Julien Gacon

> I think implementing Value::Rational will be much simpler but as in discussion https://github.com/Qiskit/qiskit/pull/14508#pullrequestreview-2889353387 implementing Value::Rational is redundant to BinaryOp::Div I might be wrong, but I believe this might have...

Moving to 2.4 as there's no associated PR by now and there's an existing alternative path.

It would be good to cover structurally different circuits here. For starters we could add a Hamiltonian simulation circuit (e.g. Heisenberg on a line and square lattice) and a Grover...

With these open questions on what to include there's not really time left to merge for 2.3.

Moving to 2.4 since it's quite a large PR and there's no review yet. (@to24toro I removed your assignment since we should find a _reviewer_ to assign, you're ofc "assigned"...

Yeah we can already include them in this PR 👍🏻 though if we move them here, then we should maybe directly update the `QkParam` class to use them, right?

@Augusto12 does this resolve the problem in your workflow? 🙂

Could you post a minimally reproducing example of what you're doing? It might be something that can be resolved in the machine learning package itself 🙂 You could open an...

Ok I see, the problem here is that `VQC` uses the `SamplerQNN` internally, which computes the gradients with the parameter-shift rule. To apply that gradient rule, `qiskit-algorithms` tries to express...

As a workaround you could use auxiliary qubits to implement the n-controlled, parameterized RY, for example something like ```python from qiskit.circuit import Parameter from qiskit.circuit.library import RYGate, MCMTVChain y =...