Just Like the Real Thing: Fast Weak Simulation of Quantum Computation

TL;DR

This paper introduces fast algorithms for weak simulation of quantum computers using decision diagrams, enabling more realistic and scalable emulation of quantum behavior on classical hardware.

Contribution

It presents novel decision diagram-based algorithms for weak quantum simulation, improving scalability and realism over traditional state-vector methods.

Findings

Enables simulation of larger quantum systems than previous methods

Produces statistically indistinguishable outputs from actual quantum computers

Demonstrates practical applicability through empirical validation

Abstract

Quantum computers promise significant speedups in solving problems intractable for conventional computers but, despite recent progress, remain limited in scaling and availability. Therefore, quantum software and hardware development heavily rely on simulation that runs on conventional computers. Most such approaches perform strong simulation in that they explicitly compute amplitudes of quantum states. However, such information is not directly observable from a physical quantum computer because quantum measurements produce random samples from probability distributions defined by those amplitudes. In this work, we focus on weak simulation that aims to produce outputs which are statistically indistinguishable from those of error-free quantum computers. We develop algorithms for weak simulation based on quantum state representation in terms of decision diagrams. We compare them to using state-vector arrays and binary search on prefix sums to perform sampling. Empirical validation shows, for the first time, that this enables mimicking of physical quantum computers of significant scale.