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Code comparison for fast flavor instability simulations

Physical Review D 2022年第4期106卷 043011-043011页

作者： Sherwood Richers Huaiyu Duan Meng-Ru Wu Soumya Bhattacharyya Masamichi Zaizen Manu George Chun-Yu Lin Zewei Xiong Department of Physics University of California Berkeley California 94720 USA Department of Physics and Astronomy University of New Mexico Albuquerque New Mexico 87131 USA Institute of Physics Academia Sinica Taipei 11529 Taiwan Institute of Astronomy and Astrophysics Academia Sinica Taipei 10617 Taiwan Tata Institute of Fundamental Research Homi Bhabha Road Mumbai 400005 India Faculty of Science and Engineering Waseda University Tokyo 169-8555 Japan Department of Astronomy Graduate School of Science University of Tokyo Tokyo 113-0033 Japan National Center for High-Performance Computing National Applied Research Laboratories Hsinchu Science Park Hsinchu City 30076 Taiwan GSI Helmholtzzentrum für Schwerionenforschung Planckstraße 1 64291 Darmstadt Germany

The fast flavor instability (FFI) is expected to be ubiquitous in core-collapse supernovae and neutron star mergers. It rapidly shuffles neutrino flavor in a way that could impact the explosion mechanism, neutrino signals, mass outflows, and nucleosynthesis. The variety of initial conditions and simulation methods employed in simulations of the FFI prevent an apples-to-apples comparison of the results. We simulate a standardized test problem using five independent codes and verify that they are all faithfully simulating the underlying quantum kinetic equations under the assumptions of axial symmetry and homogeneity in two directions. We quantify the amount of numerical error in each method and demonstrate that each method is superior in at least one metric of this error. We make the results publicly available to serve as a benchmark.

关键词： Extrasolar neutrino astronomy Neutrino oscillations Novae & supernovae Nuclear astrophysics Particle astrophysics Plasma instabilities Accretion disk & black-hole plasma Neutrinos Quantum plasmas Particle-in-cell methods Plasma kinetic theory

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Quantum Contextuality Requires Counterfactual Gain

arXiv

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arXiv 2025年

作者： Sagawa, Yuki Hance, Jonte R. Hofmann, Holger F. Ono, Takafumi Program in Advanced Materials Science Faculty of Engineering and Design Kagawa University 2217-20 Hayashi-cho Kagawa Takamatsu761-0396 Japan School of Computing Newcastle University 1 Science Square Newcastle upon TyneNE4 5TG United Kingdom Quantum Engineering Technology Laboratories Department of Electrical and Electronic Engineering University of Bristol Woodland Road BristolBS8 1US United Kingdom Department of Quantum Matter Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama 1-3-1 Higashi Hiroshima739-8530 Japan

Quantum contextuality, where measurement outcomes depend on the measurement context, implies a failure of classical realism in quantum systems. As recently shown, the transition between measurement contexts can be mapped onto the path that a quantum particle takes through an interferometer. Here, we investigate the relation between contextuality and the counterfactual gain observed in the output ports of such an interferometer when one of the paths is blocked. It is shown that experimental evidence of contextuality can only be obtained when counterfactual gain is observed for a specific combination of blocked path and output port. Using a silicon photonic integrated circuit, we experimentally observe the counterfactual gain for a selection of input states and evaluate the associated evidence for contextuality. The results confirm that contextuality can only be observed in the presence of counterfactual gain. Copyright © 2025, The Authors. All rights reserved.

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Time-reversal symmetric ODE network 20

Time-reversal symmetric ODE network

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Proceedings of the 34th International Conference on Neural Information Processing Systems

作者： In Huh Eunho Yang Sung Ju Hwang Jinwoo Shin Samsung Advanced Institute of Technology and CSE Team DIT Center Samsung Electronics Graduate School of AI Korea Advanced Institute of Science and Technology (KAIST) and School of Computing KAIST Graduate School of AI Korea Advanced Institute of Science and Technology (KAIST) and School of Electrical Engineering KAIST

ISBN: (纸本)9781713829546

Time-reversal symmetry, which requires that the dynamics of a system should not change with the reversal of time axis, is a fundamental property that frequently holds in classical and quantum mechanics. In this paper, we propose a novel loss function that measures how well our ordinary differential equation (ODE) networks comply with this time-reversal symmetry; it is formally defined by the discrepancy in the time evolutions of ODE networks between forward and backward dynamics. Then, we design a new framework, which we name as Time-Reversal Symmetric ODE Networks (TRS-ODENs), that can learn the dynamics of physical systems more sample-efficiently by learning with the proposed loss function. We evaluate TRS-ODENs on several classical dynamics, and find they can learn the desired time evolution from observed noisy and complex trajectories. We also show that, even for systems that do not possess the full time-reversal symmetry, TRS-ODENs can achieve better predictive performances over baselines.

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Anionic Ordering in Pb2Ti4O9F2 Revisited by Nuclear Magnetic Resonance and Density Functional Theory

arXiv

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arXiv 2021年

作者： Oka, Kengo Ichibha, Tom Kato, Daichi Noda, Yasuto Tominaga, Yusuke Yamada, Kosei Iwasaki, Mitsunobu Noma, Naoki Hongo, Kenta Maezono, Ryo Reboredo, Fernando A. Department of Applied Chemistry Faculty of Science and Engineering Kindai University Osaka Higashiosaka577-8502 Japan Materials Science and Technology Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Energy and Hydrocarbon Chemistry Graduate School of Engineering Kyoto University Kyoto615-8510 Japan Division of Chemistry Graduate School of Science Kyoto University Kyoto606-8502 Japan Joint Research Center Kindai University Osaka Higashiosaka577-8502 Japan Research Center for Advanced Computing Infrastructure JAIST Asahidai 1-1 Ishikawa Nomi923-1292 Japan School of Information Science JAIST Asahidai 1-1 Ishikawa Nomi923-1292 Japan

A combination of 19F magic angle spinning (MAS) nuclear magnetic resonance (NMR) and density functional theory (DFT) were used to study the ordering of F atoms in Pb2Ti4O9F2. This analysis revealed that F atoms predominantly occupy two of the six available inequivalent sites in a ratio of 73:27. DFT-based calculations explained the preference of F occupation on these sites and quantitatively reproduced the experimental occupation ratio, independent of the choice of functional. We concluded that the Pb atom's 6s2 lone pair may play a role (∼0.1 eV/f.u.) in determining the majority and minority F occupation sites with partial density of states and crystal orbital Hamiltonian population analyses applied to the DFT wave functions. Copyright © 2021, The Authors. All rights reserved.

关键词： Density functional theory

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Inverse Problem Analysis of Distribution of Power Generation Current inside PEFC Using Magnetic Field around Fuel Cell

Inverse Problem Analysis of Distribution of Power Generation...

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Fuel Cell Seminar and Energy Exposition 2019

作者： Neki, Takeshi Gotoh, Yuji Izumi, Masaaki Nara, Takaaki Department of Mechanical and Energy Systems Engineering Oita University 700 Dannoharu Oita870-1192 Japan Department of Innovative Engineering Oita University 700 Dannoharu Oita870-1192 Japan Department of Mechanical Systems Engineering University of Kitakyushu 1-1 Hibikino Wakamatsu-ku Kitakyushu Fukuoka808-0135 Japan Department of Information Physics and Computing Graduate School of Information Science and Technology University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan

ISBN: (纸本)9781607688884

A PEFC (polymer electrolyte fuel cell) is expected to be used as a power supply of the homes and electric vehicles, since it can generate electricity at low temperatures and the startup speed is fast. Since the power generation efficiency of PEFC is influenced by the mass transfer of hydrogen, oxygen and steam in it, it is important to clarify the current distribution inside MEA that is closely related to the mass transfer. In this paper, the evaluation method of the distribution of the power generation current inside MEA using the distribution of static magnetic field around PEFC is proposed. The generated current distribution in the MEA is calculated by inverse problem analysis using Ampere's law from the distribution of the magnetic field around the fuel cell. The evolutionary strategy method is used by this inverse problem analysis. In addition, the current distribution estimation accuracy inside the MEA has been improved by using the weighting coefficient according to the distance between the magnetic sensor and each position in the MEA. © 2020 ECS-The Electrochemical Society.

关键词： Mass transfer

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Continuous black-box optimization with an Ising machine and random subspace coding

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Physical Review Research 2022年第2期4卷 023062-023062页

作者： Syun Izawa Koki Kitai Shu Tanaka Ryo Tamura Koji Tsuda Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Kashiwa 277-8561 Japan Department of Mechanical Engineering The University of Tokyo Tokyo 113-8654 Japan Department of Applied Physics and Physico-Informatics Keio University Yokohama 223-8522 Japan Green Computing System Research Organization Waseda University Tokyo 162-0042 Japan International Center for Materials Nanoarchitectonics National Institute for Materials Science Tsukuba 305-0047 Japan Research and Services Division of Materials Data and Integrated System National Institute for Materials Science Tsukuba 305-0047 Japan RIKEN Center for Advanced Intelligence Project Tokyo 103-0027 Japan

A black-box optimization algorithm such as Bayesian optimization finds the extremum of an unknown function by alternating the inference of the underlying function and optimization of an acquisition function. In a high-dimensional space, such algorithms perform poorly due to the difficulty of acquisition function optimization. Herein, we apply Ising machines to overcome the difficulty in the continuous black-box optimization. As an Ising machine specializes in optimization of binary problems, a continuous vector has to be encoded to binary, and the solution by Ising machines has to be translated back. Our method has the following three parts: (1) random subspace coding based on axis-parallel hyperrectangles from continuous vector to binary vector, (2) a quadratic unconstrained binary optimization (QUBO) defined by the acquisition function based on the nonnegative-weighted linear regression model, which is solved by Ising machines, and (3) a penalization scheme to ensure that the solution can be translated back. It is shown with benchmark tests that its performance using the D-Wave Advantage quantum annealer and simulated annealing is competitive with a state-of-the-art method based on the Gaussian process in high-dimensional problems. Our method may open up the possibility of Ising machines and other QUBO solvers, including a quantum approximate optimization algorithm using gated-quantum computers, and may expand its range of application to continuous-valued problems.

关键词： Adiabatic quantum optimization Machine learning Quantum algorithms Quantum computation

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Lessons Learned from Assessing Trustworthy AI in Practice

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Digital Society 2023年第3期2卷 1-25页

作者： Vetter, Dennis Amann, Julia Bruneault, Frédérick Coffee, Megan Düdder, Boris Gallucci, Alessio Gilbert, Thomas Krendl Hagendorff, Thilo van Halem, Irmhild Hickman, Eleanore Hildt, Elisabeth Holm, Sune Kararigas, Georgios Kringen, Pedro Madai, Vince I. Wiinblad Mathez, Emilie Tithi, Jesmin Jahan Westerlund, Magnus Wurth, Renee Zicari, Roberto V. Computational Vision and Artificial Intelligence Lab Goethe University Frankfurt Frankfurt Am Main Germany Z-Inspection® Initiative Venice Italy Health Ethics and Policy Lab ETH Zurich Zurich Switzerland Strategy and Innovation Careum Foundation Zurich Switzerland Philosophie Departement Collège André-Laurendeau Montréal Canada École Des Médias Université du Québec À Montréal Montréal Canada Department of Medicine Division of Infectious Diseases and Immunology New York University Grossman School of Medicine New York City USA Department of Computer Science University of Copenhagen Copenhagen Denmark Digital Life Initiative Cornell Tech New York City USA Cluster of Excellence “Machine Learning: New Perspectives for Science” University of Tuebingen Tuebingen Germany School of Law University of Bristol Bristol UK Center for the Study of Ethics in the Professions Illinois Institute of Technology Chicago USA Department of Business Management and Analytics Arcada University of Applied Sciences Helsinki Finland Department of Food & Resource Economics University of Copenhagen Copenhagen Denmark Department of Physiology Faculty of Medicine University of Iceland Reykjavik Iceland QUEST Centre for Responsible Research Berlin Institute of Health Charité Universitätsmedizin Berlin Berlin Germany Faculty of Computing Engineering and the Built Environment School of Computing and Digital Technology Birmingham City University Birmingham UK Parallel Computing Labs Intel Santa Clara USA School of Economics Innovation and Technology Kristiania University College Oslo Norway Data Science Graduate School Seoul National University Seoul South Korea

Building artificial intelligence (AI) systems that adhere to ethical standards is a complex problem. Even though a multitude of guidelines for the design and development of such trustworthy AI systems exist, these guidelines focus on high-level and abstract requirements for AI systems, and it is often very difficult to assess if a specific system fulfills these requirements. The Z-Inspection® process provides a holistic and dynamic framework to evaluate the trustworthiness of specific AI systems at different stages of the AI lifecycle, including intended use, design, and development. It focuses, in particular, on the discussion and identification of ethical issues and tensions through the analysis of socio-technical scenarios and a requirement-based framework for ethical and trustworthy AI. This article is a methodological reflection on the Z-Inspection® process. We illustrate how high-level guidelines for ethical and trustworthy AI can be applied in practice and provide insights for both AI researchers and AI practitioners. We share the lessons learned from conducting a series of independent assessments to evaluate the trustworthiness of real-world AI systems, as well as key recommendations and practical suggestions on how to ensure a rigorous trustworthiness assessment throughout the lifecycle of an AI system. The results presented in this article are based on our assessments of AI systems in the healthcare sector and environmental monitoring, where we used the framework for trustworthy AI proposed in the Ethics Guidelines for Trustworthy AI by the European Commission’s High-Level Expert Group on AI. However, the assessment process and the lessons learned can be adapted to other domains and include additional frameworks.

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Simulation and performance analysis of quantum error correction with a rotated surface code under a realistic noise model

arXiv

引用

arXiv 2022年

作者： Katsuda, Mitsuki Mitarai, Kosuke Fujii, Keisuke Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Osaka Toyonaka560-8531 Japan Center for Quantum Information and Quantum Biology Osaka University 1-2 Machikaneyama Toyonaka560-0043 Japan JST PRESTO 4-1-8 Honcho Saitama Kawaguchi332-0012 Japan Hirosawa 2-1 Saitama Wako351-0198 Japan Fujitsu Quantum Computing Joint Research Division at QIQB Osaka University 1-2 Machikaneyama Toyonaka560-0043 Japan

The demonstration of quantum error correction (QEC) is one of the most important milestones in the realization of fully-fledged quantum computers. Toward this, QEC experiments using the surface codes have recently been actively conducted. However, it has not yet been realized to protect logical quantum information beyond the physical coherence time. In this work, we performed a full simulation of QEC for the rotated surface codes with a code distance 5, which employs 49 qubits and is within reach of the current state-of-the-art quantum computers. In particular, we evaluate the logical error probability in a realistic noise model that incorporates not only stochastic Pauli errors but also coherent errors due to a systematic control error or unintended interactions. While a straightforward simulation of 49 qubits is not tractable within a reasonable computational time, we reduced the number of qubits required to 26 qubits by delaying the syndrome measurement in simulation. This and a fast quantum computer simulator, Qulacs, implemented on GPU allows us to simulate full QEC with an arbitrary local noise within reasonable simulation time. Based on the numerical results, we also construct and verify an effective model to incorporate the effect of the coherent error into a stochastic noise model. This allows us to understand what the effect coherent error has on the logical error probability on a large scale without full simulation based on the detailed full simulation of a small scale. The present simulation framework and effective model, which can handle arbitrary local noise, will play a vital role in clarifying the physical parameters that future experimental QEC should target. © 2022, CC BY.

关键词： Stochastic systems

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Semi-supervised learning combining backpropagation and STDP: STDP enhances learning by backpropagation with a small amount of labeled data in a spiking neural network

arXiv

引用

arXiv 2021年

作者： Furuya, Kotaro Ohkubo, Jun School of Computing Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8552 Japan Graduate School of Science and Engineering Saitama University 255 Shimo-Okubo Sakura-ku Saitama-shi338-8570 Japan JST PREST 4-1-8 Honcho Kawaguchi Saitama332-0012 Japan

A semi-supervised learning method for spiking neural networks is proposed. The proposed method consists of supervised learning by backpropagation and subsequent unsupervised learning by spike-timing-dependent plasticity (STDP), which is a biologically plausible learning rule. Numerical experiments show that the proposed method improves the accuracy without additional labeling when a small amount of labeled data is used. This feature has not been achieved by existing semi-supervised learning methods of discriminative models. It is possible to implement the proposed learning method for event-driven systems. Hence, it would be highly efficient in real-time problems if it were implemented on neuromorphic hardware. The results suggest that STDP plays an important role other than self-organization when applied after supervised learning, which differs from the previous method of using STDP as pre-training interpreted as self-organization. Copyright © 2021, The Authors. All rights reserved.

关键词： Backpropagation

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Relativistic variational-quantum-eigensolver calculations of molecular electric dipole moments on quantum hardware

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Physical Review A 2025年第2期111卷 022817-022817页

作者： Palak Chawla Shweta K. R. Swain Tushti Patel Renu Bala Disha Shetty Kenji Sugisaki Sudhindu Bikash Mandal Jordi Riu Centre for Quantum Engineering Research and Education TCG Crest Kolkata 700091 India Department of Physics Indian Institute of Technology Delhi New Delhi 110016 India Present address: Department of Physics and Materials Science University of Luxembourg L-1511 Luxembourg Luxembourg. Department of Physics IIT Tirupati Chindepalle Andhra Pradesh 517619 India Present address: Institute of Physics Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Grudziadzka 5 87-100 Toruń Poland. Graduate School of Science and Technology Keio University 7-1 Shinkawasaki Saiwai-ku Kawasaki Kanagawa 212-0032 Japan Quantum Computing Center Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Kanagawa 223-8522 Japan Keio University Sustainable Quantum Artificial Intelligence Center (KSQAIC) Keio University 2-15-45 Mita Minato-ku Tokyo Japan Qilimanjaro Quantum Tech Carrer de Veneçuela 74 Sant Martí 08019 Barcelona Spain Universitat Politècnica de Catalunya Carrer de Jordi Girona 3 08034 Barcelona Spain

The quantum–classical hybrid variational quantum eigensolver (VQE) algorithm is among the most actively studied topics in atomic and molecular calculations on quantum computers, yet few studies address properties other than energies or account for relativistic effects. This work presents high-precision 18-qubit relativistic VQE simulations for calculating the permanent electric dipole moments (PDMs) of alkaline-earth metal monohydride molecules (BeH to RaH) on traditional computers, and 6- and 12-qubit PDM computations for SrH on IonQ quantum devices. To achieve high precision on current noisy intermediate-scale era quantum hardware, we apply various resource-reduction methods, including reinforcement learning-based and causal flow preserving ZX–calculus routines, along with error mitigation and postselection techniques. Our approach reduces the two-qubit gate count in our 12-qubit circuit by 99.71%, with only a 2.35% trade-off in precision for PDM when evaluated classically within a suitably chosen active space. On the current generation IonQ Forte-I hardware, the error in PDM is −1.17% relative to classical calculations and only 1.21% compared with the unoptimized circuit.

关键词： Qubits

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