发表机构
Joint Quantum Institute, Department of Physics, NIST/University of Maryland; Joint Center for Quantum Information and Computer Science, NIST/University of Maryland（联合量子研究所，马里兰大学物理系; 量子信息与计算科学联合中心，马里兰大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文证明随机超立方体线性光学网络在对数深度下产生近最大纠缠，低于该深度则无纠缠，并与高斯玻色采样硬度进展相关联。
AI 中文摘要
我们研究了随机超立方体线性光学网络中对数深度下的纠缠相变。从所有模式都被压缩的初始高斯态出发，我们证明了在$n$个模式上的随机超立方体线性光学网络，在电路深度为$\Theta(\log n)$时，能在所有子系统中产生与最大值相差常数因子的系综平均子系统纠缠。在深度低于$\log_2n$时，存在一个广泛的子系统没有纠缠。对数深度下的纠缠产生可以与近期在超立方体网络中实现$O(\log n)$深度平均情况采样硬度的高斯玻色采样进展相比较。
英文摘要
We study an entanglement transition at logarithmic depth in random hypercube linear optical networks. Starting from an initial Gaussian state with all modes squeezed, we prove that random hypercube linear optical networks on $n$ modes generate ensemble-averaged subsystem entanglement within a constant factor of its maximum in all subsystems at circuit depth $Θ(\log n)$. Below depth $\log_2n$, there is an extensive subsystem with no entanglement. The entanglement generation in logarithmic depth can be compared to recent progress towards $O(\log n)$ depth average-case sampling hardness for Gaussian boson sampling in a hypercube network.
Comments16 pages, 4 figures
