Gradient-based stopping rules for maximum-likelihood quantum-state tomography

@article{Glancy2012GradientbasedSR,
  title={Gradient-based stopping rules for maximum-likelihood quantum-state tomography},
  author={S. Glancy and E. Knill and Mark W. Girard},
  journal={New Journal of Physics},
  year={2012},
  volume={14},
  pages={095017}
}
When performing maximum-likelihood quantum-state tomography, one must find the quantum state that maximizes the likelihood of the state given observed measurements on identically prepared systems. The optimization is usually performed with iterative algorithms. This paper provides a gradient-based upper bound on the ratio of the true maximum likelihood and the likelihood of the state of the current iteration, regardless of the particular algorithm used. This bound is useful for formulating… Expand

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