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FROSch: A Fast And Robust Overlapping Schwarz Domain Decomposition Preconditioner Based on Xpetra in Trilinos 25th

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FROSch: A Fast And Robust Overlapping Schwarz Domain Decompo...

25th International Conference on Domain Decomposition Methods in science and Engineering, DD 2018

作者： Heinlein, Alexander Klawonn, Axel Rajamanickam, Sivasankaran Rheinbach, Oliver Department of Mathematics and Computer Science University of Cologne Weyertal 86-90 Köln50931 Germany Center for Data and Simulation Science University of Cologne Cologne Germany Center for Computing Research Scalable Algorithms Department Sandia National Laboratories NM 87123 Albuquerque Mexico INMO Technische Universität Bergakademie Freiberg Akademiestr. 6 Freiberg09599 Germany

ISBN: (纸本)9783030567491

This article describes a parallel implementation of a two-level overlapping Schwarz preconditioner with the GDSW (Generalized Dryja–Smith–Widlund) coarse space described in previous work [12, 10, 15] into the Trilinos framework;cf. [16]. The software is a significant improvement of a previous implementation [12];see Sec. 4 for results on the improved performance. © 2020, Springer Nature Switzerland AG.

关键词： Domain decomposition methods

NEO-QEC: Neural Network Enhanced Online Superconducting Decoder for Surface Codes

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arXiv 2022年

作者： Ueno, Yosuke Kondo, Masaaki Tanaka, Masamitsu Suzuki, Yasunari Tabuchi, Yutaka The University of Tokyo Japan Keio University Japan Nagoya University Japan NTT Computer and Data Science Laboratories Japan RIKEN Center for Quantum Computing Japan

Quantum error correction (QEC) is essential for quantum computing to mitigate the effect of errors on qubits, and surface code (SC) is one of the most promising QEC methods. Decoding SCs is the most computational expensive task in the control device of quantum computers (QCs), and many works focus on accurate decoding algorithms for SCs, including ones with neural networks (NNs). Practical QCs also require low-latency decoding because slow decoding leads to the accumulation of errors on qubits, resulting in logical failures. For QCs with superconducting qubits, a practical decoder must be very power-efficient in addition to having high accuracy and low latency. In order to reduce the hardware complexity of QC, we are supposed to decode SCs in a cryogenic environment with a limited power budget, where superconducting qubits operate. In this paper, we propose an NN-based accurate, fast, and low-power decoder capable of decoding SCs and lattice surgery (LS) operations with measurement errors on ancillary qubits. To achieve both accuracy and hardware efficiency of the SC decoder, we apply a binarized NN. We design a neural processing unit (NPU) for the decoder with SFQ-based digital circuits and evaluate it with a SPICE-level simulation. We evaluate the decoder performance by a quantum error simulator for the single logical qubit protection and the minimum operation of LS with code distances up to 13, and it achieves 2.5% and 1.0% accuracy thresholds, respectively. Copyright © 2022, The Authors. All rights reserved.

关键词： Error correction

WIT-Greedy: Hardware System Design of Weighted ITerative Greedy Decoder for Surface Code

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WIT-Greedy: Hardware System Design of Weighted ITerative Gre...

Asia and South Pacific Design Automation Conference

作者： Wang Liao Yasunari Suzuki Teruo Tanimoto Yosuke Ueno Yuuki Tokunaga Photon Science Center the University of Tokyo Japan NTT Computer and Data Science Laboratories Japan Faculty of Information Science and Electrical Engineering Kyushu University Japan Graduate School of Information Science and Technology the University of Tokyo Japan

Large error rates of quantum bits (qubits) are one of the main difficulties in the development of quantum computing. Performing quantum error correction (QEC) with surface codes is considered the most promising approach to reduce the error rates of qubits effectively. To perform error correction, we need an error-decoding unit, which estimates errors in the noisy physical qubits repetitively, to create a robust logical qubit. While complicated graph-matching problems must be solved within a strict time restriction for the error decoding, several hardware implementations that satisfy the restriction at a large code distance have been proposed. However, the existing decoder designs are still challenging in reducing the logical error rate. This is because they assume that the error rates of physical qubits are uniform while they have large variations in practice. According to our numerical simulation based on the quantum chip with the largest qubit number, neglecting the non-uniform error properties of a real quantum chip in the decoding process induces significant degradation of the logical error rate and spoils the benefit of QEC. To take the non-uniformity into account, decoders need to solve matching problems on a weighted graph, but they are difficult to solve using the existing designs without exceeding the time limit of decoding. Therefore, a decoder that can treat both the non-uniform physical error rates and the large surface code is strongly demanded. In this paper, we propose a hardware design of decoding units for the surface code that can treat the non-identical error properties with small latency at a large code distance. The key idea of our design is 1) constructing a look-up table for calculating the shortest paths between nodes in a weighted graph and 2) enabling parallel processing during decoding. The implementation results in field programmable gate array (FPGA) indicate that our design scales up to code distance 11 within a microsecond-level delay,

关键词： Codes Error analysis Qubit Hardware Decoding Delays Table lookup

ALTERNATING ENERGY MINIMIZATION METHODS FOR MULTI-TERM MATRIX EQUATIONS

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arXiv 2020年

作者： Kookjin, L.E.E. Elman, Howard C. Powell, Catherine E. Lee, Dongeun Extreme Scale Data Science and Analytics Department Sandia National Laboratories Department of Computer Science University of Maryland College Park United States Department of Mathematics University of Manchester United Kingdom Department of Computer Science Texas A&M University-Commerce

We develop computational methods for approximating the solution of a linear multi-term matrix equation in low rank. We follow an alternating minimization framework, where the solution is represented as a product of two matrices, and approximations to each matrix are sought by solving certain minimization problems repeatedly. The solution methods we present are based on a rank-adaptive variant of alternating energy minimization methods that builds an approximation iteratively by successively computing a rank-one solution component at each step. We also develop efficient procedures to improve the accuracy of the low-rank approximate solutions computed using these successive rank-one update techniques. We explore the use of the methods with linear multi-term matrix equations that arise from stochastic Galerkin finite element discretizations of parameterized linear elliptic PDEs, and demonstrate their effectiveness with numerical studies. Copyright © 2020, The Authors. All rights reserved.

关键词： Stochastic systems

Edit and Alphabet-Ordering Sensitivity of Lex-parse

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arXiv 2024年

作者： Nakashima, Yuto Köppl, Dominik Funakoshi, Mitsuru Inenaga, Shunsuke Bannai, Hideo Department of Informatics Kyushu University Japan Department of Computer Science and Engineering University of Yamanashi Japan NTT Communication Science Laboratories M&D Data Science Center Tokyo Medical and Dental University Japan

We investigate the compression sensitivity [Akagi et al., 2023] of lex-parse [Navarro et al., 2021] for two operations: (1) single character edit and (2) modification of the alphabet ordering, and give tight upper and lower bounds for both operations. For both lower bounds, we use the family of Fibonacci words. For the bounds on edit operations, our analysis makes heavy use of properties of the Lyndon factorization of Fibonacci words to characterize the structure of lex-parse. © 2024, CC BY.

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Learning Inter-Lingual Document Representations via Concept Compression 22nd

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Learning Inter-Lingual Document Representations via Concept ...

22nd International Conference on Intelligent data Engineering and Automated Learning, IDEAL 2021

作者： Lenz, Marc Tashu, Tsegaye Misikir Horváth, Tomáš Faculty of Informatics Department of Data Science and Engineering Telekom Innovation Laboratories ELTE - Eötvös Loránd University Pázmány Péter Sétány Budapest1117 Hungary College of Informatics Wollo University Kombolcha Institute of Technology Kombolcha208 Ethiopia Faculty of Science Institute of Computer Science Pavol Jozef Šafárik University Jesenná 5 Košice040 01 Slovakia

ISBN: (纸本)9783030916077

In this work, we proposed a novel approach to derive inter-lingual document representations. The introduced methods aim to enhance the quality of content-based Multilingual Document Recommendation and information retrieval Systems. The main idea centers around creating inter-lingual representations by using mappings to align monolingual representation spaces. According to the experimental results carried out on JRC-Acquis and EU bookshop multilingual corpora, the proposed concept compression approach has outperformed the traditional cross-lingual retrieval and recommendations methods. © 2021, Springer Nature Switzerland AG.

关键词： Information retrieval systems

Stimulated Emission of Superradiant Atoms in Waveguide Quantum Electrodynamics

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Physical Review Applied 2022年第6期18卷 064006-064006页

作者： Rui Asaoka Julio Gea-Banacloche Yuuki Tokunaga Kazuki Koshino Computer and Data Science Laboratories NTT Corporation Musashino 180-8585 Japan Department of Physics University of Arkansas Fayetteville Arkansas 72701 USA College of Liberal Arts and Sciences Tokyo Medical and Dental University Ichikawa 272-0827 Japan

We investigate the stimulated emission of superradiant atoms coupled to a waveguide induced by a coherent-state photon pulse. We provide an analytical result when a short π pulse is incident, which shows that the atoms emit photons coherently into the output pulse, which remains a coherent state in the short pulse limit. An incident pulse is amplified in a phase-preserving manner, where noise is added almost entirely in the phase direction in phase space. This property improves the ratio of the intensity signal to noise after the amplification for sufficiently short pulses. This is a unique feature different from general phase-preserving linear amplifiers, where the signal-to-noise ratio deteriorates in the amplification process. We also discuss the dependence of the photon-emission probability on pulse parameters, such as the pulse area and the duration.

关键词： Quantum control Quantum electrodynamics Quantum information processing with continuous variables Quantum information with atoms & light Quantum networks Spontaneous emission Superradiance & subradiance Waveguides

Generalizing Jensen and Bregman divergences with comparative convexity and the statistical Bhattacharyya distances with comparable means

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arXiv 2017年

作者： Nielsen, Frank Nock, Richard Computer Science Department LIX École Polytechnique Palaiseau Cedex91128 France Sony Computer Science Laboratories Inc Tokyo141-0022 Japan Data61 SydneyNSW Australia Australian National University University of Sydney Australia

Comparative convexity is a generalization of convexity relying on abstract notions of means. We define the (skew) Jensen divergence and the Jensen diversity from the viewpoint of comparative convexity, and show how to obtain the generalized Bregman divergences as limit cases of skewed Jensen divergences. In particular, we report explicit formula of these generalized Bregman divergences when considering quasiarithmetic means. Finally, we introduce a generalization of the Bhattacharyya statistical distances based on comparative means using relative convexity. Copyright © 2017, The Authors. All rights reserved.

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Attention-Based Multi-modal Emotion Recognition from Art 25th

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Attention-Based Multi-modal Emotion Recognition from Art

25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Tashu, Tsegaye Misikir Horváth, Tomáš Faculty of Informatics Department of Data Science and Engineering Telekom Innovation Laboratories ELTE Eötvös Loránd University Pázmány Péter sétány 1/C Budapest1117 Hungary Kombolcha Institute of Technology College of Informatics Wollo University Kombolcha208 Ethiopia Faculty of Science Institute of Computer Science Pavol Jozef Šafárik University in Košice Jesenná 5 Košice040 01 Slovakia

ISBN: (纸本)9783030687953

Emotions are very important in dealing with human decisions, interactions, and cognitive processes. Art is an imaginative human creation that should be appreciated, thought-provoking, and elicits an emotional response. The automatic recognition of emotions triggered by art is of considerable importance. It can be used to categorize artworks according to the emotions they evoke, recommend paintings that accentuate or balance a particular mood, and search for paintings of a particular style or genre that represent custom content in a custom state of impact. In this paper, we propose an attention-based multi-modal approach to emotion recognition that aims to use information from both the painting and title channels to achieve more accurate emotion recognition. Experimental results on the WikiArt emotion dataset showed the efficiency of the model we proposed and the usefulness of image and text modalities in emotion recognition. © 2021, Springer Nature Switzerland AG.

关键词： Emotion Recognition