Accession Number:

ADA566222

Title:

Quantum System Identification via L1-norm Minimization

Descriptive Note:

Final rept. 30 Sep 2009-31 Mar 2011

Corporate Author:

SC SOLUTIONS SUNNYVALE CA

Personal Author(s):

• Kosut, Robert
• Rabitz, Hersch

Report Date:

2011-06-30

Pagination or Media Count:

35.0

Abstract:

This report summarizes our efforts to apply the theory and algorithms of Compressed Sensing CS to Quantum Process Tomography QPT and Hamiltonian parameter estimation. Specific results include 1 Development of computational algorithms to include physics based constraints on the quantum process matrix, i.e., positive-semidefinite and trace preserving. 2 Simulations of two-qubit Quantum Fourier Transform interacting with an unknown environment. 3 Establishment of robustness of ideal unitary basis via singular-value-decomposition. 4 The first experimental demonstration of QPT via CS on a photonic system at the University of Queensland. The latter experimental results showed the anticipated and predicted significant reduction of estimation resources, e.g., with respect to an estimate of a 16x16 process matrix obtained from an over complete set of 576 configurations, only 32 configurations were needed to obtain a 97 fidelity, and only 18 configurations to obtain a 94 fidelity. 5 Application of CS to a nearly-sparse many-body Hamiltonian.

Descriptors:

• *QUANTUM THEORY
• HAMILTONIAN FUNCTIONS
• IDENTIFICATION

Subject Categories:

• Quantum Theory and Relativity

Distribution Statement:

APPROVED FOR PUBLIC RELEASE