March 2020 arXiv papers — page 81

Long Chen, Xin Yan, Jun Xiao, Hanwang Zhang

Despite Visual Question Answering (VQA) has realized impressive progress over the last few years, today's VQA models tend to capture superficial linguistic correlations in the train set and fail to generalize to the test set with different QA distributions. To reduce the language biases, several recent works introduce an auxiliary question-only model to

Takashi Yanagisawa

Physics of topological materials have attracted much attention from both physicists and mathematicians recently. The index and the fermion number of Dirac fermions play an important role in topological insulators and topological superconductors. A zero-energy mode exists when Dirac fermions couple to objects with soliton-like structure such as kinks, vortice

Gonzalo Bley, Søren Fournais

We provide a proof of the first correction to the leading asymptotics of the minimal energy of pseudo-relativistic molecules in the presence of magnetic fields, the so-called "relativistic Scott correction", when $\max{Z_kα} \leq 2/π$, where $Z_k$ is the charge of the $k$-th nucleus and $α$ is the fine structure constant. Our theorem extends a previo

A. S. Demyanova, A. N. Danilov, A. A. Ogloblin, V. I. Starastsin

The differential cross sections of the $^{12}$C($^3$He,t)$^{12}$N reaction leading to formation of the 1$^+$ (ground state), 2$^+$(0.96 MeV), 2$^{-}$(1.19 MeV), and 1$^{-}$(1.80 MeV) states of $^{12}$N are measured at $E$($^3$He)=40 MeV. The analysis of the data is carried out within the modified diffraction model (MDM) and distorted wave Born approximation

Xiongwei Wu, Qiang Li, Yawei Lu, H. Vincent Poor

Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations to provide communication service for remote mobile users due to their high mobility and flexible deployment. However, the line-of-sight (LoS) wireless links are vulnerable to be intercepted by the eavesdropper (Eve), which presents a major challenge for UAV-aided communications. In this

Nan Zhang, Yi Cao, Yucai Li, Andrew W. Rushforth

Current-driven switching of nonvolatile spintronic materials and devices based on spin-orbit torques offer fast data processing speed, low power consumption, and unlimited endurance for future information processing applications. Analogous to conventional CMOS technology, it is important to develop a pair of complementary spin-orbit devices with differentiat

Md Atiqul Islam, George C. Alexandropoulos, Besma Smida

In this paper, we study Full Duplex (FD) Multiple-Input Multiple-Output (MIMO) radios for simultaneous data communication and control information exchange. Capitalizing on a recently proposed FD MIMO architecture combining digital transmit and receive beamforming with reduced complexity multi-tap analog Self-Interference (SI) cancellation, we propose a novel

Gengchen Mai, Krzysztof Janowicz, Sathya Prasad, Meilin Shi

Many geoportals such as ArcGIS Online are established with the goal of improving geospatial data reusability and achieving intelligent knowledge discovery. However, according to previous research, most of the existing geoportals adopt Lucene-based techniques to achieve their core search functionality, which has a limited ability to capture the user's sea

Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton

Recent research has highlighted the role of relational inductive biases in building learning agents that can generalize and reason in a compositional manner. However, while relational learning algorithms such as graph neural networks (GNNs) show promise, we do not understand how effectively these approaches can adapt to new tasks. In this work, we study the

Chawin Sitawarin, David Wagner

We study the robustness against adversarial examples of kNN classifiers and classifiers that combine kNN with neural networks. The main difficulty lies in the fact that finding an optimal attack on kNN is intractable for typical datasets. In this work, we propose a gradient-based attack on kNN and kNN-based defenses, inspired by the previous work by Sitawari

Rekishu Yamazaki, Ayato Okada, Atsushi Noguchi, Shingo Akao

Whispering gallery modes (WGMs), circulating modes near the surface of a spheroidal material, have been known to exhibit high quality factors for both acoustic and electromagnetic waves. Here, we report an electro-optomechanical system, where the overlapping WGMs of acoustic and optical waves along the equator of a dielectric sphere strongly couple to each o

Lei Li, Zhenli Xu, Yue Zhao

We propose a fast potential splitting Markov Chain Monte Carlo method which costs $O(1)$ time each step for sampling from equilibrium distributions (Gibbs measures) corresponding to particle systems with singular interacting kernels. We decompose the interacting potential into two parts, one is of long range but is smooth, and the other one is of short range

Liqin Zhou, Zhiyun Tan, Dayu Yan, Zhong Fang

Based on the first-principles calculations and theoretical analysis, we investigate the electronic structures, topological phase transition (TPT) and topological properties of layered magnetic compound MnSb2Te4. It has the similar crystal and magnetic structure as the magnetic topological insulator MnBi2Te4. We find that when the spin-orbit coupling (SOC) is

Hadi Mansourifar, Lin Chen, Weidong Shi

Increasingly growing Cryptocurrency markets have become a hive for scammers to run pump and dump schemes which is considered as an anomalous activity in exchange markets. Anomaly detection in time series is challenging since existing methods are not sufficient to detect the anomalies in all contexts. In this paper, we propose a novel hybrid pump and dump det

Zhigang Chu, Oliver Kosut, Lalitha Sankar

A machine learning-based detection framework is proposed to detect a class of cyber-attacks that redistribute loads by modifying measurements. The detection framework consists of a multi-output support vector regression (SVR) load predictor that predicts loads by exploiting both spatial and temporal correlations, and a subsequent support vector machine (SVM)

Xiaoquan Xu, Zhongqiang Yang

For a $T_0$ space $X$, let $\mk (X)$ be the poset of all compact saturated sets of $X$ with the reverse inclusion order. The space $X$ is said to have property Q if for any $K_1, K_2\in \mk (X)$, $K_2\ll K_1$ in $\mk (X)$ if{}f $K_2\subseteq \ii~\!K_1$. In this paper, we give several connections among the well-filteredness of $X$, the sobriety of $X$, the lo

Jami J. Mulgrave, Matthew E. Levine, David J. Albers, Joon Ha

Motivation: There is a growing need to integrate mechanistic models of biological processes with computational methods in healthcare in order to improve prediction. We apply data assimilation in the context of Type 2 diabetes to understand parameters associated with the disease. Results: The data assimilation method captures how well patients improve glucose

Andrew R. Kustin

In 2018 Celikbas, Laxmi, Kraśkiewicz, and Weyman exhibited an interesting family of perfect ideals of codimension three, with five generators, of Cohen-Macaulay type two with trivial multiplication on the Tor algebra. All previously known perfect ideals of codimension three, with five generators, of Cohen-Macaulay type two had been found by Brown in 1987. Br

Matthew James, Rod Letchford, Graeme L White, Meg Emery

We report lucky imaging observations of 62 pairs at mid-southern declinations sourced from the WDS with separations larger than 4 arc seconds and magnitude less than 10. The measures comprise separations and PA calibrated against Alpha Centauri AB and drift scans, presented as weighted means of these two calibration methods, with formal internal uncertaintie

I. J. Lee, D. N. Yetter

We provide a description of adequate categorical data to give a Turaev-Viro type state-sum construct of invariants of 3-manifolds with a system of defects, generalizing the Dijkgraaf-Witten type invariants of our earlier work. We term the defects in our construction defects-with-structure because algebraic data associated to them is in general richer than a

Chaitali Joshi, Alessandro Farsi, Avik Dutt, Bok Young Kim

Frequency encoding of quantum information together with fiber and integrated photonic technologies can significantly reduce the complexity and resource requirements for realizing all-photonic quantum networks. The key challenge for such frequency domain processing of single photons is to realize coherent and selective interactions between quantum optical fie

Xinyi Zeng, Qian Zhang, Jia Chen, Guixu Zhang

Automated tongue image segmentation in tongue images is a challenging task for two reasons: 1) there are many pathological details on the tongue surface, which affect the extraction of the boundary; 2) the shapes of the tongues captured from various persons (with different diseases) are quite different. To deal with the challenge, a novel end-to-end Boundary

Krzysztof Bolejko, Matteo Cinus, Boudewijn F. Roukema

Torsion is a non-Riemannian geometrical extension of general relativity that allows including the spin of matter and the twisting of spacetime. Cosmological models with torsion have been considered in the literature to solve problems of either the very early (high redshift $z$) or the present-day Universe. This paper focuses on distinguishable observational

Carsten Gräser, Prem Anand Alathur Srinivasan

In this work we consider the regularization of a supervised learning problem by partial differential equations (PDEs) and derive error bounds for the obtained approximation in terms of a PDE error term and a data error term. Assuming that the target function satisfies an unknown PDE, the PDE error term quantifies how well this PDE is approximated by the auxi

Ya-Ping Li, Hui Li, Shengtai Li, Tilman Birnstiel

In this work, we study how the dust coagulation/fragmentation will influence the evolution and observational appearances of vortices induced by a massive planet embedded in a low viscosity disk by performing global 2D high-resolution hydrodynamical simulations. Within the vortex, due to its higher gas surface density and steeper pressure gradients, dust coag

Nikolay Malkin

The Hodge correlators ${\rm Cor}_{\mathcal H}(z_0,z_1,\dots,z_n)$ are functions of several complex variables, defined by Goncharov (arXiv:0803.0297) by an explicit integral formula. They satisfy some linear relations: dihedral symmetry relations, distribution relations, and shuffle relations. We found new second shuffle relations. When $z_i\in0\cupμ_N$, wher

Zhelun Wu, Hongyan Jiang, Siyun He

Symmetry detection has been a classical problem in computer graphics, many of which using traditional geometric methods. In recent years, however, we have witnessed the arising deep learning changed the landscape of computer graphics. In this paper, we aim to solve the symmetry detection of the occluded point cloud in a deep-learning fashion. To the best of

Jing Li, David Jewitt, Max Mutchler, Jessica Agarwal

Solar system objects with perihelia beyond the orbit of Jupiter ($q >$ 5 AU) are too cold for water ice to generate an appreciable coma via sublimation. Despite this, numerous high perihelion objects (HPOs) including many comets and recently escaped Kuiper belt objects (``Centaurs'') are observed to be active out at least to the orbit of Saturn ($q \

Jie Ying Wu, Peter Kazanzides, Mathias Unberath

Purpose Surgical simulations play an increasingly important role in surgeon education and developing algorithms that enable robots to perform surgical subtasks. To model anatomy, Finite Element Method (FEM) simulations have been held as the gold standard for calculating accurate soft-tissue deformation. Unfortunately, their accuracy is highly dependent on th

Armin Nikkhah Shirazi

In his book `Physics and Philosophy', Heisenberg suggested that the quantum world is one of ``potentialities or possibilities'' and that the classical realm is one of ``things or facts''. After ascertaining that his categories most naturally have the structure of ontological equivalence classes, we show that they cannot be seriously intro

Vinod Ramaswamy, Dario Paccagnan, Jason R. Marden

The price of anarchy and price of stability are three well-studied performance metrics that seek to characterize the inefficiency of equilibria in distributed systems. The distinction between these two performance metrics centers on the equilibria that they focus on: the price of anarchy characterizes the quality of the worst-performing equilibria, while the

Deeksha Dixit, Surabhi Verma, Pratap Tokekar

Cross-view matching refers to the problem of finding the closest match for a given query ground view image to one from a database of aerial images. If the aerial images are geotagged, then the closest matching aerial image can be used to localize the query ground view image. Due to the recent success of deep learning methods, several cross-view matching tech

Yifan Gong, Zheng Zhan, Zhengang Li, Wei Niu

Weight pruning of deep neural networks (DNNs) has been proposed to satisfy the limited storage and computing capability of mobile edge devices. However, previous pruning methods mainly focus on reducing the model size and/or improving performance without considering the privacy of user data. To mitigate this concern, we propose a privacy-preserving-oriented

Haiyun He, Qiaosheng Zhang, Vincent Y. F. Tan

This paper investigates a novel offline change-point detection problem from an information-theoretic perspective. In contrast to most related works, we assume that the knowledge of the underlying pre- and post-change distributions are not known and can only be learned from the training sequences which are available. We further require the probability of the

Ashraf Tahmasbi, Ellango Jothimurugesan, Srikanta Tirthapura, Phillip B. Gibbons

When learning from streaming data, a change in the data distribution, also known as concept drift, can render a previously-learned model inaccurate and require training a new model. We present an adaptive learning algorithm that extends previous drift-detection-based methods by incorporating drift detection into a broader stable-state/reactive-state process.

Gabriel Lima, Meeyoung Cha, Chihyung Jeon, Kyungsin Park

Regulating artificial intelligence (AI) has become necessary in light of its deployment in high-risk scenarios. This paper explores the proposal to extend legal personhood to AI and robots, which had not yet been examined through the lens of the general public. We present two studies (N = 3,559) to obtain people's views of electronic legal personhood vis-\`a

R. J. Needs, M. D. Towler, N. D. Drummond, P. Lopez Rios

We present an overview of the variational and diffusion quantum Monte Carlo methods as implemented in the CASINO program. We particularly focus on developments made in the last decade, describing state-of-the-art quantum Monte Carlo algorithms and software and discussing their strengths and their weaknesses. We review a range of recent applications of CASINO

Ning Tian, Yebin Wang, Jian Chen, Huazhen Fang

Parameter estimation is of foundational importance for various model-based battery management tasks, including charging control, state-of-charge estimation and aging assessment. However, it remains a challenging issue as the existing methods generally depend on cumbersome and time-consuming procedures to extract battery parameters from data. Departing from t

Houmem Belkhechine, Cherifa Ben Salha

Given a tournament $T$, a module of $T$ is a subset $X$ of $V(T)$ such that for $x, y\in X$ and $v\in V(T)\setminus X$, $(x,v)\in A(T)$ if and only if $(y,v)\in A(T)$. The trivial modules of $T$ are $\emptyset$, $\{u\}$ $(u\in V(T))$ and $V(T)$. The tournament $T$ is indecomposable if all its modules are trivial; otherwise it is decomposable. The decomposabi

Michele Caprio, Sayan Mukherjee

We formulate an ergodic theory for the (almost sure) limit $\mathcal{P}^\text{co}_{\tilde{\mathcal{E}}}$ of a sequence $(\mathcal{P}^\text{co}_{\mathcal{E}_n})$ of successive dynamic imprecise probability kinematics (DIPK, introduced in Caprio and Gong, 2021) updates of a set $\mathcal{P}^\text{co}_{\mathcal{E}_0}$ representing the initial beliefs of an agen

Ayman Chaouki, Stephen Hardiman, Christian Schmidt, Emmanuel Sérié

Can deep reinforcement learning algorithms be exploited as solvers for optimal trading strategies? The aim of this work is to test reinforcement learning algorithms on conceptually simple, but mathematically non-trivial, trading environments. The environments are chosen such that an optimal or close-to-optimal trading strategy is known. We study the deep det

Navdeep Kaur, Gautam Kunapuli, Sriraam Natarajan

In this work, we propose a novel knowledge graph alignment technique based upon string edit distance that exploits the type information between entities and can find similarity between relations of any arity

Xiaowei Jin, Shengze Cai, Hui Li, George Em Karniadakis

We employ physics-informed neural networks (PINNs) to simulate the incompressible flows ranging from laminar to turbulent flows. We perform PINN simulations by considering two different formulations of the Navier-Stokes equations: the velocity-pressure (VP) formulation and the vorticity-velocity (VV) formulation. We refer to these specific PINNs for the Navi

Maegan Tucker, Myra Cheng, Ellen Novoseller, Richard Cheng

Optimizing lower-body exoskeleton walking gaits for user comfort requires understanding users' preferences over a high-dimensional gait parameter space. However, existing preference-based learning methods have only explored low-dimensional domains due to computational limitations. To learn user preferences in high dimensions, this work presents LineCoSpa

Guanze Peng, Juntao Chen, Quanyan Zhu

In this paper, we study the stabilization of two interdependent Markov jump linear systems (MJLSs) with partial information, where the interdependency arises as the transition of the mode of one system depends on the states of the other system. First, we formulate a framework for the two interdependent MJLSs to capture the interactions between various entiti

Renyan Feng, Erman Acar, Stefan Schlobach, Yisong Wang

Computation Tree Logic (CTL) is one of the central formalisms in formal verification. As a specification language, it is used to express a property that the system at hand is expected to satisfy. From both the verification and the system design points of view, some information content of such property might become irrelevant for the system due to various rea

Eduardo Ruíz Duarte, Marc Paul Noordman

We use the arithmetic of the Kummer surface associated to the Jacobian of a hyperelliptic curve to study the primality of integers of the form $4m^2 5^n-1$. We provide an algorithm capable of proving the primality or compositeness of most of the integers in these families and discuss in detail the necessary steps to implement this algorithm in a computer. Al

Roy Overbeek, Jörg Endrullis

The basic principle of graph rewriting is the stepwise replacement of subgraphs inside a host graph. A challenge in such replacement steps is the treatment of the patch graph, consisting of those edges of the host graph that touch the subgraph, but are not part of it. We introduce the patch graph rewriting framework, a visual graph rewriting language with pr

Dan Alistarh, Martin Töpfer, Przemysław Uznański

There has recently been a surge of interest in the computational and complexity properties of the population model, which assumes $n$ anonymous, computationally-bounded nodes, interacting at random, and attempting to jointly compute global predicates. Significant work has gone towards investigating majority and consensus dynamics in this model: assuming that

Ion Victor Gosea, Igor Pontes Duff

The dynamic mode decomposition (DMD) is a data-driven method used for identifying the dynamics of complex nonlinear systems. It extracts important characteristics of the underlying dynamics using measured time-domain data produced either by means of experiments or by numerical simulations. In the original methodology, the measurements are assumed to be appro

Alexey Bufetov, Vadim Gorin, Dan Romik

The oriented swap process is a natural directed random walk on the symmetric group that can be interpreted as a multi-species version of the Totally Asymmetric Simple Exclusion Process (TASEP) on a finite interval. An open problem from a 2008 paper of Angel, Holroyd, and Romik asks for the limiting distribution of the absorbing time of the process. We resolv

Simone Brugiapaglia, Lorenzo Tamellini, Mattia Tani

This work is motivated by the difficulty in assembling the Galerkin matrix when solving Partial Differential Equations (PDEs) with Isogeometric Analysis (IGA) using B-splines of moderate-to-high polynomial degree. To mitigate this problem, we propose a novel methodology named CossIGA (COmpreSSive IsoGeometric Analysis), which combines the IGA principle with

Luchen Li, Ignacio Albert-Smet, Aldo A. Faisal

Our aim is to establish a framework where reinforcement learning (RL) of optimizing interventions retrospectively allows us a regulatory compliant pathway to prospective clinical testing of the learned policies in a clinical deployment. We focus on infections in intensive care units which are one of the major causes of death and difficult to treat because of

Binod Bhattarai, Tae-Kyun Kim

Conditional GANs are widely used in translating an image from one category to another. Meaningful conditions to GANs provide greater flexibility and control over the nature of the target domain synthetic data. Existing conditional GANs commonly encode target domain label information as hard-coded categorical vectors in the form of 0s and 1s. The major drawba

Ana Fernández del Río, Anna Guitart, África Periáñez

Players of a free-to-play game are divided into three main groups: non-paying active users, paying active users and inactive users. A State Space time series approach is then used to model the daily conversion rates between the different groups, i.e., the probability of transitioning from one group to another. This allows, not only for predictions on how the

N. Aizawa, Z. Kuznetsova, F. Toppan

${\mathbb Z}_2\times {\mathbb Z}_2$-graded mechanics admits four types of particles: ordinary bosons, two classes of fermions (fermions belonging to different classes commute among each other) and exotic bosons. In this paper we construct the basic ${\mathbb Z}_2\times {\mathbb Z}_2$-graded worldline multiplets (extending the cases of one-dimensional supersy

Sergio Albeverio, Francesco C. De Vecchi, Andrea Romano, Stefania Ugolini

We study a family of McKean-Vlasov (mean-field) type ergodic optimal control problems with linear control, and quadratic dependence on control of the cost function. For this class of problems we establish existence and uniqueness of an optimal control. We propose an $N$-particles Markovian optimal control problem approximating the McKean-Vlasov one and we pr

CMS Collaboration

Measurements of the cross section for the production of top quark pairs in association with a pair of jets from bottom quarks ($σ_\mathrm{t\bar{t}b\bar{b}}$) and in association with a pair of jets from quarks of any flavor or gluons ($σ_\mathrm{t\bar{t}jj}$) and their ratio are presented. The data were collected in proton-proton collisions at a center-of-mas

Nassif Ghoussoub, Young-Heon Kim, Aaron Zeff Palmer

Given a stochastic state process $(X_t)_t$ and a real-valued submartingale cost process $(S_t)_t$, we characterize optimal stopping times $\tau$ that minimize the expectation of $S_\tau$ while realizing given initial and target distributions $\mu$ and $\nu$, i.e., $X_0\sim \mu$ and $X_\tau \sim \nu$. A dual optimization problem is considered and shown to be

Ramyad Hadidi, Bahar Asgari, Jiashen Cao, Younmin Bae

Deep neural networks (DNNs) have inspired new studies in myriad edge applications with robots, autonomous agents, and Internet-of-things (IoT) devices. However, performing inference of DNNs in the edge is still a severe challenge, mainly because of the contradiction between the intensive resource requirements of DNNs and the tight resource availability in se

Kanika Bansal, Javier O. Garcia, Nina Lauharatanahirun, Sarah F. Muldoon

Cascading large-amplitude bursts in neural activity, termed avalanches, are thought to provide insight into the complex spatially distributed interactions in neural systems. In human neuroimaging, for example, avalanches occurring during resting-state show scale-invariant dynamics, supporting the hypothesis that the brain operates near a critical point that

Jessie Smith, Nasim Sonboli, Casey Fiesler, Robin Burke

Algorithmic fairness for artificial intelligence has become increasingly relevant as these systems become more pervasive in society. One realm of AI, recommender systems, presents unique challenges for fairness due to trade offs between optimizing accuracy for users and fairness to providers. But what is fair in the context of recommendation--particularly wh

Thiago R. F. P. Tomei

The CMS experiment has been designed with a two-level trigger system: the Level-1 Trigger, implemented on custom-designed electronics, and the High Level Trigger, a streamlined version of the CMS offline reconstruction software running on a computer farm. During its second phase the LHC will reach a luminosity of $7.5\times10^{34}\,\textrm{cm}^{-2}\,\textrm{

Felipe Maia Polo, Itamar Ciochetti, Emerson Bertolo

The objective of this paper is to develop predictive models to classify Brazilian legal proceedings in three possible classes of status: (i) archived proceedings, (ii) active proceedings, and (iii) suspended proceedings. This problem's resolution is intended to assist public and private institutions in managing large portfolios of legal proceedings, providin

Aditi Mandal, Nikita Dhankhar, Didier Sébilleau, Rakesh Choubisa

In this communication, we report our calculations of Triple Differential Cross-Section (TDCS) for the relativistic (e,2e) process with a twisted electron beam on Cu and Ag atomic targets in coplanar asymmetric geometry mode. The theoretical formalism has been developed in the first Born approximation (FBA) in which we use the Dirac plane wave as well as the

Xin Luo

The classical Hlawka inequality possesses deep connections with zonotopes and zonoids in convex geometry, and has been related to Minkowski space. We introduce Hlawka Type-1 and Type-2 quantities, and establish a Hlawka-type relation between them, which connects a vast number of strikingly different variants of the Hlawka inequalities, such as Serre's revers

Xingyu Zhou, Ness Shroff

In this note, we apply Stein's method to analyze the steady-state distribution of queueing systems in the traditional heavy-traffic regime. Compared to previous methods (e.g., drift method and transform method), Stein's method allows us to establish stronger results with simple and template proofs. In particular, we consider discrete-time systems in

Guenter Hesse, Christoph Matthies, Matthias Uflacker

Message brokers see widespread adoption in modern IT landscapes, with Apache Kafka being one of the most employed platforms. These systems feature well-defined APIs for use and configuration and present flexible solutions for various data storage scenarios. Their ability to scale horizontally enables users to adapt to growing data volumes and changing enviro

Marianne de Vriendt, Philip Sellars, Angelica I Aviles-Rivero

We consider the problem of classifying a medical image dataset when we have a limited amounts of labels. This is very common yet challenging setting as labelled data is expensive, time consuming to collect and may require expert knowledge. The current classification go-to of deep supervised learning is unable to cope with such a problem setup. However, using

Martin Chak, Nikolas Kantas, Grigorios A. Pavliotis

In this paper, we consider the generalised (higher order) Langevin equation for the purpose of simulated annealing and optimisation of nonconvex functions. Our approach modifies the underdamped Langevin equation by replacing the Brownian noise with an appropriate Ornstein-Uhlenbeck process to account for memory in the system. Under reasonable conditions on t

Michael P. Ross, Krishna Venkateswara, Conor Mow-Lowry, Sam Cooper

Modern gravitational-wave observatories require robust low-frequency active seismic isolation in order to keep the interferometer at its ideal operating conditions. Seismometers are used to measure both the motion of the ground and isolated platform. These devices are susceptible to contamination from ground tilt at frequencies below 0.1 Hz, particularly ari

Cesar Bonilla, Leon M. G. de la Vega, R. Ferro-Hernandez, Newton Nath

We present a minimal left-right symmetric flavor model and analyze the predictions for the neutrino sector. In this scenario, the Yukawa sector is shaped by the dihedral $D_4$ symmetry which leads to correlations for the neutrino mixing parameters. We end up with four possible solutions within this model. We further analyzed the impact of the upcoming long-b

Dušan Joksimović, Fabian Ziltener

K. Cieliebak, H. Hofer, J. Latschev, and F. Schlenk (CHLS) posed the problem of finding a minimal generating set for the (symplectic) capacities on a given symplectic category. We show that if the category contains a certain one-parameter family of objects, then every countably Borel-generating set of (normalized) capacities has cardinality (strictly) bigger

Yuya Yoshikawa, Tomoharu Iwata

For reliability, it is important that the predictions made by machine learning methods are interpretable by human. In general, deep neural networks (DNNs) can provide accurate predictions, although it is difficult to interpret why such predictions are obtained by DNNs. On the other hand, interpretation of linear models is easy, although their predictive perf

Alvaro S. de Jesus, Sergey Kovalenko, Farinaldo S. Queiroz, Carlos A. de S. Pires

We have witnessed a persistent puzzling anomaly in the muon magnetic moment that cannot be accounted for in the Standard Model even considering the large hadronic uncertainties. A new measurement is forthcoming, and it might give rise to a $5\sigma$ claim for physics beyond the Standard Model. Motivated by it, we explore the implications of this new result t

Gregory Moille, Lin Chang, Weiqiang Xie, Ashutosh Rao

We demonstrate stable microresonator Kerr soliton frequency combs in a III-V platform (AlGaAs on SiO$_2$) through quenching of thermorefractive effects by cryogenic cooling to temperatures between 4~K and 20~K. This cooling reduces the resonator's thermorefractive coefficient, whose room-temperature value is an order of magnitude larger than that of othe

Konstantin Beyer, Kimmo Luoma, Walter T. Strunz

We propose a definition of externally measurable quantum work in driven systems. Work is given as a quantum observable on a control device which is forcing the system and can be determined without knowledge of the system Hamiltonian $H_\mathcal{S}$. We argue that quantum work fluctuation theorems which rely on the knowledge of $H_\mathcal{S}$ are of little p

Gabriel F. N. Gonçalves, Assen Batchvarov, Yuyi Liu, Yuxin Liu

In chemical process engineering, surrogate models of complex systems are often necessary for tasks of domain exploration, sensitivity analysis of the design parameters, and optimization. A suite of computational fluid dynamics (CFD) simulations geared toward chemical process equipment modeling has been developed and validated with experimental results from t

Ravi B. Boppana, Harrie Hendriks, Martien C. A. van Zuijlen

Let $v_1$, $v_2$, ..., $v_n$ be real numbers whose squares add up to 1. Consider the $2^n$ signed sums of the form $S = \sum \pm v_i$. Boppana and Holzman (2017) proved that at least 13/32 of these sums satisfy $|S| \le 1$. Here we improve their bound to $0.427685$.

David V. Bowen, Todd M. Tripp, Edward B. Jenkins, Max Pettini

We present an HST Cosmic Origins Spectrograph (COS) spectrum of the QSO SDSS J095109.12+330745.8 ($z_{em} = 0.645$) whose sightline passes through the SMC-like dwarf galaxy UGC 5282 ($M_B = -16.0$, $cz = 1577$ km s$^{-1}$ ), 1.2 kpc in projection from the central HII region of the galaxy. Damped Ly$α$ (DLA) absorption is detected at the redshift of UGC 5282

Jens Stücker, Andreas. S. Schmidt, Simon D. M. White, Fabian Schmidt

We present anisotropic "separate universe" simulations which modify the N-body code Gadget-4 in order to represent a large-scale tidal field through an anisotropic expansion factor. These simulations are used to measure the linear, quasi-linear and nonlinear response of the matter power spectrum to a spatially uniform trace-free tidal field up to wavenumber

Victor Gitton, Mischa P. Woods

Starting from arbitrary sets of quantum states and measurements, referred to as the prepare-and-measure scenario, an operationally noncontextual ontological model of the quantum statistics associated with the prepare-and-measure scenario is constructed. The operationally noncontextual ontological model coincides with standard Spekkens noncontextual ontologic

C. von Essen, M. Mallonn, S. Hermansen, M. C. Nixon

We present an atmospheric transmission spectrum of the ultra-hot Jupiter WASP-76 b by analyzing archival data obtained with the Space Telescope Imaging Spectrograph (STIS) on board the Hubble Space Telescope (HST). The dataset spans three transits, two with a wavelength coverage between 2900 and 5700 Armstrong, and the third one between 5250 and 10300 Armstr

Scott Emmons, Ajay Jain, Michael Laskin, Thanard Kurutach

To operate effectively in the real world, agents should be able to act from high-dimensional raw sensory input such as images and achieve diverse goals across long time-horizons. Current deep reinforcement and imitation learning methods can learn directly from high-dimensional inputs but do not scale well to long-horizon tasks. In contrast, classical graphic

Sameer K. Deshpande, Ray Bai, Cecilia Balocchi, Jennifer E. Starling

The linear varying coefficient models posits a linear relationship between an outcome and covariates in which the covariate effects are modeled as functions of additional effect modifiers. Despite a long history of study and use in statistics and econometrics, state-of-the-art varying coefficient modeling methods cannot accommodate multivariate effect modifi

Omid Jafari, Parth Nagarkar, Jonathan Montaño

Many large multimedia applications require efficient processing of nearest neighbor queries. Often, multimedia data are represented as a collection of important high-dimensional feature vectors. Existing Locality Sensitive Hashing (LSH) techniques require users to find top-k similar feature vectors for each of the feature vectors that represent the query obj

Sebastian Eckart

For a circularly polarized single-color field at a central frequency of $2ω$ the final electron momentum distribution upon strong field ionization does not carry any information about the phase of the initial momentum distribution. Adding a weak, co-rotating, circularly polarized field at a central frequency of $ω$ gives rise to a sub-cycle interference patt

Rodrigo Voivodic, Henrique Rubira, Marcos Lima

Within the Halo Model of large scale structure, all matter is contained in dark matter halos. This simple yet powerful framework has been broadly applied to multiple data sets and enriched our comprehension of how matter is distributed in the Universe. In this work we extend this assumption by allowing for matter to rest not only inside halos but also within

Ion Victor Gosea, Stefan Güttel

A selection of algorithms for the rational approximation of matrix-valued functions are discussed, including variants of the interpolatory AAA method, the RKFIT method based on approximate least squares fitting, vector fitting, and a method based on low-rank approximation of a block Loewner matrix. A new method, called the block-AAA algorithm, based on a gen

Anthony Hu, Fergal Cotter, Nikhil Mohan, Corina Gurau

We present a novel deep learning architecture for probabilistic future prediction from video. We predict the future semantics, geometry and motion of complex real-world urban scenes and use this representation to control an autonomous vehicle. This work is the first to jointly predict ego-motion, static scene, and the motion of dynamic agents in a probabilis

M. Nilsson Tengstrand, D. Boholm, R. Sachdeva, J. Bengtsson

We investigate the rotational properties of a dipolar Bose-Einstein condensate trapped in a toroidal geometry. Studying the ground states in the rotating frame and at fixed angular momenta, we observe that the condensate acts in distinctly different ways depending on whether it is in the superfluid or in the supersolid phase. We find that intriguingly, the t

Ian Wong, Avi Shporer, Tansu Daylan, Björn Benneke

We present a systematic phase curve analysis of known transiting systems observed by the Transiting Exoplanet Survey Satellite (TESS) during year one of the primary mission. Using theoretical predictions for the amplitude of the planetary longitudinal atmospheric brightness modulation, stellar ellipsoidal distortion and Doppler boosting, as well as brightnes

P. Giommi, P. Padovani, F. Oikonomou, T. Glauch

The uncertainty region of the highly energetic neutrino IceCube200107A includes 3HSP J095507.9+355101 ($z$~=~0.557), an extreme blazar, which was detected in a high, very hard, and variable X-ray state shortly after the neutrino arrival. Following a detailed multi-wavelength investigation, we confirm that the source is a genuine BL Lac, contrary to TXS 0506+

Ardi Tampuu, Maksym Semikin, Naveed Muhammad, Dmytro Fishman

Autonomous driving is of great interest to industry and academia alike. The use of machine learning approaches for autonomous driving has long been studied, but mostly in the context of perception. In this paper we take a deeper look on the so called end-to-end approaches for autonomous driving, where the entire driving pipeline is replaced with a single neu

María Ángeles García-Ferrero, Angkana Rüland

In this article we present two mechanisms for deducing logarithmic quantitative unique continuation bounds for certain classes of integral operators. In our first method, expanding the corresponding integral kernels, we exploit the logarithmic stability of the moment problem. In our second method we rely on the presence of branch-cut singularities for certai

Roberto Fumagalli, Jonas Heverhagen, Davide Betto, Riccardo Arpaia

We investigate the Cu $L_3$ edge resonant inelastic x-ray scattering (RIXS) spectra of a quasi-1D antiferromagnet Ca$_2$CuO$_3$. In addition to the magnetic excitations, which are well-described by the two-spinon continuum, we observe two dispersive orbital excitations, the $3d_{xy}$ and the $3d_{yz}$ orbitons. We carry out a quantitative comparison of the R

Jeffrey R. Forshaw, Jack Holguin, Simon Plätzer

Modern parton showers are built using one of two models: dipole showers or angular ordered showers. Both have distinct strengths and weaknesses. Dipole showers correctly account for wide-angle, soft gluon emissions and track the leading flows in QCD colour charge but they are known to mishandle partonic recoil. Angular ordered showers keep better track of pa

Jun Zhang, Yi-Yu Lin, Hao-Chun Liang, Ke-Jia Chi

We study the pair production of charged scalar particles from the five-dimensional near extremal Reissner- Nordstr\"om-Anti de Sitter (RN-AdS5) black hole. The pair production rate and the absorption cross section ratio in the full spacetime are obtained and are shown to have proportional relation with their counterparts in the near horizon region. In additi

Stephen DiAdamo, Janis Nötzel, Benjamin Zanger, Mehmet Mert Beşe

As quantum internet technologies develop, the need for simulation software and education for quantum internet rises. QuNetSim aims to fill this need. QuNetSim is a Python software framework that can be used to simulate quantum networks up to the network layer. The goal of QuNetSim is to make it easier to investigate and test quantum networking protocols over

Miguel Zumalacarregui

Discrepant measurements of the Universe's expansion rate ($H_0$) may signal physics beyond the standard cosmological model. Here I describe two early modified gravity mechanisms that reconcile the value of $H_0$ by increasing the expansion rate in the era of matter-radiation equality. These mechanisms, based on viable Horndeski theories, require signific