Characterizing quantum systems through experimental data is critical to
applications as diverse as metrology and quantum computing. Analyzing this
experimental data in a robust and reproducible manner is made challenging,
however, by the lack of readily-available software for performing principled
statistical analysis. QInfer addresses this need. Our library makes it easy to
analyze data from tomography, randomized benchmarking, and Hamiltonian
learning experiments either in post-processing, or online as data is acquired.
We also provide functionality for predicting the performance of a proposed
experimental protocols from simulated runs.
