Renato M S Farias

Results 44 issues of Renato M S Farias

As I discussed with @stavros11 in person, Qiskit has a [built-in function](https://qiskit.org/documentation/stubs/qiskit.ignis.verification.expectation_counts.html) that returns all marginal expectation values from commuting observables of a fixed measurement set. A function like this...

enhancement

What I would like to know is if there's a built-in way of representing states in the Pauli basis and if there's an efficient way of getting that representation. Currently...

enhancement

It would be really helpful to have an implementation of the Depolarizing Channel like the one on [Qiskit](https://qiskit.org/documentation/stubs/qiskit.providers.aer.noise.depolarizing_error.html#qiskit.providers.aer.noise.depolarizing_error) Note that the Pauli noise channel already implemented in Qibo is a...

enhancement

Currently the [gates.UnitaryChannel()](https://qibo.readthedocs.io/en/stable/api-reference/qibo.html#unitary-channel) function accepts operators that are either type `np.ndarray` or `tf.Tensor`. For heavier computations it'd be best to be able to pass a list of `SymbolicHamiltonian` operators as...

enhancement

Checklist: - [ ] Reviewers confirm new code works as expected. - [x] Tests are passing. - [ ] Coverage does not decrease. - [ ] Documentation is updated.

enhancement

Something like we can see here on [Qiskit](https://qiskit.org/documentation/_modules/qiskit_aer/noise/errors/standard_errors.html#coherent_unitary_error)

enhancement

Checklist: - [ ] Reviewers confirm new code works as expected. - [x] Tests are passing. - [x] Coverage does not decrease. - [x] Documentation is updated.

bug

Checklist: - [x] Reviewers confirm new code works as expected. - [x] Tests are passing. - [x] Coverage does not decrease. - [x] Documentation is updated.

documentation
enhancement

Code to reproduce bug: ```python from qibo import Circuit, gates circuit = Circuit(2) circuit.add(gates.H(0).controlled_by(1)) circuit.unitary() ```

bug

https://github.com/numpy/numpy/releases/tag/v2.0.0b1 It might be interesting to look into it to see if any speed-up can be obtained by supporting `numpy` 2.0.0. (@BrunoLiegiBastonLiegi maybe in the Clifford implementation?)