Simulating the Sycamore quantum supremacy circuits

TL;DR

This paper introduces an efficient tensor network simulation method for quantum circuits, successfully generating high-fidelity samples from Google's Sycamore circuits using modest computational resources.

Contribution

A novel tensor network approach that significantly improves classical simulation efficiency for large quantum circuits like Sycamore.

Findings

Generated one million correlated bitstrings with high fidelity

Achieved higher XEB fidelity than Google's quantum supremacy experiments

Demonstrated simulation with only 60 GPUs

Abstract

We propose a general tensor network method for simulating quantum circuits. The method is massively more efficient in computing a large number of correlated bitstring amplitudes and probabilities than existing methods. As an application, we study the sampling problem of Google's Sycamore circuits, which are believed to be beyond the reach of classical supercomputers and have been used to demonstrate quantum supremacy. Using our method, employing a small computational cluster containing 60 graphical processing units (GPUs), we have generated one million correlated bitstrings with some entries fixed, from the Sycamore circuit with 53 qubits and 20 cycles, with linear cross-entropy benchmark (XEB) fidelity equals 0.739, which is much higher than those in Google's quantum supremacy experiments.