Quantum Tomography Benchmarking

MATLAB library for benchmarking quantum tomography (QT) methods. Full documentation is available here.

Getting Started

Prerequisites and installing

The library was tasted on MATLAB R2018b. Required toolboxes and external libraries:

• MATLAB Statistics toolbox
• DataHash library

To install the library clone the repository or download and unpack zip-archive. Before using run the startup script.

>> qtb_startup

Some of the implemented QT methods require installing external MATLAB libraries:

• est_ppi - https://github.com/qMLE/qMLE
• est_frls - http://cvxr.com/cvx/
• est_frml - https://github.com/PQCLab/RootTomography
• est_trml - https://github.com/PQCLab/RootTomography
• est_arml -https://github.com/PQCLab/RootTomography
• est_cs - http://cvxr.com/cvx/

Analyze the method benchmarks

The following code shows a basic example of running analysis for a 2-qubit tomography method on random pure states.

dim = [2,2];
result = qtb_analyze(proto_fmub(dim), est_ppi(), dim, 'rps');

The following code calculates benchmarks using raw data obtained above.

report = qtb_report(result, 'rps');
disp(report.table);