Studies on Point Estimators for Incomplete Tomography of Qutrits

TL;DR

This thesis compares different point estimators for incomplete qutrit tomography, finding that methods like maximum entropy and average estimators perform similarly, with no clear advantage for any particular approach.

Contribution

It provides a comparative analysis of estimation methods for incomplete qutrit tomography, highlighting their similar performance through numerical simulations.

Findings

Maximum entropy and average estimators perform similarly.

No estimator is significantly better than others.

Numerical simulations support the comparable performance.

Abstract

This is a Bachelor's thesis on point estimators for incomplete tomography of qutrits as of 2014, submitted to the National University of Singapore. The main content of the thesis focuses on various methods of estimation such as maximum entropy and average estimator and show that they are quite different. Numerical simulations of these methods show however that these estimators perform very close to one another. Therefore on this basis, there is no reason to favor one method over another.