- Series
- High-Dimensional Phenomena in Statistics and Machine Learning Seminar
- Time
- Tuesday, November 10, 2015 - 3:00pm for 1.5 hours (actually 80 minutes)
- Location
- Skiles 005
- Speaker
- Dong Xia – Georgia Inst. of Technology, School of Mathematics
- Organizer
- Karim Lounici
Please Note: Joint work with Vladimir Koltchinskii.
The
density matrices are positively semi-definite Hermitian matrices of
unit trace that describe the state of a quantum system. We develop
minimax lower bounds on error rates of estimation of low rank density
matrices in trace regression models used in quantum state tomography (in
particular, in the case of Pauli measurements) with explicit dependence
of the bounds on the rank and other complexity parameters.Such
bounds are established for several statistically relevant distances,
including quantum versions of Kullback-Leibler divergence (relative
entropy distance) and of Hellinger distance (so called Bures distance),
and Schatten p-norm distances. Sharp upper bounds and oracle
inequalities for least squares estimator with von Neumann entropy
penalization are obtained showing that minimax lower bounds are attained
(up to logarithmic factors) for these distances.