论文标题
有效验证抗浓缩的量子状态
Efficient Verification of Anticoncentrated Quantum States
论文作者
论文摘要
量子计算机的一种有希望的用法是准备量子状态,该状态模拟复杂的域,例如相关的电子波函数或复杂数据集的基本分布。考虑到算法近似值和设备缺陷,需要验证此类状态。但是,随着量子计算机的大小的增长,验证其产生的状态变得越来越有问题。已经设计了用于验证稀疏量子状态的相对高效的方法,但是密集的量子状态仍然昂贵。在这里,我提出了一种新的方法,用于估计可预备的量子状态$ $ $和经典指定的目标状态$τ$之间的保真度$ f(μ,τ)$,使用简单的量子电路和$τ$的选定振幅的fly量子经典计算(或查找)。值得注意的是,在目标方面,该方法证明了样品效率的指数量子优势,而不是任何经典方法。该方法的最简单版本对于抗浓缩的量子状态(包括许多难以经典模拟的状态),其样本成本约为$4ε^{ - 2}(1-f)dp _ {\ text {coll}} $,其中$ $是$ d $ $ d $ $ d $的精确性,其中$ d $是$ d $ $ d的$ hilbert Specce and $ d $。 $ p _ {\ text {coll}} $是目标分布的碰撞概率。我还提出了该方法的更复杂的版本,该版本使用任何有效的准备且良好的量子状态作为重要性采样器,以进一步减少所需的$μ$的副本数量。尽管仍然存在一些挑战,但这项工作朝着对量子处理器产生的复杂状态的可扩展验证迈出了重要一步。
A promising use of quantum computers is to prepare quantum states that model complex domains, such as correlated electron wavefunctions or the underlying distribution of a complex dataset. Such states need to be verified in view of algorithmic approximations and device imperfections. As quantum computers grow in size, however, verifying the states they produce becomes increasingly problematic. Relatively efficient methods have been devised for verifying sparse quantum states, but dense quantum states have remained costly to verify. Here I present a novel method for estimating the fidelity $F(μ,τ)$ between a preparable quantum state $μ$ and a classically specified target state $τ$, using simple quantum circuits and on-the-fly classical calculation (or lookup) of selected amplitudes of $τ$. Notably, in the targeted regime the method demonstrates an exponential quantum advantage in sample efficiency over any classical method. The simplest version of the method is efficient for anticoncentrated quantum states (including many states that are hard to simulate classically), with a sample cost of approximately $4ε^{-2}(1-F)dp_{\text{coll}}$ where $ε$ is the desired precision of the estimate, $d$ is the dimension of the Hilbert space in which $μ$ and $τ$ reside, and $p_{\text{coll}}$ is the collision probability of the target distribution. I also present a more sophisticated version of the method, which uses any efficiently preparable and well-characterized quantum state as an importance sampler to further reduce the number of copies of $μ$ needed. Though some challenges remain, this work takes a significant step toward scalable verification of complex states produced by quantum processors.