Fix bug in result creation and add instantiation of EFGSS to how-to

circuit_knitting/forging/__init__.py

@@ -25,6 +25,7 @@
    EntanglementForgingOperator
    EntanglementForgingAnsatz
    EntanglementForgingGroundStateSolver
+   EntanglementForgingResult
 
 Decomposition Functions
 =======================
@@ -43,6 +44,7 @@
 from .entanglement_forging_operator import EntanglementForgingOperator
 from .entanglement_forging_ground_state_solver import (
     EntanglementForgingGroundStateSolver,
+    EntanglementForgingResult,
 )
 from .cholesky_decomposition import cholesky_decomposition, convert_cholesky_operator
 
@@ -51,6 +53,7 @@
     "EntanglementForgingKnitter",
     "EntanglementForgingOperator",
     "EntanglementForgingGroundStateSolver",
+    "EntanglementForgingResult",
     "cholesky_decomposition",
     "convert_cholesky_operator",
 ]

circuit_knitting/forging/entanglement_forging_ground_state_solver.py

@@ -25,7 +25,6 @@
 import scipy
 import numpy as np
 
-from qiskit.algorithms.minimum_eigensolvers import MinimumEigensolverResult
 from qiskit.algorithms.optimizers import SPSA, Optimizer, OptimizerResult
 from qiskit_nature.second_q.problems import (
     ElectronicStructureProblem,
@@ -317,14 +316,11 @@ def solve(
 
         # Create the EntanglementForgingResult from the results from the
         # results of eigenvalue minimization and other meta information
-        min_eigsolver_result = MinimumEigensolverResult()
-        min_eigsolver_result.eigenvalue = optimal_evaluation.eigenvalue
-        min_eigsolver_result.eigenstate = optimal_evaluation.eigenstate
-        result = EntanglementForgingResult.from_minimum_eigensolver_result(
-            min_eigsolver_result
-        )
-        result.energy_shift = self._energy_shift
+        result = EntanglementForgingResult()
+        result.eigenvalues = np.asarray([optimal_evaluation.eigenvalue])
+        result.eigenstates = [(optimal_evaluation.eigenstate, None)]
         result.history = self._history.evaluations
+        result.energy_shift = self._energy_shift
         result.elapsed_time = elapsed_time
 
         # Close any runtime sessions

docs/entanglement_forging/how-tos/freeze-orbitals.ipynb

@@ -9,18 +9,9 @@
     "In this guide, we apply Entanglement Forging to compute the energy of a $\\mathrm{H}_2\\mathrm{O}$ molecule. We reduce the number of orbitals in the problem, in turn reducing the number of qubits needed in each circuit, following the logic given in the [explanatory material](../explanation/index.rst)."
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Import the relevant modules\n",
-    "\n",
-    "First, we import the relevant modules.  The imports are similar to the introductory tutorial, but this time, we also import the `reduce_bitstrings` function from `circuit_knitting.utils`."
-   ]
-  },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2021-04-27T13:41:07.878080Z",
@@ -33,11 +24,12 @@
     "import numpy as np\n",
     "\n",
     "from qiskit.circuit import QuantumCircuit, Parameter\n",
+    "from qiskit.algorithms.optimizers import COBYLA\n",
     "from qiskit_nature.second_q.drivers import PySCFDriver\n",
-    "from qiskit_nature.second_q.problems import ElectronicBasis\n",
     "\n",
     "from circuit_knitting.forging import (\n",
     "    EntanglementForgingAnsatz,\n",
+    "    EntanglementForgingGroundStateSolver,\n",
     ")\n",
     "from circuit_knitting.utils import reduce_bitstrings"
    ]
@@ -70,11 +62,12 @@
     "H2_x = radius_2 * np.cos(np.pi / 180 * thetas_in_deg)\n",
     "H2_y = radius_2 * np.sin(np.pi / 180 * thetas_in_deg)\n",
     "\n",
+    "# Create an ElectronicStructureProblem from the molecule using PySCFDriver\n",
     "driver = PySCFDriver(\n",
     "    f\"O 0.0 0.0 0.0; H {H1_x} 0.0 0.0; H {H2_x} {H2_y} 0.0\", basis=\"sto6g\"\n",
     ")\n",
     "driver.run()\n",
-    "problem = driver.to_problem(basis=ElectronicBasis.AO)"
+    "problem = driver.to_problem()"
    ]
   },
   {
@@ -84,13 +77,6 @@
     "### Prepare the bitstrings and the ansatz"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The ansatz for Entanglement Forging consists of a set of input bitstrings and a parameterized circuit. (See the [explanatory material](../explanation/index.rst) section of the documentation for additional background on the method.) For this demo, we will use the same bitstrings and ansatz for both the U and V subsystems. "
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -133,6 +119,13 @@
     "hop_gate.draw()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create the ansatz with a reduced set of bitstrings."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 4,
@@ -201,18 +194,40 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "From here, the problem can be solved following the same steps as in the [tutorials](../tutorials/index.rst)."
+    "Create the ``EntanglementForgingGroundStateSolver``, and specify which orbitals to reduce in the observable."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "optimizer = COBYLA(maxiter=100)\n",
+    "\n",
+    "solver = EntanglementForgingGroundStateSolver(\n",
+    "    ansatz=ansatz,\n",
+    "    optimizer=optimizer,\n",
+    "    orbitals_to_reduce=orbitals_to_reduce,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From here, the problem can be solved following the same steps as in the [tutorials](../tutorials/index.rst)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td><code>qiskit-terra</code></td><td>0.23.3</td></tr><tr><td><code>qiskit-aer</code></td><td>0.12.0</td></tr><tr><td><code>qiskit-ibmq-provider</code></td><td>0.20.2</td></tr><tr><td><code>qiskit-nature</code></td><td>0.5.2</td></tr><tr><th>System information</th></tr><tr><td>Python version</td><td>3.8.16</td></tr><tr><td>Python compiler</td><td>Clang 14.0.6 </td></tr><tr><td>Python build</td><td>default, Mar  1 2023 21:19:10</td></tr><tr><td>OS</td><td>Darwin</td></tr><tr><td>CPUs</td><td>8</td></tr><tr><td>Memory (Gb)</td><td>32.0</td></tr><tr><td colspan='2'>Tue Apr 11 19:14:09 2023 CDT</td></tr></table>"
+       "<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td><code>qiskit-terra</code></td><td>0.24.0</td></tr><tr><td><code>qiskit-aer</code></td><td>0.12.0</td></tr><tr><td><code>qiskit-ibmq-provider</code></td><td>0.20.2</td></tr><tr><td><code>qiskit-nature</code></td><td>0.6.0</td></tr><tr><th>System information</th></tr><tr><td>Python version</td><td>3.8.16</td></tr><tr><td>Python compiler</td><td>Clang 14.0.6 </td></tr><tr><td>Python build</td><td>default, Mar  1 2023 21:19:10</td></tr><tr><td>OS</td><td>Darwin</td></tr><tr><td>CPUs</td><td>8</td></tr><tr><td>Memory (Gb)</td><td>32.0</td></tr><tr><td colspan='2'>Sat Jun 17 11:51:45 2023 CDT</td></tr></table>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"

releasenotes/notes/ef-results-bug-5aa84ca5611dd827.yaml

@@ -0,0 +1,6 @@
+---
+fixes:
+  - |
+    Fixed a bug in :class:`~circuit_knitting.forging.EntanglementForgingGroundStateSolver` which was causing
+    AttributeErrors when instantiating the `~circuit_knitting.forging.EntanglementForgingResult` in certain
+    conditions, such as when reducing the orbitals over which to solve.

test/forging/test_entanglement_forging_ground_state_solver.py

@@ -70,6 +70,7 @@ def test_entanglement_forging_vqe_hydrogen(self):
         # Solve for the ground state energy
         results = solver.solve(problem)
         ground_state_energy = results.groundenergy + results.energy_shift
-
+        print(results.groundenergy)
+        print(results.energy_shift)
         # Ensure ground state energy output is within tolerance
         self.assertAlmostEqual(ground_state_energy, -1.121936544469326)