October 2020 arXiv papers — page 26

S. H. Hayakawa, K. Agari, J. K. Ahn, T. Akaishi

In an emulsion-counter hybrid experiment performed at J-PARC, a $\Xi^-$ absorption event was observed which decayed into twin single-$\Lambda$ hypernuclei. Kinematic calculations enabled a unique identification of the reaction process as $\Xi^{-} + ^{14}$N$\ \rightarrow\ ^{10}_\Lambda$Be + $^5_\Lambda$He. For the binding energy of the $\Xi^{-}$ hyperon in th

Clément Maria, Owen Rouillé

Quantum topological invariants have played an important role in computational topology, and they are at the heart of major modern mathematical conjectures. In this article, we study the experimental problem of computing large $r$ values of Turaev-Viro invariants $\mathrm{TV}_r$. We base our approach on an optimized backtracking algorithm, consisting of enume

Rong Chen, Frank Garvan

In 2012 Bryson, Ono, Pitman and Rhoades showed how the generating functions for certain strongly unimodal sequences are related to quantum modular and mock modular forms. They proved some parity results and conjectured some mod 4 congruences for the coefficients of these generating functions. In 2016 Kim, Lim and Lovejoy obtained similar results for odd-bala

Shoham Sabach, Marc Teboulle

In this paper, we aim at unifying, simplifying and improving the convergence rate analysis of Lagrangian-based methods for convex optimization problems. We first introduce the notion of nice primal algorithmic map, which plays a central role in the unification and in the simplification of the analysis of most Lagrangian-based methods. Equipped with a nice pr

Martijn den Besten

In the first part of this paper we show that path categories are enriched over groupoids, in a way that is compatible with a suitable 2-category of path categories. In the second part we introduce a new notion of homotopy exponential and homotopy Pi-type for path categories, the strong homotopy exponential and the strong homotopy Pi-type. We prove some of th

Ethan Y. H. Li, Grace M. X. Li, David G. L. Wang, Arthur L. B. Yang

Motivated by Stanley's $\mathbf{(3+1)}$-free conjecture on chromatic symmetric functions, Foley, Ho\`{a}ng and Merkel introduced the concept of strong $e$-positivity and conjectured that a graph is strongly $e$-positive if and only if it is (claw, net)-free. In order to study strongly $e$-positive graphs, they further introduced the twinning operation on a g

Baptiste Klein, Jean-François Donati, Élodie M. Hébrard, Bonnie Zaire

We report the detection of a large-scale magnetic field at the surface of the slowly-rotating fully-convective M dwarf Proxima Centauri. Ten circular polarization spectra, collected from April to July 2017 with the HARPS-Pol spectropolarimeter, exhibit rotationally-modulated Zeeman signatures suggesting a stellar rotation period of $89.8 \pm 4.0$ d. Using Ze

Margherita Nolasco

We prove the existence of a $L^2$-normalized solitary wave solution for the Maxwell-Dirac equations in (3+1)-Minkowski space. In addition, for the Coulomb-Dirac model, describing fermions with attractive Coulomb interactions in the mean-field limit, we prove the existence of the (positive) energy minimizer.

Wei Fang, Pierre Winter, Jeremy O. Richardson

Semiclassical instanton theory is a form of quantum transition-state theory which can be applied to computing thermal reaction rates for complex molecular systems including quantum tunneling effects. There have been a number of attempts to extend the theory to treat microcanonical rates. However, the previous formulations are either computationally unfeasibl

Ionel-Dumitrel Ghiba, Mircea Bîrsan, Peter Lewintan, Patrizio Neff

We consider a recently introduced geometrically nonlinear elastic Cosserat shell model incorporating effects up to order $O(h^5)$ in the shell thickness $h$. We develop the corresponding geometrically nonlinear constrained Cosserat shell model, we show the existence of minimizers for the $O(h^5)$ and $O(h^3)$ case and we draw some connections to existing mod

Franziska Hannß, Esther Lapczyna, Mathias Müller, Rainer Groh

This case study describes an approach to designing interactive museum installations as a student project with the aim of presenting the research results of the restoration process of paintings to a wide range of visitors. During one and a half years, the Chair of Media Design created five interactive media stations in two lectures to enrich the special exhib

Jason Lapano, Lauren Nuckols, Alessandro R. Mazza, Yun-Yi Pai

We report the growth of the intrinsic magnetic topological system MnTe(Bi2Te3)n by molecular beam epitaxy. By mapping the temperature and the Bi:Mn flux ratio, it is shown that there is a narrow growth window for the n=1 phase MnBi2Te4 with 2.0<Bi:Mn<2.6 at 225 {\deg}C. Here the films are stoichiometric and excess Bi and Te is not incorporated. At higher flu

Geronimo Villanueva, Martin Cordiner, Patrick Irwin, Imke de Pater

The detection of phosphine (PH3) in the atmosphere of Venus has been recently reported based on millimeter-wave radio observations (Greaves et al. 2020), and its re-analyses (Greaves et al. 2021a/b). In this Matters Arising we perform an independent reanalysis, identifying several issues in the interpretation of the spectroscopic data. As a result, we determ

Or Elmackias, Tami Zaretzky, Reuven Segev

We consider the optimization of the vector of grasping forces that support a known generalized force acting on the grasped object---a rigid body or a mechanism. Working in the framework of finite-dimensional normed vector spaces and their dual spaces, the cost function to be minimized is assumed to be a norm on the space of grasping forces. We present an exp

Matthew Pressland

Motivated by Conway and Coxeter's combinatorial results concerning frieze patterns, we sketch an introduction to the theory of cluster algebras and cluster categories for acyclic quivers. The goal is to show how these more abstract theories provide a conceptual explanation for phenomena concerning friezes, principally integrality and periodicity.

Peiyao Wang, Weixin Luo, Yanyu Xu, Haojie Li

Spatial Description Resolution, as a language-guided localization task, is proposed for target location in a panoramic street view, given corresponding language descriptions. Explicitly characterizing an object-level relationship while distilling spatial relationships are currently absent but crucial to this task. Mimicking humans, who sequentially traverse

Manu Tom, Rajanie Prabha, Tianyu Wu, Emmanuel Baltsavias

Continuous observation of climate indicators, such as trends in lake freezing, is important to understand the dynamics of the local and global climate system. Consequently, lake ice has been included among the Essential Climate Variables (ECVs) of the Global Climate Observing System (GCOS), and there is a need to set up operational monitoring capabilities. M

Laurent Bartholdi, Ville Salo

We introduce a notion of "simulation" for labelled graphs, in which edges of the simulated graph are realized by regular expressions in the simulating graph, and prove that the tiling problem (aka "domino problem") for the simulating graph is at least as difficult as that for the simulated graph. We apply this to the Cayley graph of the "lamplighter group" $

Yash Samtani, Jesse Elwell

Insider Attack Detection in commercial networks is a critical problem that does not have any good solutions at this current time. The problem is challenging due to the lack of visibility into live networks and a lack of a standard feature set to distinguish between different attacks. In this paper, we study an approach centered on using network data to ident

Jianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney

Fully quantized training (FQT), which uses low-bitwidth hardware by quantizing the activations, weights, and gradients of a neural network model, is a promising approach to accelerate the training of deep neural networks. One major challenge with FQT is the lack of theoretical understanding, in particular of how gradient quantization impacts convergence prop

K. Atalikov, A. Zotov

We give detailed description for continuous version of the classical IRF-Vertex relation, where on the IRF side we deal with the Calogero-Moser-Sutherland models. Our study is based on constructing modifications of the Higgs bundles of infinite rank over elliptic curve and its degenerations. In this way the previously predicted gauge equivalence between L-A

Agnese Chiatti, Enrico Motta, Enrico Daga, Gianluca Bardaro

Service robots can help with many of our daily tasks, especially in those cases where it is inconvenient or unsafe for us to intervene: e.g., under extreme weather conditions or when social distance needs to be maintained. However, before we can successfully delegate complex tasks to robots, we need to enhance their ability to make sense of dynamic, real wor

James Reeves, Valentina Braito, Delphine Porquet, Andrew Lobban

New Swift monitoring observations of the variable, radio-quiet quasar, PDS 456, are presented. A bright X-ray flare was captured in September 2018, the flux increasing by a factor of 4 and with a doubling time-scale of 2 days. From the light crossing argument, the coronal size is inferred to be about 30 gravitational radii for a black hole mass of $10^{9} {\

Jianhao Jiao, Haoyang Ye, Yilong Zhu, Ming Liu

Combining multiple LiDARs enables a robot to maximize its perceptual awareness of environments and obtain sufficient measurements, which is promising for simultaneous localization and mapping (SLAM). This paper proposes a system to achieve robust and simultaneous extrinsic calibration, odometry, and mapping for multiple LiDARs. Our approach starts with measu

ATLAS Collaboration

A search for the supersymmetric partners of quarks and gluons (squarks and gluinos) in final states containing jets and missing transverse momentum, but no electrons or muons, is presented. The data used in this search were recorded by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV during Run 2 of the Large

Jonte Hance, John Rarity

We give a protocol for ghost imaging in a way that is always counterfactual - while imaging an object, no light interacts with that object. This extends the idea of counterfactuality beyond communication, showing how this interesting phenomenon can be leveraged for metrology. Given, in the infinite limit, no photons ever go to the imaged object, it presents

Quanyu Liao, Xin Wang, Bin Kong, Siwei Lyu

The deep neural network is vulnerable to adversarial examples. Adding imperceptible adversarial perturbations to images is enough to make them fail. Most existing research focuses on attacking image classifiers or anchor-based object detectors, but they generate globally perturbation on the whole image, which is unnecessary. In our work, we leverage higher-l

Axel-Jan Rousseau, Thijs Becker, Jeroen Bertels, Matthew B. Blaschko

Neural networks for automated image segmentation are typically trained to achieve maximum accuracy, while less attention has been given to the calibration of their confidence scores. However, well-calibrated confidence scores provide valuable information towards the user. We investigate several post hoc calibration methods that are straightforward to impleme

Daniel Graves, Johannes Günther, Jun Luo

General value functions (GVFs) in the reinforcement learning (RL) literature are long-term predictive summaries of the outcomes of agents following specific policies in the environment. Affordances as perceived action possibilities with specific valence may be cast into predicted policy-relative goodness and modelled as GVFs. A systematic explication of this

Jan Franz, Barry Mant, Lola González-Sánchez, Roland Wester

We present an extensive range of quantum calculations for the state-changing rotational dynamics involving two simple molecular anions which are expected to play some role in evolutionary analysis of chemical networks in the Interstellar environments, C$_2$H$^-$($X^1\Sigma^+$) and C$_2$N$^-$ ($X^3 \Sigma^-$) but for which inelastic rates are only known for C

Bruno F. E. Matarèse, Sébastien Roux, Frédéric Chavane, John C. deMello

We report optical brain imaging using a semi-transparent organic light-emitting diode (OLED) based on the orange light-emitting polymer (LEP) Livilux PDO-124. The OLED serves as a compact, extended light source which is capable of uniformly illuminating the cortical surface when placed across a burr hole in the skull. Since all layers of the OLED are substan

Samuele Tosatto, João Carvalho, Jan Peters

Off-policy Reinforcement Learning (RL) holds the promise of better data efficiency as it allows sample reuse and potentially enables safe interaction with the environment. Current off-policy policy gradient methods either suffer from high bias or high variance, delivering often unreliable estimates. The price of inefficiency becomes evident in real-world sce

Antón Baleato Lizancos, Anthony Challinor, Julien Carron

Efforts to detect a primordial $B$-mode of CMB polarization generated by inflationary gravitational waves ought to mitigate the large variance associated with the $B$-modes produced by gravitational lensing, a process known as delensing. A popular approach to delensing entails building a lensing $B$-mode template by mimicking the lensing operation, either at

Spyridon Pougkakiotis, Jacek Gondzio

In this paper we generalize the Interior Point-Proximal Method of Multipliers (IP-PMM) presented in [An Interior Point-Proximal Method of Multipliers for Convex Quadratic Programming, Computational Optimization and Applications, 78, 307--351 (2021)] for the solution of linear positive Semi-Definite Programming (SDP) problems, allowing inexactness in the solu

Chengdong Han, Gang Xie, Rong Wang, Xurong Chen

We present pion and kaon parton distribution functions from a global QCD analysis of the experimental data within the framework of dynamical parton model. We use the DGLAP equations with parton-parton recombination corrections and the valence input of uniform distribution which maximizes the information entropy. At our input scale $Q_0^2$, there are no sea q

Jake A. McCoy, Marc A. Verschuuren, Drew M. Miles, Randall L. McEntaffer

Surface-relief gratings fabricated through nanoimprint lithography (NIL) are prone to topographic distortion induced by resist shrinkage. Characterizing the impact of this effect on blazed diffraction efficiency is particularly important for applications in astrophysical spectroscopy at soft x-ray wavelengths ($\lambda \approx 0.5 - 5$~nm) that call for the

Marcelo Aguiar, Jose Bastidas

We introduce the Hopf monoid of sets of cycles and paths, which contains the Fa\`a di Bruno Hopf monoid as a submonoid. We give cancellation-free and grouping-free formulas for its antipode, one in terms of tubings and one in terms of \emph{pointed} noncrossing partitions. We provide an explicit description of the group of characters of this Hopf monoid in t

Sundong Kim, Tung-Duong Mai, Sungwon Han, Sungwon Park

We study the human-in-the-loop customs inspection scenario, where an AI-assisted algorithm supports customs officers by recommending a set of imported goods to be inspected. If the inspected items are fraudulent, the officers can levy extra duties. Th formed logs are then used as additional training data for successive iterations. Choosing to inspect suspici

Hefan Li, Cuihua Du, Yanbin Yang, Heidi Jo Newberg

We use the second Gaia data release (Gaia DR2), combined with RAVE spectroscopic surveys, to identify the substructures in the nearby stellar halo. We select 3,845 halo stars kinematically and chemically, and determine their density distribution in energy and angular momentum space. To select the substructures from overdensities, we reshuffle the velocities

Andrea Braides, Valerio Vallocchia

We prove two geometric lemmas for $S^{N-1}$-valued functions that allow to modify sequences of lattice spin functions on a small percentage of nodes during a discrete-to-continuum process so as to have a fixed average. This is used to simplify known formulas for the homogenization of spin systems.

Yepeng Yan, Cuihua Du, Hefan Li, Jianrong Shi

Based on the second Gaia data release (DR2), combined with the LAMOST and APOGEE spectroscopic surveys, we study the kinematics and metallicity distribution of the high-velocity stars that have a relative speed of at least 220 ${\rm km\ s^{-1}}$ with respect to the local standard of rest in the Galaxy. The rotational velocity distribution of the high-velocit

Elham Aldufeery, Maien Binjonaid

The neutralino sector of the semi-constrained next-to-minimal supersymmetric standard model is explored under recent experimental constraints, with special attention to dark matter (DM) limits. The effects of the upper and lower bounds of dark matter relic density and recent direct detection constraints on spin-independent and -dependent cross-sections are t

Gore Lukas Bluhm, Ole Sigmund, Konstantinos Poulios

The present work proposes an extension of the third medium contact method for solving structural topology optimization problems that involve and exploit self-contact. A new regularization of the void region, which acts as the contact medium, makes the method suitable for cases with very large deformations. The proposed contact method is implemented in a seco

Matthew Edmonds, Minoru Eto, Muneto Nitta

We explore the effect of using two-dimensional matter-wave vortices to confine an ensemble of bosonic quantum impurities. This is modelled theoretically using a mass-imbalanced homogeneous two component Gross-Pitaevskii equation where each component has independent atom numbers and equal atomic masses. By changing the mass imbalance of our system we find the

William K. Hartmann, Alessandro Morbidelli

Impact rates in the first 500 Myr of the solar system are critical to an understanding of lunar geological history, but they have been controversial. The widely accepted, post-Apollo paradigm of early lunar impact cratering (ca. 1975-2014) proposed very low or negligible impact cratering in the period from accretion (>4.4 Ga) to about 4.0 Ga ago, followed by

Dhruva Tirumala, Alexandre Galashov, Hyeonwoo Noh, Leonard Hasenclever

As we deploy reinforcement learning agents to solve increasingly challenging problems, methods that allow us to inject prior knowledge about the structure of the world and effective solution strategies becomes increasingly important. In this work we consider how information and architectural constraints can be combined with ideas from the probabilistic model

Csilla Bujtás, Vesna Iršič, Sandi Klavžar

Let $\gamma_g(G)$ be the game domination number of a graph $G$. Rall conjectured that if $G$ is a traceable graph, then $\gamma_g(G) \le \left\lceil \frac{1}{2}n(G)\right\rceil$. Our main result verifies the conjecture over the class of line graphs. Moreover, in this paper we put forward the conjecture that if $\delta(G) \geq 2$, then $\gamma_g(G) \leq \left

Arda Secme, Uzay Tefek, Burak Sari, Hadi Sedaghat Pisheh

Microwave sensors can probe intrinsic material properties of analytes in a microfluidic channel at physiologically relevant ion concentrations. While microwave sensors have been used to detect single cells and microparticles in earlier studies, the synergistic use and comparative analysis of microwave sensors with optical microscopy for material classificati

Junhao Liu, Linjun Shou, Jian Pei, Ming Gong

Cross-lingual Machine Reading Comprehension (CLMRC) remains a challenging problem due to the lack of large-scale annotated datasets in low-source languages, such as Arabic, Hindi, and Vietnamese. Many previous approaches use translation data by translating from a rich-source language, such as English, to low-source languages as auxiliary supervision. However

Hao Ma, Jingbin Liu, Zhirong Hu, Hongyu Qiu

This paper designs a technique route to generate high-quality panoramic image with depth information, which involves two critical research hotspots: fusion of LiDAR and image data and image stitching. For the fusion of 3D points and image data, since a sparse depth map can be firstly generated by projecting LiDAR point onto the RGB image plane based on our r

Sivapalan Chelvaniththilan

In this paper I present a thought experiment that gives different results depending on whether or not the wavefunction collapses. Since the wavefunction does not obey the Schrodinger equation during the collapse, conservation laws are violated. This is the reason why the results are different. Quantities that are conserved if the wavefunction does not collap

Chau Luu, Peter Bell, Steve Renals

Deep speaker embeddings have become the leading method for encoding speaker identity in speaker recognition tasks. The embedding space should ideally capture the variations between all possible speakers, encoding the multiple acoustic aspects that make up a speaker's identity, whilst being robust to non-speaker acoustic variation. Deep speaker embeddings are

Zijie Ji, Phee Lep Yeoh, Gaojie Chen, Cunhua Pan

In this paper, we propose a novel encrypted data transmission scheme using an intelligent reflecting surface (IRS) to generate secret keys in wireless communication networks. We show that perfectly secure one-time pad (OTP) communications can be established by using a simple random phase shifting of the IRS elements. To maximize the secure transmission rate,

Marcel Schmittfull, Azadeh Moradinezhad Dizgah

Modern galaxy surveys focus on the galaxy power spectrum or 2-point correlation function to test and constrain cosmological models. Additional information comes from higher-order N-point functions, but their analysis is challenging. A simple solution is to compute the cross-power spectrum between the squared galaxy density and the galaxy density. Being simpl

Song-Lu Chen, Shu Tian, Jia-Wei Ma, Qi Liu

License plate detection is the first and essential step of the license plate recognition system and is still challenging in real applications, such as on-road scenarios. In particular, small-sized and oblique license plates, mainly caused by the distant and mobile camera, are difficult to detect. In this work, we propose a novel and applicable method for deg

Alexander Marx, Arthur Gretton, Joris M. Mooij

One of the core assumptions in causal discovery is the faithfulness assumption, i.e., assuming that independencies found in the data are due to separations in the true causal graph. This assumption can, however, be violated in many ways, including xor connections, deterministic functions or cancelling paths. In this work, we propose a weaker assumption that

Drew Duffield, Vincent Knibbeler, Sara Lombardo

We study automorphic Lie algebras using a family of evaluation maps parametrised by the representations of the associative algebra of functions. This provides a descending chain of ideals for the automorphic Lie algebra which is used to prove that it is of wild representation type. We show that the associated quotients of the automorphic Lie algebra are isom

Huiyue Yi

Estimating the number of signals embedded in noise is a fundamental problem in array signal processing. The classic RMT estimator based on random matrix theory (RMT) tends to under-estimate the number of signals as it does not consider the non-negligible bias term among eigenvalues for finite sample size. Moreover, the RMT estimator suffers from uncertainty

Stefano Puliti, Johannes Breidenbach, Johannes Schumacher, Marius Hauglin

This study aimed at estimating total forest above-ground net change (Delta AGB, Mt) over five years (2014-2019) based on model-assisted estimation utilizing freely available satellite imagery. The study was conducted for a boreal forest area (approx. 1.4 Mill hectares) in Norway where bi-temporal national forest inventory (NFI), Sentinel-2, and Landsat data

Hao Ma, Jingbin Liu, Keke Liu, Hongyu Qiu

Registration of 3D LiDAR point clouds with optical images is critical in the combination of multi-source data. Geometric misalignment originally exists in the pose data between LiDAR point clouds and optical images. To improve the accuracy of the initial pose and the applicability of the integration of 3D points and image data, we develop a simple but effici

Collas Fabien, Irurozki Ekhine

In this paper, we consider mixtures of two Mallows models for top-$k$ rankings, both with the same location parameter but with different scale parameters, i.e., a mixture of concentric Mallows models. This situation arises when we have a heterogeneous population of voters formed by two homogeneous populations, one of which is a subpopulation of expert voters

Dayu Yan, Daiyu Geng, Qiang Gao, Zhihai Cui

We report the synthesis of single-crystal NbC, a transition metal carbide with various unusual properties. Transport, magnetic susceptibility, and specific heat measurements demonstrate that NbC is a conventional superconductor with a superconducting transition temperature ($T_c$) of 11.5 K. Our theoretical calculations show that NbC is a type-II Dirac semim

Christian Häger, Henry D. Pfister

We propose a new machine-learning approach for fiber-optic communication systems whose signal propagation is governed by the nonlinear Schr\"odinger equation (NLSE). Our main observation is that the popular split-step method (SSM) for numerically solving the NLSE has essentially the same functional form as a deep multi-layer neural network; in both cases, on

Christian Deppe, Vladimir Lebedev

Berlekamp and Zigangirov completely determined the capacity error function for binary error correcting codes with noiseless feedback. It is still an unsolved problem if the upper bound for the capacity error function in the non-binary case of Ahlswede, Lebedev, and Deppe is sharp. We consider wraparound channels with limited magnitude and noiseless feedback.

Elias Starchl, Helmut Ritsch

Quantum annealing aims at finding optimal solutions to complex optimization problems using a suitable quantum many body Hamiltonian encoding the solution in its ground state. To find the solution one typically evolves the ground state of a soluble initial Hamiltonian adiabatically to the ground state of the designated final Hamiltonian. Here we explore wheth

Jianing Wang

Distant supervision (DS) aims to generate large-scale heuristic labeling corpus, which is widely used for neural relation extraction currently. However, it heavily suffers from noisy labeling and long-tail distributions problem. Many advanced approaches usually separately address two problems, which ignore their mutual interactions. In this paper, we propose

Zhenhao Cai, Yunfeng Xiong, Yuan Zhang

In this paper, we study the evolution of a Finitary Random Interlacement (FRI) with respect to the expected length of each fiber. In contrast to the previously proved phase transition between sufficiently large and small fiber length, we show that for $d=3,4$, FRI is NOT stochastically monotone as fiber length increasing. At the same time, numerical evidence

Kui Du, Xiao-Hui Sun

The randomized Kaczmarz algorithm has received considerable attention recently because of its simplicity, speed, and the ability to approximately solve large-scale linear systems of equations. In this paper we propose randomized double and triple Kaczmarz algorithms to solve extended normal equations of the form $\bf A^\top Ax=A^\top b-c$. The proposed algor

Edgar Liberis, Łukasz Dudziak, Nicholas D. Lane

IoT devices are powered by microcontroller units (MCUs) which are extremely resource-scarce: a typical MCU may have an underpowered processor and around 64 KB of memory and persistent storage, which is orders of magnitude fewer computational resources than is typically required for deep learning. Designing neural networks for such a platform requires an intr

Christine Utz, Steffen Becker, Theodor Schnitzler, Florian M. Farke

The COVID-19 pandemic has fueled the development of smartphone applications to assist disease management. Many "corona apps" require widespread adoption to be effective, which has sparked public debates about the privacy, security, and societal implications of government-backed health applications. We conducted a representative online study in Germany (n = 1

Vinita Jindal, Punam Bedi

Vehicular Ad-hoc NETworks (VANETs) are developing at a very fast pace to enable smart transportation in urban cities, by designing some mechanisms for decreasing travel time for commuters by reducing congestion. Inefficient Traffic signals and routing mechanisms are the major factors that contribute to the increase of road congestion. For smoother traffic mo

Lantian Li, Yang Zhang, Jiawen Kang, Thomas Fang Zheng

Domain mismatch often occurs in real applications and causes serious performance reduction on speaker verification systems. The common wisdom is to collect cross-domain data and train a multi-domain PLDA model, with the hope to learn a domain-independent speaker subspace. In this paper, we firstly present an empirical study to show that simply adding cross-d

Haoran Sun, Lantian Li, Yunqi Cai, Yang Zhang

Various information factors are blended in speech signals, which forms the primary difficulty for most speech information processing tasks. An intuitive idea is to factorize speech signal into individual information factors (e.g., phonetic content and speaker trait), though it turns out to be highly challenging. This paper presents a speech factorization app

Wolfgang Muschik

Non-equilibrium processes in Schottky systems generate by projection onto the equilibrium subspace reversible accompanying processes for which the non-equilibrium variables are functions of the equilibrium ones. The embedding theorem which guarantees the compatibility of the accompanying processes with the non-equilibrium entropy is proved. The non-equilibri

W. M. Wood-Vasey, Daniel Perrefort, Ashley Baker

We here show that dual-band GPS measurements of precipitable water vapor (PWV) at KPNO predict the overall per-image sensitivity of the Mayall z-band Legacy Survey (MzLS). The per-image variation in the brightness of individual stars is strongly correlated with the measured PWV and the color of the star. We use synthetic stellar spectra and TAPAS transmissio

Bruno Focassio, Gabriel R. Schleder, Marcio Costa, Adalberto Fazzio

We investigate the structure and electronic spectra properties of two-dimensional amorphous bismuthene structures and show that these systems are topological insulators. We employ realistic modeling of amorphous geometries together with density functional theory for electronic structure calculations. We investigate the system topological properties throughou

S. A. Buterin, M. A. Malyugina, C. -T. Shieh

We consider a second order functional-differential pencil with two constant delays of the argument and study the inverse problem of recovering its coefficients from the spectra of two boundary value problems with one common boundary condition. The uniqueness theorem is proved and a constructive procedure for solving this inverse problem along with necessary

Somrita Ray

We explore the effect of stochastic resetting on the first-passage properties of space-dependent diffusion in presence of a constant bias. In our analytically tractable model system, a particle diffusing in a linear potential $U(x)\propto\mu |x|$ with a spatially varying diffusion coefficient $D(x)=D_0|x|$ undergoes stochastic resetting, i.e., returns to its

Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alan Aspuru-Guzik

Machine learning with application to questions in the physical sciences has become a widely used tool, successfully applied to classification, regression and optimization tasks in many areas. Research focus mostly lies in improving the accuracy of the machine learning models in numerical predictions, while scientific understanding is still almost exclusively

Yao Lu, Yue Dong, Laurent Charlin

Multi-document summarization is a challenging task for which there exists little large-scale datasets. We propose Multi-XScience, a large-scale multi-document summarization dataset created from scientific articles. Multi-XScience introduces a challenging multi-document summarization task: writing the related-work section of a paper based on its abstract and

Muvazima Mansoor, Kirthika Gurumurthy, Anantharam R U, V R Badri Prasad

The Coronavirus pandemic has affected the normal course of life. People around the world have taken to social media to express their opinions and general emotions regarding this phenomenon that has taken over the world by storm. The social networking site, Twitter showed an unprecedented increase in tweets related to the novel Coronavirus in a very short spa

Ivan Poupyrev, Michael J. Lyons, Sidney Fels, Tina Blaine

The rapid evolution of electronics, digital media, advanced materials, and other areas of technology, is opening up unprecedented opportunities for musical interface inventors and designers. The possibilities afforded by these new technologies carry with them the challenges of a complex and often confusing array of choices for musical composers and performer

Yijin Pan, Kezhi Wang, Cunhua Pan, Huiling Zhu

In this paper, unmanned aerial vehicles (UAVs) and intelligent reflective surface (IRS) are utilized to support terahertz (THz) communications. To this end, the joint optimization of UAV's trajectory, the phase shift of IRS, the allocation of THz sub-bands, and the power control is investigated to maximize the minimum average achievable rate of all the users

Albin Grataloup

We study the symplectic geometry of derived intersections of Lagrangian morphisms. In particular, we show that for a functional $f : X \rightarrow \mathbb{A}_k^1$, the derived critical locus has a natural Lagrangian fibration $\textbf{Crit}(f) \rightarrow X$. In the case where $f$ is non-degenerate and the strict critical locus is smooth, we show that the La

Muhammad Umer, Saima Sadiq, Abid Ishaq, Saleem Ullah

Rapid increase of traffic volume on urban roads over time has changed the traffic scenario globally. It has also increased the ratio of road accidents that can be severe and fatal in the worst case. To improve traffic safety and its management on urban roads, there is a need for prediction of severity level of accidents. Various machine learning models are b

Nicolas Skatchkovsky, Hyeryung Jang, Osvaldo Simeone

Synergies between wireless communications and artificial intelligence are increasingly motivating research at the intersection of the two fields. On the one hand, the presence of more and more wirelessly connected devices, each with its own data, is driving efforts to export advances in machine learning (ML) from high performance computing facilities, where

Alexander Kraft, Sabine H. L. Klapp

We investigate the phase behaviour of a two-dimensional colloidal model system of ultra-soft particles on a substrate which varies periodically along one spatial direction. Our calculations are based on mean-field density functional theory for a system of particles interacting via an ultra-soft potential, that is, the generalized exponential model with index

V. G. Baryshevsky, P. I. Porshnev

The outstanding progress has been made in reducing the upper bounds on EDM of several particles. Even if significant challenges must be overcome to further improve these limits, it is still one of the best chances to detect new type of interactions beyond the standard model. Analyzing several examples, we highlight a common thread that is visible in differen

Nicolas Skatchkovsky, Hyeryung Jang, Osvaldo Simeone

Inspired by the operation of biological brains, Spiking Neural Networks (SNNs) have the unique ability to detect information encoded in spatio-temporal patterns of spiking signals. Examples of data types requiring spatio-temporal processing include logs of time stamps, e.g., of tweets, and outputs of neural prostheses and neuromorphic sensors. In this paper,

Adrian Nugraha Utama, Chang Hoong Chow, Chi Huan Nguyen, Christian Kurtsiefer

Optical cavities in the near-concentric regime have near-degenerate transverse modes; the tight focusing transverse modes in this regime enable strong coupling with atoms. These features provide an interesting platform to explore multi-mode interaction between atoms and light. Here, we use a spatial light modulator (SLM) to shape the phase of an incoming lig

Rubén Gómez González, Nagi Khalil, Vicente Garzó

The Mpemba effect occurs when two samples at different initial temperatures evolve in such a way that the temperatures cross each other during the relaxation towards equilibrium. In this paper we show the emergence of a Mpemba-like effect in a molecular binary mixture in contact with a thermal reservoir (bath). The interaction between the gaseous particles o

V. M. Romanova, G. V. Ivanenkov, E. V. Parkevich, I. N. Tilikin

This paper presents the results of studying of dispersed media formation during the electrical explosion of thin metal wires in vacuum by using low-current generators ($\sim 1$-$10$~kA). Particular attention is paid to the analysis of the composition and structure of the corresponding explosion products as well as to the problem of their visualization using

Makoto Sakamoto, Maki Takeuchi, Yoshiyuki Tatsuta

We investigate chiral zero modes and winding numbers at fixed points on $T^2/\mathbb{Z}_N$ orbifolds. It is shown that the Atiyah-Singer index theorem for the chiral zero modes leads to a formula $n_+-n_-=(-V_++V_-)/2N$, where $n_{\pm}$ are the numbers of the $\pm$ chiral zero modes and $V_{\pm}$ are the sums of the winding numbers at the fixed points on $T^

Chris Ormel, Allona Vazan, Marc Brouwers

During their formation, planets form large, hot atmospheres due to the ongoing accretion of solids. It has been customary to assume that all solids end up at the center constituting a "core" of refractory materials, whereas the envelope remains metal-free. Recent work, as well as observations by the JUNO mission, indicate however that the distinction may not

Laksh Bhatia, Michael Breza, Ramona Marfievici, Julie A. McCann

This paper presents the LoRaWAN at the Edge Dataset (LoED), an open LoRaWAN packet dataset collected at gateways. Real-world LoRaWAN datasets are important for repeatable sensor-network and communications research and evaluation as, if carefully collected, they provide realistic working assumptions. LoED data is collected from nine gateways over a four month

Jonathan Passant

Let $P$ be a finite point set in $\mathbb{R}^2$ with the set of distance $n$-chains defined as $$ \Delta_n(P)=\{(|p_1-p_2|,|p_2-p_3|,\ldots,|p_n-p_{n+1}|):p_i \in P\}.$$ We show that for $2\leq n=O_{|P|}(1)$ we have $$|\Delta_n(P)|\gtrsim \frac{|P|^{n}}{\log^{\frac{13}{2}(n-1)}|P|}.$$ Our argument uses the energy construction of Elekes and a general version

Martijn Gösgens, Teun Hendriks, Marko Boon, Stijn Keuning

In their response to the COVID-19 outbreak, governments face the dilemma to balance public health and economy. Mobility plays a central role in this dilemma because the movement of people enables both economic activity and virus spread. We use mobility data in the form of counts of travelers between regions, to extend the often-used SEIR models to include mo

Hyeryung Jang, Nicolas Skatchkovsky, Osvaldo Simeone

Spiking Neural Networks (SNNs) are biologically inspired machine learning models that build on dynamic neuronal models processing binary and sparse spiking signals in an event-driven, online, fashion. SNNs can be implemented on neuromorphic computing platforms that are emerging as energy-efficient co-processors for learning and inference. This is the first o

Emma Lumiaro, Milica Todorović, Theo Kurten, Hanna Vehkamäki

The formation, properties and lifetime of secondary organic aerosols in the atmosphere are largely determined by gas-particle partitioning coefficients of the participating organic vapours. Since these coefficients are often difficult to measure or compute, we developed a machine learning (ML) model to predict them given molecular structure as input. Our dat

Christopher W Roy, John Heerfordt, Davide Piccini, Giulia Rossi

Background: RSN whole-heart CMRA is a technique that estimates and corrects for respiratory motion. However, RSN has been limited to a 1D rigid correction which is often insufficient for patients with complex respiratory patterns. The goal of this work is therefore to improve the robustness and quality of 3D radial CMRA by incorporating both 3D motion inform