Recovery With Incomplete Knowledge: Fundamental Bounds on Real-Time Quantum Memories
Arshag Danageozian

TL;DR
This paper establishes fundamental information-theoretic bounds on the performance of real-time quantum memories that adapt to drifting noise parameters using spectator systems, highlighting the costs and potential advantages of incomplete knowledge.
Contribution
It introduces bounds on real-time quantum memory recovery performance with incomplete knowledge, linking quantum error correction, parameter estimation, and information theory.
Findings
Bounds on recovery performance quantified by diamond distance.
Fundamental limits for multi-cycle recovery with incomplete noise knowledge.
Potential advantage of noise coherence across cycles.
Abstract
The recovery of fragile quantum states from decoherence is the basis of building a quantum memory, with applications ranging from quantum communications to quantum computing. Many recovery techniques, such as quantum error correction, rely on the apriori knowledge of the environment noise parameters to achieve their best performance. However, such parameters are likely to drift in time in the context of implementing long-time quantum memories. This necessitates using a "spectator" system, which estimates the noise parameter in real-time, then feed-forwards the outcome to the recovery protocol as a classical side-information. The memory qubits and the spectator system hence comprise the building blocks for a real-time (i.e. drift-adapting) quantum memory. In this article, I consider spectator-based (incomplete knowledge) recovery protocols as a real-time parameter estimation problem…
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Taxonomy
TopicsQuantum Information and Cryptography · Quantum Computing Algorithms and Architecture
