摘要:Quantum circuit transformation (QCT, a.k.a. qubit mapping) is a critical step in quantum circuit compilation. Typically, QCT is achieved by finding an appropriate initial mapping and using SWAP gates to route the qubits such that all connectivity constraints are satisfied. The objective of QCT can be to minimise circuit size or depth. Most existing QCT algorithms prioritise minimising circuit size, potentially overlooking the impact of single-qubit gates on circuit depth. In this paper, we first point out that a single SWAP gate insertion can double the circuit depth, and then propose a simple and effective method that takes into account the impact of single-qubit gates on circuit depth. Our method can be combined with many existing QCT algorithms to optimise circuit depth. The Qiskit SABRE algorithm has been widely accepted as the state-of-the-art algorithm for optimising both circuit size and depth. We demonstrate the effectiveness of our method by embedding it in SABRE, showing that it can reduce circuit depth by up to 50% and 27% on average on, for instance, Google Sycamore and 117 real quantum circuits from MQTBench.

Joint work with Ky Dan Nguyen, Zachary Clare, and Yuan Feng.

报告人简介：Sanjiang Li received his B.Sc. and PhD in mathematics from Shaanxi Normal University in 1996 and Sichuan University in 2001. He is now a full professor in the Centre of Quantum Software & Information (QSI), Faculty of Engineering & Information Technology, University of Technology Sydney (UTS), Australia. Before joining UTS, he worked in the Computer Science and Technology Department, Tsinghua University, from September 2001 to December 2008. He was an Alexander von Humboldt research fellow at Freiburg University from January 2005 to June 2006; held a Microsoft Research Asia Young Professorship from July 2006 to June 2009; and an ARC Future Fellowship from January 2010 to December 2013.

His research interests are mainly in knowledge representation and artificial intelligence. The main objective of his previous research was to establish expressive representation formalism