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Complex diffusion-based kinetics of photoluminescence in semiconductor nanoplatelets

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arXiv 2021年

作者： Kurilovich, Aleksandr A. Mantsevich, Vladimir N. Stevenson, Keith J. Chechkin, Aleksei V. Palyulin, Vladimir V. Center for Energy Science and Technology Skolkovo Institute of Science and Technology Moscow121205 Russia Semiconductors and Cryoelectronics & Quantum Technology Center Physics department Lomonosov Moscow State University Moscow119991 Russia Institute for Physics & Astronomy University of Potsdam Potsdam-GolmD-14476 Germany Akhiezer Institute for Theoretical Physics National Science Center Kharkov Institute of Physics and Technology Kharkov61108 Ukraine Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia

We present a diffusion-based simulation and theoretical models for explanation of photoluminescence (PL) emission intensity in semiconductor nanoplatelets. It is shown that the shape of PL intensity curves can be reproduced by the interplay of recombination, diffusion and trapping of excitons. The emission intensity at short times is purely exponential and is defined by recombination. At long times it is governed by the release of excitons from surface traps and is characterized by a power-law tail. We show that the crossover from one limit to another is controlled by diffusion properties. This intermediate region exhibits a rich behaviour depending on the value of diffusivity. Proposed approach reproduces all the features of experimental curves measured for different nanoplatelet systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Diffusion

Intense harmonics with time-varying orbital angular momentum from relativistic plasma mirrors

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arXiv 2021年

作者： Wang, Jingwei Zepf, Matt Leng, Yuxin Li, Ruxin Rykovanov, Sergey G. Shanghai 201800 China Collaborative Innovation Center of IFSA Shanghai Jiao Tong University Shanghai 200240 China Helmholtz Institute Jena Fröbelstieg 3 Jena07743 Germany Faculty of Physics and Astronomy Friedrich-Schiller-Universität Jena Jena07743 Germany High Performance Computing and Big Data Laboratory Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia

In this Letter using three-dimensional particle-in-cell simulations and analytical considerations we demonstrate intense high-order plasma surface harmonics carrying a time-varying orbital angular momentum (OAM) - the self-torque. We show that by using two laser beams with different OAMs l1 and l2 and a certain delay between each other and shooting them obliquely on an overdense plasma target, one can generate harmonics with OAM spanning nl1 to nl2, where n is the order of the harmonic. Such intense self-torqued harmonics can offer new possibilities in ultrafast spectroscopy. © 2021, CC BY.

关键词： Harmonic analysis

FedMonitor: An Implementation Architecture for Monitoring of Resources and Events'Notifications on Federated Cloud Computing Infrastructures

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FedMonitor: An Implementation Architecture for Monitoring of...

International Conference on Emerging Trends in Networks and Computer Communications (ETNCC)

作者： Emmanuel Adetiba Uche Nnaji John S. Wejin Festus Ojesanmi Matthew B. Akanle Priscilla O. Ajayi Faith O. Sweetwiliams Surendra C. Thakur Ezekiel F. Adebiyi Department of Electrical and Information Engineering and Covenant Applied Informatics & Communication African Center of Excellene(CApIC-ACE) Covenant University Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Department of Computer and Information Science & CApIC-ACE Covenant University Ota Nigeria Department of Electrical and Information Engineering & CApIC-ACE Covenant University Jalingo Nigeria Department of Computer Science Tareba State University Jalingo Nigeria Covenant Applied Informatics & Communication African Center of Excellene(CApIC-ACE) Covenant University Ota Nigeria Department of Electrical and Information Engineering Covenant University & CApIC-ACE Covenant University Ota Nigeria Center for Systems and Information Services & CApIC-ACE Covenant University Ota Nigeria Department of Information Technology and KZN e-Skills Co-Laboratory Durban University of Technology Durban South Africa Covenant University Bioinformatics Research (CUBRe) Covenant University Ota Ogun State Nigeria African Center of Excellence in Bioinformatics & Data Intensive Science Makerere University Kampala Uganda

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

In the evolving landscape of cloud computing, federated cloud infrastructures present unique challenges and opportunities for resource and application monitoring. Monitoring the diverse array of cloud resources and applications within a federated cloud environment is crucial for delivering consistent Quality of Service (QoS) and continuous oversight across various cloud applications and infrastructure. Despite the various successes documented in the literature on multi-cloud monitoring, existing frameworks have not fully explored or provided enough insights into centralized monitoring of resources, applications, and network devices in a federated cloud environment. This paper introduces FedMonitor, an implementation architecture designed to enhance the monitoring and notification capabilities in federated cloud environments by building on the theoretical ideals in our earlier work (i.e. FEDARGOS-V1). FedMonitor leverages Prometheus and Grafana to crawl, manage and visualize metrics from diverse software services, hardware resources, and network devices within a federated cloud environment. The results demonstrate hat FedMonitor improves the effectiveness of resource and application monitoring in federated cloud environments.

关键词： Measurement Cloud computing Visualization Computer architecture Quality of service Production Software Real-time systems Stakeholders Monitoring

Active Brownian motion in two dimensions under stochastic resetting

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Physical Review E 2020年第5期102卷 052129-052129页

作者： Vijay Kumar Onkar Sadekar Urna Basu Centre for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Nobelya Ulitsa 3 Moscow 121205 Russia Indian Institute of Science Education and Research Homi Bhabha Road Pashan Pune 411008 India Raman Research Institute C. V. Raman Avenue Bengaluru 560080 India

We study the position distribution of an active Brownian particle (ABP) in the presence of stochastic resetting in two spatial dimensions. We consider three different resetting protocols: (1) where both position and orientation of the particle are reset, (2) where only the position is reset, and (3) where only the orientation is reset with a certain rate r. We show that in the first two cases, the ABP reaches a stationary state. Using a renewal approach, we calculate exactly the stationary marginal position distributions in the limiting cases when the resetting rate r is much larger or much smaller than the rotational diffusion constant DR of the ABP. We find that, in some cases, for a large resetting rate, the position distribution diverges near the resetting point; the nature of the divergence depends on the specific protocol. For the orientation resetting, there is no stationary state, but the motion changes from a ballistic one at short times to a diffusive one at late times. We characterize the short-time non-Gaussian marginal position distributions using a perturbative approach.

关键词： Fluctuations & noise Nonequilibrium statistical mechanics Stochastic processes

Simple heuristics for efficient parallel tensor contraction and quantum circuit simulation

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arXiv 2020年

作者： Schutski, Roman Khakhulin, Taras Oseledets, Ivan Kolmakov, Dmitry Center for Computational and Data-Intensive Science and Engineering Skoltech Skolkovo Innovation Center Moscow Region121205 Russia Central Research Institute Huawei Technologies

Tensor networks are the main building blocks in a wide variety of computational sciences, ranging from many-body theory and quantum computing to probability and machine learning. Here we propose a parallel algorithm for the contraction of tensor networks using probabilistic graphical models. Our approach is based on the heuristic solution of the μ -treewidth deletion problem in graph theory. We apply the resulting algorithm to the simulation of random quantum circuits and discuss the extensions for general tensor network contractions. Copyright © 2020, The Authors. All rights reserved.

关键词： Tensors

Estimation of the Second Moment Based on Rounded data

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Journal of Mathematical sciences (United States) 2019年第6期237卷 819-825页

作者： Samsonov, S.V. Ushakov, N.G. Ushakov, V.G. Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow Russian Federation Department of Mathematical Sciences Norwegian University of Science and Technology Trondheim Norway Moscow State University Moscow Russian Federation

Sample moments are unbiased estimators of theoretical moments (if the latter exist). In practice, however, observations are rounded under registration, which leads to systematic errors. In [1–3] it was shown that random measurement errors can provide the reduction of rounding errors, when the expectation is estimated by the first sample moment. This gives a possibility to manage the rounding error of the result, if one can add some noise to observations before registration. Moreover, this error can be made arbitrarily small. Now we find conditions under which this takes place for the second moment. © 2019, Springer science+Business Media, LLC, part of Springer Nature.

关键词： Estimators Registration second moment Noise Systematic errors Error measure Moment of force Rounding error Tea random measurement

Optimal multistage group testing algorithm for 3 defectives

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arXiv 2020年

作者： Vorobyev, Ilya Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow127051 Russia Advanced Combinatorics and Complex Networks Lab Moscow Institute of Physics and Technology Dolgoprudny141701 Russia

Group testing is a well-known search problem that consists in detecting of s defective members of a set of t samples by carrying out tests on properly chosen subsets of samples. In classical group testing the goal is to find all defective elements by using the minimal possible number of tests in the worst case. In this work, a multistage group testing problem is considered. Our goal is to construct a multistage search procedure, having asymptotically the same number of tests as an adaptive one. We propose a new approach to designing multistage algorithms, which allows us to construct a 5-stage algorithm for finding 3 defectives with the optimal number 3 log2 t(1 + o(1)) of *** Codes 68R05 Copyright © 2020, The Authors. All rights reserved.

关键词： Well testing

Incorruptible Auditing: Blockchain-Powered Graph database Management

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Incorruptible Auditing: Blockchain-Powered Graph Database Ma...

IEEE International Conference on Blockchain and Cryptocurrency (ICBC)

作者： Victor Ermolaev Indrek Klangberg Yash Madhwal Silver Vapper Sjoerd Wels Yury Yanovich Software Department Bitfury Amsterdam The Netherlands Electrical Engineering Mathematics and Computer Science Department University of Twente Enschede The Netherlands Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology (Skoltech) Moscow Russia

ISBN: (数字)9781728166803

ISBN: (纸本)9781728166810

In modern and interconnected world, information is accumulatively stored digitally, making the process of exchanging, gathering and querying the information much easier. Continuously, it has introduced new challenges about how to ensure its consistency and reliability due to the sheer volume of data. A blockchain-based information system can provide an incorruptible record of history, enabling better auditing and data management practices. The paper describes how to combine an Exonum blockchain and a Neo4j graph database into a system that can provide a verifiable audit trail of data integrity and its modifications for information stored in a graph database.

关键词： History Bitcoin Peer-to-peer computing Contracts

A Consensus Privacy Metrics Framework for Synthetic data

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arXiv 2025年

作者： Pilgram, Lisa Dankar, Fida K. Drechsler, Jörg Elliot, Mark Domingo-Ferrer, Josep Francis, Paul Kantarcioglu, Murat Kong, Linglong Malin, Bradley Muralidhar, Krishnamurty Myles, Puja Prasser, Fabian Raisaro, Jean Louis Yan, Chao El Emam, Khaled School of Epidemiology and Public Health University of Ottawa ON Canada CHEO Research Institute ON Canada Department of Nephrology and Medical Intensive Care Charité – Universitätsmedizin Berlin Berlin Germany Department for Statistical Methods Institute for Employment Research Nuernberg Germany Institute for Statistics Ludwig-Maximilians-Universität Munich Germany Joint Program in Survey Methodology University of Maryland United States The Cathie Marsh Institute Research School of Social Sciences University of Manchester Manchester United Kingdom Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Catalonia Tarragona Spain Max Planck Institute for Software Systems Germany Department of Computer Science Virginia Tech United States Department of Mathematical and Statistical Sciences University of Alberta Alberta Canada Department of Biomedical Informatics Vanderbilt University Medical Center NashvilleTN United States Department of Biostatistics Vanderbilt University Medical Center NashvilleTN United States Department of Computer Science Vanderbilt University NashvilleTN United States Department of Marketing and Supply Chain Management University of Oklahoma Oklahoma United States Medicines and Healthcare products Regulatory Agency London United Kingdom Berlin Institute of Health at Charité Universitätsmedizin Berlin Medical Informatics Group Berlin Germany Biomedical Data Science Center University Hospital Lausanne Lausanne Switzerland

Synthetic data generation is one approach for sharing individual-level data. However, to meet legislative requirements, it is necessary to demonstrate that the individuals’ privacy is adequately protected. There is no consolidated standard for measuring privacy in synthetic data. Through an expert panel and consensus process, we developed a framework for evaluating privacy in synthetic data. Our findings indicate that current similarity metrics fail to measure identity disclosure, and their use is discouraged. For differentially private synthetic data, a privacy budget other than close to zero was not considered interpretable. There was consensus on the importance of membership and attribute disclosure, both of which involve inferring personal information about an individual without necessarily revealing their identity. The resultant framework provides precise recommendations for metrics that address these types of disclosures effectively. Our findings further present specific opportunities for future research that can help with widespread adoption of synthetic data. © 2025, CC BY.

关键词： Differential privacy