Performance of Superconducting Quantum Computing Chips under Different Architecture Design

TL;DR

This paper systematically evaluates how different qubit connectivity and topology in quantum processor architectures affect the performance of quantum algorithms, highlighting the importance of connectivity over topology.

Contribution

It offers a comprehensive quantitative analysis of various quantum processor designs, emphasizing the impact of connectivity and topology on algorithm performance.

Findings

High-performance architectures typically have large connectivity.

Topology has a weak influence on performance.

Different algorithms depend differently on connectivity and topology.

Abstract

Existing and near-term quantum computers can only perform two-qubit gates between physically connected qubits. Research has been done on compilers to rewrite quantum programs to match hardware constraints. However, the quantum processor architecture, in particular the qubit connectivity and topology, still lacks enough discussion, while it potentially has a huge impact on the performance of the quantum algorithms. We perform a quantitative and comprehensive study on the quantum processor performance under different qubit connectivity and topology. We select ten representative design models with different connectivities and topologies from quantum architecture design space and benchmark their performance by running a set of standard quantum algorithms. It is shown that a high-performance architecture almost always comes with a design with a large connectivity, while the topology shows a weak influence on the performance in our experiment. Different quantum algorithms show different dependence on quantum chip connectivity and topologies. This work provides quantum computing researchers with a systematic approach to evaluating their processor design.