Remove qubits from TomographyExperiment

forest/benchmarking/direct_fidelity_estimation.py

@@ -145,7 +145,7 @@ def generate_exhaustive_process_dfe_experiment(program: Program, qubits: list,
                         qubits=qubits,
                         in_states=[None, plusX, minusX, plusY, minusY, plusZ, minusZ],
                         benchmarker=benchmarker)),
-        program=program, qubits=qubits)
+        program=program)
     return expr
 
 
@@ -184,7 +184,7 @@ def generate_exhaustive_state_dfe_experiment(program: Program, qubits: list,
                         qubits=qubits,
                         in_states=[None, plusZ],
                         benchmarker=benchmarker)),
-        program=program, qubits=qubits)
+        program=program)
     return expr
 
 
@@ -253,7 +253,7 @@ def generate_monte_carlo_state_dfe_experiment(program: Program, qubits: List[int
         _monte_carlo_dfe(program=program, qubits=qubits,
                          in_states=[None, plusZ],
                          n_terms=n_terms, benchmarker=benchmarker)),
-        program=program, qubits=qubits)
+        program=program)
     return expr
 
 
@@ -288,7 +288,7 @@ def generate_monte_carlo_process_dfe_experiment(program: Program, qubits: List[i
         _monte_carlo_dfe(program=program, qubits=qubits,
                          in_states=[None, plusX, minusX, plusY, minusY, plusZ, minusZ],
                          n_terms=n_terms, benchmarker=benchmarker)),
-        program=program, qubits=qubits)
+        program=program)
     return expr
 
 
@@ -318,9 +318,9 @@ def acquire_dfe_data(qc: QuantumComputer, expr: TomographyExperiment, n_shots=10
                    program=expr.program,
                    out_pauli=[str(e[0].out_operator) for e in expr],
                    pauli_point_est=np.array([r.expectation for r in res]),
-                   pauli_std_err=np.array([r.stddev for r in res]),
+                   pauli_std_err=np.array([r.std_err for r in res]),
                    cal_point_est=np.array([r.calibration_expectation for r in res]),
-                   cal_std_err=np.array([r.calibration_stddev for r in res]),
+                   cal_std_err=np.array([r.calibration_std_err for r in res]),
                    dimension=2**len(expr.qubits),
                    qubits=expr.qubits)
 

forest/benchmarking/randomized_benchmarking.py

@@ -287,7 +287,7 @@ def run(qc: QuantumComputer, seq: List[Program], subgraph: List[List[int]], num_
             _rs = list(measure_observables(qc, tomo_exp, num_trials))
             # Inelegant shim from state tomo refactor. To clean up!
             expectations=[r.expectation for r in _rs[1:]]
-            variances=[r.stddev ** 2 for r in _rs[1:]]
+            variances=[r.std_err ** 2 for r in _rs[1:]]
             results.append((expectations, variances))
         return results
 

forest/benchmarking/tests/test_process_tomography.py

@@ -114,7 +114,7 @@ def wfn_measure_observables(n_qubits, tomo_expt: TomographyExperiment):
             yield ExperimentResult(
                 setting=setting,
                 expectation=wfn.reset().do_program(prog).expectation(setting.out_operator),
-                stddev=0.,
+                std_err=0.,
                 total_counts=1,  # don't set to zero unless you want nans
             )
 

forest/benchmarking/tomography.py

@@ -74,7 +74,7 @@ def generate_state_tomography_experiment(program: Program, qubits: List[int]):
     :param qubits: The qubits to tomographize
     """
     return PyQuilTomographyExperiment(settings=list(_state_tomo_settings(qubits)),
-                                      program=program, qubits=qubits)
+                                      program=program)
 
 
 def _sic_process_tomo_settings(qubits: Sequence[int]):
@@ -144,7 +144,7 @@ def generate_process_tomography_experiment(program: Program, qubits: List[int],
     else:
         raise ValueError(f"Unknown basis {in_basis}")
 
-    return PyQuilTomographyExperiment(settings=list(func(qubits)), program=program, qubits=qubits)
+    return PyQuilTomographyExperiment(settings=list(func(qubits)), program=program)
 
 
 @dataclass
@@ -181,7 +181,7 @@ def shim_pyquil_results_to_TomographyData(program, qubits, results: List[Experim
         in_ops=[r.setting.in_operator for r in results[1:]],
         out_ops=[r.setting.out_operator for r in results[1:]],
         expectations=[r.expectation for r in results[1:]],
-        variances=[r.stddev ** 2 for r in results[1:]],
+        variances=[r.std_err ** 2 for r in results[1:]],
         program=program,
         number_qubits=len(qubits),
         dimension=2 ** len(qubits),
@@ -858,7 +858,7 @@ def _resample_expectations_with_beta(results, prior_counts=1):
         resampled_results += [ExperimentResult(
             setting=result.setting,
             expectation=resampled_expect,
-            stddev=result.stddev,
+            std_err=result.std_err,
             total_counts=result.total_counts,
         )]
     return resampled_results

requirements.txt

@@ -1,4 +1,4 @@
-pyquil>=2.4.0
+pyquil>=2.7.0
 numpy
 networkx
 pandas

setup.py

@@ -50,7 +50,7 @@ def find_forest_packages():
     long_description_content_type="text/markdown",
     long_description=open('README.md').read(),
     install_requires=[
-        'pyquil>=2.4.0',
+        'pyquil>=2.7.0',
         'numpy',
         'networkx',
         'pandas',