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Quantum Error Correction for Quantum Memories (1302.3428v7)

Published 14 Feb 2013 in quant-ph

Abstract: Active quantum error correction using qubit stabilizer codes has emerged as a promising, but experimentally challenging, engineering program for building a universal quantum computer. In this review we consider the formalism of qubit stabilizer and subsystem stabilizer codes and their possible use in protecting quantum information in a quantum memory. We review the theory of fault-tolerance and quantum error-correction, discuss examples of various codes and code constructions, the general quantum error correction conditions, the noise threshold, the special role played by Clifford gates and the route towards fault-tolerant universal quantum computation. The second part of the review is focused on providing an overview of quantum error correction using two-dimensional (topological) codes, in particular the surface code architecture. We discuss the complexity of decoding and the notion of passive or self-correcting quantum memories. The review does not focus on a particular technology but discusses topics that will be relevant for various quantum technologies.

Citations (910)

Summary

  • The paper presents an extensive review of quantum error correction techniques using stabilizer and topological codes for robust quantum memories.
  • It explains how two-dimensional surface codes achieve fault-tolerance with a noise threshold near 1% under depolarizing errors.
  • The review outlines challenges and potential advances, including quantum LDPC codes, for integrating theory with practical qubit architectures.

An Overview of Quantum Error Correction for Quantum Memories

Barbara M. Terhal's review paper provides an extensive examination of quantum error correction (QEC) techniques within the context of quantum memories, particularly focusing on qubit stabilizer codes and the challenges inherent in their experimental realization. The paper decouples theoretical underpinnings from practical applications, offering both a primer on fault-tolerance and an exploration of cutting-edge approaches to QEC in two-dimensional topological codes.

Stabilizer Codes and Fault-Tolerance

The paper begins by detailing the intricacies of quantum error correction, clarifying the role of stabilizer codes, which are quantum analogues of classical linear codes. These codes maintain qubit integrity by encoding quantum information across multiple physical qubits. The review elaborates on the derived error correction conditions, illustrating how logical qubits can withstand specific subsets of qubit errors through redundant encoding.

A key focus is the necessity of fault-tolerance: the inherent resilience against imperfections in quantum gate operations and measurements. The text introduces the concatenated coding paradigm, which prescribes the recursive encoding of qubits to amplify error resilience. This lays the groundwork for the fault-tolerant threshold theorem, affirming that sufficiently low error rates can sustain quantum computations, albeit with poly-logarithmic overheads in qubit resources.

Topological Codes and the Surface Code

The latter half of Terhal's review hones in on two-dimensional topological codes, particularly the surface code, which promises scalability due to its high noise threshold and error-correcting capabilities in quantum systems. The surface code's architecture, hinging on local stabilizer checks arranged in a two-dimensional lattice, leverages topological properties to shield against errors, with logical operations represented by non-contractible loops within the code's architecture.

The review underscores the surface code's impressive fault-tolerance threshold, estimated at approximately 1% under depolarizing noise—a considerable achievement when contrasted with non-topological coding strategies. Additionally, the review contemplates the challenges of syndrome extraction and classical processing latency, essential factors in sustaining real-time error correction.

Implications and Future Directions

Terhal's review highlights the interplay between theoretical QEC protocols and their realization in quantum memory systems, stressing the importance of integrating error correction with physical qubit architectures like superconducting qubits. The review points to experimental constraints, such as the necessity of maintaining coherence amidst environmental noise and decoherence.

Looking forward, Terhal suggests that advances in quantum LDPC codes, which envisage constant rate encoding with feasible noise thresholds, could mitigate overheads observed in current topological error-correction paradigms. These developments might pave the way for realizing fault-tolerant quantum computation with minimized resource expenditure.

In conclusion, Terhal's paper offers an intricate dissection of QEC strategies, juxtaposing theoretical concepts with experimental aspirations. As quantum computing strides toward practicality, overcoming challenges in QEC will be pivotal in harnessing its transformative potential. The review positions topological codes, supplemented by efficient decoding algorithms and hardware innovations, as keystones for realizing robust quantum memories and computational platforms in the imminent quantum era.