2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms

Lingling Lao, Dan Browne

Published 2021-08-04Version 1

Simulating quantum systems is one of the most important potential applications of quantum computers to demonstrate its advantages over classical algorithms. The high-level circuit defining the simulation needs to be transformed into one that compiles with hardware limitations such as qubit connectivity and hardware gate set. Many techniques have been developed to efficiently compile quantum circuits while minimizing compilation overhead. However, general-purpose quantum compilers work at the gate level and have little knowledge of the mathematical properties of quantum applications, missing further optimization opportunities. In this work, we exploit one application-level property in Hamiltonian simulation, which is, the flexibility of permuting different operators in the Hamiltonian (no matter whether they commute). We develop a compiler, named 2QAN, to optimize quantum circuits for 2-local qubit Hamiltonian simulation problems, a framework which includes the important quantum approximate optimization algorithm (QAOA). In particular, we propose permutation-aware qubit mapping, qubit routing, gate optimization and scheduling techniques to minimize the compilation overhead. We evaluate 2QAN by compiling three applications (up to 50 qubits) onto three quantum computers that have different qubit topologies and hardware two-qubit gates, namely, Google Sycamore, IBMQ Montreal and Rigetti Aspen. Compared to state-of-the-art quantum compilers, 2QAN can reduce the number of inserted SWAP gates by up to 11.5X, reduce overhead in hardware gate count by up to 30.7X, and reduce overhead in circuit depth by up to 21X. This significant overhead reduction will help improve application performance. Experimental results on the Montreal device demonstrate that benchmarks compiled by 2QAN achieve highest fidelity.