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arXiv:2403.10964 · Electronic Proceedings in Theoretical Computer Science

Procedurally Optimised ZX-Diagram Cutting for Efficient T-Decomposition in Classical Simulation

Matthew Sutcliffe, Aleks Kissinger

Published Aug 9, 2024• 4 citations
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Abstract

A quantum circuit may be strongly classically simulated with the aid of ZX-calculus by decomposing its $t$ T-gates into a sum of $2^{\alpha t}$ classically computable stabiliser terms. In this paper, we introduce a general procedure to find an optimal pattern of vertex cuts in a ZX-diagram to maximise its T-count reduction at the cost of the fewest cuts. Rather than reducing a Clifford+T diagram based on a fixed routine of decomposing its T-gates directly (as is the conventional approach), we focus instead on taking advantage of certain patterns and structures common to such circuits to, in effect, design by automatic procedure an arrangement of spider decompositions that is optimised for the particular circuit. In short, this works by assigning weights to vertices based on how many T-like gates they are blocking from fusing/cancelling and then appropriately propagating these weights through any neighbours which are then blocking weighted vertices from fusing, and so on. Ultimately, this then provides a set of weightings on relevant nodes, which can then each be cut, starting from the highest weighted down. While this is a heuristic approach, we show that, for circuits small enough to verify, this method achieves the most optimal set of cuts possible $71\%$ of the time. Furthermore, there is no upper bound for the efficiency achieved by this method, allowing, in principle, an effective decomposition efficiency $\alpha\rightarrow0$ for highly structured circuits. Even applied to random pseudo-structured circuits (produced from CNOTs, phase gates, and Toffolis), we record the number of stabiliser terms required to reduce all T-gates, via our method as compared to that of the more conventional T-decomposition approaches (namely \cite{kissinger21}, with $\alpha\approx0.47$), and show consistent improvements of orders of magnitude, with an effective efficiency $0.1\lesssim\alpha\lesssim0.2$.

DOI
10.4204/eptcs.406.3

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A quantum circuit may be strongly classically simulated with the aid of ZX-calculus by decomposing its ttt T-gates into a sum of 2αt2^{\alpha t}2αt classically computable stabiliser terms. In this paper, we introduce a general procedure to find an optimal pattern of vertex cuts in a ZX-diagram to maximise its T-count reduction at the cost of the fewest cuts. Rather than reducing a Clifford+T diagram based on a fixed routine of decomposing its T-gates directly (as is the conventional approach), we focus instead on taking advantage of certain patterns and structures common to such circuits to, in effect, design by automatic procedure an arrangement of spider decompositions that is optimised for the particular circuit. In short, this works by assigning weights to vertices based on how many T-like gates they are blocking from fusing/cancelling and then appropriately propagating these weights through any neighbours which are then blocking weighted vertices from fusing, and so on. Ultimately, this then provides a set of weightings on relevant nodes, which can then each be cut, starting from the highest weighted down. While this is a heuristic approach, we show that, for circuits small enough to verify, this method achieves the most optimal set of cuts possible 71%71\%71% of the time. Furthermore, there is no upper bound for the efficiency achieved by this method, allowing, in principle, an effective decomposition efficiency α→0\alpha\rightarrow0α→0 for highly structured circuits. Even applied to random pseudo-structured circuits (produced from CNOTs, phase gates, and Toffolis), we record the number of stabiliser terms required to reduce all T-gates, via our method as compared to that of the more conventional T-decomposition approaches (namely \cite{kissinger21}, with α≈0.47\alpha\approx0.47α≈0.47), and show consistent improvements of orders of magnitude, with an effective efficiency 0.1≲α≲0.20.1\lesssim\alpha\lesssim0.20.1≲α≲0.2.
It is known that a quantum circuit may be simulated with classical hardware via stabilizer state (T-)decomposition in [Formula: see text] time, given t non-Clifford gates and a decomposition efficiency [Formula: see text]. The past years have seen a number of papers presenting new decompositions of lower [Formula: see text] to reduce this runtime and enable simulation of ever larger circuits. More recently, it has been demonstrated that well-placed applications of apparently weaker (higher [Formula: see text]) decompositions can in fact result in better overall efficiency when paired with the circuit simplification strategies of ZX-calculus. In this work, we take the most generalized T-decomposition (namely vertex cutting), which achieves a poor efficiency of [Formula: see text] and identify common structures to which applying this can, after simplification via ZX-calculus rewriting, yield very strong effective efficiencies [Formula: see text]. By taking into account this broader scope of the ZX-diagram and incorporating the simplification facilitated by the well-motivated cuts, we derive a handful of efficient T-decompositions whose applicabilities are relatively frequent. In benchmarking these new ‘dynamic’ decompositions against the existing alternatives, we observe a significant reduction in overall [Formula: see text] and hence overall runtime for classical simulation, particularly for certain common circuit classes.
In this paper, we introduce a technique for contracting (i.e. numerically evaluating) ZX-diagrams whose complexity scales with their rank-width, a graph parameter that behaves nicely under ZX rewrite rules. Given a rank-decomposition of width RRR, our method simulates a graph-like ZX-diagram in O~(4R)Õ(4^R)O~(4R) time. Applied to classical simulation of quantum circuits, it is no slower than either naive state vector simulation or stabiliser decompositions with α=0.5α= 0.5α=0.5, and in practice can be significantly faster for suitably chosen rank-decompositions. Since finding optimal rank-decompositions is NP-hard, we introduce heuristics that produce good decompositions in practice. We benchmark our simulation routine against Quimb, a popular tensor contraction library, and observe substantial reductions in floating-point operations (often by several orders of magnitude) for random and structured non-Clifford circuits as well as random ZX-diagrams.
Abstract We introduce an enhanced technique for strong classical simulation of quantum circuits which combines the ‘sum-of-stabilisers’ method with an automated simplification strategy based on the ZX-calculus. Recently it was shown that quantum circuits can be classically simulated by expressing the non-stabiliser gates in a circuit as magic state injections and decomposing them in chunks of 2–6 states at a time, obtaining sums of (efficiently-simulable) stabiliser states with many fewer terms than the naive approach. We adapt these techniques from the original setting of Clifford circuits with magic state injection to generic ZX-diagrams and show that, by interleaving this ‘chunked’ decomposition with a ZX-calculus-based simplification strategy, we can obtain stabiliser decompositions that are many orders of magnitude smaller than existing approaches. We illustrate this technique to perform exact norm calculations (and hence strong simulation) on the outputs of random 50- and 100-qubit Clifford + T circuits with up to 70 T-gates as well as a family of hidden shift circuits previously considered by Bravyi and Gosset with over 1000 T-gates.
In the near term, programming quantum computers will remain severely limited by low quantum volumes.Therefore, it is desirable to implement quantum circuits with the fewest resources possible.For the common Clifford+T circuits, most research is focused on reducing the number of T gates, since they are an order of magnitude more expensive than Clifford gates in quantum error corrected encoding schemes.However, this optimization sometimes leads to more 2-qubit gates, which, even though they are less expensive in terms of fault-tolerance, contribute significantly to the overall circuit cost.Approaches based on the ZX-calculus have recently gained some popularity in the field, but reduction of 2-qubit gates is not their focus.In this work, we present an alternative for improving 2-qubit gate count of a quantum circuit with the ZX-calculus by using heuristics in ZX-diagram simplification.Our approach maintains the good reduction of the T gate count provided by other strategies based on ZX-calculus, thus serving as an extension for other optimization algorithms.Our results show that combining the available ZX-calculus-based optimizations with our algorithms can reduce the number of 2-qubit gates by as much as 40 % compared to current approaches using ZXcalculus.Additionally, we improve the results of the best currently available optimization technique of Nam et.al [22] for some circuits by up to 15 %.
We present a method for reducing the number of non-Clifford quantum gates, in particularly T-gates, in a circuit, an important task for efficiently implementing fault-tolerant quantum computations. This method matches or beats previous approaches to ancillae-free T-count reduction on the majority of our benchmark circuits, in some cases yielding up to 50% improvement. Our method begins by representing the quantum circuit as a ZX-diagram, a tensor networklike structure that can be transformed and simplified according to the rules of the ZX-calculus. We then extend a recent simplification strategy with a different ingredient, phase gadgetization, which we use to propagate non-Clifford phases through a ZX-diagram to find nonlocal cancellations. Our procedure extends unmodified to arbitrary phase angles and to parameter elimination for variational circuits. Finally, our optimization is self-checking, in the sense that the simplification strategy we propose is powerful enough to independently validate equality of the input circuit and the optimized output circuit. We have implemented the routines of this paper in the open-source library pyzx.
Recent developments in classical simulation of quantum circuits make use of clever decompositions of chunks of magic states into sums of efficiently simulable stabiliser states. We show here how, by considering certain non-stabiliser entangled states which have more favourable decompositions, we can speed up these simulations. This is made possible by using the ZX-calculus, which allows us to easily find instances of these entangled states in the simplified diagram representing the quantum circuit to be simulated. We additionally find a new technique of partial stabiliser decompositions that allow us to trade magic states for stabiliser terms. With this technique we require only 2αt2^{αt}2αt stabiliser terms, where α≈0.396α\approx 0.396α≈0.396, to simulate a circuit with T-count ttt. This matches the ααα found by Qassim et al., but whereas they only get this scaling in the asymptotic limit, ours applies for a circuit of any size. Our method builds upon a recently proposed scheme for simulation combining stabiliser decompositions and optimisation strategies implemented in the software QuiZX. With our techniques we manage to reliably simulate 50-qubit 1400 T-count hidden shift circuits in a couple of minutes on a consumer laptop.