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Atomic and Laser Physics
Credit: Jack Hobhouse

Jinzhao Sun

Schmidt AI in Science Fellow

Research theme

  • Quantum information and computation

Sub department

  • Atomic and Laser Physics

Research groups

  • Frontiers of quantum physics
jinzhao.sun@physics.ox.ac.uk
Clarendon Laboratory
  • About
  • Publications

Low-Depth Hamiltonian Simulation by an Adaptive Product Formula

Physical Review Letters American Physical Society (APS) 130:4 (2023) 040601

Authors:

Zi-Jian Zhang, Jinzhao Sun, Xiao Yuan, Man-Hong Yung

Experimental quantum computational chemistry with optimised unitary coupled cluster ansatz

ArXiv 2212.08006 (2022)

Authors:

Shaojun Guo, Jinzhao Sun, Haoran Qian, Ming Gong, Yukun Zhang, Fusheng Chen, Yangsen Ye, Yulin Wu, Sirui Cao, Kun Liu, Chen Zha, Chong Ying, Qingling Zhu, He-Liang Huang, Youwei Zhao, Shaowei Li, Shiyu Wang, Jiale Yu, Daojin Fan, Dachao Wu, Hong Su, Hui Deng, Hao Rong, Yuan Li, Kaili Zhang, Tung-Hsun Chung, Futian Liang, Jin Lin, Yu Xu, Lihua Sun, Cheng Guo, Na Li, Yong-Heng Huo, Cheng-Zhi Peng, Chao-Yang Lu, Xiao Yuan, Xiaobo Zhu, Jian-Wei Pan

Simple and high-precision Hamiltonian simulation by compensating Trotter error with linear combination of unitary operations

ArXiv 2212.04566 (2022)

Authors:

Pei Zeng, Jinzhao Sun, Liang Jiang, Qi Zhao

Towards a variational Jordan鈥揕ee鈥揚reskill quantum algorithm

Machine Learning: Science and Technology IOP Publishing 3:4 (2022) 045030-045030

Authors:

Junyu Liu, Zimu Li, Han Zheng, Xiao Yuan, Jinzhao Sun

Abstract:

Abstract Rapid developments of quantum information technology show promising opportunities for simulating quantum field theory in near-term quantum devices. In this work, we formulate the theory of (time-dependent) variational quantum simulation of the 1 + 1 dimensional 位 蠒 4 quantum field theory including encoding, state preparation, and time evolution, with several numerical simulation results. These algorithms could be understood as near-term variational quantum circuit (quantum neural network) analogs of the Jordan鈥揕ee鈥揚reskill algorithm, the basic algorithm for simulating quantum field theory using universal quantum devices. Besides, we highlight the advantages of encoding with harmonic oscillator basis based on the Lehmann鈥擲ymanzik鈥擹immermann reduction formula and several computational efficiency such as when implementing a bosonic version of the unitary coupled cluster ansatz to prepare initial states. We also discuss how to circumvent the 鈥榮pectral crowding鈥� problem in the quantum field theory simulation and appraise our algorithm by both state and subspace fidelities.

Perturbative quantum simulation

Physical Review Letters American Physical Society 129:12 (2022) 120505

Authors:

Jinzhao Sun, Suguru Endo, Huiping Lin, Patrick Hayden, Vlatko Vedral, Xiao Yuan

Abstract:

Approximation based on perturbation theory is the foundation for most of the quantitative predictions of quantum mechanics, whether in quantum many-body physics, chemistry, quantum field theory, or other domains. Quantum computing provides an alternative to the perturbation paradigm, yet state-of-the-art quantum processors with tens of noisy qubits are of limited practical utility. Here, we introduce perturbative quantum simulation, which combines the complementary strengths of the two approaches, enabling the solution of large practical quantum problems using limited noisy intermediate-scale quantum hardware. The use of a quantum processor eliminates the need to identify a solvable unperturbed Hamiltonian, while the introduction of perturbative coupling permits the quantum processor to simulate systems larger than the available number of physical qubits. We present an explicit perturbative expansion that mimics the Dyson series expansion and involves only local unitary operations, and show its optimality over other expansions under certain conditions. We numerically benchmark the method for interacting bosons, fermions, and quantum spins in different topologies, and study different physical phenomena, such as information propagation, charge-spin separation, and magnetism, on systems of up to 48 qubits only using an 8+1 qubit quantum hardware. We demonstrate our scheme on the IBM quantum cloud, verifying its noise robustness and illustrating its potential for benchmarking large quantum processors with smaller ones.

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