Release Notes

0.2.0

New Features

  • A new method, POVMPostProcessor.get_state_snapshot(), is implemented to easily access the classical “snapshots” of the state after taking some measurements. A classical “snapshot” of the state is the dual frame operator associated with the corresponding outcome. The new method returns the snapshot (typically as a product of local operators) associated with the queried outcome (typically a tuple of integers). In parallel, the ProductFrame.get_operator() method has been added for more general access to frame operators in a product form.

  • Add an option for the post-processors to combine the counts associated with different parameter values that were submitted in the same POVM sampler PUB. To learn more, read this how-to guide.

  • The toolbox now allows the use of non-IC measurements. This is useful, for example, if the observables to be estimated are known to consist solely of pauli X and Z (then no Y measurements are needed).

    By making this change, we now use the numpy.linalg.lstsq() method to determine the dual frame (i.e. the reconstruction operators) as opposed to the numpy.linalg.solve() method used previously, which only worked for IC measurements.

  • The MultiQubitFrame now has a shape attribute. Before, its shape was implicitly assumed to be (len(frame.num_operators),) and the operators were indexed by integers. Note that this is is still the default shape and indexing method. However, the frame operators can now also be indexed by multi-indices (tuple of integers) if a custom shape is specified.

Upgrade Notes

  • The behavior of loc=None has changed. To revert to the old behavior, update your code to use loc=....

  • This release adds support for Python 3.13. No code changes were necessary, so older releases are expected to work on Python 3.13 too.

  • This package is now compatible with Qiskit SDK 2.0 and 2.1.

Bug Fixes

Other Notes

  • Minor documentation updates to ensure PyPI releases are presented properly.

  • This release adds support for Windows. No code changes were necessary, so older releases are expected to work on Windows too.

0.1.0

Prelude

Note

Starting with this release, this project will follow semantic versioning.

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).