March 2020 arXiv papers — page 120

David R. Avellaneda B., Ramón E. R. González

In this work, we present a simple and efficient generator of polymeric linear chains, based on a random self-avoiding walk process. The chains are generated using a discrete process of growth, in cubic networks and in a finite time, without border limits and without exploring all the configurational space. First, we thoroughly describe the chains morphology

Lun Yue, Mette B. Gaarde

The semiconductor Bloch equations (SBEs) are routinely used for simulations of strong-field laser-matter interactions in condensed matter. In systems without inversion or time-reversal symmetries, the Berry connections and transition dipole phases (TDPs) must be included in the SBEs, which in turn requires the construction of a smooth and periodic structure

Javad Fotouhi, Xingtong Liu, Mehran Armand, Nassir Navab

Stitching images acquired under perspective projective geometry is a relevant topic in computer vision with multiple applications ranging from smartphone panoramas to the construction of digital maps. Image stitching is an equally prominent challenge in medical imaging, where the limited field-of-view captured by single images prohibits holistic analysis of

Rohola Zandie, Mohammad H. Mahoor

Understanding emotions and responding accordingly is one of the biggest challenges of dialog systems. This paper presents EmpTransfo, a multi-head Transformer architecture for creating an empathetic dialog system. EmpTransfo utilizes state-of-the-art pre-trained models (e.g., OpenAI-GPT) for language generation, though models with different sizes can be used

Rodrigo Henriquez-Auba, Jose D. Lara, Ciaran Roberts, Nathan Pallo

The integration of converter-interfaced generation (CIG) from renewable energy sources poses challenges to the stability and transient behavior of electric power systems. Understanding the dynamic behavior of low-inertia power systems is critical to addressing these stability questions. However, there is a limited availability of open source tools explicitly

David Fisher

This essay points to many of the interesting ramifications of Margulis' arithmeticity theorem, the superrigidity theorem, and normal subgroup theorem. We provide some history and background, but the main goal is to point to interesting open questions that stem directly or indirectly from Margulis' work and it's antecedents.

Seid Muhie Yimam, Gopalakrishnan Venkatesh, John Sie Yuen Lee, Chris Biemann

We present the first approach to automatically building resources for academic writing. The aim is to build a writing aid system that automatically edits a text so that it better adheres to the academic style of writing. On top of existing academic resources, such as the Corpus of Contemporary American English (COCA) academic Word List, the New Academic Word

Krzysztof Debicki, Lanpeng Ji, Tomasz Rolski

We derive the exact asymptotics of \[ P\left( \sup_{t\ge 0} \Bigl( X_1(t) - μ_1 t\Bigr)> u, \ \sup_{s\ge 0} \Bigl( X_2(s) - μ_2 s\Bigr)> u \right), \ \ u\to\infty, \] where $(X_1(t),X_2(s))_{t,s\ge0}$ is a correlated two-dimensional Brownian motion with correlation $ρ\in[-1,1]$ and $μ_1,μ_2>0$. It appears that the play between $ρ$ and $μ_1,μ_2$ leads to seve

István Sárándi, Timm Linder, Kai O. Arras, Bastian Leibe

Heatmap representations have formed the basis of 2D human pose estimation systems for many years, but their generalizations for 3D pose have only recently been considered. This includes 2.5D volumetric heatmaps, whose X and Y axes correspond to image space and the Z axis to metric depth around the subject. To obtain metric-scale predictions, these methods mu

Andrea Luigi Tironi

Let $X^n$ be a nonsingular hypersurface of degree $d\geq 2$ in the projective space $\mathbb{P}^{n+1}$ defined over a finite field $\mathbb{F}_q$ of $q$ elements. We prove a Homma-Kim conjecture on a upper bound about the number of $\mathbb{F}_q$-points of $X^n$ for $n=3$, and for any odd integer $n\geq 5$ and $d\leq q$.

Cesar Menendez, Claudio Cazorla

Thermal excitations typically reduce the electric polarization in ferroelectric materials. Here, we show by means of first-principles calculations that multiferroic BiFe$_{1-x}$Co$_{x}$O$_{3}$ solid solutions with $0.25 \le x \le 0.50$ (BFCO) represent a noteworthy exception to this behaviour. In particular, we find that at room temperature and for moderate

Mona Gridseth, Timothy D. Barfoot

Vision-based path following allows robots to autonomously repeat manually taught paths. Stereo Visual Teach and Repeat (VT\&R) accomplishes accurate and robust long-range path following in unstructured outdoor environments across changing lighting, weather, and seasons by relying on colour-constant imaging and multi-experience localization. We leverage multi

Pablo Llombart, Eva G. Noya, David N. Sibley, Andrew J. Archer

Understanding the wetting properties of premelting films requires knowledge of the film's equation of state, which is not usually available. Here we calculate the disjoining pressure curve of premelting films, and perform a detailed thermodynamic characterization of premelting behavior on ice. Analysis of the density profiles reveals the signature of wea

Antong Chen, Jennifer Saouaf, Bo Zhou, Randolph Crawford

Herein we propose a deep learning-based approach for the prediction of lung lesion response based on radiomic features extracted from clinical CT scans of patients in non-small cell lung cancer trials. The approach starts with the classification of lung lesions from the set of primary and metastatic lesions at various anatomic locations. Focusing on the lung

Kristof Takacs, Vince Grolmusz

The Protein Data Bank (PDB) today contains more than 153,000 entries with the 3-dimensional structures of biological macromolecules. Using the rich resources of this repository, it is possible identifying subsets with specific, interesting properties for different applications. Our research group prepared an automatically updated list of amyloid- and probabl

Zakir Hussain Shaik, Emil Björnson, Erik G. Larsson

Cell-free Massive MIMO (mMIMO) is envisaged to be a next-generation technology beyond 5G with its high spectral efficiency and superior spatial diversity as compared to that of conventional MIMO technology. The main principle is that many distributed access points (APs) cooperate to simultaneously serve all the users within the network without creating cell

Benoit Fresse, Thomas Willwacher

We define a simplicial enrichment on the category of differential graded Hopf cooperads (the category of dg Hopf cooperads for short). We prove that our simplicial enrichment satisfies, in part, the axioms of a simplicial model category structure on the category of dg Hopf cooperads. We use this simplicial model structure to define a model of mapping spaces

Brian G. Vegetabile, Beth Ann Griffin, Donna L. Coffman, Matthew Cefalu

Weighted estimators are commonly used for estimating exposure effects in observational settings to establish causal relations. These estimators have a long history of development when the exposure of interest is binary and where the weights are typically functions of an estimated propensity score. Recent developments in optimization-based estimators for cons

Viktor Khalack, Francis LeBlanc, Oleksandr Kobzar

A portion of the upper main-sequence stars, called chemically peculiar (CP) stars, show significant abundance anomalies mainly due to atomic diffusion of chemical elements within the stellar atmospheres of these stars. Slowly rotating CP stars may have hydrodynamically stable atmospheres where the competition between the gravitational and radiative forces le

Javier Pérez, María C. Quintana

We construct a new family of linearizations of rational matrices $R(λ)$ written in the general form $R(λ)= D(λ)+C(λ)A(λ)^{-1}B(λ)$, where $D(λ)$, $C(λ)$, $B(λ)$ and $A(λ)$ are polynomial matrices. Such representation always exists and are not unique. The new linearizations are constructed from linearizations of the polynomial matrices $D(λ)$ and $A(λ)$, wher

Antonio Montero

Given an abstract $n$-polytope $\mathcal{K}$, an abstract $(n+1)$-polytope $\mathcal{P}$ is an extension of $\mathcal{K}$ if all the facets of $\mathcal{P}$ are isomorphic to $\mathcal{K}$. A chiral polytope is a polytope with maximal rotational symmetry that does not admit any reflections. If $\mathcal{P}$ is a chiral extension of $\mathcal{K}$, then all bu

Aldo Pacchiano, Heinrich Jiang, Michael I. Jordan

Mode estimation is a classical problem in statistics with a wide range of applications in machine learning. Despite this, there is little understanding in its robustness properties under possibly adversarial data contamination. In this paper, we give precise robustness guarantees as well as privacy guarantees under simple randomization. We then introduce a t

Barbara Plank

Named Entity Recognition (NER) has greatly advanced by the introduction of deep neural architectures. However, the success of these methods depends on large amounts of training data. The scarcity of publicly-available human-labeled datasets has resulted in limited evaluation of existing NER systems, as is the case for Danish. This paper studies the effective

Fei Zhou, Jie Ren, Xi Lu, Shuangge Ma

Gene-environment interactions have important implications to elucidate the genetic basis of complex diseases beyond the joint function of multiple genetic factors and their interactions (or epistasis). In the past, G$\times$E interactions have been mainly conducted within the framework of genetic association studies. The high dimensionality of G$\times$E int

Fereshteh Fakhar Firouzeh, John W. Chinneck, Sreeraman Rajan

The goal in signal compression is to reduce the size of the input signal without a significant loss in the quality of the recovered signal. One way to achieve this goal is to apply the principles of compressive sensing, but this has not been particularly successful for real-world signals that are insufficiently sparse, such as speech. We present three new al

Pavlo Kashko, Viktor Khalack, Oleksandr Kobzar, Dmytro Tvardovskyi

HD~63401 is known magnetic chemically peculiar (mCP) star that shows a slow rotation and probably possesses a hydrodynamically stable stellar atmosphere. In the latter case the atomic diffusion mechanism enforced by the magnetic field can lead to stratification of elemental abundance with optical depth. HD~63401 was recently observed with the space telescope

Yimeng Lu, Maryam Kamgarpour

This paper considers safe robot mission planning in uncertain dynamical environments. This problem arises in applications such as surveillance, emergency rescue, and autonomous driving. It is a challenging problem due to modeling and integrating dynamical uncertainties into a safe planning framework, and finding a solution in a computationally tractable way.

Debora Nozza, Federico Bianchi, Dirk Hovy

Recently, Natural Language Processing (NLP) has witnessed an impressive progress in many areas, due to the advent of novel, pretrained contextual representation models. In particular, Devlin et al. (2019) proposed a model, called BERT (Bidirectional Encoder Representations from Transformers), which enables researchers to obtain state-of-the art performance o

Katalin Feher

The purpose is to investigate the expected participation and mentality of smart citizens in smart cities. The key question is the role of the human factor in smart environments globally studied through a research corpus of 150 documents including mainstream summaries trend reports, white papers and visions of business, governmental and university research co

Mohammad Akif Beg, Jia Yuan Yu

In many scenarios in computer vision, machine learning, and computer graphics, there is a requirement to learn the mapping from an image of one domain to an image of another domain, called Image-to-image translation. For example, style transfer, object transfiguration, visually altering the appearance of weather conditions in an image, changing the appearanc

Louise Harra, Sarah Matthews, David Long, Takahiro Hasegawa

One of the key processes associated with the "standard" flare model is chromospheric evaporation, a process where plasma heated to high temperatures by energy deposition at the flare footpoints is driven upwards into the corona. Despite several decades of study, a number of open questions remain, including the relationship between plasma produced dur

Choulakian Vartan, Abou Samra Ghassan

Optimization has two faces, minimization of a loss function or maximization of a gain function. We show that the mean absolute deviations about the mean, d, maximizes a gain function based on the power set of the individuals, and it is equal to twice the value of its cut-norm. This property is generalized to double-centered and triple-centered data sets. Fur

Nicolas Saintier, Juan Pablo Pinasco, Federico Vazquez

We investigate the phenomena of political bi-polarization in a population of interacting agents by means of a generalized version of the model introduced in PRE E 101, 012101 (2020) for the dynamics of voting intention. Each agent has a propensity $p$ in $[0,1]$ to vote for one of two political candidates. In an iteration step, two agents $i$ and $j$ with re

G. Garello, A. Morando

We study the continuity in weighted Fourier Lebesgue spaces for a class of pseudodifferential operators, whose symbol has finite Fourier Lebesgue regularity with respect to $x$ and satisfies a quasi-homogeneous decay of derivatives with respect to the $ξ$ variable. Applications to Fourier Lebesgue microlocal regularity of linear and nonlinear partial differe

Jakub Fil, Dominique Chu

The Multi-Spike Tempotron (MST) is a powerful single spiking neuron model that can solve complex supervised classification tasks. While powerful, it is also internally complex, computationally expensive to evaluate, and not suitable for neuromorphic hardware. Here we aim to understand whether it is possible to simplify the MST model, while retaining its abil

Dirk Keppens

Whereas for a substantial part, Finite Geometry during the past 50 years has focussed on geometries over finite fields, geometries over finite rings that are not division rings have got less attention. Nevertheless, several important classes of finite rings give rise to interesting geometries. In this paper we bring together some results, scattered over the

Priit Ulmas, Innar Liiv

The focus of this paper is using a convolutional machine learning model with a modified U-Net structure for creating land cover classification mapping based on satellite imagery. The aim of the research is to train and test convolutional models for automatic land cover mapping and to assess their usability in increasing land cover mapping accuracy and change

Glenn D. Martinez, Drew Buckley, Ilya Charaev, Andrew Dane

Superconducting devices are prone to reduced performance caused by impurities and defects along the edges of their wires, which can lead to local current crowding. In this study, we explored the use of helium ion irradiation to modify the lattice structure of the superconducting material to change its intrinsic properties. The process will allow us to direct

Sandra Benitez-Herrera, Jorge G. Rivero Gonzalez

Due to its technological, scientific and cultural dimensions, astronomy is a unique discipline to help achieve the United Nations Sustainable Development Goals. According to the United Nations High Commissioner for Refugees (UNHCR), there are currently nearly 30 million refugees in the world. While there are many (and very necessary) programmes supporting th

Manuel D. Contreras, Santiago Díaz-Madrigal, Pavel Gumenyuk

We study infinitesimal generators of one-parameter semigroups in the unit disk $\mathbb D$ having prescribed boundary regular fixed points. Using an explicit representation of such infinitesimal generators in combination with Krein-Milman Theory we obtain new sharp inequalities relating spectral values at the fixed points with other important quantities havi

Monica Alexander, Kivan Polimis, Emilio Zagheni

Measuring and forecasting migration patterns, and how they change over time, has important implications for understanding broader population trends, for designing policy effectively and for allocating resources. However, data on migration and mobility are often lacking, and those that do exist are not available in a timely manner. Social media data offer new

Corentin Thomasset, David Barrera

Network traffic whitelisting has emerged as a dominant approach for securing consumer IoT devices. However, determining what the whitelisted behavior of an IoT device should be remains an open challenge. Proposals to date have relied on manufacturers and trusted parties to provide whitelists, but these proposals require manufacturer involvement or placing tr

Ignacio Sticco, Guillermo Frank, Claudio Dorso

The Social Force Model (SFM) is a suitable model for describing crowd behaviors under emotional stress. This research analyzes the role of the body force in the original SFM. We focused on the parameter associated with the body stiffness (kn) and its impact on the pedestrian dynamics for two different geometries: bottlenecks and corridors. Increasing kn prod

Matthew Bristow, William Knafo, Pascal Reiss, William Meier

The upper critical field of multiband superconductors is an important quantity that can reveal the details about the nature of the superconducting pairing. Here we experimentally map out the complete upper critical field phase diagram of a stoichiometric superconductor, CaKFe$_4$As$_4$, up to 90T for different orientations of the magnetic field and at temper

Jarosław Grytczuk

This survey presents some combinatorial problems with number-theoretic flavor. Our journey starts from a simple graph coloring question, but at some point gets close to a dangerous territory of the Riemann Hypothesis. We will mostly focus on open problems, but we will also provide some simple proofs, just for adorning.

Omar León Sánchez, Marcus Tressl

In this short note a differential version of the classical Weil descent is established in all characteristics. This yields a ready-to-deploy tool of differential restriction of scalars for differential varieties over finite differential field extensions.

Yacine Mehtar-Tani

We revisit the calculation of the medium-induced gluon radiative spectrum and propose a novel expansion scheme that encompasses the two known analytic limits: i) the high frequency regime dominated by a single hard scattering that corresponds to the leading order in the standard opacity expansion, ii) the low frequency regime that is dominated by multiple so

Marcin Anholcer, Bartłomiej Bosek, Jarosław Grytczuk

In any vertex coloring of a graph some edges have differently colored ends (\emph{good} edges) and some are monochromatic (\emph{bad} edges). In a proper coloring all edges are good. In a \emph{majority coloring} it is enough that for every vertex $v$, the number of bad edges incident to $v$ does not exceed the number of good edges incident to $v$. A well kn

Joseph Poremba

Symmetry in finite model finding problems of many-sorted first-order logic (MSFOL) can be exploited to reduce the number of interpretations considered during search, thereby improving solver performance. In this thesis, we situate symmetry of many-sorted finite model finding (MSFMF) problems in a general framework used for constraint satisfaction problems (C

Dirk Keppens

In this survey paper we give an historical and at the same time thematical overview of the development of ring geometry from its origin to the current state of the art. A comprehensive up-to-date list of literature is added with articles that treat ring geometry within the scope of incidence geometry.

Aditya Jayaraman, Kimberly Hsieh, Bhaskar Ghawri, Phanibhusan S. Mahapatra

Resolving low-energy features in the density of states (DOS) holds the key to understanding wide variety of rich novel phenomena in graphene based 2D heterostructures. Lifshitz transition in bilayer graphene (BLG) arising from trigonal warping has been established theoretically and experimentally. Nevertheless, the experimental realization of its effects on

Shane Barratt, Jonathan Tuck, Stephen Boyd

We consider a collection of derivatives that depend on the price of an underlying asset at expiration or maturity. The absence of arbitrage is equivalent to the existence of a risk-neutral probability distribution on the price; in particular, any risk neutral distribution can be interpreted as a certificate establishing that no arbitrage exists. We are inter

Zhijing Li, Christopher De Sa, Adrian Sampson

Deep learning for computer vision depends on lossy image compression: it reduces the storage required for training and test data and lowers transfer costs in deployment. Mainstream datasets and imaging pipelines all rely on standard JPEG compression. In JPEG, the degree of quantization of frequency coefficients controls the lossiness: an 8 by 8 quantization

Aurélien F. Bibaut, Antoine Chambaz, Mark J. van der Laan

We propose the Generalized Policy Elimination (GPE) algorithm, an oracle-efficient contextual bandit (CB) algorithm inspired by the Policy Elimination algorithm of \cite{dudik2011}. We prove the first regret optimality guarantee theorem for an oracle-efficient CB algorithm competing against a nonparametric class with infinite VC-dimension. Specifically, we s

Gaston Giribet

We review old and recent results on a special limit of string theory on AdS$_3\times M_7$ with pure NS-NS fluxes: the limit in which the string length $\ell_s=\sqrt{α'}$ equals the AdS$_3$ radius $R $. At this point of the moduli space, the theory exhibits special properties, which we discuss. Special attention is focused on features of correlation funct

Federico Abbate, Andrea Possenti, Caterina Tiburzi, Ewan Barr

The Galactic magnetic field plays an important role in the evolution of the Galaxy, but its small-scale behaviour is still poorly known. It is also unknown whether it permeates the halo of the Galaxy or not. By using observations of pulsars in the halo globular cluster 47 Tucanae, we probed the Galactic magnetic field at arcsecond scales for the first time a

Jianer Chen, Ying Guo, Qin Huang

We propose a new (theoretical) computational model for the study of massive data processing with limited computational resources. Our model measures the complexity of reading the very large data sets in terms of the data size N and analyzes the computational cost in terms of a parameter k that characterizes the computational power provided by limited local c

Gaston Giribet, Matias Leoni

Motivated by the recent work on $T\bar{T}$-type deformations of 2D CFTs, a especial class of single-trace deformations of AdS$_3$/CFT$_2$ correspondence has been investigated. From the worldsheet perspective, this corresponds to a marginal deformation of the $σ$-model on AdS$_3$ that yields a string background that interpolates between AdS$_3$ and a flat lin

K. Decker French, Thomas Wevers, Jamie Law-Smith, Or Graur

Recent studies of Tidal Disruption Events (TDEs) have revealed unexpected correlations between the TDE rate and the large-scale properties of the host galaxies. In this review, we present the host galaxy properties of all TDE candidates known to date and quantify their distributions. We consider throughout the differences between observationally-identified t

Jose Luis Blázquez-Salcedo, Daniela D. Doneva, Sarah Kahlen, Jutta Kunz

We study the axial perturbations of spontaneously scalarized black holes in Einstein-Gauss-Bonnet (EGB) theories. We consider the nodeless solutions of the fundamental branch of the model studied in [1], which possesses a region of radially stable configurations, as shown in [2]. Here we show that almost all of the radially stable black holes are also stable

José Natário

Lecture notes written for a one-semester course in mathematical relativity aimed at mathematics and physics students. Not meant as an introduction to general relativity, but rather as a complementary, more advanced text.

A. I. Ahmadov, M. Demirci, S. M. Aslanova, M. F. Mustamin

Focusing on an improved approximation scheme, we present how to treat the centrifugal and the Coulombic behavior terms and then to obtain the bound state solutions of the Klein-Gordon (KG) equation with the Manning-Rosen plus a Class of Yukawa potentials. By means of the Nikiforov-Uvarov (NU) and supersymmetric quantum mechanics (SUSYQM) methods, we present

Sunghoon Jung, TaeHun Kim, Jiro Soda, Yuko Urakawa

The axion-gravity Chern-Simons coupling is well motivated but is relatively weakly constrained, partly due to difficult measurements of gravity. We study the sensitivity of LIGO measurements of chirping gravitational waves (GWs) on such coupling. When the frequency of the propagating GW matches with that of the coherent oscillation of axion dark matter field

Mohamad Shalaby, Avery E. Broderick, Philip Chang, Christoph Pfrommer

We study the longitudinal stability of beam-plasma systems in the presence of a density inhomogeneity in the background plasma. Previous works have focused on the non-relativistic regime where hydrodynamical models are used to evolve pre-existing Langmuir waves within inhomogeneous background plasmas. Here, for the first time we study the problem with kineti

Charles Aouad, Philip James, Igor Chilingarian

Star formation is one of the key factors that shapes galaxies. This process is relatively well understood from both simulations and observations on a small "local" scale of individual giant molecular clouds and also on a "global" galaxy-wide scale (e.g. the Kennicutt-Schmidt law). However, there is still no understanding on how to connect glo

Aniruddha Bapat, Eddie Schoute, Alexey V. Gorshkov, Andrew M. Childs

We propose a time-independent Hamiltonian protocol for the reversal of qubit ordering in a chain of $N$ spins. Our protocol has an easily implementable nearest-neighbor, transverse-field Ising model Hamiltonian with time-independent, non-uniform couplings. Under appropriate normalization, we implement this state reversal three times faster than a naive appro

Suyog Gupta, Berkin Akin

While neural network hardware accelerators provide a substantial amount of raw compute throughput, the models deployed on them must be co-designed for the underlying hardware architecture to obtain the optimal system performance. We present a class of computer vision models designed using hardware-aware neural architecture search and customized to run on the

Constantin Krüger, Jaco Fuchs, Laura Cattaneo, Ursula Keller

Attosecond measurements reveal new physical insights in photo ionization dynamics from atoms, molecules and condensed matter. However, on such time scales even small timing jitter can significantly reduce the time resolution in pump-probe measurements. Here, we propose a novel technique to retrieve attosecond delays from a well established attosecond interfe

Zoe Z. Yan, Jee Woo Park, Yiqi Ni, Huanqian Loh

We demonstrate microwave dressing on ultracold, fermionic ${}^{23}$Na${}^{40}$K ground-state molecules and observe resonant dipolar collisions with cross sections exceeding three times the $s$-wave unitarity limit. The origin of these collisions is the resonant alignment of the approaching molecules' dipoles along the intermolecular axis, which leads to

Krishna Kumar P., Paul Langton, Wolfgang Gatterbauer

Node classification is an important problem in graph data management. It is commonly solved by various label propagation methods that work iteratively starting from a few labeled seed nodes. For graphs with arbitrary compatibilities between classes, these methods crucially depend on knowing the compatibility matrix that must be provided by either domain expe

Iasson Karafyllis, Dionysis Theodosis, Markos Papageorgiou

The paper provides conditions that guarantee existence and uniqueness of classical solutions for a non-local conservation law on a ring-road with possible nudging (or "look behind") terms. The obtained conditions are novel, as they are not covered by existing results in the literature. The paper also provides results which indicate that nudging can i

A. Maragkoudakis, E. Peeters, A. Ricca

We present a new method to accurately describe the ionization fraction and the size distribution of polycyclic aromatic hydrocarbons (PAHs) within astrophysical sources. To this purpose, we have computed the mid-infrared emission spectra of 308 PAH molecules of varying sizes, symmetries, and compactness, generated in a range of radiation fields. We show that

Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar

Label smoothing is commonly used in training deep learning models, wherein one-hot training labels are mixed with uniform label vectors. Empirically, smoothing has been shown to improve both predictive performance and model calibration. In this paper, we study whether label smoothing is also effective as a means of coping with label noise. While label smooth

Ellis A. Avallone, Xudong Sun

It is well established that magnetic free energy associated with electric currents powers solar flares and coronal mass ejections (CMEs) from solar active regions (ARs). However, the conditions that determine whether an AR will produce an eruption are not well understood. Previous work suggests that the degree to which the driving electric currents, or the s

Wissem Zrafi, Hela Ladjimi, Halima Said, Hamid Berriche

Experiments with cold ion-atom mixtures have recently opened the way for the production and application of ultracold molecular ions. Here, in a comparative study, we theoretically investigate ground and several excited electronic states and prospects for the formation of molecular ions composed of a calcium ion and an alkali-metal atom: CaAlk$^{+}$ (Alk=Li,

Noemi Ghillani, Michael Heinz, Tatiana Gambaryan-Roisman

Wetting of surfaces with porous coating is relevant for a wide variety of technical applications, such as printing technologies and heat transfer enhancement. Imbibition and evaporation of liquids on surfaces covered with porous layers are responsible for significant improvement of cooling efficiency during drop impact cooling and flow boiling on such surfac

Toby Hocking, Joseph Vargovich

Many learning algorithms are formulated in terms of finding model parameters which minimize a data-fitting loss function plus a regularizer. When the regularizer involves the l0 pseudo-norm, the resulting regularization path consists of a finite set of models. The fastest existing algorithm for computing the breakpoints in the regularization path is quadrati

Shan Jaffry

Autonomous prediction of traffic demand will be a key function in future cellular networks. In the past, researchers have used statistical methods such as Autoregressive integrated moving average (ARIMA) to provide traffic predictions. However, ARIMA based predictions fail to give an exact and accurate forecast for dynamic input quantities such as cellular t

Xiongzhi Chen

We prove a strong law of large numbers for simultaneously testing parameters of a large number of dependent, Lancaster bivariate random variables with infinite supports, and discuss its implications.

Sourjya Roy, Priyadarshini Panda, Gopalakrishnan Srinivasan, Anand Raghunathan

Modern deep networks have millions to billions of parameters, which leads to high memory and energy requirements during training as well as during inference on resource-constrained edge devices. Consequently, pruning techniques have been proposed that remove less significant weights in deep networks, thereby reducing their memory and computational requiremen

Michael Dumbser, Simone Chiocchetti, Ilya Peshkov

In this paper we present three different numerical approaches to account for curl-type involution constraints in hyperbolic partial differential equations for continuum physics. All approaches have a direct analogy to existing and well-known divergence-preserving schemes for the Maxwell and MHD equations. The first method consists in a generalization of the

Grigory Golovin, Vojtěch Horný, Wenchao Yan, Colton Fruhling

We demonstrate a novel approach to the generation of femtosecond electron bunch trains via laser-driven wakefield acceleration. We use two independent high-intensity laser pulses, a drive, and injector, each creating their own plasma wakes. The interaction of the laser pulses and their wakes results in a periodic injection of free electrons in the drive plas

K. P. Krishnaraj

For two decades now, the importance of microstructure in the mechanical behaviour of a large collection of grains has been a topic of intense research. Many approaches have been developed to study the microstructure in granular materials, based on local or mesoscopic measures or using ideas from diverse fields like percolation theory, complex networks and pe

Christine Yuen, Piotr Fryzlewicz

We propose Combined Selection and Uncertainty Visualizer (CSUV), which estimates the set of true covariates in high-dimensional linear regression and visualizes selection uncertainties by exploiting the (dis)agreement among different base selectors. Our proposed method selects covariates that get selected the most frequently by the different variable selecti

Mathias Gehrig, Sumit Bam Shrestha, Daniel Mouritzen, Davide Scaramuzza

Spiking Neural Networks (SNNs) are bio-inspired networks that process information conveyed as temporal spikes rather than numeric values. A spiking neuron of an SNN only produces a spike whenever a significant number of spikes occur within a short period of time. Due to their spike-based computational model, SNNs can process output from event-based, asynchro

A. S. Vokhmintsev, I. A. Weinstein

We have studied the temperature dependencies of the photoluminescence (PL) intensity of 4.1 eV in microcrystalline powder of hexagonal boron nitride in the range of 7-1100 K. The results obtained have been analyzed within the band model of energy levels of associated donor-acceptor pairs based on impurity (ONCN) complexes. Luminescence enhancement processes

Habib Ammari, Pierre Millien, Alice L. Vanel

We provide a mathematical analysis for a metasurface constructed of plasmonic nanoparticles mounted periodically on the surface of a microcapsule. We derive an effective transmission condition, which exhibits resonances depending on the inter-particle distance. When the microcapsule is deformed, the resonances are shifted. We fully characterise the dependenc

Boris Klumov, Sergey Khrapak

The two-body (pair) contribution to the entropy of two-dimensional Yukawa systems is calculated and analyzed. It is demonstrated that in the vicinity of the fluid-solid (freezing) phase transition the pair entropy exhibits an abrupt jump in a narrow temperature range and this can be used to identify the freezing point. Relations to the full excess entropy an

Fernanda Duplancic, Federico Dávila-Kurbán, Georgina V. Coldwell, Sol Alonso

The main goal of this work is to investigate the influence of environment at different scales on the properties of galaxies in systems with a low number of members. To this end we used a catalogue of small galaxy systems comprising compact and locally isolated pairs, triplets and groups with four and up to six galaxies. We consider fixed aperture estimators

F. Duplancic, G. V. Coldwell, S. Alonso., D. G. Lambas

We aim at defining homogeneous selection criteria of small galaxy systems in order to build catalogues suitable to compare main properties of pairs, triplets, and groups with four or more members. To this end we use spectroscopic and photometric SDSS data to identify systems with a low number of members. We study global properties of these systems and the pr

David Grant, Katherine Blundell, James Matthews

Determining accurate orbits of binary stars with powerful winds is challenging. The dense outflows increase the effective photospheric radius, precluding direct observation of the Keplerian motion; instead the observables are broad lines emitted over large radii in the stellar wind. Our analysis reveals strong, systematic discrepancies between the radial vel

Catarina Brites, João Ascenso, Fernando Pereira

In recent years, visual sensors have been quickly improving, notably targeting richer acquisitions of the light present in a visual scene. In this context, the so-called lenslet light field (LLF) cameras are able to go beyond the conventional 2D visual acquisition models, by enriching the visual representation with directional light measures for each pixel p

Laure Dumaz, Yun Li, Benedek Valkó

The soft and hard edge scaling limits of $β$-ensembles can be characterized as the spectra of certain random Sturm-Liouville operators. It has been shown that by tuning the parameter of the hard edge process one can obtain the soft edge process as a scaling limit. We prove that this limit can be realized on the level of the corresponding random operators. Mo

Francesco A. N. Palmieri, Krishna R. Pattipati, Giovanni Fioretti, Giovanni Di Gennaro

Probability models have been proposed in the literature to account for "intelligent" behavior in many contexts. In this paper, probability propagation is applied to model agent's motion in potentially complex scenarios that include goals and obstacles. The backward flow provides precious background information to the agent's behavior, viz., i

Shafi Kamalbasha, Manuel J. A. Eugster

Controlled experiments (A/B tests or randomized field experiments) are the de facto standard to make data-driven decisions when implementing changes and observing customer responses. The methodology to analyze such experiments should be easily understandable to stakeholders like product and marketing managers. Bayesian inference recently gained a lot of popu

Jun Jin, Laura Petrich, Masood Dehghan, Martin Jagersand

We consider the problem of visual imitation learning without human supervision (e.g. kinesthetic teaching or teleoperation), nor access to an interactive reinforcement learning (RL) training environment. We present a geometric perspective to derive solutions to this problem. Specifically, we propose VGS-IL (Visual Geometric Skill Imitation Learning), an end-

Mohammadtaher Safarzadeh

Formation of binary black holes (BBHs) detected by gravitational-wave (GW) observations could be broadly divided into two categories: those formed through field binary evolution and those assembled dynamically in dense stellar systems. The branching ratio of the BBHs refers to the contribution of each channel. The dynamical assembly channel would predict a s

J. M. Wilkinson, S. J. Blundell

The unitary evolution of a quantum system preserves its coherence, but interactions between the system and its environment result in decoherence, a process in which the quantum information stored in the system becomes degraded. A spin-polarized positively-charged muon implanted in a fluoride crystal realises such a coherent quantum system, and the entangleme

Elena Ballante, Pierpaolo Uberti, Silvia Figini

This paper introduces a novel approach to assess model performance for predictive models characterized by an ordinal target variable in order to satisfy the lack of suitable tools in this framework. Our methodological proposal is a new index for model assessment which satisfies mathematical properties and can be easily computed. In order to show how our perf

Mostafa Behtouei, Luigi Faillace, Bruno Spataro, Alessandro Variola

There is a strong demand for accelerating structures able to achieve higher gradients and more compact dimensions for the next generation of linear accelerators for research, industrial and medical applications. In the framework of the Compact Light XLS project, an ultra high gradient higher harmonic RF accelerating structure is needed for the linearization