Abstracts

Experimental exploration of optimal quantum state and process tomography

Presenting Author: Nathan Lysne, University of Arizona
Contributing Author(s): Hector Sosa Martinez, Charles Baldwin, Amir Kalev, Ivan Deutsch, Poul Jessen

In principle, quantum tomography (QT) is an ideal tool for finding complete information about an unknown state (QST) or process (QPT). In practice, the protocols used for QT are resource intensive and scale poorly with system size. Utilizing our high-fidelity control capabilities over the d = 16 dimensional hyperfine manifold in the 6S1/2 electronic ground state of the 133Cs atom, we performed a comprehensive examination of six POVM sets optimal for a given structure, including Mutually Unbiased Bases (MUB), Symmetric Informationally Complete (SIC), and Pure-State Informationally Complete (PSI) POVMs. We found a clear trade-off between efficiency and robustness to measurement error within these POVM constructions, based on experimentally observed fidelities for sets of known test states and processes in Hilbert space dimensions from d = 4 to d = 16. In d = 16 this yielded average fidelities as high as 98% for QST and 90% for QPT. Maximally efficient strategies such as SIC and PSI POVMs performed rather poorly in our experiment. However, we found that their fidelity improved markedly when each POVM was implemented using several different controls and the outcomes averaged together, i. e., when measurement errors were suppressed at the cost of efficiency. Finally, we observed possible bias towards pure states and unitary processes based on the estimator used for reconstruction. We have extended our protocol to investigate tomography of mixed states, as well as the use of informationally incomplete QPT to achieve high fidelity reconstructions as efficiently as possible.

(Session 5 : Thursday from 5:00 - 7:00 pm)

 

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