Characterization of a qubit Hamiltonian using adaptive measurements in a fixed basis
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We investigate schemes for Hamiltonian parameter estimation of a two-level system using repeated measurements in a fixed basis. The simplest (Fourier based) schemes yield an estimate with a mean-square error (MSE) that decreases at best as a power law ~N-2 in the number of measurements N. By contrast, we present numerical simulations indicating that an adaptive Bayesian algorithm, where the time between measurements can be adjusted based on prior measurement results, yields a MSE which appears to scale close to exp(-0.3N). That is, measurements in a single fixed basis are sufficient to achieve exponential scaling in N.
Physical Review A (Atomic, Molecular and Optical Physics)
Copyright 2011 American Physical Society. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
Quantum Information, Computation and Communication