Graph-theoretic Simplification of Quantum Circuits with the ZX-calculus

Ross Duncan1,2, Aleks Kissinger3, Simon Perdrix4, and John van de Wetering5

1University of Strathclyde, 26 Richmond Street, Glasgow G1 1XH, UK
2Cambridge Quantum Computing Ltd, 9a Bridge Street, Cambridge CB2 1UB, UK
3Department of Computer Science, University of Oxford
4CNRS LORIA, Inria-MOCQUA, Université de Lorraine, F 54000 Nancy, France
5Institute for Computing and Information Sciences, Radboud University Nijmegen

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We present a completely new approach to quantum circuit optimisation, based on the ZX-calculus. We first interpret quantum circuits as ZX-diagrams, which provide a flexible, lower-level language for describing quantum computations graphically. Then, using the rules of the ZX-calculus, we give a simplification strategy for ZX-diagrams based on the two graph transformations of local complementation and pivoting and show that the resulting reduced diagram can be transformed back into a quantum circuit. While little is known about extracting circuits from arbitrary ZX-diagrams, we show that the underlying graph of our simplified ZX-diagram always has a graph-theoretic property called generalised flow, which in turn yields a deterministic circuit extraction procedure. For Clifford circuits, this extraction procedure yields a new normal form that is both asymptotically optimal in size and gives a new, smaller upper bound on gate depth for nearest-neighbour architectures. For Clifford+T and more general circuits, our technique enables us to to `see around' gates that obstruct the Clifford structure and produce smaller circuits than naïve `cut-and-resynthesise' methods.

Quantum circuits are a de facto assembly language for quantum software. Programs are described as list of primitive operations, or gates, which are run in sequence on a quantum computer to perform a computation. Just like with classical software, there is more that one way to write a program to do the same job, and so it's important to find programs that do that job as quickly and cheaply as possible. Looking at quantum circuits just as lists of gates doesn't tell us a whole lot about what computation is being performed, or how it might be optimised. However, if we "break open" quantum gates, we see a rich graphical/algebraic structure inside called the ZX-calculus.

In this paper, we give a technique for optimising quantum circuits that first breaks the gates open to reveal a graph-like structure underneath. We then give a strategy for reducing these graphs in size without changing the computation they represent, then extracting a new, smaller circuit out of the result.

We have implemented the technique described in this paper in a Python tool called PyZX:

For a 2-minute intro to PyZX, see this YouTube video:

If that leaves you wanting more, there is also a 40-minute talk about this and more on YouTube:

► BibTeX data

► References

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Cited by

[1] Seyon Sivarajah, Silas Dilkes, Alexander Cowtan, Will Simmons, Alec Edgington, and Ross Duncan, "t|ket⟩: a retargetable compiler for NISQ devices", Quantum Science and Technology 6 1, 014003 (2020).

[2] Aleks Kissinger and John van de Wetering, "Reducing the number of non-Clifford gates in quantum circuits", Physical Review A 102 2, 022406 (2020).

[3] Prakash Murali, David C. Mckay, Margaret Martonosi, and Ali Javadi-Abhari, Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems 1001 (2020) ISBN:9781450371025.

[4] Aleks Kissinger and John van de Wetering, "Reducing T-count with the ZX-calculus", arXiv:1903.10477.

[5] Niel de Beaudrap and Dominic Horsman, "The ZX calculus is a language for surface code lattice surgery", arXiv:1704.08670.

[6] Raban Iten, Oliver Reardon-Smith, Luca Mondada, Ethan Redmond, Ravjot Singh Kohli, and Roger Colbeck, "Introduction to UniversalQCompiler", arXiv:1904.01072.

[7] Aleks Kissinger and Arianne Meijer-van de Griend, "CNOT circuit extraction for topologically-constrained quantum memories", arXiv:1904.00633.

[8] Aleks Kissinger and John van de Wetering, "PyZX: Large Scale Automated Diagrammatic Reasoning", arXiv:1904.04735.

[9] Alexander Cowtan, Silas Dilkes, Ross Duncan, Will Simmons, and Seyon Sivarajah, "Phase Gadget Synthesis for Shallow Circuits", arXiv:1906.01734.

[10] A. D. Corcoles, A. Kandala, A. Javadi-Abhari, D. T. McClure, A. W. Cross, K. Temme, P. D. Nation, M. Steffen, and J. M. Gambetta, "Challenges and Opportunities of Near-Term Quantum Computing Systems", arXiv:1910.02894.

[11] John van de Wetering and Sal Wolffs, "Completeness of the Phase-free ZH-calculus", arXiv:1904.07545.

[12] Titouan Carette, Dominic Horsman, and Simon Perdrix, "SZX-calculus: Scalable Graphical Quantum Reasoning", arXiv:1905.00041.

[13] Titouan Carette, Emmanuel Jeandel, Simon Perdrix, and Renaud Vilmart, "Completeness of Graphical Languages for Mixed States Quantum Mechanics", arXiv:1902.07143.

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The above citations are from Crossref's cited-by service (last updated successfully 2020-11-25 13:41:48) and SAO/NASA ADS (last updated successfully 2020-11-25 13:41:50). The list may be incomplete as not all publishers provide suitable and complete citation data.