Iterative maximum-likelihood reconstruction in quantum homodyne tomography (original) (raw)

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Abstract

I propose an iterative expectation maximization algorithm for reconstructing the density matrix of an optical ensemble from a set of balanced homodyne measurements. The algorithm applies directly to the acquired data, bypassing the intermediate step of calculating marginal distributions. The advantages of the new method are made manifest by comparing it with the traditional inverse Radon transformation technique.

Publication:

Journal of Optics B: Quantum and Semiclassical Optics

Pub Date:

June 2004

DOI:

10.1088/1464-4266/6/6/014

10.48550/arXiv.quant-ph/0311097

arXiv:

arXiv:quant-ph/0311097

Bibcode:

2004JOptB...6S.556L

Keywords:

E-Print:

Journal of Optics B: Quantum and Semiclassical Optics 6 (2004) S556--S559