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Efficient Universal Quantum Compilation: An Inverse-free Solovay-Kitaev Algorithm

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arxiv 2112.02040 v1 pith:OHLP35GM submitted 2021-12-03 quant-ph cs.DSmath-phmath.MP

classification quant-phcs.DSmath-phmath.MP
keywords algorithmgatesolovay-kitaevcompilationefficientquantuminverse-freetext
verification ladder T0 review T1 audit T2 compute T3 formal

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abstract

The Solovay-Kitaev algorithm is a fundamental result in quantum computation. It gives an algorithm for efficiently compiling arbitrary unitaries using universal gate sets: any unitary can be approximated by short gates sequences, whose length scales merely poly-logarithmically with accuracy. As a consequence, the choice of gate set is typically unimportant in quantum computing. However, the Solovay-Kitaev algorithm requires the gate set to be inverse-closed. It has been a longstanding open question if efficient algorithmic compilation is possible without this condition. In this work, we provide the first inverse-free Solovay-Kitaev algorithm, which makes no assumption on the structure within a gate set beyond universality, answering this problem in the affirmative, and providing an efficient compilation algorithm in the absence of inverses for both $\text{SU}(d)$ and $\text{SL}(d, \mathbb{C})$. The algorithm works by showing that approximate gate implementations of the generalized Pauli group can self-correct their errors.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Removing Online Exponential Net Search from Solovay-Kitaev

    cs.CG 2026-07 conditional novelty 7.0 of 10

    Replacing the depth-zero net search with an 'integerized trotterization' over a good exponential basis makes online synthesis poly(d, log 1/ε), moving the exponential net cost into a one-time preprocessing step.

  2. Universal programmable waveguide arrays

    quant-ph 2024-11 conditional novelty 6.0 of 10

    Cascaded programmable waveguide arrays with strictly positive, nearest-neighbor couplings can approximate any unitary matrix to arbitrary precision, with error decreasing as the number of sections grows.

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