Release 0.1.2: bug fixes, compatibility and packaging

.coveragerc

@@ -0,0 +1,3 @@
+[run]
+omit =
+    */graphiq/data_collection/*

.github/workflows/pytest.yml

@@ -21,7 +21,9 @@ jobs:
           python -m pip install --upgrade pip
           pip install flake8 pytest
           pip install .
-          pip install .[all]
+          # optax needs jaxlib, which has no Python 3.8 wheels on PyPI any more,
+          # so on 3.8 only ray is installed from the "all" extra.
+          if [ "${{ matrix.python-version }}" = "3.8" ]; then pip install ray; else pip install .[all]; fi
 #          if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
       - name: Lint with flake8
         run: |

examples/example_solve.py

@@ -6,7 +6,10 @@
 import time
 
 from graphiq.backends.density_matrix.compiler import DensityMatrixCompiler
-from graphiq.solvers.evolutionary_solver import EvolutionarySolver
+from graphiq.solvers.evolutionary_solver import (
+    EvolutionarySolver,
+    EvolutionarySolverSetting,
+)
 from graphiq.metrics import Infidelity
 
 from graphiq.visualizers.density_matrix import density_matrix_bars
@@ -15,11 +18,8 @@
 
 
 if __name__ == "__main__":
-    # %% here we have access
-    EvolutionarySolver.n_stop = 40
-    EvolutionarySolver.n_pop = 150
-    EvolutionarySolver.n_hof = 10
-    EvolutionarySolver.tournament_k = 10
+    # %% solver settings
+    setting = EvolutionarySolverSetting(n_stop=40, n_pop=150, n_hof=10, tournament_k=10)
 
     # %% comment/uncomment for reproducibility
     EvolutionarySolver.seed(3)
@@ -40,6 +40,7 @@
         compiler=compiler,
         n_photon=n_photon,
         n_emitter=n_emitter,
+        solver_setting=setting,
     )
 
     # %% call the solver.solve() function to implement the random search algorithm

examples/startup_guide/0_implementer_quickstart.ipynb

@@ -42,7 +42,7 @@
     "3. Running a circuit (CompilerBase, DensityMatrixCompiler, StabilizerCompiler)\n",
     "4. Noise models\n",
     "5. Metrics (MetricBase, Infidelity, TraceDistance, Metrics)\n",
-    "6. Solvers (SolverBase, EvolutionarySolver, DeterministicSolver)\n",
+    "6. Solvers (SolverBase, EvolutionarySolver, TimeReversedSolver)\n",
     "7. Benchmarking\n",
     "8. (upcoming) Differentiable circuits\n",
     "\n",

examples/startup_guide/8_variational_circuits.ipynb

@@ -3,7 +3,9 @@
   {
    "cell_type": "markdown",
    "source": [
-    "# Parameterized quantum circuits [Experimental]"
+    "# Parameterized quantum circuits [Experimental]\n",
+    "\n",
+    "**Not supported in this version.** This notebook does not run as written: setting `graphiq.DENSITY_MATRIX_ARRAY_LIBRARY` after `import graphiq` does not switch the density-matrix backend to `jax`; it keeps numpy. With `jax` selected (by editing `DENSITY_MATRIX_ARRAY_LIBRARY` in `graphiq/__init__.py`), no density-matrix `QuantumState` can be built from a matrix (`QuantumState` rejects jax arrays and `DensityMatrix` rejects numpy arrays), so the target below cannot be built, and the density-matrix arm of `Infidelity` cannot be differentiated. Its saved outputs come from an older version."
    ],
    "metadata": {
     "collapsed": false,
@@ -268,34 +270,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "  0%|          | 0/100 [00:00<?, ?it/s]\n"
-     ]
-    },
-    {
-     "ename": "TracerArrayConversionError",
-     "evalue": "The numpy.ndarray conversion method __array__() was called on traced array with shape float32[].\nSee https://jax.readthedocs.io/en/latest/errors.html#jax.errors.TracerArrayConversionError",
-     "output_type": "error",
-     "traceback": [
-      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
-      "\u001B[0;31mTracerArrayConversionError\u001B[0m                Traceback (most recent call last)",
-      "Cell \u001B[0;32mIn[9], line 4\u001B[0m\n\u001B[1;32m      2\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m step \u001B[38;5;129;01min\u001B[39;00m (pbar \u001B[38;5;241m:=\u001B[39m tqdm\u001B[38;5;241m.\u001B[39mtqdm(\u001B[38;5;28mrange\u001B[39m(n_step), disable\u001B[38;5;241m=\u001B[39m(\u001B[38;5;129;01mnot\u001B[39;00m progress))):\n\u001B[1;32m      3\u001B[0m     loss \u001B[38;5;241m=\u001B[39m compute_loss(params, circuit)\n\u001B[0;32m----> 4\u001B[0m     grads \u001B[38;5;241m=\u001B[39m \u001B[43mjax\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mgrad\u001B[49m\u001B[43m(\u001B[49m\u001B[43mcompute_loss\u001B[49m\u001B[43m)\u001B[49m\u001B[43m(\u001B[49m\u001B[43mparams\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mcircuit\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m      5\u001B[0m     updates, opt_state \u001B[38;5;241m=\u001B[39m optimizer\u001B[38;5;241m.\u001B[39mupdate(grads, opt_state)\n\u001B[1;32m      6\u001B[0m     params \u001B[38;5;241m=\u001B[39m optax\u001B[38;5;241m.\u001B[39mapply_updates(params, updates)\n",
-      "    \u001B[0;31m[... skipping hidden 10 frame]\u001B[0m\n",
-      "Cell \u001B[0;32mIn[7], line 3\u001B[0m, in \u001B[0;36mcompute_loss\u001B[0;34m(params, circuit)\u001B[0m\n\u001B[1;32m      1\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mcompute_loss\u001B[39m(params: \u001B[38;5;28mdict\u001B[39m, circuit: CircuitDAG):\n\u001B[1;32m      2\u001B[0m     circuit\u001B[38;5;241m.\u001B[39mparameters \u001B[38;5;241m=\u001B[39m params\n\u001B[0;32m----> 3\u001B[0m     output_state \u001B[38;5;241m=\u001B[39m \u001B[43mcompiler\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcompile\u001B[49m\u001B[43m(\u001B[49m\u001B[43mcircuit\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m      4\u001B[0m     cost \u001B[38;5;241m=\u001B[39m metric\u001B[38;5;241m.\u001B[39mevaluate(output_state, circuit)\n\u001B[1;32m      5\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m cost\n",
-      "File \u001B[0;32m~/Library/CloudStorage/OneDrive-UniversityofWaterloo/Desktop/1 - Projects/AF Inverse Graph Design/graph-compiler/graphiq/backends/compiler_base.py:121\u001B[0m, in \u001B[0;36mCompilerBase.compile\u001B[0;34m(self, circuit, initial_state)\u001B[0m\n\u001B[1;32m    118\u001B[0m     no_noise \u001B[38;5;241m=\u001B[39m no_noise \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(op\u001B[38;5;241m.\u001B[39mnoise, nm\u001B[38;5;241m.\u001B[39mNoNoise)\n\u001B[1;32m    120\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m no_noise:\n\u001B[0;32m--> 121\u001B[0m     \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcompile_one_gate\u001B[49m\u001B[43m(\u001B[49m\n\u001B[1;32m    122\u001B[0m \u001B[43m        \u001B[49m\u001B[43mstate\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mop\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mcircuit\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mn_quantum\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mq_index\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mclassical_registers\u001B[49m\n\u001B[1;32m    123\u001B[0m \u001B[43m    \u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m    125\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m    126\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m is_controlled_op:\n",
-      "File \u001B[0;32m~/Library/CloudStorage/OneDrive-UniversityofWaterloo/Desktop/1 - Projects/AF Inverse Graph Design/graph-compiler/graphiq/backends/density_matrix/compiler.py:86\u001B[0m, in \u001B[0;36mDensityMatrixCompiler.compile_one_gate\u001B[0;34m(self, state, op, n_quantum, q_index, classical_registers)\u001B[0m\n\u001B[1;32m     80\u001B[0m     \u001B[38;5;28;01mpass\u001B[39;00m  \u001B[38;5;66;03m# TODO: should think about best way to handle inputs/outputs\u001B[39;00m\n\u001B[1;32m     82\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(op, ops\u001B[38;5;241m.\u001B[39mOneQubitOperationBase):\n\u001B[1;32m     83\u001B[0m     unitary \u001B[38;5;241m=\u001B[39m dm\u001B[38;5;241m.\u001B[39mget_one_qubit_gate(\n\u001B[1;32m     84\u001B[0m         n_quantum,\n\u001B[1;32m     85\u001B[0m         q_index(op\u001B[38;5;241m.\u001B[39mregister, op\u001B[38;5;241m.\u001B[39mreg_type),\n\u001B[0;32m---> 86\u001B[0m         \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mops\u001B[49m\u001B[43m[\u001B[49m\u001B[43mop\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[38;5;18;43m__class__\u001B[39;49m\u001B[43m]\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mparams\u001B[49m\u001B[43m)\u001B[49m,\n\u001B[1;32m     87\u001B[0m     )\n\u001B[1;32m     88\u001B[0m     state\u001B[38;5;241m.\u001B[39mapply_unitary(unitary)\n\u001B[1;32m     90\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(op, ops\u001B[38;5;241m.\u001B[39mControlledPairOperationBase):\n",
-      "File \u001B[0;32m~/Library/CloudStorage/OneDrive-UniversityofWaterloo/Desktop/1 - Projects/AF Inverse Graph Design/graph-compiler/graphiq/backends/density_matrix/compiler.py:31\u001B[0m, in \u001B[0;36mDensityMatrixCompiler.<lambda>\u001B[0;34m(theta, phi, lam)\u001B[0m\n\u001B[1;32m     19\u001B[0m \u001B[38;5;66;03m# TODO: [longer term] refactor to take a QuantumState object input instead of creating its own initial state?\u001B[39;00m\n\u001B[1;32m     21\u001B[0m name \u001B[38;5;241m=\u001B[39m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mdm\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[1;32m     22\u001B[0m ops \u001B[38;5;241m=\u001B[39m {  \u001B[38;5;66;03m# the accepted operations and the single-qubit action needed for each gate\u001B[39;00m\n\u001B[1;32m     23\u001B[0m     ops\u001B[38;5;241m.\u001B[39mInput: \u001B[38;5;28;01mlambda\u001B[39;00m: \u001B[38;5;28;01mNone\u001B[39;00m,\n\u001B[1;32m     24\u001B[0m     ops\u001B[38;5;241m.\u001B[39mIdentity: \u001B[38;5;28;01mlambda\u001B[39;00m: \u001B[38;5;28;01mNone\u001B[39;00m,\n\u001B[1;32m     25\u001B[0m     ops\u001B[38;5;241m.\u001B[39mPhase: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39mphase(),\n\u001B[1;32m     26\u001B[0m     ops\u001B[38;5;241m.\u001B[39mPhaseDagger: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39mphase_dag(),\n\u001B[1;32m     27\u001B[0m     ops\u001B[38;5;241m.\u001B[39mHadamard: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39mhadamard(),\n\u001B[1;32m     28\u001B[0m     ops\u001B[38;5;241m.\u001B[39mSigmaX: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39msigmax(),\n\u001B[1;32m     29\u001B[0m     ops\u001B[38;5;241m.\u001B[39mSigmaY: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39msigmay(),\n\u001B[1;32m     30\u001B[0m     ops\u001B[38;5;241m.\u001B[39mSigmaZ: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39msigmaz(),\n\u001B[0;32m---> 31\u001B[0m     ops\u001B[38;5;241m.\u001B[39mParameterizedOneQubitRotation: \u001B[38;5;28;01mlambda\u001B[39;00m theta, phi, lam: \u001B[43mdm\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mparameterized_one_qubit_unitary\u001B[49m\u001B[43m(\u001B[49m\n\u001B[1;32m     32\u001B[0m \u001B[43m        \u001B[49m\u001B[43mtheta\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mphi\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mlam\u001B[49m\n\u001B[1;32m     33\u001B[0m \u001B[43m    \u001B[49m\u001B[43m)\u001B[49m,\n\u001B[1;32m     34\u001B[0m     ops\u001B[38;5;241m.\u001B[39mParameterizedControlledRotationQubit: \u001B[38;5;28;01mlambda\u001B[39;00m theta, phi, lam: dm\u001B[38;5;241m.\u001B[39mparameterized_one_qubit_unitary(\n\u001B[1;32m     35\u001B[0m         theta, phi, lam\n\u001B[1;32m     36\u001B[0m     ),\n\u001B[1;32m     37\u001B[0m     ops\u001B[38;5;241m.\u001B[39mCNOT: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39msigmax(),\n\u001B[1;32m     38\u001B[0m     ops\u001B[38;5;241m.\u001B[39mCZ: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39msigmaz(),\n\u001B[1;32m     39\u001B[0m     ops\u001B[38;5;241m.\u001B[39mClassicalCNOT: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39msigmax(),\n\u001B[1;32m     40\u001B[0m     ops\u001B[38;5;241m.\u001B[39mClassicalCZ: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39msigmaz(),\n\u001B[1;32m     41\u001B[0m     ops\u001B[38;5;241m.\u001B[39mMeasurementZ: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39msigmaz(),\n\u001B[1;32m     42\u001B[0m     ops\u001B[38;5;241m.\u001B[39mMeasurementCNOTandReset: \u001B[38;5;28;01mlambda\u001B[39;00m: dm\u001B[38;5;241m.\u001B[39msigmax(),\n\u001B[1;32m     43\u001B[0m     ops\u001B[38;5;241m.\u001B[39mOutput: \u001B[38;5;28;01mlambda\u001B[39;00m: \u001B[38;5;28;01mNone\u001B[39;00m,\n\u001B[1;32m     44\u001B[0m }\n\u001B[1;32m     46\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21m__init__\u001B[39m(\u001B[38;5;28mself\u001B[39m, \u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs):\n\u001B[1;32m     47\u001B[0m \u001B[38;5;250m    \u001B[39m\u001B[38;5;124;03m\"\"\"\u001B[39;00m\n\u001B[1;32m     48\u001B[0m \u001B[38;5;124;03m    Create a compiler which acts on a DensityMatrix state representation\u001B[39;00m\n\u001B[1;32m     49\u001B[0m \n\u001B[1;32m     50\u001B[0m \u001B[38;5;124;03m    :return: nothing\u001B[39;00m\n\u001B[1;32m     51\u001B[0m \u001B[38;5;124;03m    :rtype: None\u001B[39;00m\n\u001B[1;32m     52\u001B[0m \u001B[38;5;124;03m    \"\"\"\u001B[39;00m\n",
-      "File \u001B[0;32m~/Library/CloudStorage/OneDrive-UniversityofWaterloo/Desktop/1 - Projects/AF Inverse Graph Design/graph-compiler/graphiq/backends/density_matrix/functions.py:794\u001B[0m, in \u001B[0;36mparameterized_one_qubit_unitary\u001B[0;34m(theta, phi, lam)\u001B[0m\n\u001B[1;32m    775\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mparameterized_one_qubit_unitary\u001B[39m(theta, phi, lam):\n\u001B[1;32m    776\u001B[0m \u001B[38;5;250m    \u001B[39m\u001B[38;5;124;03m\"\"\"\u001B[39;00m\n\u001B[1;32m    777\u001B[0m \u001B[38;5;124;03m    Define a generic 3-parameter one-qubit unitary gate.\u001B[39;00m\n\u001B[1;32m    778\u001B[0m \n\u001B[0;32m   (...)\u001B[0m\n\u001B[1;32m    790\u001B[0m \u001B[38;5;124;03m    :rtype: numpy.ndarray\u001B[39;00m\n\u001B[1;32m    791\u001B[0m \u001B[38;5;124;03m    \"\"\"\u001B[39;00m\n\u001B[1;32m    792\u001B[0m     gate \u001B[38;5;241m=\u001B[39m np\u001B[38;5;241m.\u001B[39marray(\n\u001B[1;32m    793\u001B[0m         [\n\u001B[0;32m--> 794\u001B[0m             [\u001B[43mnp\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcos\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtheta\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m/\u001B[39;49m\u001B[43m \u001B[49m\u001B[38;5;241;43m2\u001B[39;49m\u001B[43m)\u001B[49m, \u001B[38;5;241m-\u001B[39mnp\u001B[38;5;241m.\u001B[39mexp(\u001B[38;5;241m1\u001B[39mj \u001B[38;5;241m*\u001B[39m lam) \u001B[38;5;241m*\u001B[39m np\u001B[38;5;241m.\u001B[39msin(theta \u001B[38;5;241m/\u001B[39m \u001B[38;5;241m2\u001B[39m)],\n\u001B[1;32m    795\u001B[0m             [\n\u001B[1;32m    796\u001B[0m                 np\u001B[38;5;241m.\u001B[39mexp(\u001B[38;5;241m1\u001B[39mj \u001B[38;5;241m*\u001B[39m phi) \u001B[38;5;241m*\u001B[39m np\u001B[38;5;241m.\u001B[39msin(theta \u001B[38;5;241m/\u001B[39m \u001B[38;5;241m2\u001B[39m),\n\u001B[1;32m    797\u001B[0m                 np\u001B[38;5;241m.\u001B[39mexp(\u001B[38;5;241m1\u001B[39mj \u001B[38;5;241m*\u001B[39m (phi \u001B[38;5;241m+\u001B[39m lam)) \u001B[38;5;241m*\u001B[39m np\u001B[38;5;241m.\u001B[39mcos(theta \u001B[38;5;241m/\u001B[39m \u001B[38;5;241m2\u001B[39m),\n\u001B[1;32m    798\u001B[0m             ],\n\u001B[1;32m    799\u001B[0m         ]\n\u001B[1;32m    800\u001B[0m     )\n\u001B[1;32m    801\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m gate\n",
-      "File \u001B[0;32m~/.virtualenvs/graph-compiler/lib/python3.9/site-packages/jax/_src/core.py:640\u001B[0m, in \u001B[0;36mTracer.__array__\u001B[0;34m(self, *args, **kw)\u001B[0m\n\u001B[1;32m    639\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21m__array__\u001B[39m(\u001B[38;5;28mself\u001B[39m, \u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkw):\n\u001B[0;32m--> 640\u001B[0m   \u001B[38;5;28;01mraise\u001B[39;00m TracerArrayConversionError(\u001B[38;5;28mself\u001B[39m)\n",
-      "\u001B[0;31mTracerArrayConversionError\u001B[0m: The numpy.ndarray conversion method __array__() was called on traced array with shape float32[].\nSee https://jax.readthedocs.io/en/latest/errors.html#jax.errors.TracerArrayConversionError"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "outputs": [],
    "source": [
     "cost_curve = []\n",
     "for step in (pbar := tqdm.tqdm(range(n_step), disable=(not progress))):\n",
@@ -391,7 +367,8 @@
    "execution_count": 10,
    "outputs": [],
    "source": [
-    "from src.solvers.gradient_descent_solver import GradientDescentSolver, adagrad"
+    "from graphiq.solvers.gradient_descent_solver import GradientDescentSolver\n",
+    "from optax import adagrad"
    ],
    "metadata": {
     "collapsed": false,