October 2020 arXiv papers — page 4

S. T. H. Hartman, H. A. Winther, D. F. Mota

The aim of the present work is to better understand the gravitational drag forces, i.e. dynamical friction, acting on massive objects moving through a self-interacting Bose-Einstein condensate, also known as a superfluid, at finite temperatures. This is relevant for light scalar models of dark matter with weak self-interactions that require nonzero temperatu

Sandip Saha, Gautam Gangopadhyay, Sangeeta Kumari, Ranjit Kumar Upadhyay

In this paper, an attempt has been made to understand the parametric excitation of a periodic orbit of nonlinear oscillator which can be a limit cycle, center or a slowly decaying center-type oscillation. For this a delay model is considered with nonlinear feedback oscillator defined in terms of Li\'enard oscillator description which can give rise to any one

John E. Vaillancourt, B-G Andersson, Dan P. Clemens, Vilppu Piirola

The optical and near-infrared (OIR) polarization of starlight is typically understood to arise from the dichroic extinction of that light by dust grains whose axes are aligned with respect to a local magnetic-field. The size distribution of the aligned-grain population can be constrained by measurements of the wavelength dependence of the polarization. The l

Kristen Hendricks, Jennifer Hom, Matthew Stoffregen, Ian Zemke

We establish a surgery exact triangle for involutive Heegaard Floer homology by using a doubling model of the involution. We use this exact triangle to give an involutive version of Ozsv\'ath-Szab\'o's mapping cone formula for knot surgery. As an application, we use this surgery formula to give examples of integer homology spheres that are not homology cobor

Nick Karcher, Richard Gebauer, Robin Bauknecht, Rainer Illichmann

Modern physics experiments often utilize FPGA-based systems for real-time data acquisition. Integrated analog electronics demand for complex calibration routines. Furthermore, versatile configuration and control of the whole system is a key requirement. Beside low-level register interface to the FPGA, also access to I$^2$C and SPI buses is often needed to co

Bhavin J. Shastri, Alexander N. Tait, Thomas Ferreira de Lima, Wolfram H. P. Pernice

Research in photonic computing has flourished due to the proliferation of optoelectronic components on photonic integration platforms. Photonic integrated circuits have enabled ultrafast artificial neural networks, providing a framework for a new class of information processing machines. Algorithms running on such hardware have the potential to address the g

Abraham I. Harte

Free-fall is only approximately universal in general relativity. Different extended bodies can fall in different ways, depending on their internal dynamics. Nevertheless, certain aspects of their motion are universal. This paper examines the universal constraints on extended-body motion in vacuum type D spacetimes. Working in the quadrupole approximation, we

Houcemeddine Turki, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha

So far, multi-label classification algorithms have been evaluated using statistical methods that do not consider the semantics of the considered classes and that fully depend on abstract computations such as Bayesian Reasoning. Currently, there are several attempts to develop ontology-based methods for a better assessment of supervised classification algorit

Konstantin Eder, Hanno Sahlmann

In this paper, the classical and quantum theory of $\mathcal{N}=1$ supergravity in four spacetime dimensions will be studied in the framework of loop quantum gravity. We discuss the canonical analysis of the supergravity Holst action as first introduced by Tsuda. In this way, we also derive a compact expression of the supersymmetry constraint, which plays a

S. Hayashida, L. Huberich, D. Flavián, Z. Yan

Magnetic-field-induced phase transitions are investigated in the frustrated gapped quantum paramagnet Rb$_{2}$Cu$_{2}$Mo$_3$O$_{12}$ through dielectric and calorimetric measurements on single-crystal samples. It is clarified that the previously reported dielectric anomaly at 8~K in powder samples is not due to a chiral spin liquid state as has been suggested

Yotam Smilansky, Yaar Solomon

We prove that in every compact space of Delone sets in $\mathbb{R}^d$ which is minimal with respect to the action by translations, either all Delone sets are uniformly spread, or continuously many distinct bounded displacement equivalence classes are represented, none of which contains a lattice. The implied limits are taken with respect to the Chabauty--Fel

McKane Andrus, Elena Spitzer, Jeffrey Brown, Alice Xiang

As calls for fair and unbiased algorithmic systems increase, so too does the number of individuals working on algorithmic fairness in industry. However, these practitioners often do not have access to the demographic data they feel they need to detect bias in practice. Even with the growing variety of toolkits and strategies for working towards algorithmic f

Kun Qian, Poornima Chozhiyath Raman, Yunyao Li, Lucian Popa

Structured representations of entity names are useful for many entity-related tasks such as entity normalization and variant generation. Learning the implicit structured representations of entity names without context and external knowledge is particularly challenging. In this paper, we present a novel learning framework that combines active learning and wea

Martin Křepela, Zdeněk Mihula, Hana Turčinová

We improve the discretization technique for weighted Lorentz norms by eliminating all "non-degeneracy" restrictions on the involved weights. We use the new method to provide equivalent estimates on the optimal constant $C$ such that the inequality $$\left( \int_0^L (f^*(t))^{p_2} w(t)\,\mathrm{d}t \right)^\frac 1{p_2} \le C \left( \int_0^L \left( \int_0^t u(

Loi T. Nguyen, Robert J. Cava, Allyson M. Fry-Petit

Ba2CaMoO6 was synthesized by solid state method. The crystal structure adopts cubic Fm-3m space group at room temperature with lattice parameters of 8.378231(5) {angstroms}. Upon cooling, Ba2CaMoO6 was determined to have a structural phase transition to tetragonal I4/m (a=5.905763(6) {angstroms} and c=8.38817(1) {angstroms}) around 200 K. The phase transitio

Peiyao Sheng, Bowen Xue, Sreeram Kannan, Pramod Viswanath

A popular method in practice offloads computation and storage in blockchains by relying on committing only hashes of off-chain data into the blockchain. This mechanism is acknowledged to be vulnerable to a stalling attack: the blocks corresponding to the committed hashes may be unavailable at any honest node. The straightforward solution of broadcasting all

Lubin Meng, Jian Huang, Zhigang Zeng, Xue Jiang

Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to deeper understanding of the brain and wide adoption of sophisticated machine learning approaches for decoding the EEG signals. However, recent studies have shown that machine learning algorithms are vulnerable to adversarial atta

Zdzislaw Brzezniak, Gabriel Deugoue, Paul Andre Razafimandimby

In this manuscript, we consider a highly nonlinear and constrained stochastic PDEs modelling the dynamics of 2-dimensional nematic liquid crystals under random perturbation. This system of SPDEs is also known as the stochastic Ericksen-Leslie equations (SELEs). We discuss the existence of local strong solution to the stochastic Ericksen-Leslie equations. In

Zhongliang Jiang, Zhenyu Li, Matthias Grimm, Mingchuan Zhou

Ultrasound (US) imaging is widely employed for diagnosis and staging of peripheral vascular diseases (PVD), mainly due to its high availability and the fact it does not emit radiation. However, high inter-operator variability and a lack of repeatability of US image acquisition hinder the implementation of extensive screening programs. To address this challen

Frank A. Ibarra, Daniel Turizo, César Orozco-Henao, Javier Guerrero

This article proposes a method for generator controller tuning in a power system affected by stochastic loads. The method uses the Analysis of Variance to detect the controllers with significant effect over the quality of the system response. Such quality is measured with an objective function defined as a weighted average of the Integral Absolute Error of e

Weichao Liang, Nina H. Amini, Paolo Mason

In this paper, we consider stochastic master equations describing the evolution of a multi-qubit system interacting with electromagnetic fields undergoing continuous-time measurements. By considering multiple z-type (Pauli z matrix on different qubits) and x-type (Pauli x matrix on all qubits) measurements and one control Hamiltonian, we provide general cond

Martin Grohe, Peter Lindner

Probabilistic databases (PDBs) model uncertainty in data. The current standard is to view PDBs as finite probability spaces over relational database instances. Since many attributes in typical databases have infinite domains, such as integers, strings, or real numbers, it is often more natural to view PDBs as infinite probability spaces over database instanc

Zhaocheng Lu, Andrew N. Norris

Longitudinal wave propagation is considered in a pair of waveguides connected by bilinear spring systems. The nature of the nonlinearity causes the compressive and tensile force-displacement relations of the bilinear spring to behave in a piece-wise linear manner, and all transmitted and reflected waves scale linearly with the incident wave amplitude. We fir

Venkatraman Renganathan, Navid Hashemi, Justin Ruths, Tyler H. Summers

The identification of anomalies is a critical component of operating complex, and possibly large-scale and geo-graphically distributed cyber-physical systems. While designing anomaly detectors, it is common to assume Gaussian noise models to maintain tractability; however, this assumption can lead to the actual false alarm rate being significantly higher tha

Sai Vemprala, Ashish Kapoor

Trajectory planning is a key piece in the algorithmic architecture of a robot. Trajectory planners typically use iterative optimization schemes for generating smooth trajectories that avoid collisions and are optimal for tracking given the robot's physical specifications. Starting from an initial estimate, the planners iteratively refine the solution so as t

Hongbo Zou, Guangjing Chen, Pengtao Xie, Sean Chen

Industrial Artificial Intelligence (Industrial AI) is an emerging concept which refers to the application of artificial intelligence to industry. Industrial AI promises more efficient future industrial control systems. However, manufacturers and solution partners need to understand how to implement and integrate an AI model into the existing industrial contr

Yuan Chen, Donglin Zeng, Tianchen Xu, Yuanjia Wang

For mental disorders, patients' underlying mental states are non-observed latent constructs which have to be inferred from observed multi-domain measurements such as diagnostic symptoms and patient functioning scores. Additionally, substantial heterogeneity in the disease diagnosis between patients needs to be addressed for optimizing individualized treatmen

Chaitanya Talnikar, Tatiana Likhomanenko, Ronan Collobert, Gabriel Synnaeve

Self-supervised learning (SSL) has shown promise in learning representations of audio that are useful for automatic speech recognition (ASR). But, training SSL models like wav2vec~2.0 requires a two-stage pipeline. In this paper we demonstrate a single-stage training of ASR models that can utilize both unlabeled and labeled data. During training, we alternat

Dhruvil Gala, Mohammad Omar Khursheed, Hannah Lerner, Brendan O'Connor

Popular media reflects and reinforces societal biases through the use of tropes, which are narrative elements, such as archetypal characters and plot arcs, that occur frequently across media. In this paper, we specifically investigate gender bias within a large collection of tropes. To enable our study, we crawl tvtropes.org, an online user-created repositor

Aswin Shanmugam Subramanian, Chao Weng, Shinji Watanabe, Meng Yu

This paper proposes a new paradigm for handling far-field multi-speaker data in an end-to-end neural network manner, called directional automatic speech recognition (D-ASR), which explicitly models source speaker locations. In D-ASR, the azimuth angle of the sources with respect to the microphone array is defined as a latent variable. This angle controls the

Shubho Banerjee, Thomas Peters, Nolan Brown, Yi Song

We present exact closed-form expressions and complete asymptotic expansions for the electrostatic force between two charged conducting spheres of arbitrary sizes. Using asymptotic expansions of the force we confirm that even like-charged spheres attract each other at sufficiently small separation unless their voltages/charges are the same as they would be at

Arianna I. Krinos, Sarah K. Hu, Natalie R. Cohen, Harriet Alexander

The assessment of microbial species biodiversity is essential in ecology and evolutionary biology (Reaka-Kudla et al. 1996), but especially challenging for communities of microorganisms found in the environment (Das et al. 2006, Hillebrand et al. 2018). Beyond providing a census of organisms in the ocean, assessing marine microbial biodiversity can reveal ho

Sarah Oh, Elijah FW Bowen, Antonio Rodriguez, Damian Sowinski

Although perceptual (dis)similarity between sensory stimuli seems akin to distance, measuring the Euclidean distance between vector representations of auditory stimuli is a poor estimator of subjective dissimilarity. In hearing, nonlinear response patterns, interactions between stimulus components, temporal effects, and top-down modulation transform the info

Soumajyoti Sarkar

Motivated by recent applications of sequential decision making in matching markets, in this paper we attempt at formulating and abstracting market designs for P2P lending. We describe a paradigm to set the stage for how peer to peer investments can be conceived from a matching market perspective, especially when both borrower and lender preferences are respe

Canran Wang, Netanel Raviv

Although blockchain, the supporting technology of Bitcoin and various cryptocurrencies, has offered a potentially effective framework for numerous applications, it still suffers from the adverse affects of the impossibility triangle. Performance, security, and decentralization of blockchains normally do not scale simultaneously with the number of participant

Carlos A. Galeano-Rios, Radu Cimpeanu, Isabelle A. Bauman, Annika MacEwen

A millimetre-size superhydrophobic sphere impacting on the free surface of a quiescent bath can be propelled back into the air by capillary effects and dynamic fluid forces, whilst transferring part of its energy to the fluid. We report the findings of a thorough investigation of this phenomenon, involving different approaches. Over the range from minimum im

Yongming Luo

We consider a state-of-the-art ferroelectric phase-field model arising from the engineering area in recent years, which is mathematically formulated as a coupled elliptic-parabolic differential system. We utilize a fixed point theorem based on the maximal parabolic regularity theory to show the local in time well-posedness of the ferroelectric problem. The w

Patrick Vogt, Felix V. E. Hensling, Kathy Azizie, Celesta S. Chang

This paper introduces a growth method---suboxide molecular-beam epitaxy (S-MBE)---which enables the growth of Ga2O3 and related materials at growth rates exceeding 1 micrometer per hours with excellent crystallinity in an adsorptioncontrolled regime. Using a Ga + Ga2O3 mixture with an oxygen mole fraction of x(O) = 0.4 as an MBE source, we overcome kinetic l

Jayadev Acharya, Peter Kairouz, Yuhan Liu, Ziteng Sun

We consider the problem of estimating sparse discrete distributions under local differential privacy (LDP) and communication constraints. We characterize the sample complexity for sparse estimation under LDP constraints up to a constant factor and the sample complexity under communication constraints up to a logarithmic factor. Our upper bounds under LDP are

Sarira Sahu, Carlos E. López Fortín, Luis H. Castañeda Hernández, Subhash Rajpoot

The high-energy-peaked blazar 1ES 1959+650 is a well-known and well studied nearby blazar that has undergone several episodes of multi-TeV flaring. In 2002 for the first time an orphan TeV flare was observed from this blazar. During a multiwavelength campaign between 29th April to 21st November 2016, MAGIC telescopes observed multi-TeV flarings during the ni

Hosein Barzekar, Zeyun Yu

Cancers are the leading cause of death in many countries. Early diagnosis plays a crucial role in having proper treatment for this debilitating disease. The automated classification of the type of cancer is a challenging task since pathologists must examine a huge number of histopathological images to detect infinitesimal abnormalities. In this study, we pro

John P. Lalor, Hong Yu

Curriculum learning methods typically rely on heuristics to estimate the difficulty of training examples or the ability of the model. In this work, we propose replacing difficulty heuristics with learned difficulty parameters. We also propose Dynamic Data selection for Curriculum Learning via Ability Estimation (DDaCLAE), a strategy that probes model ability

Olivier Sète, Jan Zur

We present a continuation method to compute all zeros of a harmonic mapping $f$ in the complex plane. Our method works without any prior knowledge of the number of zeros or their approximate location. We start by computing all solution of $f(z) = \eta$ with $|\eta|$ sufficiently large and then track all solutions as $\eta$ tends to $0$ to finally obtain all

Mathias Wanner, Igor Mezić

We analyze the performance of Dynamic Mode Decomposition (DMD)-based approximations of the stochastic Koopman operator for random dynamical systems where either the dynamics or observables are affected by noise. For many DMD algorithms, the presence of noise can introduce a bias in the DMD operator, leading to poor approximations of the dynamics. In particul

T. A. Wijkamp, A. Perek, J. Decker, B. Duval

Synchrotron radiation observed in a quiescent TCV runaway discharge is studied using filtered camera images targeting three distinct wavelength intervals. Through the tomographic SART procedure the high momentum, high pitch angle part of the spatial and momentum distribution of these relativistic particles is reconstructed. Experimental estimates of the dist

Alaa Alameer Ahmad, Yijie Mao, Aydin Sezgin, Bruno Clerckx

Cloud radio access networks (C-RAN) enable a network platform for beyond the fifth generation of communication networks (B5G), which incorporates the advances in cloud computing technologies to modern radio access networks. Recently, rate splitting multiple access (RSMA), relying on multi-antenna rate-splitting (RS) at the transmitter and successive interfer

Johann Gehringer, Xue-Mei Li

We review recent developments of slow/fast stochastic differential equations, and also present a new result on Diffusion Homogenisation Theory with fractional and non-strong-mixing noise and providing new examples. The emphasise of the review will be on the recently developed effective dynamic theory for two scale random systems with fractional noise: Stocha

Yvette Cendes, Tarraneh Eftekhari, Edo Berger, Emil Polisensky

We present continued radio and X-ray observations of the previously relativistic tidal disruption event (TDE) Swift J164449.3+573451 (\sw) extending to about 9.4 years post disruption, as part of ongoing campaigns with the Jansky Very Large Array (VLA) and the \textit{Chandra} X-ray observatory. We find that the X-ray emission has faded below detectable leve

Yao Yang, Andrew Nam, Mohamad M. Nasr-Azadani, Teresa Tung

In this study, we introduce a novel platform Resource-Aware AutoML (RA-AutoML) which enables flexible and generalized algorithms to build machine learning models subjected to multiple objectives, as well as resource and hard-ware constraints. RA-AutoML intelligently conducts Hyper-Parameter Search(HPS) as well as Neural Architecture Search (NAS) to build mod

Shahbaz Abdul Khader, Hang Yin, Pietro Falco, Danica Kragic

Reinforcement Learning (RL) of robotic manipulation skills, despite its impressive successes, stands to benefit from incorporating domain knowledge from control theory. One of the most important properties that is of interest is control stability. Ideally, one would like to achieve stability guarantees while staying within the framework of state-of-the-art d

Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan

EfficientNets are a family of state-of-the-art image classification models based on efficiently scaled convolutional neural networks. Currently, EfficientNets can take on the order of days to train; for example, training an EfficientNet-B0 model takes 23 hours on a Cloud TPU v2-8 node. In this paper, we explore techniques to scale up the training of Efficien

Francesco Calivá, Kaiyang Cheng, Rutwik Shah, Valentina Pedoia

Deep Learning (DL) has shown potential in accelerating Magnetic Resonance Image acquisition and reconstruction. Nevertheless, there is a dearth of tailored methods to guarantee that the reconstruction of small features is achieved with high fidelity. In this work, we employ adversarial attacks to generate small synthetic perturbations, which are difficult to

Thomas Bronzwaer, Jordy Davelaar, Ziri Younsi, Monika Mościbrodzka

Accreting black holes tend to display a characteristic dark central region called the black-hole shadow, which depends only on spacetime/observer geometry and which conveys information about the black hole's mass and spin. Conversely, the observed central brightness depression, or image shadow, additionally depends on the morphology of the emission region. I

Janez Brest, Borko Bošković

In this paper, we present a computational search for best-known merit factors of longer binary sequences with an odd length. Finding low autocorrelation binary sequences with optimal or suboptimal merit factors is a very difficult optimization problem. An improved version of the heuristic algorithm is presented and tackled to search for aperiodic binary sequ

Stefan Huber, Igor Konorov, Dmytro Levit, Stephan Paul

The SuperKEKB accelerator in Tsukuba, Japan is providing e$^+$e$^-$ beams for the Belle II experiment since March 2019. To deal with the aimed peak luminosity being forty times higher than the one recorded at Belle, a pixel detector based on DEPFET technology has been installed. It features a long integration time of 20 $\mu$s resulting in an expected data r

Dimitar Popmintchev, Siyang Wang, Xiaoshi Zhang, Tenio Popmintchev

We derive general analytic expressions for the chromatic dispersion orders valid to infinity, due to the k vector or phase {\phi} dependence on the wavelength. Additionally, we identify polynomials and recursion relations associated with the chromatic dispersion orders and draw analogy to the generalized Lah and Laguerre transformations. Further, we give exp

Marzieh Fadaee, Olga Gureenkova, Fernando Rejon Barrera, Carsten Schnober

To provide AI researchers with modern tools for dealing with the explosive growth of the research literature in their field, we introduce a new platform, AI Research Navigator, that combines classical keyword search with neural retrieval to discover and organize relevant literature. The system provides search at multiple levels of textual granularity, from s

G. Christopher Hruska, Emily Stark, Hung Cong Tran

For a group $G$ (of type $F$) acting properly on a coarse Poincar\'{e} duality space $X$, Kapovich-Kleiner introduced a coarse version of Alexander duality between $G$ and its complement in $X$. More precisely, the cohomology of $G$ with group ring coefficients is dual to a certain \v{C}ech homology group of the family of increasing neighborhoods of a $G$-or

Harshit Jain, Nishant Raj, Suyash Mishra

Extraction of adverse drug events from biomedical literature and other textual data is an important component to monitor drug-safety and this has attracted attention of many researchers in healthcare. Existing works are more pivoted around entity-relation extraction using bidirectional long short term memory networks (Bi-LSTM) which does not attain the best

Nick Webb, Dan Smith, Christopher Ludwick, Trent Victor

Waymo's safety methodologies, which draw on well established engineering processes and address new safety challenges specific to Automated Vehicle technology, provide a firm foundation for safe deployment of Waymo's Level 4 ADS, which Waymo also refers to as the Waymo Driver. Waymo's determination of its readiness to deploy its AVs safely in different settin

Asmit Kumar Singh, Paras Mehan, Divyanshu Sharma, Rohan Pandey

Wearing masks is a useful protection method against COVID-19, which has caused widespread economic and social impact worldwide. Across the globe, governments have put mandates for the use of face masks, which have received both positive and negative reaction. Online social media provides an exciting platform to study the use of masks and analyze underlying m

Alessandro Mininno, Angel M. Uranga

Non-supersymmetric string models are plagued with tadpoles for dynamical fields, which signal uncanceled forces sourced by the vacuum. We argue that in certain cases, uncanceled dynamical tadpoles can lead to inconsistencies with quantum gravity, via violation of swampland constraints. We describe an explicit realization in a supersymmetric toroidal ${\textb

Timothy Nguyen, Zhourong Chen, Jaehoon Lee

One of the most fundamental aspects of any machine learning algorithm is the training data used by the algorithm. We introduce the novel concept of $\epsilon$-approximation of datasets, obtaining datasets which are much smaller than or are significant corruptions of the original training data while maintaining similar model performance. We introduce a meta-l

Stella Sue Gastineau

In 2014, Reeder and Yu constructed epipelagic representations of a reductive $p$-adic group $G$ from stable functions on shallowest Moy-Prasad quotients. In this paper, we extend these methods when $G$ is split. In particular, we classify all complex-valued characters vanshing on a slightly deeper Moy-Prasad subgroup and show that, while sufficient, a naive

A. Mishev, P. I. Y. Velinov

The effect of precipitating high-energy particles on atmospheric physics and chemistry is extensively studied over the last decade. In majority of the existing models, the precipitating particles induced ionization plays an essential role. For such effects, it is necessary to possess enhanced increase in ion production, specifically during the winter period.

Lucky Qiaofeng Li, Xizhi Su

We study an iteration approach to solve the coupled algebraic Riccati equations when they appear in general two player closed-loop type Nash differential games over an infinite time horizon. Also, we propose an effective algorithm for finding positive definite solutions. In particular, we present various numerical examples connected with matrix Riccati equat

Edoardo Belli, Simone Vantini

We propose a tree-based algorithm for classification and regression problems in the context of functional data analysis, which allows to leverage representation learning and multiple splitting rules at the node level, reducing generalization error while retaining the interpretability of a tree. This is achieved by learning a weighted functional $L^{2}$ space

Timon S. Gutleb, José A. Carrillo, Sheehan Olver

We introduce a method to numerically compute equilibrium measures for problems with attractive-repulsive power law kernels of the form $K(x-y) = \frac{|x-y|^\alpha}{\alpha}-\frac{|x-y|^\beta}{\beta}$ using recursively generated banded and approximately banded operators acting on expansions in ultraspherical polynomial bases. The proposed method reduces what

Taichi Uyama, Bin Ren, Dimitri Mawet, Garreth Ruane

High-contrast imaging of exoplanets and protoplanetary disks depends on wavefront sensing and correction made by adaptive optics instruments. Classically, wavefront sensing has been conducted at optical wavelengths, which made high-contrast imaging of red targets such as M-type stars or extincted T Tauri stars challenging. Keck/NIRC2 has combined near-infrar

Zhengyuan Yang, Amanda Kay, Yuncheng Li, Wendi Cross

Inspired by the human ability to infer emotions from body language, we propose an automated framework for body language based emotion recognition starting from regular RGB videos. In collaboration with psychologists, we further extend the framework for psychiatric symptom prediction. Because a specific application domain of the proposed framework may only su

V. V. Zhuravlev

Dust is the usual minor component of the interstellar medium. Its dynamic role in the contraction of the diffuse gas into molecular clouds is commonly assumed to be negligible because of the small mass fraction, $f \simeq 0.01$. However, as shown in this study, the collective motion of dust grains with respect to the gas may considerably contribute to the de

Belbahri Mouloud, Gandouet Olivier, Kazma Ghaith

Uplift is a particular case of individual treatment effect modeling. Such models deal with cause-and-effect inference for a specific factor, such as a marketing intervention. In practice, these models are built on customer data who purchased products or services to improve product marketing. Uplift is estimated using either i) conditional mean regression or

Josep Batle, Joan J. Cerdà, Ph. Depondt, J. -C. S. Lévy

The speed at which the magnetic interaction propagates along a chain of classic dipoles is discussed here. While in the quantum information counterpart for long-range interacting spins, where the speed of propagation of the information plays a paramount role, it is not strictly clear whether a light cone exists or not, here we provide numerical evidence that

Jean Dolbeault, Maria J. Esteban, Michael Loss

This paper is devoted to the study of the two-dimensional Dirac-Coulomb operator in presence of an Aharonov-Bohm external magnetic potential. We characterize the highest intensity of the magnetic field for which a two-dimensional magnetic Hardy inequality holds. Up to this critical magnetic field, the operator admits a distinguished self-adjoint extension an

Matthew Schwall, Tom Daniel, Trent Victor, Francesca Favaro

Waymo's mission to reduce traffic injuries and fatalities and improve mobility for all has led us to expand deployment of automated vehicles on public roads without a human driver behind the wheel. As part of this process, Waymo is committed to providing the public with informative and relevant data regarding the demonstrated safety of Waymo's automated driv

Brando Bellazzini, Joan Elias Miró, Riccardo Rattazzi, Marc Riembau

We find the complete set of conditions satisfied by the forward $2\to2$ scattering amplitude in unitarity and causal theories. These are based on an infinite set of energy dependent quantities -- the arcs -- which are dispersively expressed as moments of a positive measure defined at (arbitrarily) higher energies. We identify optimal finite subsets of constr

Ilya Belopolski

Topological phases of matter have established a new paradigm in physics, bringing quantum phenomena to the macroscopic scale and hosting exotic emergent quasiparticles. In this thesis, I theoretically and experimentally demonstrate with my collaborators the first Weyl semimetal, TaAs, using angle-resolved photoemission spectroscopy (ARPES), directly observin

S. Al Kharusi, S. Y. BenZvi, J. S. Bobowski, W. Bonivento

The next core-collapse supernova in the Milky Way or its satellites will represent a once-in-a-generation opportunity to obtain detailed information about the explosion of a star and provide significant scientific insight for a variety of fields because of the extreme conditions found within. Supernovae in our galaxy are not only rare on a human timescale bu

Jingxi Xu, Cassie Meeker, Ava Chen, Lauren Winterbottom

In order to provide therapy in a functional context, controls for wearable robotic orthoses need to be robust and intuitive. We have previously introduced an intuitive, user-driven, EMG-based method to operate a robotic hand orthosis, but the process of training a control that is robust to concept drift (changes in the input signal) places a substantial burd

Juan Luis Vázquez

We consider the natural time-dependent fractional $p$-Laplacian equation posed in the whole Euclidean space, with parameter $1<p<2$ and fractional exponent $s\in (0,1)$. Rather standard theory shows that the Cauchy Problem for data in the Lebesgue $L^q$ spaces is well posed, and the solutions form a family of non-expansive semigroups with regularity and othe

Xutai Ma, Yongqiang Wang, Mohammad Javad Dousti, Philipp Koehn

Transformer-based models have achieved state-of-the-art performance on speech translation tasks. However, the model architecture is not efficient enough for streaming scenarios since self-attention is computed over an entire input sequence and the computational cost grows quadratically with the length of the input sequence. Nevertheless, most of the previous

Ruben Grandia, Andrew J. Taylor, Aaron D. Ames, Marco Hutter

The problem of dynamic locomotion over rough terrain requires both accurate foot placement together with an emphasis on dynamic stability. Existing approaches to this problem prioritize immediate safe foot placement over longer term dynamic stability considerations, or relegate the coordination of foot placement and dynamic stability to heuristic methods. We

W. Deng, Z. Song, G. Huang, G. De Lentdecker

Real-time track tracking in high energy physics experiments at colliders running at high luminosity is very challenging for trigger systems. To perform pattern-recognition and track fitting in online trigger system, the artificial Retina algorithm has been introduced in the field. Retina can be implemented in the state of the art FPGA devices. Our developmen

Sepideh Bakhoda, Thomas Thiemann

The utility of the U(1)$^3$ model as a test laboratory for quantum gravity has recently been emphasized in a recent series of papers due to Varadarajan et al. The simplification from SU(2) to U(1)$^3$ can be performed simply by hand within the Hamiltonian formulation by dropping all non-Abelian terms from the Gauss, spatial diffeomorphism and Hamiltonian con

Shanshan Wang, Annamaria Mesaros, Toni Heittola, Tuomas Virtanen

This paper introduces a curated dataset of urban scenes for audio-visual scene analysis which consists of carefully selected and recorded material. The data was recorded in multiple European cities, using the same equipment, in multiple locations for each scene, and is openly available. We also present a case study for audio-visual scene recognition and show

Florent Foucaud, Shih-Shun Kao, Ralf Klasing, Mirka Miller

We introduce a new graph-theoretic concept in the area of network monitoring. A set $M$ of vertices of a graph $G$ is a \emph{distance-edge-monitoring set} if for every edge $e$ of $G$, there is a vertex $x$ of $M$ and a vertex $y$ of $G$ such that $e$ belongs to all shortest paths between $x$ and $y$. We denote by $dem(G)$ the smallest size of such a set in

Yunong Shi, Pranav Gokhale, Prakash Murali, Jonathan M. Baker

Building a quantum computer that surpasses the computational power of its classical counterpart is a great engineering challenge. Quantum software optimizations can provide an accelerated pathway to the first generation of quantum computing applications that might save years of engineering effort. Current quantum software stacks follow a layered approach sim

Amira Abbas, David Sutter, Christa Zoufal, Aurélien Lucchi

Fault-tolerant quantum computers offer the promise of dramatically improving machine learning through speed-ups in computation or improved model scalability. In the near-term, however, the benefits of quantum machine learning are not so clear. Understanding expressibility and trainability of quantum models-and quantum neural networks in particular-requires f

Emilie Jean, Francois Therriault-Proulx, Luc Beaulieu

This study introduces the HYPERSCINT research platform, the first commercially available scintillation dosimetry platform capable of multi-point dosimetry through the hyperspectral approach. Optic and dosimetric performances of the system were investigated through comparison with another commercially available solution, the Ocean Optics QE65Pro spectrometer.

Geoff Vooys

In this expository paper we provide a geometric proof of the local Langlands Correspondence for the groups $\operatorname{GL}_{1}$ defined over $p$-adic fields $K$. We do this by redeveloping the theory of proalgebraic groups and use this to derive local class field theory in the style of Serre and Hazewinkel. In particular, we show that the local class fiel

Daniel Klaewer, Seung-Joo Lee, Timo Weigand, Max Wiesner

We study quantum corrections in four-dimensional theories with $N=1$ supersymmetry in the context of Quantum Gravity Conjectures. According to the Emergent String Conjecture, infinite distance limits in quantum gravity either lead to decompactification of the theory or result in a weakly coupled string theory. We verify this conjecture in the framework of $N

Juan Liao, Wei Liu, Xiaoyan Wang

The truncated Milstein method, which was initially proposed in (Guo, Liu, Mao and Yue 2018), is extended to the non-autonomous stochastic differential equations with the super-linear state variable and the H\"older continuous time variable. The convergence rate is proved. Compared with the initial work, the requirements on the step-size is also significantly

Avery Bailey, Jim Stone, Jeffrey Fung

We investigate the properties of the hydrodynamic flow around eccentric protoplanets and compare them with the often assumed case of a circular orbit. To this end, we perform a set of 3D hydrodynamic simulations of protoplanets with small eccentricities ($e\leq 0.1$). We adopt an isothermal equation of state and concentrate resolution on the protoplanet to i

Carlos Barrera, Nathan W. C. Leigh, Bastián Reinoso, Amelia M. Stutz

Direct collisions between finite-sized particles occur commonly in many areas of astrophysics. Such collisions are typically mediated by chaotic, bound gravitational interactions involving small numbers of particles. An important application is stellar collisions, which occur commonly in dense star clusters, and their relevance for the formation of various t

Nina S. Sartorio, Bert Vandenbroucke, Diego Falceta-Goncalves, Kenneth Wood

We present a study of the impact of photoionization feedback from young massive stars on the turbulent statistics of star-forming molecular clouds. This feedback is expected to alter the density structure of molecular clouds and affect future star formation. Using the AMUN- Rad code, we first generate a converged isothermal forced turbulent density structure

Massimo Mannarelli, Dario Grasso, Silvia Trabucco, Maria Luisa Chiofalo

Acoustic holes are the hydrodynamic analogue of standard black holes. Featuring an acoustic horizon, these systems spontaneously emit phonons at the Hawking temperature. We derive the Hawking temperature of the acoustic horizon by fully exploiting the analogy between black and acoustic holes within a covariant kinetic theory approach. After deriving the phon

A. Collier Cameron, E. B. Ford, S. Shahaf, S. Aigrain

Stellar magnetic activity produces time-varying distortions in the photospheric line profiles of solar-type stars. These lead to systematic errors in high-precision radial-velocity measurements, which limit efforts to discover and measure the masses of low-mass exoplanets with orbital periods of more than a few tens of days. We present a new data-driven meth

Shamik Banerjee, Sudip Ghosh

We show that the Mellin transform of an $n$-point tree level MHV gluon scattering amplitude, also known as the celestial amplitude in pure Yang-Mills theory, satisfies a system of $(n-2)$ linear first order partial differential equations corresponding to $(n-2)$ positive helicity gluons. Although these equations closely resemble Knizhnik-Zamolodchikov equati

Adam J. Finley, Michael D. McManus, Sean P. Matt, Justin C. Kasper

An accurate assessment of the Sun's angular momentum (AM) loss rate is an independent constraint for models that describe the rotation evolution of Sun-like stars. In-situ measurements of the solar wind taken by Parker Solar Probe (PSP), at radial distances of $\sim 28-55R_{\odot}$, are used to constrain the solar wind AM-loss rate. For the first time with P

Kai Klocke, David Aasen, Roger S. K. Mong, Eugene A. Demler

Motivated by recent experiments on the Kitaev honeycomb magnet $\alpha\text{-RuCl}_3$, we introduce time-domain probes of the edge and quasiparticle content of non-Abelian spin liquids. Our scheme exploits ancillary quantum spins that communicate via time-dependent tunneling of energy into and out of the spin liquid's chiral Majorana edge state. We show that