Removing the dependencies 'qiskit_optimization' and 'qiskit_algorithms' by implementing QAOA to solve a QUBO problem. Additional fixes to support Qiskit >= 2.0.0.

Author: tobi-forster

.pre-commit-config.yaml

@@ -90,3 +90,5 @@ repos:
           - mqt.ddsim
           - pytest
           - pandas-stubs
+          - scipy-stubs
+          - mqt.core

pyproject.toml

@@ -19,17 +19,19 @@ requires-python = ">=3.8"
 dynamic = ["version"]
 
 dependencies = [
-    "qiskit>=0.36.0,<0.42.0",
+    "qiskit>=2.0.0",
     "joblib",
     "numpy",
     "matplotlib",
-    "mqt.ddsim",
+    "mqt.core",
     "networkx",
     "python_tsp",
     "docplex",
-    "qiskit_optimization",
+    "qubovert",
     "qiskit_aer",
-    "pandas"
+    "qiskit_ibm_runtime",
+    "pandas",
+    "scipy"
 ]
 
 classifiers = [

src/mqt/problemsolver/csp.py

@@ -3,9 +3,10 @@
 from typing import TYPE_CHECKING, TypedDict
 
 import numpy as np
-from qiskit import QuantumCircuit, QuantumRegister, execute
+from qiskit import QuantumCircuit, QuantumRegister, qasm3
 
-from mqt.ddsim import DDSIMProvider
+import mqt.core
+from mqt.core.dd import sample
 
 if TYPE_CHECKING:
     from qiskit.circuit import Instruction
@@ -223,7 +224,7 @@ def create_oracle(
         compute = qc.to_instruction()
 
         # mark solution
-        qc.mct(mct_list, flag, ancilla_qubits=anc_mct, mode="v-chain")
+        qc.mcx(mct_list, flag, ancilla_qubits=anc_mct, mode="v-chain")
 
         # uncompute
         uncompute = compute.inverse()
@@ -309,9 +310,10 @@ def create_grover(
         return qc
 
     def simulate(self, qc: QuantumCircuit) -> tuple[int, int, int, int] | None:
-        backend = DDSIMProvider().get_backend("qasm_simulator")
-        job = execute(qc, backend, shots=10000)
-        counts = job.result().get_counts(qc)
+        qc = qc.decompose()
+        qasm_string = qasm3.dumps(qc)
+        quantum_computation = mqt.core.ir.QuantumComputation().from_qasm_str(qasm_string)
+        counts = sample(quantum_computation, shots=10000)
 
         mean_counts = np.mean(list(counts.values()))