Return
Optimality Study of Existing Quantum Computing Layout Synthesis Tools
DOI:10.1109/TC.2020.3009140.png)
Abstract
En 中文
Layout synthesis, an important step in quantum computing, processes quantum circuits to satisfy device layout constraints. In this paper, we construct QUEKO benchmarks for this problem, which have known optimal depths and gate counts. We use QUEKO to evaluate the optimality of current layout synthesis tools, including Cirq from Google, Qiskit from IBM, tjketi from Cambridge Quantum Computing, and a recent academic work. To our surprise, despite over a decade of research and development by academia and industry on compilation and synthesis for quantum circuits, we are still able to demonstrate large optimality gaps: 1.5-12x on average on a smaller device and 5-45x on average on a larger device. This suggests substantial room for improvement of the efficiency of quantum computer by better layout synthesis tools. Finally, we also prove the NP-completeness of the layout synthesis problem for quantum computing. We have made the QUEKO benchmarks open-source.
Keywords:
Quantum computing
layout
placement and routing
scheduling
allocation
optimality
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.8
Papers:
5.3K
Citations:
9.8K

