Importance of Diagonal Gates in Tensor Network Simulations
AI Breakdown
Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.
Abstract
In this work, we present two techniques that tremendously increase the performance of tensor-network based quantum circuit simulations. The techniques are implemented in the QTensor package and benchmarked using Quantum Approximate Optimization Algorithm (QAOA) circuits. It allowed increasing the size and depth of QAOA circuits, which can be simulated. In particular, we increased QAOA depth p from 2 to 5 and the size of a QAOA circuit N from 180 to 244 qubits. Moreover, we increased the speed of simulations by up to 10 million times. Our work provides important insights into how various techniques can dramatically speed up the simulations of circuits.