update few links in the code (#13427) (#13434)

(cherry picked from commit 7c6a547)

Co-authored-by: Luciano Bello <[email protected]>

qiskit/primitives/utils.py

@@ -82,7 +82,7 @@ def init_observable(observable: BaseOperator | str) -> SparsePauliOp:
     since="1.2",
     additional_msg="Use ``QuantumCircuit.layout`` and ``SparsePauliOp.apply_layout`` "
     + "to adjust an operator for a layout. Otherwise, use ``mthree.utils.final_measurement_mapping``. "
-    + "See https://qiskit-extensions.github.io/mthree/apidocs/utils.html for details.",
+    + "See <https://qiskit.github.io/qiskit-addon-mthree/apidocs/utils> for details.",
 )
 def final_measurement_mapping(circuit: QuantumCircuit) -> dict[int, int]:
     """Return the final measurement mapping for the circuit.

qiskit/providers/__init__.py

@@ -160,7 +160,7 @@
    interacting with a running job.
 
 For a simple example of a provider, see the
-`qiskit-aqt-provider <https://github.com/Qiskit-Partners/qiskit-aqt-provider>`__
+`qiskit-aqt-provider <https://github.com/qiskit-community/qiskit-aqt-provider>`__
 
 Provider
 --------
@@ -664,7 +664,7 @@ def status(self):
 concentrate on higher level applications using these outputs.
 
 For example, if your backends were well suited to leverage
-`mthree <https://github.com/Qiskit-Partners/mthree/>`__ measurement
+`mthree <https://github.com/Qiskit/qiskit-addon-mthree>`__ measurement
 mitigation to improve the quality of the results, you could implement a
 provider-specific :class:`~.Sampler` implementation that leverages the
 ``M3Mitigation`` class internally to run the circuits and return