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arXiv 2105.05018quant-ph
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用于海森堡型哈密顿量量子模拟的相位估计算法的优化

Optimizing the Phase Estimation Algorithm Applied to the Quantum Simulation of Heisenberg-Type Hamiltonians

Scott Johnstun, Jean-François Van Huele

摘要:

相位估计算法是一种功能强大的量子算法,在密码学、数论和量子系统模拟中有着广泛的应用。我们用这个算法模拟了两个自旋为1/2的粒子系统在海森堡哈密顿量下的时间演化。演化是通过量子计算机的经典模拟和IBM Qiskit平台的真实量子计算机来进行的。我们还介绍了三种优化算法:循环,迭代和贝叶斯。我们将这些优化应用到我们的模拟中,并研究性能如何提高。我们还讨论了迭代和基于更新的算法的范例,这些优化的属性,可以改善量子算法一般。

英文摘要:

The phase estimation algorithm is a powerful quantum algorithm with applications in cryptography, number theory, and simulation of quantum systems. We use this algorithm to simulate the time evolution of a system of two spin-1/2 particles under a Heisenberg Hamiltonian. The evolution is performed through both classical simulations of quantum computers and real quantum computers via IBM's Qiskit platform. We also introduce three optimizations to the algorithm: circular, iterative, and Bayesian. We apply these optimizations to our simulations and investigate how the performance improves. We also discuss the paradigms of iterative and update-based algorithms, which are attributes of these optimizations that can improve quantum algorithms generally.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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