Entanglement and circuit complexity in finite-depth random linear optical networks
Laura Shou, Joseph T. Iosue, Yu-Xin Wang, Victor Galitski, Alexey V. Gorshkov

TL;DR
This paper investigates how entanglement and circuit complexity evolve in finite-depth random linear optical networks, providing bounds and scaling laws for entanglement growth and circuit complexity in various circuit geometries.
Contribution
It establishes bounds on entanglement growth and circuit complexity in random linear optical networks, revealing diffusive scaling with circuit depth and high-fidelity approximate implementations.
Findings
Entanglement grows at most diffusively with circuit depth in brickwall circuits.
Bounds are proven for entanglement in arbitrary circuit geometries.
Robust circuit complexity scales at most diffusively in depth with high probability.
Abstract
We study the growth of entanglement and circuit complexity in random passive linear optical networks as a function of the circuit depth. For entanglement dynamics, we start with an initial Gaussian state with all modes squeezed. For random brickwall circuits, we show that entanglement, as measured by the R\'enyi-2 entropy, grows at most diffusively as a function of the depth. In the other direction, for arbitrary circuit geometries we prove bounds on depths which ensure the average subsystem entanglement reaches within a constant factor of the maximum value in all subsystems, and bounds which ensure closeness of the random linear optical unitary to a Haar random unitary in Wasserstein distance. We also consider robust circuit complexity for random one-dimensional brickwall circuits, as measured by the minimum number of gates required in any circuit that approximately…
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