IA Scholar Query: Quantum Supremacy Circuit Simulation on Sunway TaihuLight.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgThu, 17 Nov 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440Near-Term Quantum Computing Techniques: Variational Quantum Algorithms, Error Mitigation, Circuit Compilation, Benchmarking and Classical Simulation
https://scholar.archive.org/work/5cil662o5bclbky4ypzlw2akiq
Quantum computing is a game-changing technology for global academia, research centers and industries including computational science, mathematics, finance, pharmaceutical, materials science, chemistry and cryptography. Although it has seen a major boost in the last decade, we are still a long way from reaching the maturity of a full-fledged quantum computer. That said, we will be in the Noisy-Intermediate Scale Quantum (NISQ) era for a long time, working on dozens or even thousands of qubits quantum computing systems. An outstanding challenge, then, is to come up with an application that can reliably carry out a nontrivial task of interest on the near-term quantum devices with non-negligible quantum noise. To address this challenge, several near-term quantum computing techniques, including variational quantum algorithms, error mitigation, quantum circuit compilation and benchmarking protocols, have been proposed to characterize and mitigate errors, and to implement algorithms with a certain resistance to noise, so as to enhance the capabilities of near-term quantum devices and explore the boundaries of their ability to realize useful applications. Besides, the development of near-term quantum devices is inseparable from the efficient classical simulation, which plays a vital role in quantum algorithm design and verification, error-tolerant verification and other applications. This review will provide a thorough introduction of these near-term quantum computing techniques, report on their progress, and finally discuss the future prospect of these techniques, which we hope will motivate researchers to undertake additional studies in this field.He-Liang Huang, Xiao-Yue Xu, Chu Guo, Guojing Tian, Shi-Jie Wei, Xiaoming Sun, Wan-Su Bao, Gui-Lu Longwork_5cil662o5bclbky4ypzlw2akiqThu, 17 Nov 2022 00:00:00 GMTA density-matrix renormalization group algorithm for simulating quantum circuits with a finite fidelity
https://scholar.archive.org/work/zensymejbbamxhz6pebjpz37g4
We develop a density-matrix renormalization group (DMRG) algorithm for the simulation of quantum circuits. This algorithm can be seen as the extension of time-dependent DMRG from the usual situation of hermitian Hamiltonian matrices to quantum circuits defined by unitary matrices. For small circuit depths, the technique is exact and equivalent to other matrix product state (MPS) based techniques. For larger depths, it becomes approximate in exchange for an exponential speed up in computational time. Like an actual quantum computer, the quality of the DMRG results is characterized by a finite fidelity. However, unlike a quantum computer, the fidelity depends strongly on the quantum circuit considered. For the most difficult possible circuit for this technique, the so-called "quantum supremacy" benchmark of Google Inc. , we find that the DMRG algorithm can generate bit strings of the same quality as the seminal Google experiment on a single computing core. For a more structured circuit used for combinatorial optimization (Quantum Approximate Optimization Algorithm or QAOA), we find a drastic improvement of the DMRG results with error rates dropping by a factor of 100 compared with random quantum circuits. Our results suggest that the current bottleneck of quantum computers is their fidelities rather than the number of qubits.Thomas Ayral, Thibaud Louvet, Yiqing Zhou, Cyprien Lambert, E. Miles Stoudenmire, Xavier Waintalwork_zensymejbbamxhz6pebjpz37g4Mon, 29 Aug 2022 00:00:00 GMTLarge-Scale Simulation of Quantum Computational Chemistry on a New Sunway Supercomputer
https://scholar.archive.org/work/kermpxzi2fhkdnh5rmwmvjuv74
Quantum computational chemistry (QCC) is the use of quantum computers to solve problems in computational quantum chemistry. We develop a high performance variational quantum eigensolver (VQE) simulator for simulating quantum computational chemistry problems on a new Sunway supercomputer. The major innovations include: (1) a Matrix Product State (MPS) based VQE simulator to reduce the amount of memory needed and increase the simulation efficiency; (2) a combination of the Density Matrix Embedding Theory with the MPS-based VQE simulator to further extend the simulation range; (3) A three-level parallelization scheme to scale up to 20 million cores; (4) Usage of the Julia script language as the main programming language, which both makes the programming easier and enables cutting edge performance as native C or Fortran; (5) Study of real chemistry systems based on the VQE simulator, achieving nearly linearly strong and weak scaling. Our simulation demonstrates the power of VQE for large quantum chemistry systems, thus paves the way for large-scale VQE experiments on near-term quantum computers.Honghui Shang, Li Shen, Yi Fan, Zhiqian Xu, Chu Guo, Jie Liu, Wenhao Zhou, Huan Ma, Rongfen Lin, Yuling Yang, Fang Li, Zhuoya Wang, Yunquan Zhang, Zhenyu Liwork_kermpxzi2fhkdnh5rmwmvjuv74Fri, 08 Jul 2022 00:00:00 GMTQuantum computational advantage via high-dimensional Gaussian boson sampling
https://scholar.archive.org/work/llv672r4ebhpfmr42t73nhxpfy
Photonics is a promising platform for demonstrating a quantum computational advantage (QCA) by outperforming the most powerful classical supercomputers on a well-defined computational task. Despite this promise, existing proposals and demonstrations face challenges. Experimentally, current implementations of Gaussian boson sampling (GBS) lack programmability or have prohibitive loss rates. Theoretically, there is a comparative lack of rigorous evidence for the classical hardness of GBS. In this work, we make progress in improving both the theoretical evidence and experimental prospects. We provide evidence for the hardness of GBS, comparable to the strongest theoretical proposals for QCA. We also propose a QCA architecture we call high-dimensional GBS, which is programmable and can be implemented with low loss using few optical components. We show that particular algorithms for simulating GBS are outperformed by high-dimensional GBS experiments at modest system sizes. This work thus opens the path to demonstrating QCA with programmable photonic processors.Abhinav Deshpande, Arthur Mehta, Trevor Vincent, Nicolás Quesada, Marcel Hinsche, Marios Ioannou, Lars Madsen, Jonathan Lavoie, Jens Eisert, Dominik Hangleiter, Universitätsbibliothek Der FU Berlinwork_llv672r4ebhpfmr42t73nhxpfyMon, 04 Jul 2022 00:00:00 GMTLifetime-based Method for Quantum Simulation on a New Sunway Supercomputer
https://scholar.archive.org/work/lcw3l24gzbenljisgppjbkwbeq
Faster classical simulation becomes essential for the validation of quantum computer, and tensor network contraction is a widely-applied simulation approach. Due to the memory limitation, slicing is adopted to help cutting down the memory size by reducing the tensor dimension, which also leads to additional computation overhead. This paper proposes novel lifetime-based methods to reduce the slicing overhead and improve the computing efficiency, including: interpretation for slicing overhead, an in place slicing strategy to find the smallest slicing set, a corresponding iterative method, and an adaptive path refiner customized for Sunway architecture. Experiments show that our in place slicing strategy reduces the slicing overhead to less than 1.2 and obtains 100-200 times speedups over related efforts. The resulting simulation time is reduced from 304s (2021 Gordon Bell Prize) to 149.2s on Sycamore RQC, with a sustainable mixed-precision performance of 416.5 Pflops using over 41M cores to simulate 1M correlated samples.Yaojian Chen, Yong Liu, Xinmin Shi, Jiawei Song, Xin Liu, Lin Gan, Chu Guo, Haohuan Fu, Dexun Chen, Guangwen Yangwork_lcw3l24gzbenljisgppjbkwbeqSun, 01 May 2022 00:00:00 GMTQuantum computational advantage via high-dimensional Gaussian boson sampling
https://scholar.archive.org/work/6m3qqa3elbf2jpc44t5uix3sii
[Figure: see text].Abhinav Deshpande, Arthur Mehta, Trevor Vincent, Nicolás Quesada, Marcel Hinsche, Marios Ioannou, Lars Madsen, Jonathan Lavoie, Haoyu Qi, Jens Eisert, Dominik Hangleiter, Bill Fefferman, Ish Dhandwork_6m3qqa3elbf2jpc44t5uix3siiFri, 07 Jan 2022 00:00:00 GMT