Adding AFQMC tutorial

.github/workflows/config/spelling_allowlist.txt

@@ -1,4 +1,5 @@
 ABI
+AFQMC
 API
 APIs
 AST
@@ -48,7 +49,9 @@ JupyterLab
 Kagome
 Kraus
 LLVM
+LPX
 LSB
+LXmn
 Libraries
 MCA
 MLIR
@@ -153,6 +156,7 @@ coreset
 cortex-cli
 coupler
 couplers
+cpp
 cuQuantum
 cuTensor
 cudaq
@@ -212,6 +216,7 @@ instantiations
 interferometer
 interoperational
 intrinsics
+ipie
 iterable
 iteratively
 kets
@@ -230,13 +235,20 @@ namespace
 namespaces
 natively
 normalization
+np
 nullary
+nvidia
+occa
+occb
+openfermion
 optimizer
 optimizers
 parallelization
 parallelize
 parallelizing
+param
 parameterization
+params
 performant
 photonic
 precompute
@@ -246,6 +258,7 @@ preprocessor
 probability
 programmatically
 pybind
+pyscf
 quantize
 quantized
 qubit

.github/workflows/python_wheels.yml

@@ -316,7 +316,7 @@ jobs:
  docker run --rm -dit --name wheel-validation-examples wheel_validation:local
  status_sum=0
 
- for ex in `find docs/sphinx/examples/python -name '*.py' -not -path '*/providers/*' -not -path '*/divisive_clustering_src/*'`; do
+ for ex in `find docs/sphinx/examples/python -name '*.py' -not -path '*/providers/*' -not -path '*/divisive_clustering_src/*' -not -path '*/utils_ipie.py' -not -path '*/vqe_cudaq_qnp.py'`; do
  file="${ex#docs/sphinx/examples/python/}"
  echo "__Example ${file}:__" >> /tmp/validation.out
  (docker exec wheel-validation-examples bash -c "python${{ inputs.python_version }} /tmp/examples/$file" >> /tmp/validation.out) && success=true || success=false

docs/notebook_validation.py

@@ -35,6 +35,10 @@ def validate(notebook_filename, available_backends):
  match = re.search('--target ([^ ]+)', notebook_content)
  if match and (match.group(1) not in available_backends):
  return False
+ for notebook_content in lines:
+ match = re.search('(config.update_option)', notebook_content)
+ if match and match.group(1):
+ return False
  return True
 
 

docs/sphinx/examples/python/tutorials/readout_error_mitigation.ipynb

@@ -29,7 +29,60 @@
  "execution_count": 1,
  "id": "04b58854-7dab-4f1b-8c59-d8b9506bce44",
  "metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Requirement already satisfied: matplotlib==3.8.4 in /usr/local/lib/python3.10/dist-packages (3.8.4)\n",
+ "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.8.4) (1.4.5)\n",
+ "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.8.4) (24.0)\n",
+ "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.8.4) (3.1.2)\n",
+ "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.8.4) (0.12.1)\n",
+ "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.8.4) (1.2.1)\n",
+ "Requirement already satisfied: numpy>=1.21 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.8.4) (1.26.4)\n",
+ "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.8.4) (2.9.0.post0)\n",
+ "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.8.4) (4.51.0)\n",
+ "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.10/dist-packages (from matplotlib==3.8.4) (10.3.0)\n",
+ "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib==3.8.4) (1.16.0)\n",
+ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+ "\u001b[0mRequirement already satisfied: pandas==2.2.2 in /usr/local/lib/python3.10/dist-packages (2.2.2)\n",
+ "Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.10/dist-packages (from pandas==2.2.2) (1.26.4)\n",
+ "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas==2.2.2) (2024.1)\n",
+ "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas==2.2.2) (2024.1)\n",
+ "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas==2.2.2) (2.9.0.post0)\n",
+ "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas==2.2.2) (1.16.0)\n",
+ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+ "\u001b[0mCollecting scipy==1.13.1\n",
+ " Using cached scipy-1.13.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (38.6 MB)\n",
+ "Requirement already satisfied: numpy<2.3,>=1.22.4 in /usr/local/lib/python3.10/dist-packages (from scipy==1.13.1) (1.26.4)\n",
+ "Installing collected packages: scipy\n",
+ " Attempting uninstall: scipy\n",
+ " Found existing installation: scipy 1.13.0\n",
+ " Uninstalling scipy-1.13.0:\n",
+ " Successfully uninstalled scipy-1.13.0\n",
+ "Successfully installed scipy-1.13.1\n",
+ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+ "\u001b[0mRequirement already satisfied: seaborn==0.13.2 in /usr/local/lib/python3.10/dist-packages (0.13.2)\n",
+ "Requirement already satisfied: numpy!=1.24.0,>=1.20 in /usr/local/lib/python3.10/dist-packages (from seaborn==0.13.2) (1.26.4)\n",
+ "Requirement already satisfied: matplotlib!=3.6.1,>=3.4 in /usr/local/lib/python3.10/dist-packages (from seaborn==0.13.2) (3.8.4)\n",
+ "Requirement already satisfied: pandas>=1.2 in /usr/local/lib/python3.10/dist-packages (from seaborn==0.13.2) (2.2.2)\n",
+ "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn==0.13.2) (4.51.0)\n",
+ "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn==0.13.2) (1.4.5)\n",
+ "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn==0.13.2) (1.2.1)\n",
+ "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn==0.13.2) (3.1.2)\n",
+ "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn==0.13.2) (0.12.1)\n",
+ "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn==0.13.2) (10.3.0)\n",
+ "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn==0.13.2) (2.9.0.post0)\n",
+ "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib!=3.6.1,>=3.4->seaborn==0.13.2) (24.0)\n",
+ "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.2->seaborn==0.13.2) (2024.1)\n",
+ "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.2->seaborn==0.13.2) (2024.1)\n",
+ "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib!=3.6.1,>=3.4->seaborn==0.13.2) (1.16.0)\n",
+ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+ "\u001b[0m"
+ ]
+ }
+ ],
  "source": [
  "# Install the relevant packages.\n",
  "\n",
@@ -91,12 +144,13 @@
  " Args:\n",
  " n_qubits (int): The number of qubits in the quantum circuit.\n",
  " probs (Union[float, list[float]]): Probabilities of a bit flip error occurring on each qubit.\n",
- " If a single probability value is provided, it will be applied to all qubits. If a list of\n",
- " probabilities is provided, each qubit will have its own probability.\n",
+ "  If a single probability value is provided, it will be applied to all qubits. If a list of\n",
+ "  probabilities is provided, each qubit will have its own probability.\n",
  "\n",
  " Returns:\n",
  " cudaq noise model\n",
  " \"\"\"\n",
+ " \n",
  " noise = cudaq.NoiseModel()\n",
  "\n",
  " if not isinstance(probs, list):\n",
@@ -130,9 +184,7 @@
  " for i, val in enumerate(state_label):\n",
  " if val == 1:\n",
  " x(qvector[i])\n",
- " rx(\n",
- " 0.0, qvector[i]\n",
- " ) # Identity gate at the end on each qubit to model readout error\n",
+ " rx(0.0, qvector[i]) # Identity gate at the end on each qubit to model readout error\n",
  " mz(qvector)"
  ]
  },
@@ -229,8 +281,14 @@
  "\n",
  " # Constraint: all elements of p must be positive, and the distribution must sum to 1\n",
  " cons = (\n",
- " {\"type\": \"ineq\", \"fun\": lambda p: p},\n",
- " {\"type\": \"eq\", \"fun\": lambda p: np.sum(p) - 1},\n",
+ " {\n",
+ " \"type\": \"ineq\",\n",
+ " \"fun\": lambda p: p\n",
+ " },\n",
+ " {\n",
+ " \"type\": \"eq\",\n",
+ " \"fun\": lambda p: np.sum(p) - 1\n",
+ " },\n",
  " )\n",
  " bnds = [(0, 1) for _ in range(len(empirical_dist))]\n",
  " initial_value = np.random.uniform(size=len(empirical_dist))\n",
@@ -332,10 +390,14 @@
  "\n",
  "noise_1 = get_noise(n_qubits, p)\n",
  "\n",
- "ghz_result = cudaq.sample(ghz_kernel, n_qubits, shots_count=shots, noise_model=noise_1)\n",
+ "ghz_result = cudaq.sample(ghz_kernel,\n",
+ " n_qubits,\n",
+ " shots_count=shots,\n",
+ " noise_model=noise_1)\n",
  "noisy_dict_1 = dict(list(ghz_result.items()))\n",
  "\n",
- "noisy_res_1 = np.array([noisy_dict_1.get(state, 0) for i, state in enumerate(states)])\n",
+ "noisy_res_1 = np.array(\n",
+ " [noisy_dict_1.get(state, 0) for i, state in enumerate(states)])\n",
  "\n",
  "noisy_dict_1"
  ]
@@ -378,10 +440,14 @@
  "\n",
  "noise_2 = get_noise(n_qubits, p)\n",
  "\n",
- "ghz_result = cudaq.sample(ghz_kernel, n_qubits, shots_count=shots, noise_model=noise_2)\n",
+ "ghz_result = cudaq.sample(ghz_kernel,\n",
+ " n_qubits,\n",
+ " shots_count=shots,\n",
+ " noise_model=noise_2)\n",
  "noisy_dict_2 = dict(list(ghz_result.items()))\n",
  "\n",
- "noisy_res_2 = np.array([noisy_dict_2.get(state, 0) for i, state in enumerate(states)])\n",
+ "noisy_res_2 = np.array(\n",
+ " [noisy_dict_2.get(state, 0) for i, state in enumerate(states)])\n",
  "\n",
  "noisy_dict_2"
  ]
@@ -485,7 +551,8 @@
  "source": [
  "A = reduce(np.kron, [A_1] * n_qubits) # joint confusion matrix\n",
  "A_pinv = np.linalg.pinv(A) # Generate pseudoinverse confusion matrix.\n",
- "mitigated = np.array(np.dot(A_pinv, noisy_res_1), dtype=int) # Obtain mitigated counts\n",
+ "mitigated = np.array(np.dot(A_pinv, noisy_res_1),\n",
+ " dtype=int) # Obtain mitigated counts\n",
  "print(f\"Mitigated counts:\\n{mitigated}\")\n",
  "\n",
  "if not np.all(mitigated >= 0):\n",
@@ -512,15 +579,16 @@
  }
  ],
  "source": [
- "df = pd.DataFrame(\n",
- " {\n",
- " \"states\": states,\n",
- " \"noisy\": np.around(noisy_res_1 / sum(noisy_res_1), 3),\n",
- " \"mitigated_sg\": np.around(mitigated / sum(mitigated), 3),\n",
- " }\n",
- ")\n",
+ "df = pd.DataFrame({\n",
+ " \"states\": states,\n",
+ " \"noisy\": np.around(noisy_res_1 / sum(noisy_res_1), 3),\n",
+ " \"mitigated_sg\": np.around(mitigated / sum(mitigated), 3),\n",
+ "})\n",
  "\n",
- "ax = df.plot(x=\"states\", y=[\"noisy\", \"mitigated_sg\"], kind=\"bar\", figsize=(8, 5))\n",
+ "ax = df.plot(x=\"states\",\n",
+ " y=[\"noisy\", \"mitigated_sg\"],\n",
+ " kind=\"bar\",\n",
+ " figsize=(8, 5))\n",
  "ax.bar_label(ax.containers[0], labels=df[\"noisy\"])\n",
  "ax.bar_label(ax.containers[1], labels=df[\"mitigated_sg\"])\n",
  "ax.set_ylabel(\"probabilities\")\n",
@@ -561,8 +629,11 @@
  "local_states = [\"0\" * n_qubits, \"1\" * n_qubits]\n",
  "\n",
  "results = [\n",
- " cudaq.sample(kernel, n_qubits, label, shots_count=shots, noise_model=noise_2)\n",
- " for label in local_labels\n",
+ " cudaq.sample(kernel,\n",
+ " n_qubits,\n",
+ " label,\n",
+ " shots_count=shots,\n",
+ " noise_model=noise_2) for label in local_labels\n",
  "]\n",
  "\n",
  "for i, state in enumerate(local_states):\n",
@@ -585,7 +656,9 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "counts = [dict(list(results[i].items())) for i, state in enumerate(local_states)]\n",
+ "counts = [\n",
+ " dict(list(results[i].items())) for i, state in enumerate(local_states)\n",
+ "]\n",
  "matrices = []\n",
  "\n",
  "for k in range(n_qubits):\n",
@@ -600,7 +673,8 @@
  " # matrix[i][j] is the probability of counting i for expected j\n",
  " for i in range(2):\n",
  " for j in range(2):\n",
- " matrix[i][j] = marginalized_counts[j].get(str(i), 0) / total_shots[j]\n",
+ " matrix[i][j] = marginalized_counts[j].get(str(i),\n",
+ " 0) / total_shots[j]\n",
  " matrices.append(matrix)"
  ]
  },
@@ -697,15 +771,16 @@
  }
  ],
  "source": [
- "df = pd.DataFrame(\n",
- " {\n",
- " \"states\": states,\n",
- " \"noisy\": np.around(noisy_res_2 / sum(noisy_res_2), 3),\n",
- " \"mitigated_k_local\": np.around(mitigated / sum(mitigated), 3),\n",
- " }\n",
- ")\n",
+ "df = pd.DataFrame({\n",
+ " \"states\": states,\n",
+ " \"noisy\": np.around(noisy_res_2 / sum(noisy_res_2), 3),\n",
+ " \"mitigated_k_local\": np.around(mitigated / sum(mitigated), 3),\n",
+ "})\n",
  "\n",
- "ax = df.plot(x=\"states\", y=[\"noisy\", \"mitigated_k_local\"], kind=\"bar\", figsize=(8, 5))\n",
+ "ax = df.plot(x=\"states\",\n",
+ " y=[\"noisy\", \"mitigated_k_local\"],\n",
+ " kind=\"bar\",\n",
+ " figsize=(8, 5))\n",
  "ax.bar_label(ax.containers[0], labels=df[\"noisy\"])\n",
  "ax.bar_label(ax.containers[1], labels=df[\"mitigated_k_local\"])\n",
  "ax.set_ylabel(\"probabilities\")\n",
@@ -745,8 +820,11 @@
  ],
  "source": [
  "results = [\n",
- " cudaq.sample(kernel, n_qubits, label, shots_count=shots, noise_model=noise_2)\n",
- " for label in labels\n",
+ " cudaq.sample(kernel,\n",
+ " n_qubits,\n",
+ " label,\n",
+ " shots_count=shots,\n",
+ " noise_model=noise_2) for label in labels\n",
  "]\n",
  "\n",
  "for i, state in enumerate(states):\n",
@@ -866,7 +944,7 @@
  " x=\"states\",\n",
  " y=[\"noisy\", \"mitigated_k_local\", \"mitigated_full\"],\n",
  " kind=\"bar\",\n",
- " figsize=(12, 5),\n",
+ " figsize=(12, 5)\n",
  ")\n",
  "ax.bar_label(ax.containers[0], labels=df[\"noisy\"])\n",
  "ax.bar_label(ax.containers[1], labels=df[\"mitigated_k_local\"])\n",
@@ -892,7 +970,7 @@
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
- "version": "3.10.0"
+ "version": "3.10.12"
  }
  },
  "nbformat": 4,

docs/sphinx/examples/python/tutorials/src/geo_fenta.xyz

@@ -0,0 +1,28 @@
+26
+Energy = -2155.935897674
+C -1.0290441 -0.9471117 -1.9865887 
+C -2.2505436 -0.7922495 0.1582250 
+C -0.2593185 -2.2544373 0.0162178 
+O -1.3454085 0.8783278 -3.5342318 
+O -1.1347371 1.1483476 1.0151618 
+O 0.8453748 -2.7999130 2.0922098 
+O -0.2780587 1.3040005 -1.6070564 
+O -3.2498211 0.8000765 1.6534429 
+C -0.9188318 0.5115628 -2.4417824 
+C -2.2565356 0.4618854 1.0159078 
+C 0.5342286 -1.9274094 1.2848894 
+N -0.9221422 -1.0235290 -0.5013883 
+Fe 0.2526900 0.4497192 0.0039380 
+O 1.8221685 -0.2815654 -1.0936915 
+H -1.9555949 -1.4065777 -2.3473606 
+H -0.1824638 -1.4867161 -2.4264081 
+H -2.5130292 -1.6526686 0.7833244 
+H -3.0320380 -0.6959329 -0.6040366 
+H 0.4617231 -2.6044401 -0.7316186 
+H -0.9840969 -3.0551564 0.1969690 
+H 2.1227503 0.3853924 -1.7373941 
+H 2.5891208 -0.4447721 -0.5150575 
+O 0.9052095 -0.6681693 1.3941789 
+O 1.4573655 1.9796179 0.5273073 
+H 1.0868407 2.8424014 0.2685815 
+H 1.5840897 2.0352695 1.4913642 

docs/sphinx/examples/python/tutorials/src/geo_o3.xyz

@@ -0,0 +1,5 @@
+3
+Energy
+O 0.0000000 0.0000000 0.0000000
+O 0.0000000 0.0000000 1.2717000
+O 1.1383850 0.0000000 1.8385340