January 2022 arXiv papers — page 59

Xiaobo Ma, Guangwei Wang, Huican Mao, Zhihong Yuan

The electronic structures and topological properties of the orthorhombic and monoclinic phases of the quasi-one-dimensional excitonic insulator Ta2NiSe5 are investigated based on density functional theory. In contrast to a single parity or band inversion across the Fermi level in many topological insulators studied previously, there are multiple parity and b

Sean Deyo, Michelle Kelley, Nathan Sitaraman, Thomas Oseroff

Recent experiments on superconducting cavities have found that under large radio-frequency (RF) electromagnetic fields the quality factor can improve with increasing field amplitude, a so-called "anti-Q slope." Linear theories of dissipation break down under these extreme conditions and are unable to explain this behavior. We numerically solve the Bogoliubov

Philipp Zabka, Klaus-Tycho Foerster, Stefan Schmid, Christian Decker

Payment channel networks (PCNs) such as the Lightning Network offer an appealing solution to the scalability problem faced by many cryptocurrencies operating on a blockchain such as Bitcoin. However, PCNs also inherit the stringent dependability requirements of blockchain. In particular, in order to mitigate liquidity bottlenecks as well as on-path attacks,

Man Luo, Arindam Mitra, Tejas Gokhale, Chitta Baral

Information retrieval (IR) is essential in search engines and dialogue systems as well as natural language processing tasks such as open-domain question answering. IR serve an important function in the biomedical domain, where content and sources of scientific knowledge may evolve rapidly. Although neural retrievers have surpassed traditional IR approaches s

Stefan Banholzer, Luca Mechelli, Stefan Volkwein

In the present paper non-convex multi-objective parameter optimization problems are considered which are governed by elliptic parametrized partial differential equations (PDEs). To solve these problems numerically the Pascoletti-Serafini scalarization is applied and the obtained scalar optimization problems are solved by an augmented Lagrangian method. Howev

Richard Evan Schwartz

This note gives a very succinct conceptual proof of Brahmagupta's formula for cyclic quadrilaterals, and then a long discussion about how the proof is inspired by ideas from modern mathematics.

James E. Smith

This document is focused on computing systems implemented in technologies that communicate and compute with temporal transients. Although described in general terms, implementations of spiking neural networks are of primary interest. As background, an algebra for constructing temporal networks is summarized. Then, a system organization consisting of synchron

Tasho Kaletha

We discuss progress towards the classification of irreducible admissible representations of reductive groups over non-archimedean local fields and the local Langlands correspondence. We also state some (partly conjectural) compatibility properties of the refined local Langlands correspondence.

Tiantian Gong, Ryan Henry, Alexandros Psomas, Aniket Kate

A long line of research on secure computation has confirmed that anything that can be computed, can be computed securely using a set of non-colluding parties. Indeed, this non-collusion assumption makes a number of problems solvable, as well as reduces overheads and bypasses computational hardness results, and it is pervasive across different privacy-enhanci

Justin Tahmassebpur, Patrick H. Diamond

We show that enhanced turbulent mixing can be used to mitigate airborne COVID-19 transmission by dispersing virus-laden clouds in enclosed, poorly ventilated spaces. A simple system of fan-driven turbulent jets is designed so as to minimize peak concentrations of passive contaminants on time scales short compared to the room ventilation time. Standard Reynol

Célestin Coquidé, José Lages, Leonardo Ermann, Dima L. Shepelyansky

Using the United Nations Comtrade database, we perform the Google matrix analysis of the multiproduct World Trade Network (WTN) for the years 2018-2020 comprising the emergence of the COVID-19 as a global pandemic. The applied algorithms -- the PageRank, the CheiRank and the reduced Google matrix -- take into account the multiplicity of the WTN links providi

Guy Blanc, Caleb Koch, Jane Lange, Li-Yang Tan

We study the problem of {\sl certification}: given queries to a function $f : \{0,1\}^n \to \{0,1\}$ with certificate complexity $\le k$ and an input $x^\star$, output a size-$k$ certificate for $f$'s value on $x^\star$. This abstractly models a central problem in explainable machine learning, where we think of $f$ as a blackbox model that we seek to explain

Andrei Tokovinin

A compact bound group of four active M-type dwarfs containing V1311 Ori is identified in the Gaia catalog of nearby stars. Located at a distance of 39 pc, it is likely related to the beta Pictoris and 32 Ori moving groups by kinematics, isochronal age, and other indicators of youth (Halpha emission, presence of lithium, and fast rotation). The brightest star

S. A. Kaplan

The preprint is an English translation of the paper by famous astrophysicist Samuil Kaplan (1921-1978) "O krugovykh orbitakh v teorii tyagoteniya Einsteina (On circular orbits in Einstein's theory of gravitation)", published in 1949 in the Journal of Experimental and Theoretical Physics (Vol. 19, No. 10, pp. 951-952) in Russian. This important 1 and 1/3 page

Jiaojiao Zhang, Huikang Liu, Anthony Man-Cho So, Qing Ling

In Part I of this work, we have proposed a general framework of decentralized stochastic quasi-Newton methods, which converge linearly to the optimal solution under the assumption that the local Hessian inverse approximations have bounded positive eigenvalues. In Part II, we specify two fully decentralized stochastic quasi-Newton methods, damped regularized

Po-Wen Tang, Shiue-Yuan Shiau, He-Chun Chou, Xin-Quan Zhang

Beyond-diffraction-limit optical absorption spectroscopy provides profound information on the graded band structures of composition-spread and stacked two-dimensional materials, in which direct/indirect bandgap, interlayer coupling, sliding, and possible defects significantly modify their optoelectronic functionalities such as photoluminescence efficiency. W

Andrey Grankin, Victor Galitski

Hyperbolic plasmons are collective electron excitations in layered conductors. They are of relevance to a number of superconducting materials, including the cuprates and layered hyperbolic metamaterials [V. N. Smolyaninova, et al. Scientific Reports 6, 34140 (2016)]. This work studies how the unusual dispersion of hyperbolic plasmons affects Cooped pairing.

Yash More, Prashanthi Ramachandran, Priyam Panda, Arup Mondal

Federated learning enables multiple data owners to jointly train a machine learning model without revealing their private datasets. However, a malicious aggregation server might use the model parameters to derive sensitive information about the training dataset used. To address such leakage, differential privacy and cryptographic techniques have been investi

Neelesh Kr. Sharma, Mayank Tiwari, Atul Thakur, Anindya K. Ganguli

Challenges of enhancing productivity by amplifying efficiency and man-machine compatibility of equipment can be achieved by adopting advanced technologies. This study aims to present and exemplify methodology for incorporating ergonomics pro-actively into the design using computer-aided design and digital human modeling-based analysis. The cleaning equipment

Noam Soker

I propose a new scenario, the polar common envelope jets supernova (CEJSN) impostor scenario, to account for AT2018cow-like fast blue optical transients (FBOTs). The polar CEJSN impostor scenario evolves through four main phases. (1) A red supergiant (RSG) star expands to tidally interact with a neutron star (NS) companion (or a black hole). The interaction

G. Lacedelli, T. G. Wilson, L. Malavolta, M. J. Hooton

We present a precise characterization of the TOI-561 planetary system obtained by combining previously published data with TESS and CHEOPS photometry, and a new set of $62$ HARPS-N radial velocities (RVs). Our joint analysis confirms the presence of four transiting planets, namely TOI-561 b ($P = 0.45$ d, $R = 1.42$ R$_\oplus$, $M = 2.0$ M$_\oplus$), c ($P =

Chen Ling, Krishna P. Gummadi, Savvas Zannettou

During the COVID-19 pandemic, health-related misinformation and harmful content shared online had a significant adverse effect on society. To mitigate this adverse effect, mainstream social media platforms employed soft moderation interventions (i.e., warning labels) on potentially harmful posts. Despite the recent popularity of these moderation intervention

Jochen L. Leidner

Big data, i.e. collecting, storing and processing of data at scale, has recently been possible due to the arrival of clusters of commodity computers powered by application-level distributed parallel operating systems like HDFS/Hadoop/Spark, and such infrastructures have revolutionized data mining at scale. For data mining project to succeed more consistently

Jun Yuan, Brian Barr, Kyle Overton, Enrico Bertini

One of the potential solutions for model interpretation is to train a surrogate model: a more transparent model that approximates the behavior of the model to be explained. Typically, classification rules or decision trees are used due to the intelligibility of their logic-based expressions. However, decision trees can grow too deep and rule sets can become

Fan Xu, Fang Yang

Let $\Lambda_Q$ be the preprojective algebra of a finite acyclic quiver $Q$ of non-Dynkin type and $D^b(\mathrm{rep}^n \Lambda_Q)$ be the bounded derived category of finite dimensional nilpotent $\Lambda_Q$-modules. We define spherical twist functors over the root category $\mathcal{R}_{\Lambda_Q}$ of $D^b(\mathrm{rep}^n \Lambda_Q)$ and then realize the Weyl

Ali Zafari, Saeid Alikhani

The task of identifying resolving sets has been extensively studied due to its wide relevance in fields such as chemistry, robot navigation, combinatorial optimization, pattern recognition, and image processing. These applications have helped motivate and establish the theoretical foundations of the subject. Notably, problems of this type are generally known

Jie Qiu, Liang Hao, Lihua Cao, Shiyang Zou

In a laser-irradiated plasma, the Langdon effect can result in a super-Gaussian electron energy distribution function (EEDF), imposing significant influences on the stimulated backward Raman scattering (SRS). In this work, the influence of a super-Gaussian EEDF on the nonlinear evolution of SRS is investigated by three wave model simulation and Vlasov-Maxwel

Jasleen Kaur, Aritra Ghosh, Malay Bandyopadhyay

In this brief report, following the recent developments on formulating a quantum analogue of the classical energy equipartition theorem for open systems where the heat bath comprises of independent oscillators, i.e. bosonic degrees of freedom, we present an analogous result for fermionic systems. The most general case where the system is connected to multipl

Ami M. DuBois, Chris Crabtree, Gurudas Ganguli, David M. Malaspina

Spacecraft data reveals a nonuniform ambipolar electric field transverse to the magnetic field in a thin magnetotail current sheet that leads to intense ExB velocity shear and non-gyrotropic particle distributions. The ExB drift far exceeds the diamagnetic drift and drives lower hybrid waves localized to the magnetic field reversal region, which is ideally s

Federico Malato, Joona Jehkonen, Ville Hautamäki

Behavioural cloning has been extensively used to train agents and is recognized as a fast and solid approach to teach general behaviours based on expert trajectories. Such method follows the supervised learning paradigm and it strongly depends on the distribution of the data. In our paper, we show how combining behavioural cloning with human-in-the-loop trai

Hossam Donya, Sheikh Othman, Alexis Dimitriadis

Evaluation the prediction of Efficiency index by DVH parameter for SRS treatment plans using Supervised Machine learning and the performance of predictive model algorithms of RapidMiner GO in the parameter prediction are investigated. Dose volume histogram (DVH) based Efficiency index was calculated for 100 clinical SRS plans generated by Leksell Gamma plan,

Xiaotao Huang, Yu-Kuo Hsiao, Jike Wang, Liang Sun

The forward-backward angular asymmetry (${\cal A}_{FB}$) for $\bar B^0\to \Lambda\bar p\pi^+$ measured by Belle has presented an experimental value in the range of $-30\%$ to $-50\%$. In our study, we find that ${\cal A}_{FB}[\bar B^0\to\Lambda\bar p \pi^+(B^-\to \Lambda\bar p\pi^0)]$ can be as large as $(-14.6^{+0.9}_{-1.5}\pm 6.9)\%$. In addition, we prese

Baruch Margulis, Prerna Paliwal, Wojciech Skomorowski, Mariusz Pawlak

Partial wave resonances are quasi-bound states that are formed by tunneling through the centrifugal barrier. Such states are important to collisions that deviate from the Langevin limit where direct collision path is suppressed due to quantum symmetry or a potential barrier. In such a case, quantum resonances play a major role in the dynamics at low temperat

Zahra Tarkhani, Lorena Qendro, Malachy O'Connor Brown, Oscar Hill

Brain computing interfaces (BCI) are used in a plethora of safety/privacy-critical applications, ranging from healthcare to smart communication and control. Wearable BCI setups typically involve a head-mounted sensor connected to a mobile device, combined with ML-based data processing. Consequently, they are susceptible to a multiplicity of attacks across th

Atsushi Atsuji, Hiroshi Kaneko

A Riemann-Roch theorem on graph was initiated by M. Baker and S. Norine. In their article [2], a Riemann-Roch theorem on a finite graph with uniform vertex-weight and uniform edge-weight was established and it was suggested a Riemann-Roch theorem on an infinite graph was feasible. In this article, we take an edge-weighted infinite graph and focus on the impo

Katherine Benjamin, Lamisah Mukta, Gabriel Moryoussef, Christopher Uren

Quantification and classification of protein structures, such as knotted proteins, often requires noise-free and complete data. Here we develop a mathematical pipeline that systematically analyzes protein structures. We showcase this geometric framework on proteins forming open-ended trefoil knots, and we demonstrate that the mathematical tool, persistent ho

Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang

Most existing Graph Neural Networks (GNNs) are proposed without considering the selection bias in data, i.e., the inconsistent distribution between the training set with test set. In reality, the test data is not even available during the training process, making selection bias agnostic. Training GNNs with biased selected nodes leads to significant parameter

Thanawuth Thanathibodee, Nuria Calvet, Jesus Hernandez, Karina Mauco

Observations have shown that the disk frequency and the fraction of accreting pre-main-sequence stars decrease with the age of the population and that some stars appear to have disks while their accretion has stopped. Still, it is unclear how disk-bearing stars stop their accretion. To provide insight into the last stages of accretion in low-mass young stars

Dongjie Wang, Kunpeng Liu, Hui Xiong, Yanjie Fu

In this paper, we focus on the problem of modeling dynamic geo-human interactions in streams for online POI recommendations. Specifically, we formulate the in-stream geo-human interaction modeling problem into a novel deep interactive reinforcement learning framework, where an agent is a recommender and an action is a next POI to visit. We uniquely model the

Abhishek Balasubramaniam, Sudeep Pasricha

Object detection is a computer vision task that has become an integral part of many consumer applications today such as surveillance and security systems, mobile text recognition, and diagnosing diseases from MRI/CT scans. Object detection is also one of the critical components to support autonomous driving. Autonomous vehicles rely on the perception of thei

Arthi Padmanabhan, Neil Agarwal, Anand Iyer, Ganesh Ananthanarayanan

Video analytics pipelines have steadily shifted to edge deployments to reduce bandwidth overheads and privacy violations, but in doing so, face an ever-growing resource tension. Most notably, edge-box GPUs lack the memory needed to concurrently house the growing number of (increasingly complex) models for real-time inference. Unfortunately, existing solution

Cosmin Andrei, Anna Ijjas, Paul J. Steinhardt

If dark energy is a form of quintessence driven by a scalar field $\phi$ evolving down a monotonically decreasing potential $V(\phi)$ that passes sufficiently below zero, the universe is destined to undergo a series of smooth transitions. The currently observed accelerated expansion will cease; soon thereafter, expansion will come to end altogether; and the

Zhexin Li, Tong Yang, Peisong Wang, Jian Cheng

In this paper, we propose a fully differentiable quantization method for vision transformer (ViT) named as Q-ViT, in which both of the quantization scales and bit-widths are learnable parameters. Specifically, based on our observation that heads in ViT display different quantization robustness, we leverage head-wise bit-width to squeeze the size of Q-ViT whi

Vipin Kumar Kukkala, Sooryaa Vignesh Thiruloga, Sudeep Pasricha

Autonomous vehicles are on the horizon and will be transforming transportation safety and comfort. These vehicles will be connected to various external systems and utilize advanced embedded systems to perceive their environment and make intelligent decisions. However, this increased connectivity makes these vehicles vulnerable to various cyber-attacks that c

Xiaojun Yao

Quarkonium suppression in relativistic heavy ion collisions has been studied experimentally for decades to probe the properties of the quark-gluon plasma. For this purpose, complete theoretical understanding of the time evolution of quarkonium inside the quark-gluon plasma is needed but challenging. Here I review recent progress in applying the open quantum

Irene Viola, Shishir Subramanyam, Jie Li, Pablo Cesar

Fuelled by the increase in popularity of virtual and augmented reality applications, point clouds have emerged as a popular 3D format for acquisition and rendering of digital humans, thanks to their versatility and real-time capabilities. Due to technological constraints and real-time rendering limitations, however, the visual quality of dynamic point cloud

Sara Akan, Taymaz Akan

Gamed-based is a new stochastic metaheuristics optimization category that is inspired by traditional or digital game genres. Unlike SI-based algorithms, in-dividuals do not work together with the goal of defeating other individuals and winning the game. Battle royale optimizer (BRO) is a Gamed-based me-taheuristic optimization algorithm that has been recentl

Stephen McAleer, Kevin Wang, John Lanier, Marc Lanctot

Policy space response oracles (PSRO) is a multi-agent reinforcement learning algorithm that has achieved state-of-the-art performance in very large two-player zero-sum games. PSRO is based on the tabular double oracle (DO) method, an algorithm that is guaranteed to converge to a Nash equilibrium, but may increase exploitability from one iteration to the next

Jiaojiao Zhang, Huikang Liu, Anthony Man-Cho So, Qing Ling

In this work, we investigate stochastic quasi-Newton methods for minimizing a finite sum of cost functions over a decentralized network. In Part I, we develop a general algorithmic framework that incorporates stochastic quasi-Newton approximations with variance reduction so as to achieve fast convergence. At each time each node constructs a local, inexact qu

Susanne K. Suter, Georg R. Spinner, Bianca Hoelz, Sofia Rey

Effective visualizations were evaluated to reveal relevant health patterns from multi-sensor real-time wearable devices that recorded vital signs from patients admitted to hospital with COVID-19. Furthermore, specific challenges associated with wearable health data visualizations, such as fluctuating data quality resulting from compliance problems, time need

Claudio Guarcello, Luca Chirolli, Maria Teresa Mercaldo, Francesco Giazotto

The Josephson equations predict remarkable effects concerning the phase state of a superconducting junction with an oscillating current induced by a static voltage. Whether the paradigm can be twisted by yielding an oscillating voltage without making use of harmonic drives is a fundamentally relevant problem yet not fully settled. Here, we demonstrate that a

Kirill Andreev, Pavel Rybin, Alexey Frolov

We consider a coded compressed sensing approach for the unsourced random access and replace the outer tree code proposed by Amalladinne et al. with the list recoverable code capable of correcting t errors. A finite-length random coding bound for such codes is derived. The numerical experiments in the single antenna quasi-static Rayleigh fading MAC show that

Alex V. Plyukhin

We consider an open (Brownian) classical harmonic oscillator in contact with a non-Markovian thermal bath and described by the generalized Langevin equation. When the bath's spectrum has a finite upper cutoff frequency, the oscillator may have ergodic and nonergodic configurations. In ergodic configurations (when exist, they correspond to lower oscillato

Martin Bojowald

In canonical gravity, general covariance is implemented by hypersurface-deformation symmetries on phase space. The different versions of hypersurface deformations required for full covariance have complicated interplays with one another, governed by non-Abelian brackets with structure functions. For spherically symmetric space-times, it is possible to identi

Wolfgang Fuhl

In this paper, we present a new approach for decomposing scan paths and its utility for generating new scan paths. For this purpose, we use the K-Means clustering procedure to the raw gaze data and subsequently iteratively to find more clusters in the found clusters. The found clusters are grouped for each level in the hierarchy, and the most important princ

Wolfgang Fuhl, Daniel Weber, Shahram Eivazi

In this paper we present GroupGaze. It is a tool that can be used to calculate the gaze direction and the gaze position of whole groups. GroupGazer calculates the gaze direction of every single person in the image and allows to map these gaze vectors to a projection like a projector. In addition to the person-specific gaze direction, the person affiliation o

Huan-Yu Ku, Chung-Yun Hsieh, Shin-Liang Chen, Yueh-Nan Chen

Quantum steering is the central resource for one-sided device-independent quantum information. It is manipulated via one-way local operations and classical communication, such as local filtering on the trusted party. Here, we provide a necessary and sufficient condition for a steering assemblage to be transformable into another one via local filtering. We ch

Kathryn Mann, Kasra Rafi

We answer two questions about the topology of end spaces of infinite type surfaces and the action of the mapping class group that have appeared in the literature. First, we give examples of infinite type surfaces with end spaces that are not self-similar, but a unique maximal type of end, either a singleton or Cantor set. Secondly, we use an argument of Tsan

Adrien Hélias, Matthieu Labousse

A drop bouncing on a vertically-vibrated surface may self-propel forward by standing waves and travels along a fluid interface. This system called walking drop forms a non-quantum wave-particle association at the macroscopic scale. The dynamics of one particle has triggered many investigations and has resulted in spectacular experimental results in the last

Sylvian Kahane

A series of simulations were conducted with Geant4 in order to verify the electron backscattering experiments performed by Tabata in the low Z elements of Be, C, and Al. In general, quite good agreement was obtained by carefully choosing the physics lists employed. These results invalidate the claim made before about the presence of experimental errors in th

Feyza Baspehlivan, Burak Dagli, Osman Emre Delialioglu, Saleh Sultansoy

There are two strong arguments in favor of vector-like leptons and quarks: Flavor Democracy call for them, and E6 GUT predicts existence of iso-singlet quarks and iso-doublet leptons. Vector-like quarks (VLQ) are extensively searched by ATLAS and CMS collaborations, but this is not the case for vector-like leptons (VLL), while they have actually similar stat

Akshay Gaikwad, Arvind, Kavita Dorai

We experimentally implement the Sz.-Nagy dilation algorithm to simulate open quantum dynamics on an nuclear magnetic resonance (NMR) quantum processor. The Sz.-Nagy algorithm enables the simulation of the dynamics of arbitrary-dimensional open quantum systems, using only a single ancilla qubit. We experimentally simulate the action of two non-unitary process

Dirk van der Marel, Jorge E Hirsch

Recently the discovery of room-temperature superconductivity was announced for a carbonaceous sulfur hydride (CSH) under high pressure. The evidence for superconductivity was based on resistance and magnetic susceptibility measurements. In the figures showing the susceptibility it was stated that "the background signal, determined from a non-superconducting

Irène Cucchi, Simone Lisi, Florian Margot, Hugo Henck

Angle-resolved photoemission is a direct probe of the momentum-resolved electronic structure and proved influential in the study of bulk crystals with novel electronic properties. Thanks to recent technical advances, this technique can now be applied for the first time for the study of van der Waals heterostructures built by stacking two-dimensional crystals

Ahmet Alacaoglu, Volkan Cevher, Stephen J. Wright

We prove complexity bounds for the primal-dual algorithm with random extrapolation and coordinate descent (PURE-CD), which has been shown to obtain good practical performance for solving convex-concave min-max problems with bilinear coupling. Our complexity bounds either match or improve the best-known results in the literature for both dense and sparse (str

Li Peide, Seyyid Emre Sofuoglu, Tapabrata Maiti, Selin Aviyente

Multimodal data arise in various applications where information about the same phenomenon is acquired from multiple sensors and across different imaging modalities. Learning from multimodal data is of great interest in machine learning and statistics research as this offers the possibility of capturing complementary information among modalities. Multimodal m

P. Diego-Palazuelos, J. R. Eskilt, Y. Minami, M. Tristram

We search for the signature of parity-violating physics in the cosmic microwave background, called cosmic birefringence, using the Planck data release 4. We initially find a birefringence angle of $\beta=0.30\pm0.11$ (68% C.L.) for nearly full-sky data. The values of $\beta$ decrease as we enlarge the Galactic mask, which can be interpreted as the effect of

Yuguang Yue, Yuanpu Xie, Huasen Wu, Haofeng Jia

Listwise ranking losses have been widely studied in recommender systems. However, new paradigms of content consumption present new challenges for ranking methods. In this work we contribute an analysis of learning to rank for personalized mobile push notifications and discuss the unique challenges this presents compared to traditional ranking problems. To ad

Md. Manirul Ali, Chandrashekar Radhakrishnan

The transient dynamics of quantum coherence of Gaussian states are investigated. The state is coupled to an external environment which can be described by a Fano-Anderson type Hamiltonian. Solving the quantum Langevin equation, we obtain the Greens functions which are used to compute the time evolved first and second moments of the quadrature operators. From

Andrea Gentile, Raffaella Giova

We establish some higher differentiability results for solution to non-autonomous obstacle problems of the form \begin{equation*} \min \left\{\int_{\Omega}f\left(x, Dv(x)\right)dx\,:\, v\in \mathcal{K}_\psi(\Omega)\right\}, \end{equation*} where the function $f$ satisfies $p-$growth conditions with respect to the gradient variable, for $1<p<2$, and $\mathcal

Pieter M. Gunnink, Benedetta Flebus, Hilary M. Hurst, Rembert A. Duine

We numerically determine the robustness of the lasing edge modes in a spin-torque oscillator array that realizes the non-Hermitian Su-Schrieffer-Heeger model. Previous studies found that the linearized dynamics can enter a topological regime in which the edge mode is driven into auto-oscillation, while the bulk dynamics are suppressed. Here we investigate th

Wiebke Toussaint, Aaron Yi Ding, Fahim Kawsar, Akhil Mathur

Billions of distributed, heterogeneous and resource constrained IoT devices deploy on-device machine learning (ML) for private, fast and offline inference on personal data. On-device ML is highly context dependent, and sensitive to user, usage, hardware and environment attributes. This sensitivity and the propensity towards bias in ML makes it important to s

Jessie Galasso, Michalis Famelis, Houari Sahraoui

A typical approach to programming is to first code the main execution scenario, and then focus on filling out alternative behaviors and corner cases. But, almost always, there exist unusual conditions that trigger atypical behaviors, which are hard to predict in program specifications, and are thus often not coded. In this paper, we consider the problem of d

Sergey Ivanov

This textbook covers principles behind main modern deep reinforcement learning algorithms that achieved breakthrough results in many domains from game AI to robotics. All required theory is explained with proofs using unified notation and emphasize on the differences between different types of algorithms and the reasons why they are constructed the way they

Camille Maestre, Yangdi Li, Vincent Garnier, Philippe Steyer

In the wide world of 2D materials, hexagonal boron nitride (hBN) holds a special place due to its excellent characteristics. In addition to its thermal, chemical and mechanical stability, hBN demonstrates high thermal conductivity, low compressibility, and wide band gap around 6 eV, making it promising candidate for many groundbreaking applications and more

Anil Kumar Karn

We introduce the notion centre of a convex set and study the space of continuous affine functions on a compact convex set with a centre. We show that these spaces are precisely the dual of a base normed space in which the underlying base has a (unique) centre. We also characterize the corresponding base norm space. We obtain a condition on a compact, balance

Kilian Theil, Dirk Hovy, Heiner Stuckenschmidt

How much does a CEO's personality impact the performance of their company? Management theory posits a great influence, but it is difficult to show empirically -- there is a lack of publicly available self-reported personality data of top managers. Instead, we propose a text-based personality regressor using crowd-sourced Myers--Briggs Type Indicator (MBTI) a

Sayak Ray, Amichay Vardi, Doron Cohen

The driven-dissipative Dicke model features normal, superradiant, and lasing steady-states that may be regular or chaotic. We report quantum signatures of chaos in a quench protocol from the lasing states. Within the framework of a classical mean-field perspective, once quenched, the system relaxes either to the normal or to the superradiant state. Quench-fr

Gernot Akemann, Sung-Soo Byun

We study the product $P_m$ of $m$ real Ginibre matrices with Gaussian elements of size $N$, which has received renewed interest recently. Its eigenvalues, which are either real or come in complex conjugate pairs, become all real with probability one when $m\to\infty$ at fixed $N$. In this regime the statistics becomes deterministic and the Lyapunov spectrum

Arian Askari, Suzan Verberne, Gabriella Pasi

Expert finding has been well-studied in community question answering (QA) systems in various domains. However, none of these studies addresses expert finding in the legal domain, where the goal is for citizens to find lawyers based on their expertise. In the legal domain, there is a large knowledge gap between the experts and the searchers, and the content o

Kenneth Blomqvist, Jen Jen Chung, Lionel Ott, Roland Siegwart

Creating computer vision datasets requires careful planning and lots of time and effort. In robotics research, we often have to use standardized objects, such as the YCB object set, for tasks such as object tracking, pose estimation, grasping and manipulation, as there are datasets and pre-learned methods available for these objects. This limits the impact o

Yuangang Deng, Su Yi

The supersolid phase characterized by the superfluid and long-range spatial periodicity of crystalline order is central to many branches of science ranging from condensed matter physics to ultracold atomic physics. Here we study a self-ordered checkerboard supersolid phase originating from dynamical spin-orbit coupling for a transversely pumped atomic Bose-E

Gui-Lei Zhu, Amir Targholizadeh, Xin-You Lu, Cem Yuce

We propose a metallic-silicon system with a complex optical potential modulated along the length of the waveguide for a robust higher harmonic generation. For right moving fields when the strength of non-Hermiticity becomes equal to the real part of the optical potential, the dynamical equations associated with modal field amplitudes in our proposed system a

Robert F. Penna

Cylindrical gravitational pulse waves are cylindrical gravitational waves with a pulse profile in the radial direction. The dynamics of cylindrical gravitational pulse waves is governed by a two dimensional integrable sigma model with an infinite dimensional hidden symmetry called the Geroch group. Piran, Safier, and Katz obtained an exact solution for a sin

Christian Reul, Stefan Tomasek, Florian Langhanki, Uwe Springmann

This paper deals with the task of practical and open source Handwritten Text Recognition (HTR) on German medieval manuscripts. We report on our efforts to construct mixed recognition models which can be applied out-of-the-box without any further document-specific training but also serve as a starting point for finetuning by training a new model on a few page

Erhan Bayraktar, Zhenhua Wang, Zhou Zhou

We consider three equilibrium concepts proposed in the literature for time-inconsistent stopping problems, including mild equilibria, weak equilibria and strong equilibria. The discount function is assumed to be log sub-additive and the underlying process is one-dimensional diffusion. We first provide necessary and sufficient conditions for the characterizat

Huchan Lee

This thesis covers a few successes of the SM and its limitations. The limitations implement that the SM must be expanded to explain the observables which can not be addressed by the SM such as mass of neutrinos, a few of anomalies, DM, DE, etc. In order to extend the SM, we take the model-dependent approach and a minimal extension to the SM. For the minimal

Le Thi Khanh Hien, Dimitri Papadimitriou

This paper proposes a multiblock alternating direction method of multipliers for solving a class of multiblock nonsmooth nonconvex optimization problem with nonlinear coupling constraints. We employ a majorization minimization procedure in the update of each block of the primal variables. Subsequential and global convergence of the generated sequence to a cr

Sergey Nadtochiy, Yuan Yin

This paper presents a tractable sufficient condition for the consistency of maximum likelihood estimators (MLEs) in partially observed diffusion models, stated in terms of stationary distribution of the associated fully observed diffusion, under the assumption that the set of unknown parameter values is finite. This sufficient condition is then verified in t

Sahar Atallah, Michael Garn, Sania Jevtic, Yukuan Tao

We provide new examples of pure entangled systems related to cluster state quantum computation that can be efficiently simulated classically. In cluster state quantum computation input qubits are initialised in the `equator' of the Bloch sphere, $CZ$ gates are applied, and finally the qubits are measured adaptively using $Z$ measurements or measurements of $

Marsela Polic, Marko Car, Jelena Tabak, Matko Orsag

In this paper we propose a robotic system for Irrigation Water Management (IWM) in a structured robotic greenhouse environment. A commercially available robotic manipulator is equipped with an RGB-D camera and a soil moisture sensor. The two are used to automate the procedure known as "feel and appearance method", which is a way of monitoring soil moisture t

Alain Durmus, Andreas Eberle, Arnaud Guillin, Katharina Schuh

We develop a new approach to study the long time behaviour of solutions to nonlinear stochastic differential equations in the sense of McKean, as well as propagation of chaos for the corresponding mean-field particle system approximations. Our approach is based on a sticky coupling between two solutions to the equation. We show that the distance process betw

P. B. Mucha, W. S. Ożański

We consider a pressureless hydrodynamic model of collective behaviour, which is concerned with a density function $\rho$ and a velocity field $v$ on the torus, and is described by the continuity equation for $\rho$, $\partial_t \rho + \mathrm{div} (v\rho )=0$, and a compressible hydrodynamic equation for $v$, $\rho v_t + \rho v\cdot \nabla v - \Delta v = -\r

Dylan Bayerl, Christopher M. Andolina, Shyam Dwaraknath, Wissam A. Saidi

Machine learning potentials (MLPs) for atomistic simulations have an enormous prospective impact on materials modeling, offering orders of magnitude speedup over density functional theory (DFT) calculations without appreciably sacrificing accuracy in the prediction of material properties. However, the generation of large datasets needed for training MLPs is

S. D. Odintsov, V. K. Oikonomou

In the recent literature it has been shown that the $H_0$ tension may be eliminated if an abrupt physics transition changed the Cepheid parameters in the near past of the Universe, nearly $70-150\,$Myrs ago. In this letter we stress the possibility that this abrupt transition was caused by the smooth passage of our Universe through a pressure finite-time cos

Muhammad Muneeb Saad, Ruairi O'Reilly, Mubashir Husain Rehmani

In biomedical image analysis, the applicability of deep learning methods is directly impacted by the quantity of image data available. This is due to deep learning models requiring large image datasets to provide high-level performance. Generative Adversarial Networks (GANs) have been widely utilized to address data limitations through the generation of synt

Beverly J. LaMarr, Gregory Y. Prigozhin, Eric D. Miller, Carolyn Thayer

Future high-resolution imaging X-ray observatories may require detectors with both fine spatial resolution and high quantum efficiency at relatively high X-ray energies (>5keV). A silicon imaging detector meeting these requirements will have a ratio of detector thickness to pixel size of six or more, roughly twice that of legacy imaging sensors. This implies

Yoshimasa Hidaka, Shi Pu, Qun Wang, Di-Lun Yang

Many novel quantum phenomena emerge in non-equilibrium relativistic quantum matter under extreme conditions such as strong magnetic fields and rotations. The quantum kinetic theory based on Wigner functions in quantum field theory provides a powerful and effective microscopic description of these quantum phenomena. In this article we review some of recent ad

Martin Szomszor, Euan Adie

This paper presents an analysis of the Overton policy document database, describing the makeup of materials indexed and the nature in which they cite academic literature. We report on various aspects of the data, including growth, geographic spread, language representation, the range of policy source types included, and the availability of citation links in

Philipp Rosenthal, Oliver Niggemann

Artificial Intelligence (AI) has significant potential for product design: AI can check technical and non-technical constraints on products, it can support a quick design of new product variants and new AI methods may also support creativity. But currently product design and AI are separate communities fostering different terms and theories. This makes a map