Entanglement is one of the physical properties of quantum systems responsible for the computational hardness of simulating quantum systems. But while the runtime of specific algorithms, notably tensor network algorithms, explicitly depends on the amount of entanglement in the system, it is unknown whether this connection runs deeper and entanglement can also cause inherent, algorithm-independent complexity. In this work, we quantitatively connect the entanglement present in certain quantum systems to the computational complexity of simulating those systems. Moreover, we completely characterize the entanglement and complexity as a function of a system parameter. Specifically, we consider the task of simulating single-qubit measurements of $k$--regular graph states on $n$ qubits. We show that, as the regularity parameter is increased from $1$ to $n-1$, there is a sharp transition from an easy regime with low entanglement to a hard regime with high entanglement at $k=3$, and a transition back to easy and low entanglement at $k=n-3$. As a key technical result, we prove a duality for the simulation complexity of regular graph states between low and high regularity.
翻译:缠绕是量子系统中对模拟量子系统的计算硬度负责的物理特性之一。 但是,尽管特定算法运行的时间,特别是高频网络算法的运行时间明确取决于系统中的纠缠程度,但不清楚这种连接是否更深,纠缠是否也会造成内在的、不依赖算法的复杂程度。在这项工作中,我们从数量上将某些量子系统中存在的缠绕与模拟这些系统的计算复杂度联系起来。此外,我们完全将纠缠和复杂性定性为系统参数的一个函数。具体地说,我们考虑模拟以美元平方位计算的美元-普通图形状态的单方位测量值。我们表明,由于常规参数从1美元增加到1美元-美元,因此,从一个轻离心的简单系统向以美元=3美元高度缠绕的硬系统急剧转换。此外,我们完全把纠缠和复杂程度归为以$k=n-3美元-3美元的系统参数的一个函数。我们发现,一个关键的技术结果是,在常规的复杂程度之间,我们证明了一种经常性的双重性。