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Optimal approximate quantum error correction for quantum metrology

Zhou, Sisi, Jiang, Liang

2020Open MIND35 citationsDOIOpen Access PDF

Abstract

For a generic set of Markovian noise models, the estimation precision of a parameter associated with the Hamiltonian is limited by the 1 / \sqrt{t} scaling, where t is the total probing time, in which case the maximal possible quantum improvement in the asymptotic limit of large t is restricted to a constant factor. However, situations arise where the constant factor improvement could be significant, yet no effective quantum strategies are known. Here we propose an optimal approximate quantum error correction (AQEC) strategy asymptotically saturating the precision lower bound in the most general adaptive parameter estimation scheme, where arbitrary and frequent quantum controls are allowed. We also provide an efficient numerical algorithm finding the optimal code. Finally, we consider highly biased noise and show that using the optimal AQEC strategy, strong noises are fully corrected, while the estimation precision depends only on the strength of weak noises in the limiting case.

Topics & Concepts

QuantumHamiltonian (control theory)Asymptotically optimal algorithmUpper and lower boundsScalingQuantum error correctionConstant (computer programming)MathematicsNoise (video)Quantum metrologyQuantum algorithmStatistical physicsApplied mathematicsAlgorithmQuantum mechanicsComputer sciencePhysicsMathematical optimizationQuantum computerMathematical analysisQuantum simulatorProgramming languageImage (mathematics)GeometryArtificial intelligenceQuantum Information and CryptographyQuantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications
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