Practical error analysis is essential for the design, optimization, and evaluation of Noisy Intermediate-Scale Quantum(NISQ) computing. However, bounding errors in quantum programs is a grand challenge, because the effects of quantum errors depend on exponentially large quantum states. In this work, we present Gleipnir, a novel methodology toward practically computing verified error bounds in quantum programs. Gleipnir introduces the $(\hat\rho,\delta)$-diamond norm, an error metric constrained by a quantum predicate consisting of the approximate state $\hat\rho$ and its distance $\delta$ to the ideal state $\rho$. This predicate $(\hat\rho,\delta)$ can be computed adaptively using tensor networks based on the Matrix Product States. Gleipnir features a lightweight logic for reasoning about error bounds in noisy quantum programs, based on the $(\hat\rho,\delta)$-diamond norm metric. Our experimental results show that Gleipnir is able to efficiently generate tight error bounds for real-world quantum programs with 10 to 100 qubits, and can be used to evaluate the error mitigation performance of quantum compiler transformations.
翻译:实际错误分析是设计、 优化和评估 Noisy 中级量子( NASQ) 计算的关键。 然而, 量子方案中的界限错误是一个巨大的挑战, 因为量子错误的影响取决于指数型大量子状态。 在此工作中, 我们提出Gleipnir, 这是在量子方案中实际计算经核实的错误界限的新方法。 Gleipnir 引入了$( hat\rho,\delta) 和 diamon 标准, 由量子基底值限制的错误衡量标准, 由大约的 $\ hat\ rho$及其与理想状态的距离 $\delta$\delta$来限制。 这个前提值 $( hat\rho,\delta) 可以使用基于 母体产品国的 Exgorm 网络进行适应性计算 。 Gleipnir 以 $ (\\\\\\\ rho,\ delta) $- dimond 标准衡量。 我们的实验结果表明, Gleipnir 能够有效地生成真实世界量度变制程序的精确, 10 和 使用 度 度的计算。