Paesani S, Gentile A A, Santagati R, Wang J, Wiebe N, Tew D P, O'Brien J L, Thompson M G
Quantum Engineering Technology Labs, H. H. Wills Physics Laboratory and Department of Electrical and Electronic Engineering, University of Bristol, BS8 1FD, United Kingdom.
Quantum Architectures and Computation Group, Microsoft Research, Redmond, Washington 98052, USA.
Phys Rev Lett. 2017 Mar 10;118(10):100503. doi: 10.1103/PhysRevLett.118.100503. Epub 2017 Mar 7.
Quantum phase estimation is a fundamental subroutine in many quantum algorithms, including Shor's factorization algorithm and quantum simulation. However, so far results have cast doubt on its practicability for near-term, nonfault tolerant, quantum devices. Here we report experimental results demonstrating that this intuition need not be true. We implement a recently proposed adaptive Bayesian approach to quantum phase estimation and use it to simulate molecular energies on a silicon quantum photonic device. The approach is verified to be well suited for prethreshold quantum processors by investigating its superior robustness to noise and decoherence compared to the iterative phase estimation algorithm. This shows a promising route to unlock the power of quantum phase estimation much sooner than previously believed.
量子相位估计是许多量子算法中的一个基本子程序，包括肖尔因式分解算法和量子模拟。然而，到目前为止，研究结果对其在近期、非容错量子设备上的实用性提出了质疑。在此，我们报告实验结果，表明这种直觉不一定正确。我们实现了一种最近提出的用于量子相位估计的自适应贝叶斯方法，并将其用于在硅量子光子器件上模拟分子能量。通过研究该方法与迭代相位估计算法相比对噪声和退相干具有更强的鲁棒性，验证了该方法非常适合阈值前量子处理器。这表明了一条比之前认为的更早释放量子相位估计能力的有前景的途径。
