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Parameters estimation by fitting correlation functions of continuous quantum measurement

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arxiv 2410.11955 v1 pith:YZMWP2WS submitted 2024-10-15 quant-ph

classification quant-ph
keywords measuredparameterssignalapproachcorrelationestimationfittingfunctions
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We propose a simple method to estimate the parameters of a continuously measured quantum system, by fitting correlation functions of the measured signal. We demonstrate the approach in simulation, both on toy examples and on a recent superconducting circuits experiment which proved particularly difficult to characterise using conventional methods. The idea is applicable to any system whose evolution is described by a jump or diffusive stochastic master equation. It allows the simultaneous estimation of many parameters, is practical for everyday use, is suitable for large Hilbert space dimensions, and takes into account experimental constraints such as detector imperfections and signal filtering and digitisation. Unlike existing methods, it also provides a direct way to understand how each parameter is estimated from the measured signal. This makes the approach interpretable, facilitates debugging, and enables validating the adequacy of a model with the observed data.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. An operational continuum limit of quantum combs

    quant-ph 2026-01 unverdicted novelty 8.0 of 10

    A continuous process tensor is defined by embedding the discrete multi-partite Choi matrix of a quantum comb into bosonic Fock space, closing the gap between discrete and continuum descriptions of multi-time quantum p...

  2. Time-dependent multiparameter estimation for quantum experiments via online-offline sequential Monte-Carlo method

    quant-ph 2026-07 conditional novelty 6.0 of 10

    Hybrid online-offline SMC with batch-averaged Kraus maps estimates time-dependent multiparameters from noisy continuous quantum measurements better than calibration on two superconducting-qubit datasets.

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