Merge pull request #621 from haimeng-zhang/upgrade-to-qiskit-1.2

Update to use qiskit-ibm-runtime and qiskit >= 1.2

_common/qiskit/execute.py

@@ -149,10 +149,9 @@ def __init__(self, qiskit_result):
     def get_counts(self, qc=0):
         # counts= self.qiskit_result.quasi_dists[0].binary_probabilities()
         # for key in counts.keys():
-        #     counts[key] = int(counts[key] * self.qiskit_result.metadata[0]['shots'])        
+        #     counts[key] = int(counts[key] * self.qiskit_result.metadata[0]['shots'])
         qc_index = 0 # this should point to the index of the circuit in a pub
-        register_name = list(self.qiskit_result[qc_index].data.keys())[0]
-        bitvals = getattr(self.qiskit_result[qc_index].data, register_name)
+        bitvals = next(iter(self.qiskit_result[qc_index].data.values()))
         counts = bitvals.get_counts()
         return counts
 
@@ -254,6 +253,7 @@ def set_execution_target(backend_id='qasm_simulator',
                         provider_name='Quantinuum')
     """
     global backend
+    global sampler
     global session
     global use_sessions
     global session_count
@@ -295,7 +295,11 @@ def set_execution_target(backend_id='qasm_simulator',
     # handle Statevector simulator specially
     elif backend_id == 'statevector_simulator':
         backend = Aer.get_backend("statevector_simulator")
-
+
+    elif backend_id == "statevector_sampler":
+        from qiskit.primitives import StatevectorSampler
+        sampler = StatevectorSampler()
+
     # handle 'fake' backends here
     elif 'fake' in backend_id:
         backend = getattr(
@@ -310,7 +314,6 @@ def set_execution_target(backend_id='qasm_simulator',
     # otherwise use the given providername or backend_id to find the backend
     else:
         global service
-        global sampler
 
         # if provider_module name and provider_name are provided, obtain a custom provider
         if provider_module_name and provider_name:  
@@ -389,8 +392,8 @@ def set_execution_target(backend_id='qasm_simulator',
 
                     # get Sampler resilience level and transpiler optimization level from exec_options
                     options = Options()
-                    options.resilience_level = exec_options.get("resilience_level", 1)
-                    options.optimization_level = exec_options.get("optimization_level", 3)
+                    # options.resilience_level = exec_options.get("resilience_level", 1)
+                    # options.optimization_level = exec_options.get("optimization_level", 3)
 
                     # special handling for ibmq_qasm_simulator to set noise model
                     if backend_id == "ibmq_qasm_simulator":
@@ -430,11 +433,10 @@ def set_execution_target(backend_id='qasm_simulator',
             from qiskit_ibm_runtime import QiskitRuntimeService, Session, SamplerOptions as Options, SamplerV2 as Sampler
 
             # create the Runtime Service object
-            service = QiskitRuntimeService(instance=f'{hub}/{group}/{project}')
-            print(f'setting instance {hub}/{group}/{project}')
+            service = QiskitRuntimeService()
             # obtain a backend from the service
             backend = service.backend(backend_id)
-               
+
             # DEVNOTE: here we assume if the sessions flag is set, we use Sampler
             # however, we may want to add a use_sampler option so that we can separate these
 
@@ -679,7 +681,7 @@ def execute_circuit(circuit):
 
             #************************************************
             # Initiate execution (with noise if specified and this is a simulator backend)
-            if this_noise is not None and not use_sessions and backend_name.endswith("qasm_simulator"):
+            if this_noise is not None and not sampler and backend_name.endswith("qasm_simulator"):
                 logger.info(f"Performing noisy simulation, shots = {shots}")
 
                 # if the noise model has associated QV value, copy it to metrics module for plotting
@@ -754,9 +756,9 @@ def execute_circuit(circuit):
                 logger.info(f'Running trans_qc, shots={shots}')
                 st = time.time() 
 
-                if use_sessions:
+                if sampler:
                     # turn input into pub-like
-                    job = sampler.run([trans_qc], shots=shots, **backend_exec_options_copy)
+                    job = sampler.run([trans_qc], shots=shots)
                 else:
                     job = backend.run(trans_qc, shots=shots, **backend_exec_options_copy)
 
@@ -1133,16 +1135,15 @@ def job_complete(job):
         # if we are using sessions, structure of result object is different;
         # use a BenchmarkResult object to hold session result and provide a get_counts()
         # that returns counts to the benchmarks in the same form as without sessions
-        if use_sessions:
+        if sampler:
             result = BenchmarkResult(result)
             #counts = result.get_counts()
 
             # actual_shots = result.metadata[0]['shots']
             # get the name of the classical register
             # TODO: need to rewrite to allow for submit multiple circuits in one job
-            register_name = list(result.qiskit_result[0].data.keys())[0]
             # get DataBin associated with the classical register
-            bitvals = getattr(result.qiskit_result[0].data, register_name)
+            bitvals = next(iter(result.qiskit_result[0].data.values()))
             actual_shots = bitvals.num_shots
             result_obj = result.metadata # not sure how to update to be V2 compatible
             results_obj = result.metadata

monte-carlo/qiskit/mc_benchmark.py

@@ -120,7 +120,7 @@ def square_on_objective(qc, qr):
         qc.cx(control, num_state_qubits)
 
 def state_prep(qc, qr, target_dist, num_state_qubits):
-    """
+    r"""
     Use controlled Ry gates to construct the superposition Sum \sqrt{p_i} |i>
     """
     r_probs = mc_utils.region_probs(target_dist, num_state_qubits)
@@ -505,7 +505,7 @@ def get_args():
     parser.add_argument("--skip_qubits", "-k", default=1, help="Number of qubits to skip", type=int)
     parser.add_argument("--max_circuits", "-c", default=3, help="Maximum circuit repetitions", type=int)  
     parser.add_argument("--method", "-m", default=1, help="Algorithm Method", type=int)
-    parser.add_argument("--num_state_qubits", "-nsq", default=0.0, help="Number of State Qubits", type=int)
+    parser.add_argument("--num_state_qubits", "-nsq", default=1, help="Number of State Qubits", type=int)
     parser.add_argument("--nonoise", "-non", action="store_true", help="Use Noiseless Simulator")
     parser.add_argument("--verbose", "-v", action="store_true", help="Verbose")
     return parser.parse_args()

quantum-fourier-transform/qiskit/qft_benchmark.py

@@ -131,7 +131,8 @@ def QuantumFourierTransform (num_qubits, secret_int, method=1):
 
 def qft_gate(input_size):
     global QFT_, num_gates, depth
-    qr = QuantumRegister(input_size); qc = QuantumCircuit(qr, name="qft")
+    # avoid name "qft" as workaround of https://github.com/Qiskit/qiskit/issues/13174
+    qr = QuantumRegister(input_size); qc = QuantumCircuit(qr, name="qft_")
 
     # Generate multiple groups of diminishing angle CRZs and H gate
     for i_qubit in range(0, input_size):

shors/qiskit/shors_benchmark.py

@@ -338,7 +338,7 @@ def analyze_and_print_result(qc, result, num_qubits, order, num_shots, method):
 
 # Execute program with default parameters
 def run (min_qubits=3, max_circuits=1, max_qubits=18, num_shots=100, method = 1,
-        verbose=verbose, backend_id='qasm_simulator', provider_backend=None,
+        verbose=verbose, backend_id='statevector_sampler', provider_backend=None,
         hub="ibm-q", group="open", project="main", exec_options=None,
         context=None):