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Self-torqued harmonics and attosecond pulses driven by time-delayed relativistic vortex lasers

Physical Review A 2022年第3期106卷 033515-033515页

作者： Jingwei Wang Matt Zepf Yuxin Leng Ruxin Li Sergey G. Rykovanov State Key Laboratory of High Field Laser Physics and Chinese Academy of Sciences Center for Excellence in Ultra-Intense Laser Science Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai 201800 China China-Russian Belt and Road Joint Laboratory on Laser Science Shanghai 201800 China Collaborative Innovation Center of IFSA Shanghai Jiao Tong University Shanghai 200240 China Helmholtz Institute Jena Fröbelstieg 3 07743 Jena Germany Faculty of Physics and Astronomy Friedrich-Schiller-Universität Jena 07743 Jena Germany High Performance Computing and Big Data Laboratory Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow 121205 Russia

Light carrying time-varying orbital angular momentum (OAM) is a recently discovered type of structured electromagnetic field compared with a typical vortex field whose OAM is static. Such so-called self-torqued light is employed for manipulating the fast magnetic, topological, and quantum excitations and increasing its intensity and having access to shorter pulse durations would be of great benefit. Here we theoretically and numerically demonstrate the generation of intense self-torqued harmonics and attosecond pulses in the relativistic regime, driven by two time-delayed relativistic vortex lasers with different OAMs l1 and l2. The OAM of the nth harmonic spans nl1 to nl2, and the OAM of the attosecond pulses changes from l1 to l2. Such intense self-torqued harmonics and attosecond pulses may offer alternative possibilities in ultrafast spectroscopy.

关键词： High intensity laser-plasma interactions High-energy-density plasmas Radiation & particle generation in plasmas Ultrafast phenomena Relativistic plasmas Particle-in-cell methods Relativistic hydrodynamics

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Topology Optimizer for Inverse Design and Fabrication of Passive Photonic Integrated Components UsingWeighted Target

Topology Optimizer for Inverse Design and Fabrication of Pas...

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Advanced Solid State Lasers, ASSL 2021 - Part of Laser Congress, LAC 2021

作者： Minin, Iurii Kazakov, Ivan Kontorov, Sergey Shipulin, Arkady Matveev, Sergey Fedorov, Maxim Skoltech Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 bld.1 Moscow Russia Skoltech Center for Photonics and Quantum Materials Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 building 1 Moscow Russia Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Leninskie Gory 1-52 2nd educational building 6th floor room 663 Moscow Russia

We propose a novel approach optimizing passive photonic integrated component topology computations. It is based on Green's Function Integral Equation method, utilizes weighted optimization methods and fast Toeplit... 详细信息

ISBN: (纸本)9781557528209

关键词： Integral equations

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Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats (vol 16, 585, 2025)

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NATURE COMMUNICATIONS 2025年第1期16卷 1-15页

作者： Steinfeldt, Jakob Wild, Benjamin Buergel, Thore Pietzner, Maik Upmeier zu Belzen, Julius Vauvelle, Andre Hegselmann, Stefan Denaxas, Spiros Hemingway, Harry Langenberg, Claudia Landmesser, Ulf Deanfield, John Eils, Roland Department of Cardiology Angiology and Intensive Care Medicine Deutsches Herzzentrum der Charité (DHZC) Berlin Germany Charité – Universitätsmedizin Berlin corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin Klinik/Centrum Berlin Germany Computational Medicine Berlin Institute of Health (BIH) Charite - University Medicine Berlin Berlin Germany Friede Springer Cardiovascular Prevention Center@Charite Charite - University Medicine Berlin Berlin Germany Institute of Cardiovascular Sciences University College London London UK Berlin Institute of Health (BIH) Charite - University Medicine Berlin Berlin Germany DZHK (German Centre for Cardiovascular Research) Partner Site Berlin Berlin Berlin Germany MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK Precision Health University Research Institute Queen Mary University of London and Barts NHS Trust London UK Center for Digital Health Berlin Institute of Health (BIH) Charite - University Medicine Berlin Berlin Germany Health Data Science Unit Heidelberg University Hospital and BioQuant Heidelberg Germany Institute of Health Informatics University College London London UK British Heart Foundation Data Science Centre London UK Health Data Research UK London UK National Institute for Health Research Biomedical Research Centre at University College London Hospitals London UK Institute for Medical Engineering and Science Massachusetts Institute of Technology Massachusetts USA Pattern Recognition and Image Analysis Lab University of Münster Münster Germany

The COVID-19 pandemic exposed a global deficiency of systematic, data-driven guidance to identify high-risk individuals. Here, we illustrate the utility of routinely recorded medical history to predict the risk for 1741 diseases across clinical specialties and support the rapid response to emerging health threats such as COVID-19. We developed a neural network to learn from health records of 502,489 UK Biobank participants. Importantly, we observed discriminative improvements over basic demographic predictors for 1546 (88.8%) endpoints. After transferring the unmodified risk models to the All of US cohort, we replicated these improvements for 1115 (78.9%) of 1414 investigated endpoints, demonstrating generalizability across healthcare systems and historically underrepresented groups. Ultimately, we showed how this approach could have been used to identify individuals vulnerable to severe COVID-19. Our study demonstrates the potential of medical history to support guidance for emerging pandemics by systematically estimating risk for thousands of diseases at once at minimal cost.

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A S I N G L E I M AG E D E E P L E A R N I N G A P P ROAC H TO R E S TO R AT I O N O F C O R RU P T E D R E M OT E S E N S I N G P RO D U C T S

arXiv

引用

arXiv 2020年

作者： Petrovskaia, Anna Jana, Raghavendra B. Oseledets, Ivan V. Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia

Remote sensing images are used for a variety of analyses, from agricultural monitoring, to disaster relief, to resource planning, among others. The images can be corrupted due to a number of reasons, including instrument errors and natural obstacles such as clouds. We present here a novel approach for reconstruction of missing information in such cases using only the corrupted image as the input. The Deep Image Prior methodology eliminates the need for a pre-trained network or an image database. It is shown that the approach easily beats the performance of traditional single-image methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Disaster prevention

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Tensor BM-Decomposition for Compression and Analysis of Video data

arXiv

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arXiv 2023年

作者： Tian, Fan Kilmer, Misha E. Miller, Eric Patra, Abani Department of Mathematics Tufts University MedfordMA02115 United States Electrical and Computer Engineering Tufts University MedfordMA02115 United States Computer Science Department Tufts University MedfordMA02115 United States Data Intensive Studies Center Tufts University MedfordMA02115 United States Tufts Institute for Artificial Intelligence Tufts University MedfordMA02115 United States

Given tensors A, B, C of size m × 1 × n, m × p × 1, and 1 × p × n, respectively, their Bhattacharya-Mesner (BM) product will result in a third-order tensor of dimension m × p × ... 详细信息

Given tensors A, B, C of size m × 1 × n, m × p × 1, and 1 × p × n, respectively, their Bhattacharya-Mesner (BM) product will result in a third-order tensor of dimension m × p × n and BM-rank of 1 (Mesner and Bhattacharya, 1990). Thus, if an arbitrary m × p × n third-order tensor can be written as a sum of a small number, relative to m, p, n, of such BM-rank 1 terms, this BM-decomposition (BMD) offers an implicitly compressed representation of the tensor. In this paper, we first show that grayscale surveillance video can be accurately captured by a low BM-rank decomposition and give methods for efficiently computing this decomposition. To this end, we first give results that connect rank-revealing matrix factorizations to the BMD. Next, we present a generative model that illustrates that spatio-temporal video data can be expected to have low BM-rank. We combine these observations to derive a regularized alternating least squares (ALS) algorithm to compute an approximate BMD of the video tensor. The algorithm itself is highly parallelizable since the bulk of the computations break down into relatively small regularized least squares problems that can be solved independently. We study the ability of our algorithm to separate the video data into stationary and non-stationary components while simultaneously compressing the data. We then introduce a new type of BM-product suitable for color video and provide an algorithm that shows an impressive ability to extract important temporal information from color video while simultaneously compressing the data. Extensive numerical results compared against the state-of-the-art matrix-based DMD for surveillance video separation show our algorithms can consistently produce results with superior compression properties while simultaneously providing better separation of stationary and non-stationary features in the data. © 2023, CC BY.

关键词： Tensors

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Topology Optimizer for Inverse Design and Fabrication of Passive Photonic Integrated Components Using Weighted Target

Topology Optimizer for Inverse Design and Fabrication of Pas...

引用

Laser Applications Conference, LAC 2021 - Part of Laser Congress 2021

作者： Minin, Iurii Kazakov, Ivan Kontorov, Sergey Shipulin, Arkady Matveev, Sergey Fedorov, Maxim Skoltech Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 bld.1 Moscow121205 Russia Skoltech Center for Photonics and Quantum Materials Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 building 1 Moscow121205 Russia Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Leninskie Gory 1-52 2nd educational building 6th floor room 663 Moscow119991 Russia

We propose a novel approach optimizing passive photonic integrated component topology computations. It is based on Green’s Function Integral Equation method, utilizes weighted optimization methods and fast Toeplitz-l... 详细信息

ISBN: (纸本)9781557528209

关键词： Integral equations

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Duplication with transposition distance to the root for q-ary strings

Duplication with transposition distance to the root for q-ar...

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IEEE International Symposium on Information Theory

作者： Nikita Polyanskii Ilya Vorobyev Institute for Communications Engineering Technical University of Munich Munich Germany Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow Russia

ISBN: (数字)9781728164328

ISBN: (纸本)9781728164335

We study the duplication with transposition distance between strings of length n over a q-ary alphabet and their roots. In other words, we investigate the number of duplication operations of the form x = (abcd) →y = (abcbd), where x and y are strings and a, b, c and d are their substrings, needed to get a q-ary string of length n starting from the set of strings without duplications. For exact duplication, we prove that the maximal distance between a string of length at most n and its root has the asymptotic order n/logn. For approximate duplication, where a β-fraction of symbols may be duplicated incorrectly, we show that the maximal distance has a sharp transition from the order n/logn to logn at β = (q - 1)/q. The motivation for this problem comes from genomics, where such duplications represent a special kind of mutation and the distance between a given biological sequence and its root is the smallest number of transposition mutations required to generate the sequence.

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Kalman Filtering for Accurate and Fast Plant Growth Dynamics Assessment

Kalman Filtering for Accurate and Fast Plant Growth Dynamics...

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IEEE Instrumentation and Measurement Technology Conference

作者： Dmitrii Shadrin Tatiana Podladchikova George Ovchinnikov Artem Pavlov Mariia Pukalchik Andrey Somov Center for Computational and Data-Intensive Science and Engineering (CDISE) Space Center Skolkovo Institute of Science and Technology (SkolTech) Moscow Russia

ISBN: (数字)9781728144603

ISBN: (纸本)9781728144610

Artificial growth systems are the essential part of the precision agriculture. It allows solving many problems associated with the growing demand in the environmental friendly food production in the context of increasing world population. Accurate and reliable assessment of plant growth dynamics parameters is crucial for the future success of the whole growing system parameters optimization. In this research, we report on the implementation of the extended Kalman filtering method for insitu evaluation of plant growth dynamics parameters. We show the reliability and benefits of the proposed approach on the simulated and experimental data obtained from the IoT-based testbed. We demonstrate that our method serves as a robust and computationally cost-effective tool for the accurate assessment of the growing dynamics that, in turn, could be used for the further optimization of the whole plant cultivation process in artificial conditions.

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Average age of information of irregular repetition slotted ALOHA

arXiv

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arXiv 2020年

作者： Munari, Andrea Frolov, Alexey Wessling82234 Germany Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia

Flanking traditional metrics such as throughput and reliability, age of information (AoI) is emerging as a fundamental tool to capture the performance of IoT systems. In this context, we focus on a setup in which a large number of nodes attempt delivery of time-stamped updates to a common destination over a shared channel, and investigate the ability of different grant-free access strategies to maintain fresh information at the receiver. Specifically, we derive for the first time an exact closed-form expression of the average AoI achieved by irregular repetition slotted ALOHA (IRSA), and compare its performance to that of a slotted ALOHA approach. Our analysis reveals the potential of modern random access schemes, and pinpoints some fundamental trade-offs, providing useful hints for proper system design. Copyright © 2020, The Authors. All rights reserved.

关键词： Economic and social effects

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Almost affinely disjoint subspaces

arXiv

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arXiv 2020年

作者： Liu, Hedongliang Polianskii, Nikita Vorobyev, Ilya Wachter-Zeh, Antonia Technical University of Munich Institute for Communications Engineering Munich80333 Germany Skolkovo Institute of Science and Technology Center for Computational and Data-Intensive Science and Engineering Moscow121205 Russia

In this work, we introduce a natural notion concerning finite vector spaces. A family of k-dimensional subspaces of Fnq, which forms a partial spread, is called almost affinely disjoint if any (k + 1)-dimensional subspace containing a subspace from the family non-trivially intersects with only a few subspaces from the family. The central question discussed in the paper is the polynomial growth (in q) of the maximal cardinality of these families given the parameters k and n. For the cases k = 1 and k = 2, optimal families are constructed. For other settings, we find lower and upper bounds on the polynomial growth. Additionally, some connections with problems in coding theory are shown. © 2020, CC BY-NC-ND.

关键词： Vectors

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