PyZX: Large Scale Automated Diagrammatic Reasoning

Kissinger, Aleks; Wetering, John van de

doi:10.4204/eptcs.318.14

Cited by 83 publications

(74 citation statements)

References 17 publications

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“…The pattern optimisation algorithm of Theorem 4.21 and the circuit extraction algorithm of Section 5 have been implemented in the ZX-calculus rewriting system PyZX 5 [38]. The reduction in non-Clifford gates using this method matches the state-of-the-art for ancillae-free circuits [39] at the time of development.…”

Section: Discussionmentioning

confidence: 99%

There and back again: A circuit extraction tale

Backens

Miller-Bakewell

Felice

et al. 2021

Quantum

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Translations between the quantum circuit model and the measurement-based one-way model are useful for verification and optimisation of quantum computations. They make crucial use of a property known as gflow. While gflow is defined for one-way computations allowing measurements in three different planes of the Bloch sphere, most research so far has focused on computations containing only measurements in the XY-plane. Here, we give the first circuit-extraction algorithm to work for one-way computations containing measurements in all three planes and having gflow. The algorithm is efficient and the resulting circuits do not contain ancillae. One-way computations are represented using the ZX-calculus, hence the algorithm also represents the most general known procedure for extracting circuits from ZX-diagrams. In developing this algorithm, we generalise several concepts and results previously known for computations containing only XY-plane measurements. We bring together several known rewrite rules for measurement patterns and formalise them in a unified notation using the ZX-calculus. These rules are used to simplify measurement patterns by reducing the number of qubits while preserving both the semantics and the existence of gflow. The results can be applied to circuit optimisation by translating circuits to patterns and back again.

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Section: Discussionmentioning

confidence: 99%

There and back again: A circuit extraction tale

Backens

Miller-Bakewell

Felice

et al. 2021

Quantum

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“…To this end, we compared the performance of voqc's verified (unitary) optimizations against IBM's Qiskit compiler [Aleksandrowicz et al 2019], CQC's t⋃︀ket̃︀ [Cambridge Quantum Computing Ltd 2019;Sivarajah et al 2020], PyZX [Kissinger and van de Wetering 2020], and the optimizers presented by Nam et al [2018] and Amy et al [2013] on a set of benchmarks developed by Amy et al We find that voqc has comparable performance to all of these: it generally beats all but Nam et al in terms of both total gate count reduction and T -gate reduction, and often matches Nam et al However, our aim is not to claim superiority over these tools (after all, we have implemented a subset of the unitary optimizations available in Nam et al, and Qiskit and t⋃︀ket̃︀ contain many features that Nam et al does not), but to demonstrate that the optimizations we have implemented are on par with existing unverified tools.…”

Section: Experimental Evaluationmentioning

confidence: 99%

“…Of course, both compiler and by-hand optimizations will inevitably have bugs. As evidence of the former, Kissinger and van de Wetering [2020] discovered mistakes in the optimized outputs produced by the circuit optimizer of Nam et al [2018], and Nam et al themselves found that the optimization library they compared against (Amy et al [2013]) sometimes produced incorrect results. Likewise, Amy [2018] discovered an optimizer they had recently developed produced buggy results .…”

Section: Introductionmentioning

confidence: 99%

A verified optimizer for Quantum circuits

Hietala

Rand

Hung

et al. 2021

Proc. ACM Program. Lang.

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We present VOQC, the first fully verified optimizer for quantum circuits, written using the Coq proof assistant. Quantum circuits are expressed as programs in a simple, low-level language called SQIR, a simple quantum intermediate representation, which is deeply embedded in Coq. Optimizations and other transformations are expressed as Coq functions, which are proved correct with respect to a semantics of SQIR programs. SQIR uses a semantics of matrices of complex numbers, which is the standard for quantum computation, but treats matrices symbolically in order to reason about programs that use an arbitrary number of quantum bits. SQIR's careful design and our provided automation make it possible to write and verify a broad range of optimizations in VOQC, including full-circuit transformations from cutting-edge optimizers.

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“…On the other hand, quantum circuit simplification and optimization are crucial for reducing the cost of both simulations and experiments. The ongoing circuit simplification project [94] will also support better pattern matching and term rewriting system with support of ZX calculus [95]. This will allows smarter and more systematic circuit simplifications such as the ones in Refs.…”

Section: Circuit Compilation and Optimizationmentioning

confidence: 99%

Yao.jl: Extensible, Efficient Framework for Quantum Algorithm Design

Luo

Liu

Zhang

et al. 2020

Quantum

117

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We introduce Yao, an extensible, efficient open-source framework for quantum algorithm design. Yao features generic and differentiable programming of quantum circuits. It achieves state-of-the-art performance in simulating small to intermediate-sized quantum circuits that are relevant to near-term applications. We introduce the design principles and critical techniques behind Yao. These include the quantum block intermediate representation of quantum circuits, a builtin automatic differentiation engine optimized for reversible computing, and batched quantum registers with GPU acceleration. The extensibility and efficiency of Yao help boost innovation in quantum algorithm design.

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PyZX: Large Scale Automated Diagrammatic Reasoning

Cited by 83 publications

References 17 publications

There and back again: A circuit extraction tale

There and back again: A circuit extraction tale

A verified optimizer for Quantum circuits

Yao.jl: Extensible, Efficient Framework for Quantum Algorithm Design

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