Year: 2020
Type: conference-paper
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.
Authors: Stefan Hillmich, Igor L. Markov, Robert Wille
Institutions: Johannes Kepler University of Linz, University of Michigan
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3045772113