December 2020 arXiv papers — page 124

A. Santamaría-Miranda, I. de Gregorio-Monsalvo, A. L. Plunkett, N. Huélamo

The dominant mechanism leading to the formation of brown dwarfs (BDs) remains uncertain. The most direct keys to formation, which are obtained from younger objects (pre-BD cores and proto-BDs), are limited by the very low number statistics available. We aim to identify and characterize a set of pre- and proto-BDs as well as Class II BDs in the Lupus 1 and 3

Xiao-Chuan Wu, Wenjie Ji, Cenke Xu

We study the concept of "categorical symmetry" introduced recently, which in the most basic sense refers to a pair of dual symmetries, such as the Ising symmetries of the $1d$ quantum Ising model and its self-dual counterpart. In this manuscript we study discrete categorical symmetry at higher dimensional critical points and gapless phases. At these

Samir Choudhuri, Preetha Saha, Nirupam Roy, Somnath Bharadwaj

The study of the intensity fluctuation power spectrum of individual supernova remnants (SNRs) can reveal the structures present at sub-pc scales, and also constrain the physical process that generates those structures. There are various effects, such as the remnant shell thickness, projection of a three-dimensional structure onto a two-dimensional observatio

Charli M. Sakari, Matthew D. Shetrone, Andrew McWilliam, George Wallerstein

G1, also known as Mayall II, is one of the most massive star clusters in M31. Its mass, ellipticity, and location in the outer halo make it a compelling candidate for a former nuclear star cluster. This paper presents an integrated light abundance analysis of G1, based on a moderately high-resolution (R=15,000) spectrum obtained with the High Resolution Spec

Roberto Soria, Manfred Pakull, Christian Motch, James Miller-Jones

Some ultraluminous X-ray sources (ULXs) are surrounded by collisionally ionized bubbles, larger and more energetic than supernova remnants: they are evidence of the powerful outflows associated with super-Eddington X-ray sources. We illustrate the most recent addition to this class: a huge (350 pc x 220 pc in diameter) bubble around a ULX in NGC 5585. We mod

Jun Gao, Xiao-Wei Wang, Wen-Hao Zhou, Zhi-Qiang Jiao

Quantum computer, harnessing quantum superposition to boost a parallel computational power, promises to outperform its classical counterparts and offer an exponentially increased scaling. The term "quantum advantage" was proposed to mark the key point when people can solve a classically intractable problem by artificially controlling a quantum system

Eric V. Linder, Stephen Appleby

When faced with two nigh intractable problems in cosmology -- how to remove the original cosmological constant problem and how to parametrize modified gravity to explain current cosmic acceleration -- we can make progress by counterposing them. The well tempered solution to the cosmological constant through degenerate scalar field dynamics also relates dispa

Shahar Hod

The existence of closed null circular geodesics around black holes is one of the most intriguing predictions of general relativity. It has recently been conjectured that the radii of black-hole photonspheres are bounded from below by the simple relation $r_{\text{ph}}\geq {3\over2}r_{\text{H}}$, where $r_{\text{H}}$ is the radius of the outer black-hole hori

Dongwook Lim, Young-Wook Lee, Andreas Koch, Seungsoo Hong

The double red clump (RC) observed in color-magnitude diagrams of the Milky Way bulge is at the heart of the current debate on the structure and formation origin of the bulge. This feature can be explained by the difference between the two RCs either in distance ("X-shaped scenario") or in chemical composition ("multiple-population scenario")

Marieke Postma, Graham White

To obtain a first order phase transition requires large new physics corrections to the Standard Model (SM) Higgs potential. This implies that the scale of new physics is relatively low, raising the question whether an effective field theory (EFT) description can be used to analyse the phase transition in a (nearly) model-independent way. We show analytically

Jorge F. M. Delgado, Carlos A. R. Herdeiro, Eugen Radu

We construct and analyse Kerr black holes (BHs) with synchronised axionic hair. These are the BH generalisations of the recently constructed rotating axion boson stars arXiv:2005.05982. Such BHs are stationary, axially symmetric, asymptotically flat solutions of the complex Einstein-Klein-Gordon theory with a QCD axion-like potential. They are regular everyw

E. Asencio, I. Banik, P. Kroupa

El Gordo (ACT-CL J0102-4915) is an extremely massive galaxy cluster ($M_{200} \approx 3 \times 10^{15}$ $M_{\odot}$) at redshift $z = 0.87 $ composed of two subclusters with mass ratio 3.6 merging at speed $V_{infall} \approx 2500$ km/s. Such a fast collision between individually rare massive clusters is unexpected in Lambda cold dark matter ($Λ$CDM) cosmolo

André R. da Silva, Rodolfo Smiljanic, Riano E. Giribaldi

Metal-poor stars play an import role in the understanding of Galaxy formation and evolution. Evidence of the early mergers that built up the Galaxy might remain in the distributions of abundances, kinematics, and orbital parameters of the stars. In this work, we report on preliminary results of an on-going chemo-kinematic analysis of a sample of metal-poor (

John Southworth, D. M. Bowman, K. Pavlovski

We present an analysis of the high-mass eclipsing binary system VV Ori based on photometry from the TESS satellite. The primary star (B1V, 9.5 Msun) shows beta Cephei pulsations and the secondary (B7V, 3.8 Msun) is possibly a slowly-pulsating B star. We detect 51 significant oscillation frequencies, including two multiplets with separations equal to the orbi

C. Porzio, C. Michelagnoli, N. Cieplicka-Orynczak, M. Sferrazza

An extended investigation of the low-spin structure of the $^{65}$Ni nucleus was performed at the Institut Laue-Langevin, Grenoble, via the neutron capture reaction $^{64}$Ni(n,$γ$)$^{65}$Ni, using the FIPPS HPGe array. The level scheme of $^{65}$Ni was significantly expanded, with 2 new levels and 87 newly found transitions. Angular correlation analyses wer

Alexandre Baldare, Rémi Côme, Victor Nistor

Let $G$ be a compact Lie group acting smoothly on a smooth, compact manifold $M$, let $P \in ψ^m(M; E_0, E_1)$ be a $G$--invariant, classical pseudodifferential operator acting between sections of two vector bundles $E_i \to M$, $i = 0,1$, and let $α$ be an irreducible representation of the group $G$. Then $P$ induces a map $π_α(P) : H^s(M; E_0)_α\to H^{s-m}

Daohuai Jiang, Hengrong Lan, Yiyun Wang, Feng Gao

Photoacoustic tomography (PAT) is an emerging technology for biomedical imaging that combines the superiorities of high optical contrast and acoustic penetration. In the PAT system, more photoacoustic (PA) signals are preferred to be detected from full field of view to reconstruct PA images with higher fidelity. However, the requirement for more PA signals d

Allen Roush

Competitive Debate's increasingly technical nature has left competitors looking for tools to accelerate evidence production. We find that the unique type of extractive summarization performed by competitive debaters - summarization with a bias towards a particular target meaning - can be performed using the latest innovations in unsupervised pre-trained

Xiaoyi Dong, Jianmin Bao, Dongdong Chen, Weiming Zhang

DeepFake detection has so far been dominated by ``artifact-driven'' methods and the detection performance significantly degrades when either the type of image artifacts is unknown or the artifacts are simply too hard to find. In this work, we present an alternative approach: Identity-Driven DeepFake Detection. Our approach takes as input the suspect

Pratul P. Srinivasan, Boyang Deng, Xiuming Zhang, Matthew Tancik

We present a method that takes as input a set of images of a scene illuminated by unconstrained known lighting, and produces as output a 3D representation that can be rendered from novel viewpoints under arbitrary lighting conditions. Our method represents the scene as a continuous volumetric function parameterized as MLPs whose inputs are a 3D location and

Ali Davody, Mahmoud Safari, Răzvan V. Florian

We propose a new method of program learning in a Domain Specific Language (DSL) which is based on gradient descent with no direct search. The first component of our method is a probabilistic representation of the DSL variables. At each timestep in the program sequence, different DSL functions are applied on the DSL variables with a certain probability, leadi

Eric Blais, Renato Ferreira Pinto, Nathaniel Harms

We consider the problem of determining which classes of functions can be tested more efficiently than they can be learned, in the distribution-free sample-based model that corresponds to the standard PAC learning setting. Our main result shows that while VC dimension by itself does not always provide tight bounds on the number of samples required to test a c

Xinxin Chen, Christophe Garban, Atul Shekhar

In this work, we characterize all the point processes $θ=\sum_{i\in \mathbb{N}} δ_{x_i}$ on $\mathbb{R}$ which are left invariant under branching Brownian motions with critical drift $-\sqrt{2}$. Our characterization holds under the only assumption that $θ(\mathbb{R}_+)<\infty$ almost surely.

John Keith Magali

Classically, anisotropic surface wave tomography is treated as an optimisation problem where it proceeds through a linearised two-step approach. It involves the construction of 2D group or phase velocity maps for each considered period, followed by the inversion of local dispersion curves inferred from these maps for 1D depth-functions of the elastic paramet

Xinxin Chen, Christophe Garban, Atul Shekhar

In this note, we give a new proof of Liggett&#39;s theorem on the invariant measures of independent particle systems from [Lig78] in the particular case of independent drifted Brownian motions. This particular case has received a lot of attention recently due to its applications for the analysis of the local extrema of discrete Gaussian free field. The novel

André Gaul, Jörg Liesen

The federated Byzantine agreement system (FBAS) is a consensus model introduced by Mazières in 2016 where the participating nodes conceptually form a network, with links between them being established by each node individually and thus in a decentralized way. An important question is whether these decentralized decisions lead to an overall decentralized netw

Saim Wani, Shivansh Patel, Unnat Jain, Angel X. Chang

Navigation tasks in photorealistic 3D environments are challenging because they require perception and effective planning under partial observability. Recent work shows that map-like memory is useful for long-horizon navigation tasks. However, a focused investigation of the impact of maps on navigation tasks of varying complexity has not yet been performed.

Joakim Johnander, Emil Brissman, Martin Danelljan, Michael Felsberg

Most existing approaches to video instance segmentation comprise multiple modules that are heuristically combined to produce the final output. Formulating a purely learning-based method instead, which models both the temporal aspect as well as a generic track management required to solve the video instance segmentation task, is a highly challenging problem.

Lixin Sun, Jonathan Vandermause, Simon Batzner, Yu Xie

Computing accurate reaction rates is a central challenge in computational chemistry and biology because of the high cost of free energy estimation with unbiased molecular dynamics. In this work, a data-driven machine learning algorithm is devised to learn collective variables with a multitask neural network, where a common upstream part reduces the high dime

Suhas Lohit, Michael Jones

Model compression methods are important to allow for easier deployment of deep learning models in compute, memory and energy-constrained environments such as mobile phones. Knowledge distillation is a class of model compression algorithm where knowledge from a large teacher network is transferred to a smaller student network thereby improving the student&#39

A. V. Chukhnova, A. E. Lobanov

We study the propagation of neutrinos from compact astrophysical objects with strong magnetic field, such as magnetars. Both neutrino spin rotation and oscillations in a realistic three-flavor model are taken into account. We solve the neutrino evolution equation in the magnetic field near the object and obtain the probabilities of all possible spin-flavor t

Filippo Biondi, Pia Addabbo, Carmine Clemente, Danilo Orlando

We design the proof of concept for high-resolution (HR) real-time (RT), Geosynchronous and Geostationary (Geo) Polarimetric (Pol) using orbital angular momentum (OAM) interferometry - radio detection and ranging (RADAR) (HR-RT-GeoPolInt-OAM-RADAR) and multi-chromatic analysis (MCA) extended to Tomography (HR-RT-GeoPolInt-OAM-MCA-TomoRADAR). The OAM interfero

Qian Luo, Jing Wu, Matthew Gombolay

Learning from demonstration (LfD) is a powerful learning method to enable a robot to infer how to perform a task given one or more human demonstrations of the desired task. By learning from end-user demonstration rather than requiring that a domain expert manually programming each skill, robots can more readily be applied to a wider range of real-world appli

V. M. Malkin, N. J. Fisch

Exact four-photon resonance of collinear planar laser pulses is known to be prohibited by the classical dispersion law of electromagnetic waves in plasma. We show here that the renormalization produced by an arbitrarily small relativistic electron nonlinearity removes this prohibition. The laser frequency shifts in collinear resonant four-photon scattering i

Elias R. Most, L. Jens Papenfort, Samuel Tootle, Luciano Rezzolla

High-mass gravitational-wave events in the neutron-star mass range, such as GW190425, have recently started to be detected by the LIGO/Virgo detectors. If the masses of the two binary components fall in the neutron-star mass range, such a system is typically classified as a binary neutron-star system, although the detected gravitational-wave signal may be to

Wolfgang Lucha, Dmitri Melikhov, Hagop Sazdjian

We discuss the Operator Product Expansion (OPE) and quark-hadron duality for two-point Green functions of tetraquark currents. We emphasize that the factorizable part of the OPE series for such Green functions, including nonperturbative contributions described by QCD condensates, is saturated by the full system of ordinary hadrons and therefore cannot have a

Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi

In this paper we prove that the sample complexity of properly learning a class of Littlestone dimension $d$ with approximate differential privacy is $\tilde O(d^6)$, ignoring privacy and accuracy parameters. This result answers a question of Bun et al. (FOCS 2020) by improving upon their upper bound of $2^{O(d)}$ on the sample complexity. Prior to our work,

Amalie Trewartha, John Dagdelen, Haoyan Huo, Kevin Cruse

The ongoing COVID-19 pandemic has had far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community&#39;s COVID-19 response has lead to the emergence of new research literature on a remarkable scale -- as of October 2020, over 81,000 COVID-19 related scientific papers have been released, at a

Ioannis Caltzidis, Harald Kübler, Tilman Pfau, Robert Löw

We demonstrate an atomic Faraday dichroic beam splitter suitable to spatially separate signal and idler fields from pump degenerate four-wave mixing in an atomic source. By rotating the plane of polarization of one mode $90^{\circ}$ with respect to the other, a subsequent polarizing beam splitter separates the two frequencies, which differ by only 13.6 GHz,

Matthew Corsetti, Ernest Fokoué

Nonnegative matrix factorization (NMF) is a relatively new unsupervised learning algorithm that decomposes a nonnegative data matrix into a parts-based, lower dimensional, linear representation of the data. NMF has applications in image processing, text mining, recommendation systems and a variety of other fields. Since its inception, the NMF algorithm has b

Emil Karshalev, Cristian Silva-Lopez, Kyle Chan, Jieming Yan

Herein, self-healing small-scale swimmers capable of autonomous propulsion and on-the-fly structural recovery are described. The new strategy instantaneously restores the functionality of the swimmer after it has suffered severe damage. Incorporation of magnetic microparticles in strips along with the printed functional body layers (consisting of conductive

Marcelo T. Yamashita, Tobias Frederico, Lauro Tomio

A three-atom molecule AAB, formed by two identical bosons A and a distinct one B, is studied by considering coupled channels close to a Feshbach resonance. It is assumed that the subsystems AB and AA have, respectively, one and two channels, where, in this case, AA has open and closed channels separated by an energy gap. The induced three-body interaction ap

Avantika Singh, Chirag Vashist, Pratyush Gaurav, Aditya Nigam

Massive biometric deployments are pervasive in today&#39;s world. But despite the high accuracy of biometric systems, their computational efficiency degrades drastically with an increase in the database size. Thus, it is essential to index them. An ideal indexing scheme needs to generate codes that preserve the intra-subject similarity as well as inter-subje

M. Trevisan, G. A. Mamon, T. X. Thuan, F. Ferrari

In the local Universe, there is a handful of dwarf compact star-forming galaxies with extremely low oxygen abundances. It has been proposed that they are young, having formed a large fraction of their stellar mass during their last few hundred Myr. However, little is known about the fraction of young stellar populations in more massive galaxies. In a previou

Munish Sharma

The waste heat management becomes very important with increasing energy demand and limited fossil resources. Here, we demonstrate thermoelectric performance of allotropic TeSe2. Based on the first-principle calculations, we confirm the energetic and kinetic stability of five TeSe2 allotropes. We predict δ-TeSe2 as a new direct band gap semiconductor having 1

D. S. Smirnov, A. V. Shumilin

We demonstrate that nuclear spin fluctuations lead to the electric current noise in the mesoscopic samples of organic semiconductors showing the pronounced magnetoresistance in weak fields. For the bipolaron and electron-hole mechanisms of organic magnetoresistance, the current noise spectrum consists of the high frequency peak related to the nuclear spin pr

Colin Defant

Let $s$ denote West&#39;s stack-sorting map. For all positive integers $m$ and all integers $n\geq 2m-2$, we give a simple characterization of the set $s^{n-m}(S_n)$; as a consequence, we find that $|s^{n-m}(S_n)|$ is the $m^\text{th}$ Bell number $B_m$. We also prove that the restriction $n\geq 2m-2$ is tight by showing that $|s^{m-3}(S_{2m-3})|=B_m+m-2$ fo

J. Belhadi, F. Ravaux, H. Bouyanfif, M. Jouiad

We report on quantification and elastic strain mapping in two artificial BaZrO3/BaTiO3 (BZ/BT) superlattices having periods of 6.6 nm and 11 nm respectively, grown on (001) SrTiO3 single crystal substrate by pulsed laser deposition technique. The methodology consists of a combination of high-resolution scanning transmission electron microscopy and nanobeam e

Lizhen Tan, Olga Golovneva

With the recent explosion in popularity of voice assistant devices, there is a growing interest in making them available to user populations in additional countries and languages. However, to provide the highest accuracy and best performance for specific user populations, most existing voice assistant models are developed individually for each region or lang

Ryan M. Corey, Andrew C. Singer

Hearing aids use dynamic range compression (DRC), a form of automatic gain control, to make quiet sounds louder and loud sounds quieter. Compression can improve listening comfort, but it can also cause distortion in noisy environments. It has been widely reported that DRC performs poorly in noise, but there has been little mathematical analysis of these dist

José Lopes, Francisco J. Chiyah Garcia, Helen Hastie

Challenges around collecting and processing quality data have hampered progress in data-driven dialogue models. Previous approaches are moving away from costly, resource-intensive lab settings, where collection is slow but where the data is deemed of high quality. The advent of crowd-sourcing platforms, such as Amazon Mechanical Turk, has provided researcher

M. Ciavarella, A. Papangelo, G. Cricri

In a recent very interesting and illuminating proposal, Yao et al. (2014) have discussed the use of the strain energy release rate (SERR) as a parameter to characterize fatigue delamination growth in composite materials. They consider fatigue delamination data strongly affected by R-curve behaviour due to fibres bridging and argue that a better approach is t

G. Peter Lepage

This article describes how the author successfully adapted techniques drawn from the literature on active learning for use in a graduate-level course on quantum field theory. Students completed readings and online questions ahead of each class and spent class time working through problems that required them to practice the decisions and skills typical of a t

Jean-Baptiste Camps, Thibault Clérice, Ariane Pinche

Stylometric analysis of medieval vernacular texts is still a significant challenge: the importance of scribal variation, be it spelling or more substantial, as well as the variants and errors introduced in the tradition, complicate the task of the would-be stylometrist. Basing the analysis on the study of the copy from a single hand of several texts can part

Gyutaek Oh, Hyokyoung Bae, Hyun-Seo Ahn, Sung-Hong Park

Quantitative susceptibility mapping (QSM) is a useful magnetic resonance imaging (MRI) technique which provides spatial distribution of magnetic susceptibility values of tissues. QSMs can be obtained by deconvolving the dipole kernel from phase images, but the spectral nulls in the dipole kernel make the inversion ill-posed. In recent times, deep learning ap

Supratim Das Bakshi, Joydeep Chakrabortty, Michael Spannowsky

Effective theories are well established theoretical frameworks to describe the effect of energetically widely separated UV models on observables at lower energy scales. Due to the complexity of the effective theory when taking all the Standard Model symmetries and degrees of freedoms into account, tensioning the entire system in a completely agnostic way aga

Francesco Calavalle, Paul Dreher, Ananthu P. Surdendran, Wen Wan

Two-dimensional transition metal dichalcogenides (TMDs) represent an ideal testbench for the search of materials by design, because their optoelectronic properties can be manipulated through surface engineering and molecular functionalization. However, the impact of molecules on intrinsic physical properties of TMDs, such as superconductivity, remains largel

Francesco Furno

I study the economic effects of testing during the outbreak of a novel disease. I propose a model where testing permits isolation of the infected and provides agents with information about the prevalence and lethality of the disease. Additional testing reduces the perceived lethality of the disease, but might increase the perceived risk of infection. As a re

Timothee Mickus, Timothée Bernard, Denis Paperno

Compositionality is a widely discussed property of natural languages, although its exact definition has been elusive. We focus on the proposal that compositionality can be assessed by measuring meaning-form correlation. We analyze meaning-form correlation on three sets of languages: (i) artificial toy languages tailored to be compositional, (ii) a set of Eng

Fei Huang, Alexandre Sava, Kondo H. Adjallah, Wang Zhouhang

Condition-based maintenance of rotating mechanics requests efficient bearings degradation monitoring. The accuracy of bearings degradation measure depends largely on degradation indicators. To extract efficient indicators, in this paper we propose a method based on the discarded projected space information and piecewise linear representation (PLR) to build t

Sam Armon, Tom Halverson

We derive a formula for the entries in the change-of-basis matrix between Young&#39;s seminormal and natural representations of the symmetric group. These entries are determined as sums over weighted paths in the weak Bruhat graph on standard tableaux, and we show that they can be computed recursively as the weighted sum of at most two previously-computed en

Yael Ben-Guigui, Jacob Goldberger, Tammy Riklin-Raviv

The pressing need to reduce the capacity of deep neural networks has stimulated the development of network dilution methods and their analysis. While the ability of $L_1$ and $L_0$ regularization to encourage sparsity is often mentioned, $L_2$ regularization is seldom discussed in this context. We present a novel framework for weight pruning by sampling from

A. Morbidelli, D. Nesvorny, W. F. Bottke, S. Marchi

We combine several constraints provided by the crater records on Arrokoth and the worlds of the Pluto system to compute the size-frequency distribution (SFD) of the crater production function for craters with diameter D<10km. For this purpose, we use a Kuiper belt objects (KBO) population model calibrated on telescopic surveys, that describes also the evolut

Xinrun Wang, Tarun Nair, Haoyang Li, Yuh Sheng Reuben Wong

Dams impact downstream river dynamics through flow regulation and disruption of upstream-downstream linkages. However, current dam operation is far from satisfactory due to the inability to respond the complicated and uncertain dynamics of the upstream-downstream system and various usages of the reservoir. Even further, the unsatisfactory dam operation can c

Harald Hofstätter

In a recent paper the author derived a formula for calculating common denominators for the homogeneous components of the Baker-Campbell-Hausdorff (BCH) series. In the present work it is proved that this formula actually yields the smallest such common denominators. In an appendix a new efficient algorithm for computing coefficients of the BCH series is prese

Qingjuan Yu

This is an invited commentary on the Nobel Prize in Physics 2020 which was awarded to Roger Penrose &#34;for the discovery that black hole formation is a robust prediction of the general theory of relativity,&#34; and Reinhard Genzel and Andrea Ghez &#34;for the discovery of a supermassive compact object at the center of our galaxy.&#34;

Éireann Leverett, Matilda Rhode, Adam Wedgbury

Why wait for zero-days when you could predict them in advance? It is possible to predict the volume of CVEs released in the NVD as much as a year in advance. This can be done within 3 percent of the actual value, and different predictive algorithms perform well at different lookahead values. It is also possible to estimate the proportions of that total volum

Thierry Bodineau, Isabelle Gallagher, Laure Saint-Raymond, Sergio Simonella

It has been known since Lanford [19] that the dynamics of a hard sphere gas is described in the low density limit by the Boltzmann equation, at least for short times. The classical strategy of proof fails for longer times, even close to equilibrium. In this paper, we introduce a duality method coupled with a pruning argument to prove that the covariance of t

Mohammad Mahdi Khalili, Xueru Zhang, Mahed Abroshan, Somayeh Sojoudi

Supervised learning models have been increasingly used for making decisions about individuals in applications such as hiring, lending, and college admission. These models may inherit pre-existing biases from training datasets and discriminate against protected attributes (e.g., race or gender). In addition to unfairness, privacy concerns also arise when the

Yunfeng Chen, Qingjuan Yu, Youjun Lu

Stars can be consumed (either tidally disrupted or swallowed whole) by massive black holes (MBHs) at galactic centers when they move into the vicinity of the MBHs. In this study, we investigate the rates of stellar consumption by central MBHs and their cosmic distributions, including the effects of triaxial galaxy shapes in enhancing the reservoir of low-ang

Axel Wilson, Aude Bailly, Romain Bernard, Yves Borensztein

Au-Cu bimetallic nanoparticles (NPs) grown on TiO 2 (110) have been followed in-situ using grazing incidence x-ray diffraction and x-ray photoemission spectroscopy from their synthesis to their exposure to a CO/O 2 mixture at low pressure (P < 10-5 mbar) and at different temperatures (300 K-470 K). As-prepared samples are composed of two types of alloyed NPs

Song Fang, Quanyan Zhu

This short note is on a property of the $\mathcal{W}_2$ Wasserstein distance which indicates that independent elliptical distributions minimize their $\mathcal{W}_2$ Wasserstein distance from given independent elliptical distributions with the same density generators. Furthermore, we examine the implications of this property in the Gelbrich bound when the di

Sebastian Höfer, Kostas Bekris, Ankur Handa, Juan Camilo Gamboa

This report presents the debates, posters, and discussions of the Sim2Real workshop held in conjunction with the 2020 edition of the &#34;Robotics: Science and System&#34; conference. Twelve leaders of the field took competing debate positions on the definition, viability, and importance of transferring skills from simulation to the real world in the context

Ruibin Yuan, Ge Zhang, Anqiao Yang, Xinyue Zhang

In this paper, we propose to adapt the method of mutual information maximization into the task of Chinese lyrics conditioned melody generation to improve the generation quality and diversity. We employ scheduled sampling and force decoding techniques to improve the alignment between lyrics and melodies. With our method, which we called Diverse Melody Generat

Joseph D. Romano, Jeffrey S. Hazboun, Xavier Siemens, Anne M. Archibald

The North American Nanohertz Observatory for Gravitational Waves (NANOGrav) has recently reported strong statistical evidence for a common-spectrum red-noise process for all pulsars, as seen in their 12.5-yr analysis for an isotropic stochastic gravitational-wave background. However, there is currently very little evidence for quadrupolar spatial correlation

Bahman Angoshtari, Virginia R. Young

We find the optimal indemnity to minimize the probability of ruin when premium is calculated according to the distortion premium principle with a proportional risk load, and admissible indemnities are such that both the indemnity and retention are non-decreasing functions of the underlying loss. We reformulate the problem with the inverse survival function a

Antonio Bueno, Irene Ortiz

In this paper we study rotational surfaces in the space $\mathbb{H}^2\times\mathbb{R}$ whose mean curvature is given as a prescribed function of their angle function. These surfaces generalize, among others, the ones of constant mean curvature and the translating solitons of the mean curvature flow. Using a phase plane analysis we construct entire rotational

Matthias Wuttig, Carl-Friedrich Schoen, Mathias Schumacher, John Robertson

Third-generation photovoltaic (PV) materials combine many advantageous properties, including a high optical absorption together with a large charge carrier mobility, facilitated by small effective masses. Halide perovskites (ABX3, where X is I, Br or Cl) appear to be the most promising third-generation PV materials at present. Their opto-electronic propertie

Andrew Hryniowski, Alexander Wong

The quantitative analysis of information structure through a deep neural network (DNN) can unveil new insights into the theoretical performance of DNN architectures. Two very promising avenues of research towards quantitative information structure analysis are: 1) layer similarity (LS) strategies focused on the inter-layer feature similarity, and 2) intrinsi

Peter J. Cameron, Bojan Kuzma

The purpose of this note is to define a graph whose vertex set is a finite group $G$, whose edge set is contained in that of the commuting graph of $G$ and contains the enhanced power graph of $G$. We call this graph the deep commuting graph of $G$. Two elements of $G$ are joined in the deep commuting graph if and only if their inverse images in every centra

Eric S. Pahl, W. Nick Street, Hans J. Johnson, Alan I. Reed

Kidney transplantation is the best treatment for end-stage renal failure patients. The predominant method used for kidney quality assessment is the Cox regression-based, kidney donor risk index. A machine learning method may provide improved prediction of transplant outcomes and help decision-making. A popular tree-based machine learning method, random fores

Fuxin Jiang, Chengyuan Zhang, Shaolong Sun, Jingyun Sun

For hourly PM2.5 concentration prediction, accurately capturing the data patterns of external factors that affect PM2.5 concentration changes, and constructing a forecasting model is one of efficient means to improve forecasting accuracy. In this study, a novel hybrid forecasting model based on complete ensemble empirical mode decomposition with adaptive noi

Koya Murakami, Atsushi J. Nishizawa

A novel method images to estimate cosmological parameters based on images is presented. In this paper, we demonstrate the use of a convolutional neural network (CNN) for constraining the mass of dark matter particle. For this purpose, we perform a suite of N-body simulations with different dark matter particle masses to train CNN and estimate dark matter mas

Theodoros Giannakas, Anastasios Giovanidis, Thrasyvoulos Spyropoulos

Caching content over CDNs or at the network edge has been solidified as a means to improve network cost and offer better streaming experience to users. Furthermore, nudging the users towards low-cost content has recently gained momentum as a strategy to boost network performance. We focus on the problem of optimal policy design for Network Friendly Recommend

Ivan Pan

Let K be an algebraically closed field. We prove that a polynomial K-derivation $D$ in two variables is locally nilpotent if and only if the subgroup of polynomial K-automorphisms which commute with D admits elements whose degree is arbitrary big.

Mihai Ciucu

In earlier work we showed that in the bulk, the correlation of gaps in dimer systems on the hexagonal lattice is governed, in the fine mesh limit, by Coulomb&#39;s law for 2D electrostatics. We also proved that the scaling limit of the discrete field ${\bold F}$ of average tile orientations is, up to a multiplicative constant, the electric field produced by

Xiaowei Wu, Bo Li, Jiarui Gan

The Nash social welfare (NSW) is a well-known social welfare measurement that balances individual utilities and the overall efficiency. In the context of fair allocation of indivisible goods, it has been shown by Caragiannis et al. (EC 2016 and TEAC 2019) that an allocation maximizing the NSW is envy-free up to one good (EF1). In this paper, we are intereste

Pilar Oplustil-Gallegos, Simon King

Many speech synthesis datasets, especially those derived from audiobooks, naturally comprise sequences of utterances. Nevertheless, such data are commonly treated as individual, unordered utterances both when training a model and at inference time. This discards important prosodic phenomena above the utterance level. In this paper, we leverage the sequential

Xu Yan, Jiantao Gao, Jie Li, Ruimao Zhang

LiDAR point cloud analysis is a core task for 3D computer vision, especially for autonomous driving. However, due to the severe sparsity and noise interference in the single sweep LiDAR point cloud, the accurate semantic segmentation is non-trivial to achieve. In this paper, we propose a novel sparse LiDAR point cloud semantic segmentation framework assisted

Raghu Pasupathy, Yongjia Song

We present adaptive sequential SAA (sample average approximation) algorithms to solve large-scale two-stage stochastic linear programs. The iterative algorithm framework we propose is organized into \emph{outer} and \emph{inner} iterations as follows: during each outer iteration, a sample-path problem is implicitly generated using a sample of observations or

Igor Lima, Jefferson Silva, Breno Miranda, Gustavo Pinto

Context. JavaScript is a popular programming language today with several implementations competing for market dominance. Although a specification document and a conformance test suite exist to guide engine development, bugs occur and have important practical consequences. Implementing correct engines is challenging because the spec is intentionally incomplet

Jennifer O&#39;Kane, Cecilia Mac Cormack, Cristina H. Mandrini, Pascal Démoulin

Interest in stealth coronal mass ejections (CMEs) is increasing due to their relatively high occurrence rate and space weather impact. However, typical CME signatures such as extreme-ultraviolet dimmings and post-eruptive arcades are hard to identify and require extensive image processing techniques. These weak observational signatures mean that little is cu

Bob Coecke, Giovanni de Felice, Konstantinos Meichanetzidis, Alexis Toumi

We provide conceptual and mathematical foundations for near-term quantum natural language processing (QNLP), and do so in quantum computer scientist friendly terms. We opted for an expository presentation style, and provide references for supporting empirical evidence and formal statements concerning mathematical generality. We recall how the quantum model f

Thanh Thi Nguyen, Hammad Tahir, Mohamed Abdelrazek, Ali Babar

Credit card frauds are at an ever-increasing rate and have become a major problem in the financial sector. Because of these frauds, card users are hesitant in making purchases and both the merchants and financial institutions bear heavy losses. Some major challenges in credit card frauds involve the availability of public data, high class imbalance in data,

Alessandro Pina, Marcos Baez, Florian Daniel

In this paper we explore the opportunities brought by cognitive augmentation to provide a more natural and accessible web browsing experience. We explore these opportunities through \textit{conversational web browsing}, an emerging interaction paradigm for the Web that enables blind and visually impaired users (BVIP), as well as regular users, to access the

Wellington Oliveira, Hugo Matalonga, Gustavo Pinto, Fernando Castor

In the last few years, a growing body of research has proposed methods, techniques, and tools to support developers in the construction of software that consumes less energy. These solutions leverage diverse approaches such as version history mining, analytical models, identifying energy-efficient color schemes, and optimizing the packaging of HTTP requests.

Elnaz Darsheshdar, Mathilde Hugbart, Romain Bachelard, Celso Jorge Villas-Boas

We investigate two-color photon correlations in the light emitted by strongly coupled two-level emitters. Spectral filtering allows us to manipulate the collected light statistics and we show that the resonances induced by dipole-dipole interactions give rise to specific correlations, where the time-symmetry of the correlations is broken. Based on the collec

Lin Chen, Anastasios Giovanidis, Wei Wang, Lin Shan

We formulate and analyze a generic sequential resource access problem arising in a variety of engineering fields, where a user disposes a number of heterogeneous computing, communication, or storage resources, each characterized by the probability of successfully executing the user&#39;s task and the related access delay and cost, and seeks an optimal access

Qing-Sen Chen, Hui-Feng Fu, Yong-Liang Ma, Qing Wang

As a successive work to [Phys.Rev.D 102 (2020), 034034], we derive the $1/m_Q$ corrections to chiral effective Lagrangian for heavy-light mesons from QCD under proper approximations. The low energy constants in the effective Lagrangian are expressed in terms of the light quark self-energy and heavy quark mass $m_Q$. Numerical results of the low energy consta

Zizhen Guo, Wenchuan Wu

As wind power penetration increases, the wind farms are required by newly released grid codes to provide frequency regulation service. The most critical challenge is how to formulate the dynamic model of wind farm for dynamic control, since it is essentially is nonlinear and there are huge amount of parameters to be maintained frequently. This paper proposes