September 2019 arXiv papers — page 52

Fabio Tardivo

The focus of my PhD thesis is on exploring parallel approaches to efficiently solve problems modeled by constraints and presenting a new proposal. Current solvers are very advanced; they are carefully designed to effectively manage the high-level problems' description and include refined strategies to avoid useless work. Despite this, finding a solution

Hauke Kraemer, Norbert Marwan

Recurrence Quantification Analysis (RQA) defines a number of quantifiers, which base upon diagonal line structures in the recurrence plot (RP). Due to the finite size of an RP, these lines can be cut by the borders of the RP and, thus, bias the length distribution of diagonal lines and, consequently, the line based RQA measures. In this letter we investigate

Daniel P. Thorngren, Mark S. Marley, Jonathan J. Fortney

Probabilistic relationships between the mass and radius of planets are useful for a variety of purposes, including estimating the yields of planet discovery efforts and the radii of discovered planets given their masses. Previous work on giant planets often do not make the important distinction between cool and (inflated) hot giants. This can lead to needles

D. J. Mullan, J. MacDonald

The onset of cool massive winds in evolved giants is correlated with an evolutionary feature on the red giant branch known as the bump. Also at the bump, shear instability in the star leads to magnetic fields that occur preferentially on small length scales. Pneuman (1983) has suggested that the emergence of small scale flux tubes in the Sun can give rise to

Mengyao Li, Dmitry Zhirihin, Dmitry Filonov, Xiang Ni

The discovery of topological phases has recently led to a paradigm shift in condensed matter physics, and facilitated breakthroughs in engineered photonics and acoustic metamaterials. Topological insulators (TIs) enable the generation of electronic, photonic, and acoustic modes exhibiting wave propagation that is resilient to disorder, irrespective of manufa

Sai Nithin R. Kantareddy, Ian Mathews, Shijing Sun, Mariya Layurova

Photovoltaic (PV) cells have the potential to serve as on-board power sources for low-power IoT devices. Here, we explore the use of perovskite solar cells to power Radio Frequency (RF) backscatter-based IoT devices with a few μW power demand. Perovskites are suitable for low-cost, high-performance, low-temperature processing, and flexible light energy harve

J. P. Blakeslee, A. Adamson, C. Davis, R. Díaz

We present the Strategic Scientific Plan (SSP) for the direction and activities of the Gemini Observatory in the 2020s. The overarching goal is to ensure that Gemini best uses the available resources to serve the needs of its international user community throughout the coming decade. The actionable items fall into three general categories: (1) preserving Gem

Francesca Scuratti, Giorgio E. Bonacchini, Caterina Bossio, Jorge M. Salazar-Rios

Cell-based biosensors constitute a fundamental tool in biotechnology, and their relevance has greatly increased in recent years as a result of a surging demand for reduced animal testing and for high-throughput and cost-effective in vitro screening platforms dedicated to environmental and biomedical diagnostics, drug development and toxicology. In this conte

Vardaan Pahuja, Jie Fu, Christopher J. Pal

There has been a rapid progress in the task of Visual Question Answering with improved model architectures. Unfortunately, these models are usually computationally intensive due to their sheer size which poses a serious challenge for deployment. We aim to tackle this issue for the specific task of Visual Question Answering (VQA). A Convolutional Neural Netwo

A. D. Supanitsky, G. Medina-Tanco

The origin of the ultra high energy cosmic rays (UHECRs, $E>10^{18}$ eV) is still uncertain. However, great progress has been achieved due to the data taken by The Pierre Auger and Telescope Array observatories. The UHECR flux presents two main features, a hardening of the spectrum known as the ankle and a suppression at higher energies. The experimental dat

A. E. Järvinen, S. L. Allen, A. W. Leonard, A. G. McLean

Simulations for DIII-D high confinement mode plasmas with the multifluid code UEDGE show a strong role of poloidal $\mathbf{E}\times\mathbf{B}$ drifts on divertor heat transport, challenging the paradigm of conduction limited scrape-off layer (SOL) transport. While simulations with reduced drift magnitude are well aligned with the assumption that electron he

Subhasish Mandal, Kristjan Haule, Karin M. Rabe, David Vanderbilt

Using the ab initio embedded DMFT (eDMFT) approach, we study the effect of long-range magnetic ordering on the spectral properties in the binary transition metal oxides, and find that the most significant changes appear in the momentum resolved spectral functions, which sharpen into quite well-defined bands in the antiferromagnetic (AFM) phase. The strongest

Michael Kapovich, Beibei Liu

Geometrically infinite Kleinain groups have nonconical limit sets with the cardinality of the continuum. In this paper, we construct a geometrically infinite Fuchsian group such that the Hausdorff dimension of the nonconical limit set equals zero. For finitely generated, geometrically infinite Kleinian groups, we prove that the Hausdorff dimension of the non

Sitao Luan, Xiao-Wen Chang, Doina Precup

In tabular case, when the reward and environment dynamics are known, policy evaluation can be written as $\bm{V}_{\bmπ} = (I - γP_{\bmπ})^{-1} \bm{r}_{\bmπ}$, where $P_{\bmπ}$ is the state transition matrix given policy ${\bmπ}$ and $\bm{r}_{\bmπ}$ is the reward signal given ${\bmπ}$. What annoys us is that $P_{\bmπ}$ and $\bm{r}_{\bmπ}$ are both mixed with

Thomas F. Banchoff, Felix Günther

In discrete differential geometry, it is widely believed that the discrete Gaussian curvature of a polyhedral vertex star equals the algebraic area of its Gauss image. However, no complete proof has yet been described. We present an elementary proof in which we compare, for a particular normal vector, its winding numbers around the Gauss image and its antipo

Tao Chen, Aigen Li

Context. As the 4th most abundant element in the universe, carbon (C) is widespread in the interstellar medium (ISM) in various allotropic forms (e.g., fullerenes have been identified unambiguously in many astronomical environments, the presence of polycyclic aromatic hydrocarbon molecules in space has been commonly admitted, and presolar graphite as well as

Hongxiang Xie, Javier Rodríguez-Fernández, Nuria González-Prelcic

Exploiting channel sparsity at millimeter wave (mmWave) frequencies reduces the high training overhead associated with the channel estimation stage. Compressive sensing (CS) channel estimation techniques usually adopt the (overcomplete) wavelet/Fourier transform matrix as a sparsifying dictionary. This may not be the best choice when considering non-uniform

O. G. Udalov, I. S. Beloborodov

We consider phase separated states in magnetic oxides (MO) thin films. We show that these states have a non-zero electric polarization. Moreover, the polarization is intimately related to a spatial distribution of magnetization in the film. Polarized states with opposite polarization and opposite magnetic configuration are degenerate. An external electric fi

Andreas Papaefstathiou, Gilberto Tetlalmatzi-Xolocotzi, Marco Zaro

We investigate the production of three Higgs bosons at a proton-proton collider running at a centre-of-mass energy of 100 TeV, all of which decay into $b$-jets. This final state encapsulates by far the largest fraction of the total cross section of triple Higgs boson production, approximately $20\%$. We examine, by constructing detailed phenomenological anal

Yutaka Hirai, Shinya Wanajo, Takayuki R. Saitoh

Light trans-iron elements such as Sr serve as the key to understanding the astrophysical sites of heavy elements. Spectroscopic studies of metal-poor stars have revealed large star-to-star scatters in the ratios of [Sr/Ba], which indicates that there are multiple sites for the production of Sr. Here we present the enrichment history of Sr by a series of the

S. Molkov, A. Lutovinov, S. Tsygankov, I. Mereminskiy

We report the discovery of absorption features in the X-ray spectrum of the transient X-ray pulsar GROJ2058+42. The features are detected around $\sim10$, $\sim20$ and $\sim30$ keV in both NuSTAR observations carried out during the source type II outburst in spring 2019. The most intriguing property is that the deficit of photons around these energies is reg

Moshe Hanukoglu, Nissan Goldberg, Aviv Rovshitz, Amos Azaria

In this paper, we introduce a learning model able to conceals personal information (e.g. gender, age, ethnicity, etc.) from an image, while maintaining any additional information present in the image (e.g. smile, hair-style, brightness). Our trained model is not provided the information that it is concealing, and does not try learning it either. Namely, we c

Dalel Jabri, Kevin Guelton, Noureddine Manamanni, Mohammed Naceur Abdelkrim

This paper deals with the non-quadratic decentralized stabilization of a set of n Takagi-Sugeno descriptors. To ensure the stability of the whole closed-loop dynamics and to minimize interconnection effects between subsystems, the main result allows designing a network of non Parallel Distributed Compensation control laws via a H $\infty$ criterion. Sufficie

Anne Marie Delaney, Eoin Brophy, Tomas E. Ward

Access to medical data is highly restricted due to its sensitive nature, preventing communities from using this data for research or clinical training. Common methods of de-identification implemented to enable the sharing of data are sometimes inadequate to protect the individuals contained in the data. For our research, we investigate the ability of generat

Marc Wenninger, Sebastian P. Bayerl, Jochen Schmidt, Korbinian Riedhammer

Time series are series of values ordered by time. This kind of data can be found in many real world settings. Classifying time series is a difficult task and an active area of research. This paper investigates the use of transfer learning in Deep Neural Networks and a 2D representation of time series known as Recurrence Plots. In order to utilize the researc

Michael Thomas Smith, Mauricio A. Alvarez, Neil D. Lawrence

A continuing challenge for machine learning is providing methods to perform computation on data while ensuring the data remains private. In this paper we build on the provable privacy guarantees of differential privacy which has been combined with Gaussian processes through the previously published \emph{cloaking method}. In this paper we solve several short

Raphael Galicher, Pierre Baudoz, Jacques-Robert Delorme, Dimitry Mawet

The two main advantages of exoplanet imaging are the discovery of objects in the outer part of stellar systems -- constraining models of planet formation --, and its ability to spectrally characterize the planets -- information on their atmosphere. It is however challenging because exoplanets are up to 1e10 times fainter than their star and separated by a fr

Saima Rathore, Muhammad Aksam Iftikhar, Zissimos Mourelatos

Cancer histology reveals disease progression and associated molecular processes, and contains rich phenotypic information that is predictive of outcome. In this paper, we developed a computational approach based on deep learning to predict the overall survival and molecular subtypes of glioma patients from microscopic images of tissue biopsies, reflecting me

Richard Matovu, Isaac Griswold-Steiner, Abdul Serwadda

Music is an expression of our identity, showing a significant correlation with other personal traits, beliefs, and habits. If accessed by a malicious entity, an individual's music listening habits could be used to make critical inferences about the user. In this paper, we showcase an attack in which the vibrations propagated through a user's phone wh

Yuval Peres, Andrew Swan

Let $T_λ$ be a Galton--Watson tree with Poisson($λ$) offspring, and let $A$ be a tree property. In this paper, are concerned with the regularity of the function $\mathbb{P}_λ(A):= \mathbb{P}(T_λ\vdash A)$. We show that if a property $A$ can be uniformly approximated by a sequence of properties $A_k$, depending only on the first $k$ vertices in the breadth fi

Davide Poderini, Rafael Chaves, Iris Agresti, Gonzalo Carvacho

Instrumental variables allow the estimation of cause and effect relations even in presence of unobserved latent factors, thus providing a powerful tool for any science wherein causal inference plays an important role. More recently, the instrumental scenario has also attracted increasing attention in quantum physics, since it is related to the seminal Bell&#

John Campbell, Tobias Neumann

Without proper control of numerical and methodological errors in theoretical predictions at the per mille level it is not possible to study the effect of input parameters in current hadron-collider measurements at the required precision. We present a new version of the parton-level code MCFM that achieves this requirement through its highly-parallelized natu

Tianwei Shen, Lei Zhou, Zixin Luo, Yao Yao

The self-supervised learning of depth and pose from monocular sequences provides an attractive solution by using the photometric consistency of nearby frames as it depends much less on the ground-truth data. In this paper, we address the issue when previous assumptions of the self-supervised approaches are violated due to the dynamic nature of real-world sce

Toni Ikonen

We establish a uniformization result for metric surfaces - metric spaces that are topological surfaces with locally finite Hausdorff 2-measure. Using the geometric definition of quasiconformality, we show that a metric surface that can be covered by quasiconformal images of Euclidean domains is quasiconformally equivalent to a Riemannian surface. To prove th

Lasse Bjørn Kristensen, Morten Kjaergaard, Christian Kraglund Andersen, Nikolaj Thomas Zinner

Noise and errors are inevitable parts of any practical implementation of a quantum computer. As a result, large-scale quantum computation will require ways to detect and correct errors on quantum information. Here, we present such a quantum error correcting scheme for correcting the dominant error sources, phase decoherence and energy relaxation, in qubit ar

Leo Polansky, Ken B. Newman, Lara Mitchell

State-space models (SSMs) are a popular tool for modeling animal abundances. Inference difficulties for simple linear SSMs are well known, particularly in relation to simultaneous estimation of process and observation variances. Several remedies to overcome estimation problems have been studied for relatively simple SSMs, but whether these challenges and pro

Dante Minniti, Bruno Dias, Matías Gómez, Tali Palma

Only four globular cluster planetary nebulae (GCPN) are known so far in the Milky Way. About 50 new globular clusters have been recently discovered towards the Galactic bulge. We present a search for planetary nebulae within 3 arcmin of the new globular clusters, revealing the identification of new candidate GCPN. These possible associations are PN SB 2 with

Waldemar Barrera, Luis Montes de Oca, Didier A. Solis

In this work we study the geodesic structure of the space $Σ(X)$ of compact balls of a complete and locally compact metric length space endowed with the Hausdorff distance $d_H$. In particular, we focus on a geometric condition (referred to as the shooting property) that enables us to give an explicit isometry between $(Σ(X),d_H)$ and the closed half-space $

Madeline Brandt, Alheydis Geiger

There are 280 binodal cubic surfaces passing through 17 general points. For the typically used tropical point conditions, we show that 214 of these give tropicalizations such that the nodes are separated on the tropical cubic surface.

Donald L. Kreher, Douglas R. Stinson, Shannon Veitch

A cyclic ordering of the points in a Mendelsohn triple system of order $v$ (or MTS$(v)$) is called a sequencing. A sequencing $D$ is $\ell$-good if there does not exist a triple $(x,y,z)$ in the MTS$(v)$ such that (1) the three points $x,y,$ and $z$ occur (cyclically) in that order in $D$; and (2) $\{x,y,z\}$ is a subset of $\ell$ cyclically consecutive poin

Jorge González-Gutiérrez, Octavio Moctezuma, Verónica Angeles, Maricarmen Rios-Ramirez

Watercolor or aquarelle is one of the oldest painting methods in which pigments suspended in an aqueous liquid are deposited over a substrate, typically an absorbing material such as paper. The physical processes which lead to pattern formation have not been studied in any depth, in spite of being closely related to flows in other contexts. Identifying and u

Thembelihle Dlamini

Future Mobile Networks (MNs), 5G and beyond 5G, will require a paradigm shift from traditional resource allocation mechanisms as Base Stations (BSs) will be empowered with computation capabilities (i.e., offloading and computation is performed closer to mobile users). This is motivated by the expected data explosion in the volume, variety, and velocity, gene

Peter Werner, Matthias Hofer, Carmelo Sferrazza, Raffaello D'Andrea

This paper presents a vision-based sensing approach for a soft linear actuator, which is equipped with an integrated camera. The proposed vision-based sensing pipeline predicts the three-dimensional position of a point of interest on the actuator. To train and evaluate the algorithm, predictions are compared to ground truth data from an external motion captu

Sheng Gui, Minxin Chen, Benzhuo Lu

In this paper, we propose a model and algorithm for sparse representing Gaussian molecular surface. The original Gaussian molecular surface is approximated by a relatively small number of radial basis functions (RBFs) with rotational ellipsoid feature. The sparsity of the RBF representation is achieved by solving a nonlinear $L_1$ optimization problem. Exper

Yair Caro, Randy Davila, Ryan Pepper

In this paper we study relationships between the \emph{matching number}, written $μ(G)$, and the \emph{independence number}, written $α(G)$. Our first main result is to show \[ α(G) \le μ(G) + |X| - μ(G[N_G[X]]), \] where $X$ is \emph{any} intersection of maximum independent sets in $G$. Our second main result is to show \[ δ(G)α(G) \le Δ(G)μ(G), \] where $δ

Alexandre Graell i Amat, Gianluigi Liva, Fabian Steiner

Approaching capacity with low complexity is a very challenging task. In this paper, we review and compare three promising coding solutions to achieve that, which are suitable for future very high-throughput, low-complexity optical communications.

Valeria Gelardi, Joël Fagot, Alain Barrat, Nicolas Claidière

The stability of social relationships is important to animals living in groups, and social network analysis provides a powerful tool to help characterize and understand their (in)stability and the consequences at the group level. However, the use of dynamic social networks is still limited in this context as it requires long-term social data and new analytic

Yeunhwan Lim, Jeremy W. Holt

We investigate the adiabatic index $Γ_{\mathrm{th}}$ of hot and dense nuclear matter from chiral effective field theory and find that the results are systematically larger than from typical mean field models. We start by constructing the finite-temperature equation of state from chiral two- and three-nucleon forces, which we then use to fit a class of extend

Davide Rozza

We present high-statistics, precision measurements by AMS of the detailed time and rigidity dependence of the primary cosmic-ray electron, positron, proton and helium fluxes over 79 Bartels rotations from May 2011 to May 2017 in the energy range from 1 to 50 GeV. For the first time, the charge-sign dependent modulation during solar maximum has been investiga

Hoang-Dung Tran, Luan Viet Nguyen, Patrick Musau, Weiming Xiang

Safety-critical distributed cyber-physical systems (CPSs) have been found in a wide range of applications. Notably, they have displayed a great deal of utility in intelligent transportation, where autonomous vehicles communicate and cooperate with each other via a high-speed communication network. Such systems require an ability to identify maneuvers in real

Gabor T. Herman

The purpose of this short paper is to identify the mathematical essence of the superiorization methodology. This methodology has been developed in recent years while attempting to solve specific application-oriented problems. Consequently, superiorization is often presented using the terminology of such problems. A more general approach is provided here by d

G. Bonfiglio, K. Rode, K. Siewerska, J. Besbas

Here we study both static and time-resolved dynamic magnetic properties of the compensated ferrimagnet from room temperature down to 10K, thus crossing the magnetic compensation temperature $T_{M}$. The behaviour is analysed with a model of a simple collinear ferrimagnet with uniaxial anisotropy and site-specific gyromagnetic ratios. We find a maximum zero-a

Guido Masella, Adriano Angelone, Fabio Mezzacapo, Guido Pupillo

Strong, long-range interactions present a unique challenge for the theoretical investigation of quantum many-body lattice models, due to the generation of large numbers of competing states at low energy. Here, we investigate a class of extended bosonic Hubbard models with off-site terms interpolating between short and infinite range, thus allowing for an exa

Ayesh Gunawardana

The rare inclusive decay $\bar{B}\rightarrow X_sγ$ is an important probe of physics beyond the standard model. The largest uncertainty on the decay rate and CP asymmetry comes from operators that appear at order $1/m_b$ in the heavy quark expansion. One of the three leading contributions in the heavy quark expansion, $Q_1^q-Q_{7γ}$ is described by a non-loca

Patrick M. Ogle, Thomas Jarrett, Lauranne Lanz, Michelle Cluver

Super spirals are the most massive star-forming disk galaxies in the universe (Ogle et al. 2016, 2019). We measured rotation curves for 23 massive spirals and find a wide range of fast rotation speeds (240-570 km/s), indicating enclosed dynamical masses of 0.6 - 4E12 Msun. Super spirals with mass in stars log Mstars / Msun > 11.5 break from the baryonic Tull

Giro Candelario, Alicia Cordero, Juan R. Torregrosa

Some fractional Newton methods have been proposed in order to find roots of nonlinear equations using fractional derivatives. In this paper we introduce a fractional Newton method with order $α+1$ and compare with another fractional Newton method with order $2α$. We also introduce a fractional Traub method with order $2α+1$ and compare with its first step (f

The Pierre Auger Collaboration, A. Aab, P. Abreu, M. Aglietta

Contributions of the Pierre Auger Collaboration to the 36th International Cosmic Ray Conference (ICRC 2019), 24 July - 1 August 2019, Madison, Wisconsin, USA.

Ahmed Moussa, Xudong Liu

We consider learning problems of an intuitive and concise preference model, called lexicographic preference lists (LP-lists). Given a set of examples that are pairwise ordinal preferences over a universe of objects built of attributes of discrete values, we want to learn (1) an optimal LP-list that decides the maximum number of these examples, or (2) a near-

Jose Manuel Gomez-Perez, Raul Ortega

Compared to natural images, understanding scientific figures is particularly hard for machines. However, there is a valuable source of information in scientific literature that until now has remained untapped: the correspondence between a figure and its caption. In this paper we investigate what can be learnt by looking at a large number of figures and readi

Amin Talaeizadeh, Duarte Antunes, Hossein Nejat Pishkenari, Aria Alasty

It is wellknown that helicopters descending fast may enter the so called VRS, a region in the velocity space where the blade's lift differs significantly from regular regions. This may lead to instability and therefore this region is avoided, typically by increasing the horizontal speed. This paper researches this phenomenon in the context of small scale

Florian Kirchschlager, Franziska D. Schmidt, M. J. Barlow, Erica L. Fogerty

Observations of the ejecta of core-collapse supernovae have shown that dust grains form in over-dense gas clumps in the expanding ejecta. The clumps are later subject to the passage of the reverse shock and a significant amount of the newly formed dust material can be destroyed due to the high temperatures and high velocities in the post-shock gas. To determ

Alessia Battisti, Sarah Ebling

In this paper, we present a corpus for use in automatic readability assessment and automatic text simplification of German. The corpus is compiled from web sources and consists of approximately 211,000 sentences. As a novel contribution, it contains information on text structure, typography, and images, which can be exploited as part of machine learning appr

Joseph Allen, Ahmed Moussa, Xudong Liu

In this work, we present a novel human-in-the-loop framework to help the human user understand the decision making process that involves choosing preferred options. We focus on qualitative preference models over alternatives from combinatorial domains. This framework is interactive: the user provides her behavioral data to the framework, and the framework ex

Ziyao Zhang, Liang Ma, Konstantinos Poularakis, Kin K. Leung

In distributed software-defined networks (SDN), multiple physical SDN controllers, each managing a network domain, are implemented to balance centralised control, scalability, and reliability requirements. In such networking paradigms, controllers synchronize with each other, in attempts to maintain a logically centralised network view. Despite the presence

Bashar H. Malkawi, Mohammad I. El-Shafie

Rules of origin (ROO) are pivotal element of the Greater Arab Free Trade Area (GAFTA). ROO are basically established to ensure that only eligible products receive preferential tariff treatment. Taking into consideration the profound implications of ROO for enhancing trade flows and facilitating the success of regional integration, this article sheds light on

Titus Leistner, Hendrik Schilling, Radek Mackowiak, Stefan Gumhold

We propose a method for depth estimation from light field data, based on a fully convolutional neural network architecture. Our goal is to design a pipeline which achieves highly accurate results for small- and wide-baseline light fields. Since light field training data is scarce, all learning-based approaches use a small receptive field and operate on small

Sarat Chandra Varanasi

Our research concerns generating imperative programs from Answer Set Programming Specifications. ASP is highly declarative and is ideal for writing specifications. Further with negation-as-failure it is easy to succinctly represent combinatorial search problems. We are currently working on synthesizing imperative programs from ASP programs by turning the neg

Osama D. Sweidan, Bashar H. Malkawi

We seek to investigate the effect of oil price on UAE goods trade deficit with the U.S. The current increase in the price of oil and the absence of significant studies in the UAE economy are the main motives behind the current study. Our paper focuses on a small portion of UAE trade, which is 11% of the UAE foreign trade, however, it is a significant part si

Tong Wang, Tongtong Zhu, Tim J. Puchtler, Claudius C. Kocher

Non-polar (11-20) a-plane quantum dots (QDs) are strong candidates for both > 200 K on-chip ultrafast polarized single-photon generation and the investigation of high temperature semiconductor QD photophysics. In this work, we report progress in the growth of a-plane InGaN QDs with a quasi-two-temperature method, which produces smooth epilayers and significa

Alex Clesio Nunes Martins, Mark W. Suffak, Hubert de Guise

We discuss the construction and symmetries of su(3) Clebsch-Gordan coefficients arising from the su(3) basis states constructed as triple tensor products of two-dimensional harmonic oscillator states. Because of the su(2) symmetry of the basis states, matrix elements and recursion relations are easily expressed in terms of su(2) technology. As the Weyl group

Jamie Watson, Michael Firman, Gabriel J. Brostow, Daniyar Turmukhambetov

Monocular depth estimators can be trained with various forms of self-supervision from binocular-stereo data to circumvent the need for high-quality laser scans or other ground-truth data. The disadvantage, however, is that the photometric reprojection losses used with self-supervised learning typically have multiple local minima. These plausible-looking alte

Avraham Aizenbud, Raf Cluckers

In the context of geometry and analysis on non-archimedean local fields, we study two recent notions, $C^{\mathrm exp}$-class distributions from [11] and WF-holonomicity from [1], and we show that any distribution of $C^{\mathrm exp}$-class is WF-holonomic. Thus we answer a question from [1] by providing a framework of WF-holonomic distributions for non-arch

Steve Tonneau, Daeun Song, Pierre Fernbach, Nicolas Mansard

One of the main challenges of planning legged locomotion in complex environments is the combinatorial contact selection problem. Recent contributions propose to use integer variables to represent which contact surface is selected, and then to rely on modern mixed-integer (MI) optimization solvers to handle this combinatorial issue. To reduce the computationa

Eryk Lipka

We will consider some extensions of the polygonal art gallery problem. In a recent paper Morrison has shown the smallest (9 sides) example of an art gallery that cannot be observed by guards placed in every third corner. Author also mentioned two related problems, for which the minimal examples are not known. We will show that a polygonal fortress such that

Pian Yu, Dimos V. Dimarogonas

Discrete abstractions have become a standard approach to assist control synthesis under complex specifications. Most techniques for the construction of discrete abstractions are based on sampling of both the state and time spaces, which may not be able to guarantee safety for continuous-time systems. In this work, we aim at addressing this problem by conside

Wei Su, Martin White, Anthony G. Williams, Yongcheng Wu

Current interpretations of the LHC results on two Higgs doublet models (2HDM) underestimate the sensitivity due to neglecting higher order effects. In this work, we revisit the impact of these effects using the current cross-section times branching ratio limits of the $A\to hZ, H \to VV$ and $H\to hh$ channels. With a degenerate heavy Higgs mass $m_Φ$, we fi

A. Strantzalis, D. Hatzidimitriou, A. Zezas, V. Antoniou

We present the results of the photometric analysis of a large part of the main body of the Small Magellanic Cloud. Using the 6.5m Magellan Telescope at the Las Campanas Observatory in Chile, we have acquired deep B and I images in four fields (0.44 degree each in diameter), yielding accurate photometry for 1,068,893 stars down to 24th magnitude, with a spati

Juri Opitz

We formulate argumentative relation classification (support vs. attack) as a text-plausibility ranking task. To this aim, we propose a simple reconstruction trick which enables us to build minimal pairs of plausible and implausible texts by simulating natural contexts in which two argumentative units are likely or unlikely to appear. We show that this method

Alexei Glutsyuk, Ivan Izmestiev, Serge Tabachnikov

By a classical result of Darboux, a foliation of a Riemannian surface has the Graves property (also known as the strong evolution property) if and only if the foliation comes from a Liouville net. A similar result of Blaschke says that a pair of orthogonal foliations has the Ivory property if and only if they form a Liouville net. Let us say that a geodesica

Andrew A. Catellier, Stephen D. Voran

We describe a new convolutional framework for waveform evaluation, WEnets, and build a Narrowband Audio Waveform Evaluation Network, or NAWEnet, using this framework. NAWEnet is single-ended (or no-reference) and was trained three separate times in order to emulate PESQ, POLQA, or STOI with testing correlations 0.95, 0.92, and 0.95, respectively when trainin

Damien Gayet

Let $n\geq 1$ be an integer, $\mathcal L \subset \mathbb{R}^n$ be a compact smooth affine real hypersurface, not necessarily connected. We prove that there exists $c>0$ and $d_0\geq 1$, such that for any $d\geq d_0$, any smooth complex projective hypersurface $Z$ in $\mathbb{C} P^n$ of degree $d$ contains at least $ c\dim H_*(Z, \mathbb{R})$ disjoint Lagrang

Ciprian Tudor, Nakahiro Yoshida

By combining the Malliavin calculus with Fourier techniques, we develop a high-order asymptotic expansion theory for a sequence of vector-valued random variables. Our asymptotic expansion formulas give the development of the characteristic functional and of the local density of the random vectors up to an arbitrary order. We analyzed in details an example re

Xiao-Long Ren, Nino Antulov-Fantulin

Finding a set of nodes in a network, whose removal fragments the network below some target size at minimal cost is called network dismantling problem and it belongs to the NP-hard computational class. In this paper, we explore the (generalized) network dismantling problem by exploring the spectral approximation with the variant of the power-iteration method.

K. Lacombe, C. Amoros, J. -L. Atteia, A. Bajat

We discuss the need for very large detection planes for the detection of hard X-ray transients in the multi-messenger era that started with the quasi-simultaneous detection of GRB~170817A by \textit{Fermi}/GBM and \textit{INTEGRAL}/SPI on one hand and the gravitational waves event GW 170817, detected by the LVC collaboration, on the other hand. Then, we pres

Fatma Ezzahra Salem, Tijani Chahed, Eitan Altman, Azeddine Gati

We study in this paper optimal control strategy for Advanced Sleep Modes (ASM) in 5G networks. ASM correspond to different levels of sleep modes ranging from deactivation of some components of the base station for several micro-seconds to switching off of almost all of them for one second or more. ASMs are made possible in 5G networks thanks to the definitio

Chaoping Zhang, Florian Dubost, Marleen de Bruijne, Stefan Klein

Deep learning has been successfully demonstrated in MRI reconstruction of accelerated acquisitions. However, its dependence on representative training data limits the application across different contrasts, anatomies, or image sizes. To address this limitation, we propose an unsupervised, auto-calibrated k-space completion method, based on a uniquely designe

Sarah Ayman Goldrup, Kaitlyn Phillipson

Neural codes, represented as collections of binary strings, encode neural activity and show relationships among stimuli. Certain neurons, called place cells, have been shown experimentally to fire in convex regions in space. A natural question to ask is: Which neural codes can arise as intersection patterns of convex sets? While past research has established

Ruben Becker, Yuval Emek, Christoph Lenzen

In many models for large-scale computation, decomposition of the problem is key to efficient algorithms. For distance-related graph problems, it is often crucial that such a decomposition results in clusters of small diameter, while the probability that an edge is cut by the decomposition scales linearly with the length of the edge. There is a large body of

Murthy Durbhakula

Major chip manufacturers have all introduced Multithreaded processors. These processors are used for running a variety of workloads. Efficient resource utilization is an important design aspect in such processors. Depending on the workload, mis-speculated execution can severely impact resource utilization and power utilization. In general, compared to a unip

Hope Mogale, Michael Esiefarienrhe, Naison Gasela, Lucia Letlonkane

In this paper we present a novel strategy for accelerating green computing by utilizing and adopting the Hybrid Asymmetric Multicore Architectures (HAMA) model with Safe Parallelism. Most of the modern computing is serial and contributes to the global footprint of energy consumption. These impacts are often witnessed and experienced in many server farms and

Jaap Jumelet, Willem Zuidema, Dieuwke Hupkes

Extensive research has recently shown that recurrent neural language models are able to process a wide range of grammatical phenomena. How these models are able to perform these remarkable feats so well, however, is still an open question. To gain more insight into what information LSTMs base their decisions on, we propose a generalisation of Contextual Deco

Tzuf Paz-Argaman, Reut Tsarfaty

Following navigation instructions in natural language requires a composition of language, action, and knowledge of the environment. Knowledge of the environment may be provided via visual sensors or as a symbolic world representation referred to as a map. Here we introduce the Realistic Urban Navigation (RUN) task, aimed at interpreting navigation instructio

R. Guerin

This note is concerned with the impact on job latency of splitting a token bucket into multiple sub-token buckets with equal aggregate parameters and offered the same job arrival process. The situation commonly arises in distributed computing environments where job arrivals are rate controlled (each job needs one token to enter the system), but capacity limi

Tom Bridgeland, Antony Maciocia

We examine the extent to which a smooth minimal complex projective surface X is determined by its derived category of coherent sheaves D(X). To do this we find, for each such surface X, the set of surfaces Y for which there exists a Fourier-Mukai transform D(Y) --> D(X).

Aviral Goel, Jan Vitek

The R programming language has been lazy for over twenty-five years. This paper presents a review of the design and implementation of call-by-need in R, and a data-driven study of how generations of programmers have put laziness to use in their code. We analyze 16,707 packages and observe the creation of 270.9 B promises. Our data suggests that there is litt

Alexander Levin

We use the method of characteristic sets with respect to two term orderings to prove the existence and obtain a method of computation of a bivariate Kolchin-type dimension polynomial associated with a non-reflexive difference-differential ideal in the algebra of difference-differential polynomials with several basic derivations and one translation. In partic

V. Guzey, M. Klasen

We present a next-to-leading order QCD calculation of inclusive dijet photoproduction in ultraperipheral Pb-Pb collisions at the LHC and show that the results agree very well with various kinematic distributions measured by the ATLAS collaboration. The effect of including these data in nCTEQ or EPPS16 nuclear parton density functions (nPDFs) is then studied

Julio Andrade, Asmaa Shamesaldeen

In this paper we extend the hybrid Euler-Hadamard product model for quadratic Dirichlet $L$-functions associated to irreducible polynomials over function fields. We also establish an asymptotic formula for the first twisted moment in this family of L-functions and then we provide further evidence for the conjectural asymptotic formulas for its moments.

Davor Sudar, Roman Brajša, Ivica Skokić, Arnold O. Benz

Science Verification (SV) data of solar observations with Atacama Large Millimeter-submillimeter Array (ALMA) telescope were released to the scientific community. Understanding the centre to limb brightness function is necessary to compare features in full disk images. Our goals are to find the empirical centre to limb brightness functions in two available s

A. Chiotellis, P. Boumis, S. Derlopa, W. Steffen

We present a model for the Galactic supernova remnant (SNR) VRO 42.05.01, suggesting that its intriguing morphology can be explained by a progenitor model of a supersonically moving, mass losing star. The mass outflows of the progenitor star were in the form of an asymmetric stellar wind focused on the equatorial plane of the star. The systemic motion of the