quantum-information

Describe the Issue!

Most of the functions in random_objects.py take an N input and an optional dims. Those input are redundant as the size (N) can be obtained from the dims. However the way they handle this inconsistent:

• Many functions, such as rand_super, rand_dm, check that the dims matches the size and raise an error if it doesn't.
• rand_dm_ginibre, rand_super_bcsz j

What is the expected enhancement?

The openQASM project should have release notes associated with each tagged release (see #321). These should contain a summary of all changes included in the prepared release (or the development branch). For ease (and distribution) of maintenance, we should consider using reno which has been used with success in Qiski

There's an obvious extension of ZMask() to "masked" S, T, and general PhaseRootN gates.ZMask() calculates parity of each masked permutation, and applies a -1 multiplicative factor if the parity is odd, achieving a batched set of masked Pauli Z gates. Similarly, for a general batched PhaseRootN gate, the effective extension of this parity calculation is to a ring with 2^(n+1) phas

Implement a function that calculates the max-relative entropy for quantum channels.

The functionality for this should be created in channel_props/max_relative_entropy.py with corresponding unit tests found in tests/test_channel_props/test_max_relative_entropy.py. Be sure to also update the docs in /docs/channels.rst under "Properties of Quantum Channels" with `toqito.channel_props.max_re

Now that Q# + Python can use project files for references, we should add them here so IntelliSense can work better :)

Is your feature request related to a problem? Please describe

Current implementation of Model Learning (C_3 step) suggests duplication of code and lack of integration/reuse with existing solutions (possible case of NIH syndrome).

Describe the solution you'd like

Integrate C3 Model Learning with the Tensorflow ML ecosystem by extending Model and Layer to wrap C3 computations and sta

Need more tutorials contributed by the community