Reliable process tomography with QPtomographer

This Python package implements practical and reliable diamond norm estimation to any reference channel, given any measurements taken in a quantum process tomography procedure, using the method described in [arXiv:XXXX.XXXXX (TBD)].

Contents:

• Installation instructions
  • Prerequisite: Install BLAS/Lapack
  • Prerequisite: Compile SCS
  • Prerequisite: Install tomographer and other Python packages
  • Download and install QPtomographer
• Figures of Merit for Channels
  • The diamond norm distance
  • The entanglement fidelity for channels
  • The worst-case entanglement fidelity
  • References
• Conventions for specifying channels and states
• Package: QPtomographer
  • Channel-space sampling method: QPtomographer.channelspace
  • Bipartite sampling method: QPtomographer.bistates
  • Evaluating the figures of merit: QPtomographer.figofmerit
  • Some utilities: QPtomographer.util
  • Version information from QPtomographer members

Indices and tables

• Index
• Module Index
• Search Page