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Complexity Classification of Conjugated Clifford Circuits
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abstract
Clifford circuits -- i.e. circuits composed of only CNOT, Hadamard, and $\pi/4$ phase gates -- play a central role in the study of quantum computation. However, their computational power is limited: a well-known result of Gottesman and Knill states that Clifford circuits are efficiently classically simulable. We show that in contrast, "conjugated Clifford circuits" (CCCs) -- where one additionally conjugates every qubit by the same one-qubit gate $U$ -- can perform hard sampling tasks. In particular, we fully classify the computational power of CCCs by showing that essentially any non-Clifford conjugating unitary $U$ can give rise to sampling tasks which cannot be efficiently classically simulated to constant multiplicative error, unless the polynomial hierarchy collapses. Furthermore, by standard techniques, this hardness result can be extended to allow for the more realistic model of constant additive error, under a plausible complexity-theoretic conjecture. This work can be seen as progress towards classifying the computational power of all restricted quantum gate sets.
Forward citations
Cited by 3 Pith papers
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Sampling hard circuits with verifiably high fidelity
A 97-qubit experiment certifies a 0.284 fidelity lower bound for a 468-T-gate sampling circuit by combining spacetime-code error detection with the measured fidelity of an undoped Clifford reference.
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Low-overhead error detection with spacetime codes
Spacetime coherent Pauli checks, found by reducing check search to a linear-code decoding problem, detect errors in Clifford circuits with mild overhead and improve single-shot state fidelity by up to 236x in experime...
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Hardness and Complexity Transition of Noisy Random Circuit Sampling
Under the standard ideal-RCS #P-hardness conjecture, noisy random circuit sampling remains hard for depolarizing noise γ = O(log n/(nd)), and matching simulability results make γ = Θ(log n/(nd)) the transition scale.
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