Resilience of Quantum Random Access Memory to Generic Noise

Quantum random access memory (QRAM)—memory which stores classical data but allows queries to be performed in superposition—is required for the implementation of numerous quantum algorithms. While naive implementations QRAM are highly susceptible decoherence and hence not scalable, it has been argued that bucket-brigade architecture [Giovannetti et al., Phys. Rev. Lett. 100, 160501 (2008)] is resilient noise, with infidelity a query scaling only logarithmically size. In prior analyses, however, this favorable followed directly from use contrived noise models, thus leaving open question whether experimental would actually enjoy purported advantage. work, we study effects on full generality. Our main result proof holds arbitrary error channels (including, e.g., depolarizing coherent errors). identifies origin resilience as limited entanglement among memory’s components, also reveals significant architectural simplifications can made while preserving resilience. We verify these results numerically using novel algorithm efficient simulation noisy circuits. findings indicate implemented existing hardware realistically devices, high-fidelity possible without correction. Furthermore, prove benefits persist when correction used, case scheme offers improved efficiency logical errors.4 MoreReceived 21 December 2020Accepted 13 April 2021DOI:https://doi.org/10.1103/PRXQuantum.2.020311Published by American Physical Society under terms Creative Commons Attribution 4.0 International license. Further distribution work must maintain attribution author(s) published article's title, journal citation, DOI.Published SocietyPhysics Subject Headings (PhySH)Research AreasQuantum algorithmsQuantum computationQuantum information architectures & platformsQuantum processingQuantum Information