Title: Emergent Unitary Designs for Encoded Qubits from Coherent Errors and Syndrome Measurements
Unitary k -designs are distributions of unitary gates that match the Haar distribution up to its kth statistical moment. They are a crucial resource for randomized quantum protocols. However, their implementation on encoded logical qubits is nontrivial due to the need for magic gates, which can require a large resource overhead. In this work, we propose an efficient approach to generate unitary designs for encoded qubits in surface codes by applying local unitary rotations (“coherent errors”) on the physical qubits followed by syndrome measurement and error correction. We prove that, under some conditions on the coherent errors (notably including all single-qubit unitaries) and on the error-correcting code, this process induces a unitary transformation of the logical subspace. We numerically show that the ensemble of logical unitaries (indexed by the random syndrome outcomes) converges to a unitary design in the thermodynamic limit, provided that the density or strength of coherent errors is above a finite threshold. This “unitary design” phase transition coincides with the code’s coherent error threshold under optimal decoding. Furthermore, we propose a classical algorithm to simulate the protocol based on a “staircase” implementation of the surface code encoder and decoder circuits. This enables a mapping to a (1+1) -dimensional monitored circuit, where we observe an entanglement phase transition (and thus a classical complexity phase transition of the decoding algorithm) coinciding with the aforementioned unitary design phase transition. Our results provide a practical way to realize unitary designs on encoded qubits, with applications including quantum state tomography and benchmarking in error-correcting codes.  more » « less
Award ID(s):
2120757
PAR ID:
10678990
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
PRX Quantum
Date Published:
Journal Name:
PRX Quantum
Volume:
6
Issue:
3
ISSN:
2691-3399
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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