An Enhanced Hybrid HHL Algorithm
arxiv(2024)
摘要
We present a classical enhancement to improve the accuracy of the Hybrid
variant (Hybrid HHL) of the quantum algorithm for solving liner systems of
equations proposed by Harrow, Hassidim, and Lloyd (HHL). We achieve this by
using higher precision quantum estimates of the eigenvalues relevant to the
linear system, and an enhanced classical processing step to guide the
eigenvalue inversion part of Hybrid HHL. We show that eigenvalue estimates with
just two extra bits of precision results in tighter error bounds for our
Enhanced Hybrid HHL compared to HHL. We also show that our enhancement reduces
the error of Hybrid HHL by an average of 57 percent on an ideal quantum
processor for a representative sample of 2x2 systems. On IBM Hanoi and IonQ
Aria-1 hardware, we see that the error of Enhanced Hybrid HHL algorithm is on
average 13 percent and 20 percent (respecitvely) less than that of HHL for a
similar set of 2x2 systems. Finally, we use simulated eigenvalue estimates to
perform an inversion of a 4x4 matrix on IonQ Aria-1 with a fidelity of 0.61. To
our knowledge this is the largest HHL implementation with a fidelity greater
than 0.5.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要