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|Author(s):||Scott C. Glancy; Emanuel H. Knill; Thomas Gerrits; Tracy S. Clement; Brice R. Calkins; Adriana E. Lita; Aaron J. Miller; Alan L. Migdall; Sae Woo Nam; Richard P. Mirin;|
|Title:||Innovations in Maximum Likelihood Quantum State Tomography|
|Published:||October 09, 2009|
|Abstract:||At NIST we are engaged in an experiment whose goal is to create superpositions of optical coherent states (such superpositions are sometimes called "Schroedinger cat" states). We use homodyne detection to measure the light, and we apply maximum likelihood quantum state tomography to the homodyne data to estimate the state that we have created. To assist in this analysis we have made a few improvements to quantum state tomography: we have devised a new iterative method (that has faster convergence than R*\rho*R iterations) to find the maximum likelihood state, we have formulated a stopping criterion that can upper-bound the actual maximum likelihood, and we have implemented a bias-corrected resampling strategy to estimate confidence intervals.|
|Citation:||PERIMETER INSTITUTE RECORDED SEMINAR ARCHIVE|
|Keywords:||homodyne detection, maximum likelihood, quantum state estimation, quantum state tomography|
|Research Areas:||Quantum Information, Statistics, Quantum Optics|
|PDF version:||Click here to retrieve PDF version of paper (1MB)|