QCQMC notebook refactor

conftest.py

@@ -11,12 +11,13 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Tuple
+import pathlib
+from typing import Dict, Tuple
 
 import numpy as np
 import pytest
 
-from recirq.qcqmc import blueprint, qubit_maps
+from recirq.qcqmc import analysis, blueprint, data, experiment, qubit_maps
 from recirq.qcqmc.hamiltonian import (
     HamiltonianData,
     HamiltonianFileParams,
@@ -30,9 +31,18 @@
 
 
 @pytest.fixture(scope="package")
-def fixture_4_qubit_ham() -> HamiltonianData:
+def package_tmp_path(tmp_path_factory: pytest.TempPathFactory) -> pathlib.Path:
+    return tmp_path_factory.mktemp("data", numbered=True)
+
+
+@pytest.fixture(scope="package")
+def fixture_4_qubit_ham(package_tmp_path) -> HamiltonianData:
     params = HamiltonianFileParams(
-        name="test hamiltonian 4 qubits", integral_key="fh_sto3g", n_orb=2, n_elec=2
+        name="test hamiltonian 4 qubits",
+        integral_key="fh_sto3g",
+        n_orb=2,
+        n_elec=2,
+        path_prefix=str(package_tmp_path),
     )
 
     hamiltonian_data = build_hamiltonian_from_file(params)
@@ -41,9 +51,13 @@ def fixture_4_qubit_ham() -> HamiltonianData:
 
 
 @pytest.fixture(scope="package")
-def fixture_8_qubit_ham() -> HamiltonianData:
+def fixture_8_qubit_ham(package_tmp_path) -> HamiltonianData:
     params = HamiltonianFileParams(
-        name="test hamiltonian 8 qubits", integral_key="h4_sto3g", n_orb=4, n_elec=4
+        name="test hamiltonian 8 qubits",
+        integral_key="h4_sto3g",
+        n_orb=4,
+        n_elec=4,
+        path_prefix=str(package_tmp_path),
     )
 
     hamiltonian_data = build_hamiltonian_from_file(params)
@@ -52,13 +66,14 @@ def fixture_8_qubit_ham() -> HamiltonianData:
 
 
 @pytest.fixture(scope="package")
-def fixture_12_qubit_ham() -> HamiltonianData:
+def fixture_12_qubit_ham(package_tmp_path) -> HamiltonianData:
     params = HamiltonianFileParams(
         name="test hamiltonian 12 qubits",
         integral_key="diamond_dzvp/cas66",
         n_orb=6,
         n_elec=6,
         do_eri_restore=True,
+        path_prefix=str(package_tmp_path),
     )
 
     hamiltonian_data = build_hamiltonian_from_file(params)
@@ -76,6 +91,7 @@ def fixture_4_qubit_ham_and_trial_wf(
         heuristic_layers=tuple(),
         do_pp=True,
         restricted=True,
+        path_prefix=fixture_4_qubit_ham.params.path_prefix,
     )
 
     trial_wf = build_pp_plus_trial_wavefunction(
@@ -96,6 +112,7 @@ def fixture_8_qubit_ham_and_trial_wf(
         initial_orbital_rotation=None,
         initial_two_body_qchem_amplitudes=np.asarray([0.3, 0.4]),
         do_optimization=False,
+        path_prefix=fixture_8_qubit_ham.params.path_prefix,
     )
 
     trial_wf = build_pp_plus_trial_wavefunction(
@@ -120,6 +137,7 @@ def fixture_4_qubit_ham_trial_wf_and_blueprint(
             tuple(qubit_maps.get_qubits_a_b_reversed(n_orb=trial_wf_params.n_orb)),
         ),
         seed=1,
+        path_prefix=ham_data.params.path_prefix,
     )
 
     bp = blueprint.BlueprintData.build_blueprint_from_dependencies(
@@ -129,6 +147,51 @@ def fixture_4_qubit_ham_trial_wf_and_blueprint(
     return ham_data, trial_wf_data, bp
 
 
+@pytest.fixture(scope="package")
+def fixture_4_qubit_ham_trial_wf_and_overlap_analysis(
+    fixture_4_qubit_ham_trial_wf_and_blueprint,
+) -> Tuple[HamiltonianData, TrialWavefunctionData, analysis.OverlapAnalysisData]:
+    """Construct fixtures for the hamiltonian, trial wavefunction and overlap analysis.
+
+    Returns:
+        ham_data: The hamiltonian for the 4 qubit test system.
+        trial_wf_data: The trial wavefunction data for the 4 qubit system.
+        ovlp_analysis: The overlap analysis data used to reconstruct the
+            wavefunction via shadow tomography.
+    """
+    ham_data, trial_wf_data, bp_data = fixture_4_qubit_ham_trial_wf_and_blueprint
+    simulated_experiment_params = experiment.SimulatedExperimentParams(
+        name="test_1",
+        blueprint_params=bp_data.params,
+        noise_model_name="None",
+        noise_model_params=(0,),
+        n_samples_per_clifford=10,
+        seed=1,
+        path_prefix=ham_data.params.path_prefix,
+    )
+    exp = experiment.ExperimentData.build_experiment_from_dependencies(
+        params=simulated_experiment_params, dependencies={bp_data.params: bp_data}
+    )
+
+    analysis_params = analysis.OverlapAnalysisParams(
+        "TEST_analysis",
+        experiment_params=exp.params,
+        k_to_calculate=(1,),
+        path_prefix=ham_data.params.path_prefix,
+    )
+    all_dependencies: Dict[data.Params, data.Data] = {
+        ham_data.params: ham_data,
+        trial_wf_data.params: trial_wf_data,
+        bp_data.params: bp_data,
+        simulated_experiment_params: exp,
+    }
+    ovlp_analysis = analysis.OverlapAnalysisData.build_analysis_from_dependencies(
+        analysis_params, dependencies=all_dependencies
+    )
+
+    return ham_data, trial_wf_data, ovlp_analysis
+
+
 def pytest_addoption(parser):
     parser.addoption("--skipslow", action="store_true", help="skips slow tests")
 

docs/qcqmc/index.md

@@ -0,0 +1,26 @@
+# QCQMC
+
+Notebooks outlining how to reproduce the results of [Unbiasing fermionic quantum Monte Carlo with a quantum computer](https://www.nature.com/articles/s41586-021-04351-z).
+Quantum Monte Carlo methods are a class of classical algorithms that can offer
+an efficient solution to the many-electron schroedinger equation but are plagued
+by the `fermion sign problem`. Typically, a constraint is introduced to overcome
+this problem at the cost of introducing an uncontrolled bias in the results. In
+this paper, it was shown that a quantum computer could be used to prepare
+complicated trial wavefunctions in order to unbias the classical results. 
+
+## Code Overview
+The [Code Overview](./high-level.ipynb) notebook introduces the basic structure
+of the code provided in recirq to generate the trial wavefunction's prepare in the [QCQMC paper](https://www.nature.com/articles/s41586-021-04351-z).
+
+## End-to-End
+The [End-to-End](./full_workflow.ipynb) notebook provides and end-to-end example
+for the H4 molecule and interfaces with ipie to produce numbers similar to those
+reported in the [QCQMC](https://www.nature.com/articles/s41586-021-04351-z)
+paper.
+
+
+## Experimental Wavefunctions
+
+The [Experimental Wavefunctions](./experimental_wavefunctions.ipynb) notebook demonstrates
+how to download and analyze the experimental wavefunctions, which can reproduce
+the results in [QCQMC](https://www.nature.com/articles/s41586-021-04351-z).

recirq/qcqmc/__init__.py

@@ -54,6 +54,11 @@ def _resolve_json(cirq_type: str) -> Optional[ObjectFactory]:
             PyscfHamiltonianParams,
             SimulatedExperimentParams,
             TrialWavefunctionData,
+            BlueprintParamsTrialWf,
+            BlueprintParamsRobustShadow,
+            BlueprintData,
+            ExperimentData,
+            SimulatedExperimentParams,
         ]
     }.get(cirq_type, None)
 

recirq/qcqmc/analysis.py

@@ -48,7 +48,7 @@ class OverlapAnalysisParams(data.Params):
     name: str
     experiment_params: experiment.SimulatedExperimentParams
     k_to_calculate: Tuple[int, ...] = attrs.field(converter=tuple)
-    path_prefix: str = ""
+    path_prefix: str = "."
 
     def __attrs_post_init__(self):
         if not isinstance(

recirq/qcqmc/blueprint.py

@@ -19,7 +19,7 @@
 import numpy as np
 import quaff
 
-from recirq.qcqmc import config, data, trial_wf, for_refactor
+from recirq.qcqmc import config, data, for_refactor, trial_wf
 
 BlueprintParams = Union["BlueprintParamsTrialWf", "BlueprintParamsRobustShadow"]
 
@@ -132,7 +132,7 @@ class BlueprintParamsTrialWf(data.Params):
     )
     seed: int = 0
     optimizer_suite: int = 0
-    path_prefix: str = ""
+    path_prefix: str = "."
 
     @property
     def path_string(self) -> str:
@@ -190,6 +190,7 @@ class BlueprintData(data.Data):
     def _json_dict_(self):
         simple_dict = attrs.asdict(self)
         simple_dict["params"] = self.params
+        return simple_dict
 
     @property
     def resolved_clifford_circuits(self) -> Iterator[Tuple[cirq.Circuit, ...]]:

recirq/qcqmc/blueprint_test.py

@@ -18,14 +18,12 @@
 import pytest
 import quaff
 
-from recirq.qcqmc.blueprint import (
-    BlueprintParamsTrialWf,
-    _get_truncated_cliffords,
-    BlueprintData
-)
+from recirq.qcqmc.blueprint import (BlueprintData, BlueprintParamsTrialWf,
+                                    _get_truncated_cliffords)
 from recirq.qcqmc.hamiltonian import HamiltonianData, HamiltonianFileParams
 from recirq.qcqmc.qubit_maps import get_qubits_a_b_reversed
-from recirq.qcqmc.trial_wf import TrialWavefunctionData, TrialWavefunctionParams
+from recirq.qcqmc.trial_wf import (TrialWavefunctionData,
+                                   TrialWavefunctionParams)
 
 
 class FakeTrialWfParams(TrialWavefunctionParams):

recirq/qcqmc/config.py

@@ -22,12 +22,12 @@
 class OutputDirectories:
     """Default output directories for qcqmc data."""
 
-    DEFAULT_HAMILTONIAN_DIRECTORY: str = "./data/hamiltonians/"
-    DEFAULT_TRIAL_WAVEFUNCTION_DIRECTORY: str = "./data/trial_wfs/"
-    DEFAULT_QMC_DIRECTORY: str = "./data/afqmc/"
-    DEFAULT_BLUEPRINT_DIRECTORY: str = "./data/blueprints/"
-    DEFAULT_EXPERIMENT_DIRECTORY: str = "./data/experiments/"
-    DEFAULT_ANALYSIS_DIRECTORY: str = "./data/analyses/"
+    DEFAULT_HAMILTONIAN_DIRECTORY: str = "/data/hamiltonians/"
+    DEFAULT_TRIAL_WAVEFUNCTION_DIRECTORY: str = "/data/trial_wfs/"
+    DEFAULT_QMC_DIRECTORY: str = "/data/afqmc/"
+    DEFAULT_BLUEPRINT_DIRECTORY: str = "/data/blueprints/"
+    DEFAULT_EXPERIMENT_DIRECTORY: str = "/data/experiments/"
+    DEFAULT_ANALYSIS_DIRECTORY: str = "/data/analyses/"
 
     def make_output_directories(self) -> None:
         """Make the output directories given in OUTDIRS"""