Statistical analysis of compressive low rank tomography with random measurementsTools Acharya, Anirudh and Guţă, Mădălin (2017) Statistical analysis of compressive low rank tomography with random measurements. Journal of Physics A: Mathematical and Theoretical, 50 (19). p. 195301. ISSN 1751-8121 Full text not available from this repository.AbstractWe consider the statistical problem of 'compressive' estimation of low rank states (r«d ) with random basis measurements, where r, d are the rank and dimension of the state respectively. We investigate whether for a fixed sample size N, the estimation error associated with a 'compressive' measurement setup is 'close' to that of the setting where a large number of bases are measured. We generalise and extend previous results, and show that the mean square error (MSE) associated with the Frobenius norm attains the optimal rate rd/N with only O(rlogd) random basis measurements for all states. An important tool in the analysis is the concentration of the Fisher information matrix (FIM). We demonstrate that although a concentration of the MSE follows from a concentration of the FIM for most states, the FIM fails to concentrate for states with eigenvalues close to zero.
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