POVM Toolbox¶

This is a toolbox for working with positive operator-valued measures (POVMs). It enables users to use POVMs for sampling the state of quantum circuits (see also povm_toolbox.sampler) and compute expectation values of any observable of interest (see also povm_toolbox.post_processor). The toolbox includes a library of pre-defined POVMs (see povm_toolbox.library) which provide ready-to-go POVM circuit definitions. You can also implement your own POVM circuits by following the provided interface. Additionally, you can work with POVMs on a quantum-informational theoretical footing (see povm_toolbox.quantum_info).

In this documentation you can find a number of resources including:

explanations to learn more about POVMs
how to get started with coding using one of the tutorials
dive into more specific features with the how-to guides
and, of course, look up specific details of the API

Installation¶

Make sure that you have the correct Python environment active, into which you want to install this code, before running the below.

You can install this code via pip:

pip install povm-toolbox

Alternatively, you can install it from source:

git clone git@github.com:qiskit-community/povm-toolbox.git
cd povm-toolbox
pip install -e .

This performs an editable install to simplify code development.

If you intend to develop on this code, you should consider reading the contributing guide.

Citation¶

If you use this project, please cite the following reference:

Laurin E. Fischer, Timothée Dao, Ivano Tavernelli, and Francesco Tacchino; “Dual-frame optimization for informationally complete quantum measurements”; Phys. Rev. A 109, 062415; DOI: https://doi.org/10.1103/PhysRevA.109.062415