Quantum Linear System Solver Based on Time-optimal Adiabatic Quantum Computing and Quantum Approximate Optimization Algorithm

Quantum Linear System Solver Based on Time-optimal Adiabatic Quantum Computing and Quantum Approximate Optimization Algorithm
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基于时间最优绝热量子计算和量子近似优化算法的量子线性系统求解器

DOI:
10.1145/3498331
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发表时间:
2022
期刊:
ACM Transactions on Quantum Computing
影响因子:
--
通讯作者:
Lin, Lin
Lin, Lin
中科院分区:
--
文献类型:
--
作者:
An, Dong;Lin, Lin

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证明了利用优化调度函数,绝热量子计算可以在较短的时间内求解量子线性系统问题,其中κ为条件数,为目标精度。这对于κ和ε都是近乎最佳的,并且无需依赖难以实现的复杂的幅度放大过程即可实现。我们的方法适用于一般的非厄米特矩阵,当限制到厄米特矩阵,进而限制到厄米特正定矩阵时,可以减少量子比特的数量和成本。时间最优AQC的成功表明,具有最优控制协议的量子近似优化算法(QAOA)在运行时间方面也可以达到相同的复杂度。数值结果表明,与时间最优的AQC、Vanilla AQC和最近提出的随机化方法相比,QAOA可以产生最低的运行时间。
We demonstrate that with an optimally tuned scheduling function, adiabatic quantum computing (AQC) can readily solve a quantum linear system problem (QLSP) withO(κ poly(log (κ ε))) runtime, where κ is the condition number, and ε is the target accuracy. This is near optimal with respect to both κ and ε, and is achieved without relying on complicated amplitude amplification procedures that are difficult to implement. Our method is applicable to general non-Hermitian matrices, and the cost as well as the number of qubits can be reduced when restricted to Hermitian matrices, and further to Hermitian positive definite matrices. The success of the time-optimal AQC implies that the quantum approximate optimization algorithm (QAOA) with an optimal control protocol can also achieve the same complexity in terms of the runtime. Numerical results indicate that QAOA can yield the lowest runtime compared to the time-optimal AQC, vanilla AQC, and the recently proposed randomization method.
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