Optimal Layout Synthesis for Quantum Computing

• URL: http://arxiv.org/abs/2007.15671v1
• Date: Thu, 30 Jul 2020 18:05:56 GMT
• Title: Optimal Layout Synthesis for Quantum Computing
• Authors: Bochen Tan and Jason Cong
• Abstract summary: layout synthesis, which transforms quantum programs to meet hardware limitations, is a crucial step in the realization of quantum computing. We present two synthesizers, one optimal and one approximate but nearly optimal. The key to this success is a more efficient spacetime-based variable encoding of the layout synthesis problem as a mathematical programming problem.
• Score: 9.530683922512873
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent years have witnessed the fast development of quantum computing. Researchers around the world are eager to run larger and larger quantum algorithms that promise speedups impossible to any classical algorithm. However, the available quantum computers are still volatile and error-prone. Thus, layout synthesis, which transforms quantum programs to meet these hardware limitations, is a crucial step in the realization of quantum computing. In this paper, we present two synthesizers, one optimal and one approximate but nearly optimal. Although a few optimal approaches to this problem have been published, our optimal synthesizer explores a larger solution space, thus is optimal in a stronger sense. In addition, it reduces time and space complexity exponentially compared to some leading optimal approaches. The key to this success is a more efficient spacetime-based variable encoding of the layout synthesis problem as a mathematical programming problem. By slightly changing our formulation, we arrive at an approximate synthesizer that is even more efficient and outperforms some leading heuristic approaches, in terms of additional gate cost, by up to 100%, and also fidelity by up to 10x on a comprehensive set of benchmark programs and architectures. For a specific family of quantum programs named QAOA, which is deemed to be a promising application for near-term quantum computers, we further adjust the approximate synthesizer by taking commutation into consideration, achieving up to 75% reduction in depth and up to 65% reduction in additional cost compared to the tool used in a leading QAOA study.

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