Time-Sliced Quantum Circuit Partitioning for Modular Architectures

TL;DR

This paper introduces a time-sliced partitioning heuristic for quantum circuits that leverages modular architectures, significantly reducing non-local communication overhead compared to static mapping methods.

Contribution

It presents a novel, computationally tractable heuristic for quantum circuit partitioning that optimizes mappings over time slices in modular quantum architectures.

Findings

Reduces non-local communication overhead by up to 89.8%.

Outperforms static mapping baseline in quantum circuit partitioning.

Provides a scalable approach suitable for larger quantum systems.

Abstract

Current quantum computer designs will not scale. To scale beyond small prototypes, quantum architectures will likely adopt a modular approach with clusters of tightly connected quantum bits and sparser connections between clusters. We exploit this clustering and the statically-known control flow of quantum programs to create tractable partitioning heuristics which map quantum circuits to modular physical machines one time slice at a time. Specifically, we create optimized mappings for each time slice, accounting for the cost to move data from the previous time slice and using a tunable lookahead scheme to reduce the cost to move to future time slices. We compare our approach to a traditional statically-mapped, owner-computes model. Our results show strict improvement over the static mapping baseline. We reduce the non-local communication overhead by 89.8\% in the best case and by 60.9\% on average. Our techniques, unlike many exact solver methods, are computationally tractable.