Reformatted using black. Deleted unecessary comments. Renamed NoiseModel serialization format to match the rest of the code.

Author: smaugdela

qiskit_scaleway/backends/aer/backend.py

@@ -54,12 +54,6 @@ def __init__(self, provider, client: QaaSClient, platform: QaaSPlatform):
 
         self._target = self._convert_to_target()
 
-        ### LEGACY qiskit 1.4
-        # self._target = convert_to_target(
-        #     self._configuration, properties=self._properties, defaults=None, custom_name_mapping=NAME_MAPPING
-        # )
-        ###
-
     def __repr__(self) -> str:
         return f"<AerBackend(name={self.name},num_qubits={self.num_qubits},platform_id={self.id})>"
 
@@ -130,4 +124,6 @@ def _convert_to_target(self) -> Target:
         if conf_dict.get("custom_name_mapping") is None:
             conf_dict["custom_name_mapping"] = NAME_MAPPING
 
-        return Target.from_configuration(**{k: conf_dict[k] for k in args_lis if k in conf_dict})
+        return Target.from_configuration(
+            **{k: conf_dict[k] for k in args_lis if k in conf_dict}
+        )

qiskit_scaleway/backends/base_job.py

@@ -98,8 +98,10 @@ def submit(self, session_id: str) -> None:
         if noise_model:
             noise_model_dict = _encode_numpy_complex(noise_model.to_dict(False))
             noise_model = QaaSNoiseModelData(
-                serialization_format = QaaSNoiseModelSerializationFormat.PATCHED_JSON,
-                noise_model_serialization = zlib.compress(json.dumps(noise_model_dict).encode()),
+                serialization_format=QaaSNoiseModelSerializationFormat.AER_COMPRESSED_JSON,
+                noise_model_serialization=zlib.compress(
+                    json.dumps(noise_model_dict).encode()
+                ),
             )
             ### Uncomment to use standard JSON serialization, provided there is no more issue with AER deserialization logic
             # noise_model = QaaSNoiseModelData(
@@ -224,17 +226,13 @@ def _encode_numpy_complex(obj):
     """
     if isinstance(obj, np.ndarray):
         return {
-            '__ndarray__': True,
-            'data': _encode_numpy_complex(obj.tolist()), # Recursively encode data
-            'dtype': obj.dtype.name,
-            'shape': obj.shape,
+            "__ndarray__": True,
+            "data": _encode_numpy_complex(obj.tolist()),  # Recursively encode data
+            "dtype": obj.dtype.name,
+            "shape": obj.shape,
         }
     elif isinstance(obj, (complex, np.complex128)):
-        return {
-            '__complex__': True,
-            'real': obj.real,
-            'imag': obj.imag
-        }
+        return {"__complex__": True, "real": obj.real, "imag": obj.imag}
     elif isinstance(obj, dict):
         return {key: _encode_numpy_complex(value) for key, value in obj.items()}
     elif isinstance(obj, (list, tuple)):

tests/test_aer_multiple_circuits.py

@@ -54,7 +54,9 @@ def test_aer_multiple_circuits():
         url=os.getenv("QISKIT_SCALEWAY_API_URL"),
     )
 
-    backend = provider.get_backend(os.getenv("QISKIT_SCALEWAY_BACKEND_NAME", "aer_simulation_pop_c16m128"))
+    backend = provider.get_backend(
+        os.getenv("QISKIT_SCALEWAY_BACKEND_NAME", "aer_simulation_pop_c16m128")
+    )
 
     assert backend is not None
 
@@ -94,16 +96,16 @@ def _get_noise_model():
 
     # Error probabilities (exaggerated to get a noticeable effect for demonstration)
     prob_1 = 0.01  # 1-qubit gate
-    prob_2 = 0.1   # 2-qubit gate
+    prob_2 = 0.1  # 2-qubit gate
 
     # Depolarizing quantum errors
     error_1 = noise.depolarizing_error(prob_1, 1)
     error_2 = noise.depolarizing_error(prob_2, 2)
 
     # Add errors to noise model
     noise_model = noise.NoiseModel()
-    noise_model.add_all_qubit_quantum_error(error_1, ['rz', 'sx', 'x'])
-    noise_model.add_all_qubit_quantum_error(error_2, ['cx'])
+    noise_model.add_all_qubit_quantum_error(error_1, ["rz", "sx", "x"])
+    noise_model.add_all_qubit_quantum_error(error_2, ["cx"])
 
     return noise_model
 
@@ -131,7 +133,9 @@ def test_aer_with_noise_model():
         url=os.getenv("QISKIT_SCALEWAY_API_URL"),
     )
 
-    backend = provider.get_backend(os.getenv("QISKIT_SCALEWAY_BACKEND_NAME", "aer_simulation_pop_c16m128"))
+    backend = provider.get_backend(
+        os.getenv("QISKIT_SCALEWAY_BACKEND_NAME", "aer_simulation_pop_c16m128")
+    )
 
     assert backend is not None
 
@@ -159,7 +163,7 @@ def test_aer_with_noise_model():
             shots=1000,
             max_parallel_experiments=0,
             session_id=session_id,
-            noise_model=_get_noise_model()
+            noise_model=_get_noise_model(),
         ).result()
 
         ideal_results = run_ideal_result.results

tests/test_estimator.py

@@ -32,7 +32,9 @@ def test_estimator():
         url=os.getenv("QISKIT_SCALEWAY_API_URL"),
     )
 
-    backend = provider.get_backend(os.getenv("QISKIT_SCALEWAY_BACKEND_NAME", "aer_simulation_pop_c16m128"))
+    backend = provider.get_backend(
+        os.getenv("QISKIT_SCALEWAY_BACKEND_NAME", "aer_simulation_pop_c16m128")
+    )
 
     assert backend is not None
 

tests/test_qsim_simple_circuit.py

@@ -25,7 +25,9 @@ def test_qsim_simple_circuit():
         url=os.getenv("QISKIT_SCALEWAY_API_URL"),
     )
 
-    backend = provider.get_backend(os.getenv("QSIM_SCALEWAY_BACKEND_NAME", "qsim_simulation_pop_c16m128"))
+    backend = provider.get_backend(
+        os.getenv("QSIM_SCALEWAY_BACKEND_NAME", "qsim_simulation_pop_c16m128")
+    )
 
     assert backend is not None
 

tests/test_sampler.py

@@ -29,7 +29,9 @@ def test_sampler():
         url=os.getenv("QISKIT_SCALEWAY_API_URL"),
     )
 
-    backend = provider.get_backend(os.getenv("QISKIT_SCALEWAY_BACKEND_NAME", "aer_simulation_pop_c16m128"))
+    backend = provider.get_backend(
+        os.getenv("QISKIT_SCALEWAY_BACKEND_NAME", "aer_simulation_pop_c16m128")
+    )
 
     assert backend is not None
 
@@ -49,8 +51,6 @@ def test_sampler():
         circuit = iqp(mat)
         circuit.measure_all()
 
-        # isa_circuit = transpile(circuit, backend=backend, optimization_level=1)
-        # job = sampler.run([isa_circuit], shots=100)
         job = sampler.run([circuit], shots=100)
         result = job.result()