Use qiskit-algorithms library and upgrade to SamplerV2

[BrunoRosendo]

Currently, I am using a modified local copy of qiskit-algorithms, because its current version is not compatible with an update made recently by IBM (March 2024): https://docs.quantum.ibm.com/run/primitives-examples

beginning 1 March 2024, Qiskit Runtime will require that circuits and observables are transformed to use only instructions supported by the system (referred to as instruction set architecture (ISA) circuits and observables) before being submitted to the primitives

The issue was created a while ago without much track qiskit-community/qiskit-algorithms#164, but there is currently work being done to fix it: qiskit-community/qiskit-algorithms#197

Other than fixing the ISA issue, it also updates the library to SamplerV2.

When the PR is merged and release, I should update this library as well.

[edoaltamura]

Hi, some more updates on gradients, optimizers and state fidelities with V2 primitives can be found here: https://github.com/qiskit-community/qiskit-machine-learning/tree/main/qiskit_machine_learning. Qiskit Algorithms is no longer supported by IBM, but we migrated and updated some functionalities (only the ones we strictly needed) to Qiskit ML. Feel free to pick some of them up if needed.

However, it looks like your implementation uses mostly Qiskit Optimization, which depends on Algorithms and (as far as I'm aware) still doesn't support V2s.