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arXiv:2509.08658 · Quantum

Simulating magic state cultivation with few Clifford terms

Kwok Ho Wan, Zhenghao Zhong, Ainhoa Zapirain

Published Jun 12, 2026• 0 citations
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Abstract

Building upon Wan, Zhong (2025) \cite{wan2025cuttingstabiliserdecompositionsmagic} we present a few methods on how to simulate the non-Clifford d = 5 magic state cultivation circuits\cite{gidney2024magicstatecultivationgrowing} with a sum of ≈ 8 Clifford ZX-diagrams on average, at 0.1 % noise. Compared to a magic cat state stabiliser decomposition of all 53 non-Clifford spiders ( 6,377,292 terms required), this is more than 7 × 10 5 times reduction in the number of terms. Our stabiliser decomposition has the advantage of representing the final non-Clifford state (in light of circuit errors) as a sum of Clifford ZX-diagrams. This will be useful in simulating the escape stage of magic state cultivation, where one needs to port the resultant state of cultivation into a larger Clifford circuit with many more qubits. Still, it's necessary to only track ≈ 8 Clifford terms. Our result sheds light on the simulability of operationally relevant, high T -count quantum circuits with some internal structure.Finally, we provide numerical results for full non-Clifford stabiliser rank simulation based on t s i m along with optimisations using our cutting decompositions. Nearly 4 × 10 6 shots per second can be obtained on a laptop for the smaller d = 3 circuits at uniform circuit level noise p = 0.0005 , making it only ∼ 1.1 times slower than its (circuit-unspecific and un-optimised) fully Clifford proxy simulation via s t i m using S gates.

DOI
10.22331/q-2026-06-12-2134

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Building upon Wan, Zhong (2025) \cite{wan2025cuttingstabiliserdecompositionsmagic} we present a few methods on how to simulate the non-Clifford d = 5 magic state cultivation circuits\cite{gidney2024magicstatecultivationgrowing} with a sum of ≈ 8 Clifford ZX-diagrams on average, at 0.1 % noise. Compared to a magic cat state stabiliser decomposition of all 53 non-Clifford spiders ( 6,377,292 terms required), this is more than 7 × 10 5 times reduction in the number of terms. Our stabiliser decomposition has the advantage of representing the final non-Clifford state (in light of circuit errors) as a sum of Clifford ZX-diagrams. This will be useful in simulating the escape stage of magic state cultivation, where one needs to port the resultant state of cultivation into a larger Clifford circuit with many more qubits. Still, it's necessary to only track ≈ 8 Clifford terms. Our result sheds light on the simulability of operationally relevant, high T -count quantum circuits with some internal structure.Finally, we provide numerical results for full non-Clifford stabiliser rank simulation based on t s i m along with optimisations using our cutting decompositions. Nearly 4 × 10 6 shots per second can be obtained on a laptop for the smaller d = 3 circuits at uniform circuit level noise p = 0.0005 , making it only ∼ 1.1 times slower than its (circuit-unspecific and un-optimised) fully Clifford proxy simulation via s t i m using S gates.
We apply the cutting stabiliser decomposition techniques [arXiv:2403.10964] to the quantum states generated from magic state cultivation [arXiv:2409.17595], post-selected upon all +1+1+1 measured values for simplicity. The resultant states to the d=3d=3d=3 and d=5d=5d=5 variant magic state cultivation circuits can be expressed as a sum of 444 and 888 Clifford ZX-digrams respectively. Modifications to existing ZX-calculus stabiliser decomposition methods may enable better simulation of non-Clifford circuits containing a moderate number of TTT gates in the context of quantum error correction.
Developing space- and time-efficient logical magic state preparation protocols will likely be an essential step towards building a large-scale fault-tolerant quantum computer. Motivated by this need, we introduce a scalable method for simulating logical magic state preparation protocols under the standard circuit-level noise model. When applied to protocols based on code switching, magic state cultivation, and magic state distillation, our method yields a complexity polynomial in (i) the number of qubits and (ii) the non-stabilizerness, e.g., stabilizer rank or Pauli rank, of the target encoded magic state. The efficiency of our simulation method is rooted in a curious fact: every circuit-level Pauli error in these protocols propagates to a Clifford error at the end. This property is satisfied by a large family of protocols, including those that repeatedly measure a transversal Clifford that squares to a Pauli. We provide a proof-of-principle numerical simulation that prepares a magic state using such logical Clifford measurements. Our work enables practical simulation of logical magic state preparation protocols without resorting to approximations or resource-intensive state-vector simulations.
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.
Magic state cultivation prepares high-fidelity magic states at low expected space-time costs; however, the exact performance of some schemes is unsettled due to the difficulty in simulating non-Clifford circuits. Here, we use matrix-product states (MPS) based methods to compute the exact performance of two types of fold-transversal cultivation schemes: (i) the Sahay et al method based on the regular surface code S gate, and (ii) a method we propose based on a partially fault-tolerant fold-transversal S gate. We show that for the former protocol at d=5d=5d=5, the ∣T⟩|T\rangle∣T⟩ output reaches similar logical error rates to the ∣S⟩|S\rangle∣S⟩ output, traditionally used as a cheap full Clifford proxy. This contrasts with the ∼10×\sim10\times∼10× discrepancy reported for the d=5d=5d=5 colour-code scheme of Gidney et al. We also find that our new d=5d=5d=5 scheme has ∼1.3×\sim1.3\times∼1.3× lower expected space-time cost while still reaching 10−910^{-9}10−9 logical error rate. We show that MPS and Clifford-augmented MPS (CAMPS) perform on par with or even better than the recently introduced near-Clifford simulator Clifft on the hardest d=5d=5d=5 regular surface code scheme. Additionally, to speed up simulation, we propose a new pre-screening method based on simple Pauli propagation, lowering by up to three orders of magnitude the required number of exact simulations, and use several simulator-agnostic sampling methods such as subset sampling.
Exact classical simulation of fault-tolerant quantum circuits remains limited by a tradeoff between exponential state vector scaling, exponential TTT-count scaling in stabilizer-rank approaches, and per-shot tracking overhead in sparse generalized stabilizer simulators. In this work, we introduce Clifft, an open-source simulator that shifts the dominant exponential cost from the total qubit count to a dynamic active subspace by factoring the quantum state into an offline Clifford frame, an online Pauli frame, and a dynamically sized active state vector. This architecture resolves deterministic Clifford coordinate transformations ahead of time, generalizing Stim's compile-once, sample-many execution model to circuits with non-Clifford operations. Consequently, exponential simulation costs are determined by the peak active virtual dimension, which expands during non-Clifford operations and contracts during measurements. Clifft remains within a constant factor of standard tools in the pure-Clifford and non-Clifford limits, while delivering up to orders-of-magnitude throughput gains over GPU-accelerated near-Clifford simulators on low-magic fault-tolerant benchmarks. Executing on commodity CPUs and exposing a Stim-like API, Clifft enables, to our knowledge, the first exact end-to-end simulation of magic state cultivation including the escape stage, over hundreds of billions of shots. These simulations show that escape-stage failures suppress the discrepancy between the true TTT-gate circuit and its SSS-proxy at low decoder-gap thresholds, while at high thresholds the full-protocol behavior approaches the larger discrepancy observed in the cultivation stages alone.
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.