy in many visual recognition tasks,the growing computational complexity and energy con-sumption of networks remains an issue, especially for ap-plications on platforms with limited resources and requir-ing real-time processing. Filter pruning techniques haverecently shown promising resu

Keting Cen, Huawei Shen, Jinhua Gao, Qi Cao

Attributed network embedding aims to learn low-dimensional node representations from both network structure and node attributes. Existing methods can be categorized into two groups: (1) the first group learns two separated node representations from network structure and node attribute respectively and concatenates them together; (2) the other group obtains n

Rajan Amit Mehta, Ruoqi Zhang

We give a characterization, in terms of simplicial sets, of Frobenius objects in the category of relations. This result generalizes a result of Heunen, Contreras, and Cattaneo showing that special dagger Frobenius objects in the category of relations are in correspondence with groupoids. As an additional example, we construct a Frobenius object in the catego

Roberto Tauraso

Let $p$ be a prime and let $x$ be a $p$-adic integer. We provide two supercongruences for truncated series of the form $$\sum_{k=1}^{p-1} \frac{(x)_k}{(1)_k}\cdot \frac{1}{k}\sum_{1\le j_1\le\cdots\le j_r\le k}\frac{1}{j_1^{}\cdots j_r^{}}\quad\mbox{and}\quad \sum_{k=1}^{p-1} \frac{(x)_k(1-x)_k}{(1)_k^2}\cdot \frac{1}{k}\sum_{1\le j_1\le\cdots\le j_r\le k}\f

Kota Murakami

For a symmetrizable GCM $C$ and its symmetrizer $D$, Geiss-Leclerc-Schr\"oer [Invent. Math. 209 (2017)] has introduced a generalized preprojective algebra $\Pi$ associated to $C$ and $D$, that contains a class of modules, called locally free modules. We show that any basic support $\tau$-tilting $\Pi$-module is locally free and gives a classification theorem

Olivia Caramello

We systematically investigate morphisms and equivalences of toposes from multiple points of view. We establish a dual adjunction between morphisms and comorphisms of sites, introduce the notion of weak morphism of toposes and characterize the functors which induce such morphisms. In particular, we examine continuous comorphism of sites and show that this cla

Chuanlai. Liu, Pratheek. Shanthraj, Joseph. Robson, Martin. Diehl

Although magnesium alloys deform extensively through shear strains and crystallographic re-orientations associated with the growth of twins, little is known about the strengthening mechanisms associated with this deformation mode. A crystal plasticity based phase field model for twinning is employed in this work to study the strengthening mechanisms resultin

Carlos Cardona

The bulk point singularity limit of conformal correlation functions in Lorentzian signature acts as a microscope to look into local bulk physics in AdS. From it we can extract flat space scattering processes localized in AdS that ultimate should be related to corresponding observables on the conformal field theory at the boundary. In this paper we use this i

Shuchi Chawla, Christina Ilvento, Meena Jagadeesan

Fairness in advertising is a topic of particular concern motivated by theoretical and empirical observations in both the computer science and economics literature. We examine the problem of fairness in advertising for general purpose platforms that service advertisers from many different categories. First, we propose inter-category and intra-category fairnes

Sandro Stucki, César Sánchez, Gerardo Schneider, Borzoo Bonakdarpour

Many important system properties, particularly in security and privacy, cannot be verified statically. Therefore, runtime verification is an appealing alternative. Logics for hyperproperties, such as HyperLTL, support a rich set of such properties. We first show that black-box monitoring of HyperLTL is in general unfeasible, and suggest a gray-box approach.

Callum R. Brodie, Andrei Constantin, Rehan Deen, Andre Lukas

We investigate different approaches to machine learning of line bundle cohomology on complex surfaces as well as on Calabi-Yau three-folds. Standard function learning based on simple fully connected networks with logistic sigmoids is reviewed and its main features and shortcomings are discussed. It has been observed recently that line bundle cohomology can b

Sokratia Georgaka, Giovanni Stabile, Kelbij Star, Gianluigi Rozza

A parametric, hybrid reduced order model approach based on the Proper Orthogonal Decomposition with both Galerkin projection and interpolation based on Radial Basis Functions method is presented. This method is tested against a case of turbulent non-isothermal mixing in a T-junction pipe, a common ow arrangement found in nuclear reactor cooling systems. The

Ali Seiphoori, Xiao-guang Ma, Paulo E. Arratia, Douglas J. Jerolmack

When a colloidal suspension is dried, capillary pressure may overwhelm repulsive electrostatic forces, assembling aggregates that are out of thermal equilibrium. This poorly understood process confers cohesive strength to many geological and industrial materials. Here we observe evaporation-driven aggregation of natural and synthesized particulates, probe th

Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu

We study the question of how to aggregate controllers for dynamical systems in order to improve their performance. To this end, we propose a framework of boosting for online control. Our main result is an efficient boosting algorithm that combines weak controllers into a provably more accurate one. Empirical evaluation on a host of control settings supports

P. Lira, R. W. Goosmann, M. Kishimoto, R. Cartier

Using the STOKES Monte Carlo radiative transfer code we revisit the predictions of the spectropolarimetric signal from a disc-like Broad Emission Line Region (BLR) in Type I AGN due to equatorial scattering. We reproduce the findings of previous works, but only for a scatterer which is much more optically and geometrically thick than previously proposed. We

Murat Özer

We first present the salient features of the gravitational time dilation and redshift effects in two ways; by considering the oscillation frequencies/rates of clocks at different heights/potentials and by considering the photons emitted by these clocks such as atoms/nuclei. We then point out to the extension of these gravitational effects to static electrici

Komla Domelevo, Stefanie Petermichl, Kristina Ana Škreb

We prove failure of the natural formulation of a matrix weighted bilinear Carleson embedding theorem, featuring a matrix valued Carleson sequence as well as products of norms for the embedding. We show that assuming an A2 weight is also not sufficient. Indeed, a uniform bound on the conditioning number of the matrix weight is necessary and sufficient to get

Mehmet Yamac, Mete Ahishali, Nikolaos Passalis, Jenni Raitoharju

Security monitoring via ubiquitous cameras and their more extended in intelligent buildings stand to gain from advances in signal processing and machine learning. While these innovative and ground-breaking applications can be considered as a boon, at the same time they raise significant privacy concerns. In fact, recent GDPR (General Data Protection Regulati

Jinkai Li

In this paper, we consider the Cauchy problem to the heat conductive compressible Navier-Stokes equations in the presence of vacuum and with vacuum far field. Global well-posedness of strong solutions is established under the assumption, among some other regularity and compatibility conditions, that the scaling invariant quantity $\|\rho_0\|_\infty(\|\rho_0\

Yutai Hou, Zhihan Zhou, Yijia Liu, Ning Wang

While few-shot classification has been widely explored with similarity based methods, few-shot sequence labeling poses a unique challenge as it also calls for modeling the label dependencies. To consider both the item similarity and label dependency, we propose to leverage the conditional random fields (CRFs) in few-shot sequence labeling. It calculates emis

Mikkel V. Larsen, Xueshi Guo, Casper R. Breum, Jonas S. Neergaard-Nielsen

Measurement-based quantum computation offers exponential computational speed-up via simple measurements on a large entangled cluster state. We propose and demonstrate a scalable scheme for the generation of photonic cluster states suitable for universal measurement-based quantum computation. We exploit temporal multiplexing of squeezed light modes, delay loo

Samuel Lensgraf, Karim Itani, Yinan Zhang, Zezhou Sun

This paper presents a method of computing free motions of a planar assembly of rigid bodies connected by loose joints. Joints are modeled using local distance constraints, which are then linearized with respect to configuration space velocities, yielding a linear programming formulation that allows analysis of systems with thousands of rigid bodies. Potentia

Brandon Amos, Vladlen Koltun, J. Zico Kolter

We propose the Limited Multi-Label (LML) projection layer as a new primitive operation for end-to-end learning systems. The LML layer provides a probabilistic way of modeling multi-label predictions limited to having exactly k labels. We derive efficient forward and backward passes for this layer and show how the layer can be used to optimize the top-k recal

M. A. Raj, E. Iodice, N. R. Napolitano, M. Spavone

We present the study of a magnitude limited sample (mB < 16.6 mag) of 13 late type galaxies (LTGs), observed inside the virial radius, Rvir 0.7 Mpc, of the Fornax cluster within the Fornax Deep Survey (FDS). The main objective is to use surface brightness (SB) profiles and g-i colour maps to obtain information on the internal structure of these galaxies and

Weichao Yu, Jin Lan, Jiang Xiao

Spin wave, the precession of magnetic order in magnetic materials, is a collective excitation that carries spin angular momentum. Similar to the acoustic or optical waves, the spin wave also possesses the polarization degree of freedom. Although such polarization degrees of freedom are frozen in ferromagnets, they are fully unlocked in antiferromagnets or fe

J. Kocz, V. Ravi, M. Catha, L. D&#39;Addario

The Deep Synoptic Array 10 dish prototype is an instrument designed to detect and localise fast radio bursts with arcsecond accuracy in real time. Deployed at Owens Valley Radio Observatory, it consists of ten 4.5m diameter dishes, equipped with a 250MHz bandwidth dual polarisation receiver, centered at 1.4GHz. The 20 input signals are digitised and field pr

Martin Balko, Máté Vizer

We introduce and study a variant of Ramsey numbers for edge-ordered graphs, that is, graphs with linearly ordered sets of edges. The edge-ordered Ramsey number $\overline{R}_e(\mathfrak{G})$ of an edge-ordered graph $\mathfrak{G}$ is the minimum positive integer $N$ such that there exists an edge-ordered complete graph $\mathfrak{K}_N$ on $N$ vertices such t

Anagha Vasudevan, Mikhail M. Ivanov, Sergey Sibiryakov, Julien Lesgourgues

We extend the formalism of time-sliced perturbation theory (TSPT) for cosmological large-scale structure to include non-Gaussian initial conditions. We show that in such a case the TSPT interaction vertices acquire new contributions whose time-dependence factorizes for the Einstein-de Sitter cosmology. The new formulation is free from spurious infrared (IR)

Xi Chen, E. javier Elizondo

We study the relations between the finite generation of Cox ring, the rationality of Euler-Chow series and Poincar\'e series and Zariski's conjecture on dimensions of linear systems. We prove that if the Cox ring of a smooth projective variety is finitely generated, then all Poincar\'e series of the variety are rational. We also prove that the multi-variable

Thibaud Lutellier, Lawrence Pang, Viet Hung Pham, Moshi Wei

Automated generate-and-validate (G&V) program repair techniques typically rely on hard-coded rules, only fix bugs following specific patterns, and are hard to adapt to different programming languages. We propose ENCORE, a new G&V technique, which uses ensemble learning on convolutional neural machine translation (NMT) models to automatically fix bugs in mult

Alejandra Consejo, Clara Llorens-Quintana, Hema Radhakrishnan, D. Robert Iskander

Purpose: To characterize the mean topographical shape of the human limbus of a normal eye and ascertain whether it depends on age and refractive power. Setting: Academic institution. Design: Prospective case series. Methods: 74 subjects aged from 20 to 84 years and with no previous ocular surgeries were included in this study. The left eye was measured four

Lu Yuan, Jie Ren, Ling Gao, Zhanyong Tang

The web has become a ubiquitous application development platform for mobile systems. Yet, web access on mobile devices remains an energy-hungry activity. Prior work in the field mainly focuses on the initial page loading stage, but fails to exploit the opportunities for energy-efficiency optimization while the user is interacting with a loaded page. This pap

Sougata Bose, Shankara Narayanan Krishna, Anca Muscholl, Vincent Penelle

We study two formalisms that allow to compare transducers over words under origin semantics: rational and regular resynchronizers, and show that the former are captured by the latter. We then consider some instances of the following synthesis problem: given transducers T1, T2, construct a rational (resp. regular) resynchronizer R, if it exists, such that T1

Julien Alcaide, Nicolás I. Mileo

Current LHC searches for non-supersymmetric singly-charged scalars, based on Two-Higgs-Doublet models, in general focus the analysis on third-generation fermions in the final state. However, singly-charged scalars in alternative extensions of the scalar sector involve Yukawa couplings not proportional to the mass of the fermions. Assuming the scalar decays i

Arjun Berera, Joel Mabillard, Bruno W. Mintz, Rudnei O. Ramos

The escape problem is defined in the context of quantum field theory. The escape rate is explicitly derived for a scalar field governed by fluctuation-dissipation dynamics, through generalizing the standard Kramers problem. In the presence of thermal fluctuations, there is a nonvanishing probability for a classical background field, initially located at a mi

Adam Byerly, Tatiana Kalganova

Capsules are the name given by Geoffrey Hinton to vector-valued neurons. Neural networks traditionally produce a scalar value for an activated neuron. Capsules, on the other hand, produce a vector of values, which Hinton argues correspond to a single, composite feature wherein the values of the components of the vectors indicate properties of the feature suc

Daan Camps, Thomas Mach, Raf Vandebril, David S. Watkins

Pole-swapping algorithms, which are generalizations of the QZ algorithm for the generalized eigenvalue problem, are studied. A new modular (and therefore more flexible) convergence theory that applies to all pole-swapping algorithms is developed. A key component of all such algorithms is a procedure that swaps two adjacent eigenvalues in a triangular pencil.

Aikaterini Gratsea, Maciej Lewenstein, Alexandre Dauphin

We study the generation of hybrid entanglement in a one-dimensional quantum walk. In particular, we explore the preparation of maximally entangled states between position and spin degrees of freedom. We address it as an optimization problem, where the cost function is the Schmidt norm. We then benchmark the algorithm and compare the generation of entanglemen

Adrian S. Hamers, Johan Samsing

Dense stellar systems such as globular clusters are believed to harbor merging binary black holes (BHs). The evolution of such binaries is driven by interactions with other stars, most notably, binary-single interactions. Traditionally, so-called `strong&#39; interactions are believed to be the driving force in this evolution. However, we recently showed tha

M. Giammarchi

This paper descrives the first experimental evidence of antimatter-wave interference, a process at the heart of Quantum Physics and its interpretation. For the case of ordinary matter particles, interference phenomena have been observed in a variety of cases, ranging to electrons up to complex molecules. Here I present the first demonstration of single-posit

Srivatsa B. Prasad, Thomas Bland, Brendan C. Mulkerin, Nick G. Parker

The behaviour of a harmonically trapped dipolar Bose-Einstein condensate with its dipole moments rotating at angular frequencies lower than the transverse harmonic trapping frequency is explored in the co-rotating frame. We obtain semi-analytical solutions for the stationary states in the Thomas-Fermi limit of the corresponding dipolar Gross-Pitaevskii equat

Ruizhang Jin, Rahim Moosa

A criterion in the spirit of Rosenlicht is given, on the rational function f(x), for when the planar vector field defined by x&#39;=f(x) and y&#39;=xy admits a pair of algebraically independent first integrals over some extension of the base field. This proceeds from model-theoretic considerations by working in the theory of differentially closed fields of c

José Ruiz-Franco, Diego Jaramillo-Cano, Manuel Camargo, Christos N. Likos

The growing interest in the dynamical properties of colloidal suspensions, both in equilibrium and under an external drive such as shear or pressure flow, requires the development of accurate methods to correctly include hydrodynamic effects due to the suspension in a solvent. In the present work, we generalize Multi-Particle Collision Dynamics (MPCD) to be

Quentin G. Bailey

We summarize theoretical and experimental work on tests of CPT and local Lorentz symmetry in gravity. Recent developments include extending the effective field theory framework into the nonlinear regime of gravity.

S. Sridhar

Spiral structure in disk galaxies could arise from transient modes that create conditions conducive for their regeneration; this is the proposal of Sellwood and Carlberg, based on simulations of stellar disks. The linear response of an axisymmetric stellar disk, to an adiabatic non-axisymmetric transient mode, gives a final distribution function (DF) that is

Jolyon K. Bloomfield, Patrick Fitzpatrick, Kiriakos Hilbert, David I. Kaiser

We analyze the onset of inflation for a simple single-field model when the system begins with significant inhomogeneities on length-scales shorter than the initial Hubble radius. We incorporate certain nonlinear interactions among the coupled degrees of freedom by using the nonperturbative Hartree approximation. Consistent with recent, more computationally i

Jean Lahoud, Bernard Ghanem, Marc Pollefeys, Martin R. Oswald

We propose a novel method for instance label segmentation of dense 3D voxel grids. We target volumetric scene representations, which have been acquired with depth sensors or multi-view stereo methods and which have been processed with semantic 3D reconstruction or scene completion methods. The main task is to learn shape information about individual object i

Astik Biswas, Emre Yılmaz, Febe de Wet, Ewald van der Westhuizen

This paper presents recent progress in the acoustic modelling of under-resourced code-switched (CS) speech in multiple South African languages. We consider two approaches. The first constructs separate bilingual acoustic models corresponding to language pairs (English-isiZulu, English-isiXhosa, English-Setswana and English-Sesotho). The second constructs a s

Angelica I. Aviles-Rivero, Nicolas Papadakis, Ruoteng Li, Philip Sellars

Semi-supervised classification is a great focus of interest, as in real-world scenarios obtaining labels is expensive, time-consuming and might require expert knowledge. This has motivated the fast development of semi-supervised techniques, whose performance is on a par with or better than supervised approaches. A current major challenge for semi-supervised

David S. Dean, Bing Miao, Rudi Podgornik

We consider Euclidean path integrals with higher derivative actions, including those that depend quadratically on acceleration, velocity and position. Such path integrals arise naturally in the study of stiff polymers, membranes with bending rigidity as well as a number of models for electrolytes. The approach used is based on the relation between quadratic

Stanley Yao Xiao

In this paper we prove the assertion that the number of monic cubic polynomials $F(x) = x^3 + a_2 x^2 + a_1 x + a_0$ with integer coefficients and irreducible, Galois over $\mathbb{Q}$ satisfying $\max\{|a_2|, |a_1|, |a_0|\} \leq X$ is bounded from above by $O(X (\log X)^2)$. We also count the number of abelian monic binary cubic forms with integer coefficie

Jonathan S. Ramos, Carolina Y. V. Watanabe, Marcello H. Nogueira-Barbosa, Agma J. M. Traina

Segmentation of medical images is a critical issue: several process of analysis and classification rely on this segmentation. With the growing number of people presenting back pain and problems related to it, the automatic or semi-automatic segmentation of fractured vertebral bodies became a challenging task. In general, those fractures present several regio

David Ruhe, Giovanni Cinà, Michele Tonutti, Daan de Bruin

The Intensive Care Unit (ICU) is a hospital department where machine learning has the potential to provide valuable assistance in clinical decision making. Classical machine learning models usually only provide point-estimates and no uncertainty of predictions. In practice, uncertain predictions should be presented to doctors with extra care in order to prev

Daniel Harlow, Jie-qiang Wu

The covariant phase space method of Iyer, Lee, Wald, and Zoupas gives an elegant way to understand the Hamiltonian dynamics of Lagrangian field theories without breaking covariance. The original literature however does not systematically treat total derivatives and boundary terms, which has led to some confusion about how exactly to apply the formalism in th

Kevin J. Parker, Thomas Szabo, Sverre Holm

A rising wave of technologies and instruments are enabling more labs and clinics to make a variety of measurements related to tissue viscoelastic properties. These instruments include elastography imaging scanners, rheological shear viscometers, and a variety of calibrated stress-strain analyzers. From these many sources of disparate data, a common step in a

Nathan Kallus

Policy learning can be used to extract individualized treatment regimes from observational data in healthcare, civics, e-commerce, and beyond. One big hurdle to policy learning is a commonplace lack of overlap in the data for different actions, which can lead to unwieldy policy evaluation and poorly performing learned policies. We study a solution to this pr

Mayank Raikwar, Danilo Gligoroski, Katina Kralevska

The underlying fundaments of blockchain are cryptography and cryptographic concepts that provide reliable and secure decentralized solutions. Although many recent papers study the use-cases of blockchain in different industrial areas, such as finance, health care, legal relations, IoT, information security, and consensus building systems, only few studies sc

Wentao Cao, László Székelyhidi

We obtain global extensions of the celebrated Nash-Kuiper theorem for $C^{1,\theta}$ isometric immersions of compact manifolds with optimal H\"older exponent. In particular for the Weyl problem of isometrically embedding a convex compact surface in 3-space, we show that the Nash-Kuiper non-rigidity prevails upto exponent $\theta<1/5$. This extends previous r

Carlo Dri, Mirco Panighel, Daniel Tiemann, Laerte L. Patera

Time resolution is one of the most severe limitations of scanning probe microscopies (SPMs), since the typical image acquisition times are in the order of several seconds or even few minutes. As a consequence, the characterization of dynamical processes occurring at surfaces (e.g. surface diffusion, film growth, self-assembly and chemical reactions) cannot b

Fabio Staniscia, Lev Truskinovsky

Muscle cells with sarcomeric structure exhibit highly nontrivial passive mechanical response. The difficulty of its continuum modeling is due to the presence of long-range interactions transmitted by extended protein skeleton. To build a rheological model for muscle 'material' we use a stochastic micromodel and derive a linear response theory for a half-sarc

Christian Kuehn, Alexandra Neamtu, Anne Pein

We prove the existence of a global random attractor for a certain class of stochastic partly dissipative systems. These systems consist of a partial (PDE) and an ordinary differential equation (ODE), where both equations are coupled and perturbed by additive white noise. The deterministic counterpart of such systems and their long-time behaviour have already

Rajarshee Mitra

Attention is a very efficient way to model the relationship between two sequences by comparing how similar two intermediate representations are. Initially demonstrated in NMT, it is a standard in all NLU tasks today when efficient interaction between sequences is considered. However, we show that attention, by virtue of its composition, works best only when

Ian Marius Peters, Tonio Buonassisi

As the 21st century progresses, photovoltaic technology is becoming a major provider of the worlds electricity, while effects of global climate change unfold. This development begs the question: is climate change affecting the energy production of solar cells? In this article, we attempt to answer this question looking backward and forward. We start by analy

Masato Matsuura, Takahiko Sasaki, Satoshi Iguchi, Elena Gati

Inelastic neutron scattering measurements on the molecular dimer-Mott insulator $\kappa$-(BEDT-TTF)$_{2}$Cu[N(CN)$_{2}$]Cl reveal a phonon anomaly in a wide temperature range. Starting from $T_{\rm ins}\sim50$-$60$ K where the charge gap opens, the low-lying optical phonon modes become overdamped upon cooling towards the antiferromagnetic ordering temperatur

ATLAS Collaboration

Narrow resonances decaying into $WW$, $WZ$ or $ZZ$ boson pairs are searched for in 139 fb$^{-1}$ of proton-proton collision data at a centre-of-mass energy of $\sqrt{s}=13$ TeV recorded with the ATLAS detector at the Large Hadron Collider from 2015 to 2018. The diboson system is reconstructed using pairs of high transverse momentum, large-radius jets. These

Abbas Sherif, Rituparno Goswami, Sunil D. Maharaj

We study the geometrical and dynamical features of expansion-free dynamical stars in general relativity. Such stars can exist only if particular physical and geometric conditions are satisfied. Firstly, for trapping to exist in an expansion-free dynamical star, the star must accelerate and radiate simultaneously. If either are zero, then the shear \(Sigma\)

Christian Baer, Lashi Bandara

We study boundary value problems for first-order elliptic differential operators on manifolds with compact boundary. The adapted boundary operator need not be selfadjoint and the boundary condition need not be pseudo-local. We show the equivalence of various characterisations of elliptic boundary conditions and demonstrate how the boundary conditions traditi

Medina Pardell Judith, Herrero Ramon, Botey Muriel, Staliunas Kestutis

We provide a feasible and compact scheme to control and stabilize the spatiotemporal dynamics of BAS lasers. The proposal is based on the ability of non-Hermitian potentials with given local symmetries to manage the flow of light. A local PT-symmetric configuration allows to control, enhance and localize the generated light. We impose a pump modulation, with

Nikita Artamonov

We show that if $X$ is a reflexive Banach space, then a nonautonomous operator Riccati integral equation has a unique strongly continuous self-adjoint nonnegative solution $P(t)\in\mathcal{L}(X,X^*)$

Fan Wu, Jianshen Hu, Lianyi He, Xia-Ji Liu

We propose a minimal theoretical model for the description of a two-dimensional (2D) strongly interacting Fermi gas confined transversely in a tight harmonic potential, and present accurate predictions for its equation of state and breathing mode frequency. We show that the minimal model Hamiltonian needs at least two independent interaction parameters, the

Ioannis Kalogridis, Stefan Van Aelst

Penalized spline smoothing is a popular and flexible method of obtaining estimates in nonparametric regression but the classical least-squares criterion is highly susceptible to model deviations and atypical observations. Penalized spline estimation with a resistant loss function is a natural remedy, yet to this day the asymptotic properties of M-type penali

Louis-Pierre Arguin, Lisa Hartung, Nicola Kistler

We study the total mass of high points in a random model for the Riemann-Zeta function. We consider the same model as in [8], [2], and build on the convergence to &#39;Gaussian&#39; multiplicative chaos proved in [14]. We show that the total mass of points which are a linear order below the maximum divided by their expectation converges almost surely to the