凸顶逼近的变分量子算法

G. Androulakis, Ryan McGaha
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引用次数: 2

摘要

首先对二部Hilbert空间的纯态定义了许多纠缠测度,然后通过凸顶扩展扩展到混合态。在本文中,我们改变了一个纠缠测度的凸顶扩展,以产生一系列扩展,我们称之为$f$ - $d$扩展,对于$d \in \mathbb{N}$,其中$f:[0,1]\to [0, \infty)$是一个固定的连续函数,它只在零处消失。我们证明了对于任何这样的函数$f$和任何连续的、忠实的、非负的函数(如纠缠测度),$\mu$在有限维二部希尔伯特空间的纯态集合上,$\mu$的$f$ - $d$扩展集合检测到纠缠,即在有限维二部希尔伯特空间上的混合态$\rho$是可分的。当且仅当存在$d \in \mathbb{N}$使得应用于$\rho$的$\mu$的$f$ - $d$扩展等于零。我们引入了一种量子变分算法,旨在近似定义在纯态上的纠缠测度的$f$ - $d$扩展。然而,该算法也有它的缺点。我们表明,当用于近似特定函数$f$的Tsallis纠缠熵的$f$ - $d$扩展和足够深度的一元分析z $U(\theta)$时,该算法显示出荒芜的平台。在实践中,如果关于状态的附加信息是已知的,那么需要避免对长深度电路使用建议的ansatz。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Variational Quantum Algorithm for Approximating Convex Roofs
Many entanglement measures are first defined for pure states of a bipartite Hilbert space, and then extended to mixed states via the convex roof extension. In this article we alter the convex roof extension of an entanglement measure, to produce a sequence of extensions that we call $f$-$d$ extensions, for $d \in \mathbb{N}$, where $f:[0,1]\to [0, \infty)$ is a fixed continuous function which vanishes only at zero. We prove that for any such function $f$, and any continuous, faithful, non-negative function, (such as an entanglement measure), $\mu$ on the set of pure states of a finite dimensional bipartite Hilbert space, the collection of $f$-$d$ extensions of $\mu$ detects entanglement, i.e. a mixed state $\rho$ on a finite dimensional bipartite Hilbert space is separable, if and only if there exists $d \in \mathbb{N}$ such that the $f$-$d$ extension of $\mu$ applied to $\rho$ is equal to zero. We introduce a quantum variational algorithm which aims to approximate the $f$-$d$ extensions of entanglement measures defined on pure states. However, the algorithm does have its drawbacks. We show that this algorithm exhibits barren plateaus when used to approximate the family of $f$-$d$ extensions of the Tsallis entanglement entropy for a certain function $f$ and unitary ansatz $U(\theta)$ of sufficient depth. In practice, if additional information about the state is known, then one needs to avoid using the suggested ansatz for long depth of circuits.
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