Qaoa implementation

examples/evolutions.ipynb

@@ -32,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "21685242",
    "metadata": {},
    "outputs": [],
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "d8527d79",
    "metadata": {},
    "outputs": [
@@ -97,7 +97,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "5714c87f",
    "metadata": {},
    "outputs": [
@@ -115,7 +115,7 @@
       "include \"stdgates.inc\";\n",
       "qubit[4] qb;\n",
       "bit[4] cb;\n",
-      "gate TFIM_3q_J100_h70(time) aa,ab,ac{\n",
+      "gate TFIM_3q_j100_h70(time) aa,ab,ac{\n",
       "\tcnot  aa, ab;\n",
       "\trz(2.0 * time)  ab;\n",
       "\tcnot  aa, ab;\n",
@@ -132,7 +132,7 @@
       "\n",
       "gate GQSP_1_TFIM(θa,θb,θc) aa,ab,ac,ad{\n",
       "\try(θa)  aa;\n",
-      "\tctrl(1) @ TFIM_3q_J100_h70(0.1)  aa, ab, ac, ad;\n",
+      "\tctrl(1) @ TFIM_3q_j100_h70(0.1)  aa, ab, ac, ad;\n",
       "\tp(θb)  aa;\n",
       "\try(θc)  aa;\n",
       "}\n",
@@ -149,7 +149,7 @@
       "include \"stdgates.inc\";\n",
       "qubit[4] qb;\n",
       "bit[4] cb;\n",
-      "gate TFIM_3q_J100_h70(time) aa,ab,ac{\n",
+      "gate TFIM_3q_j100_h70(time) aa,ab,ac{\n",
       "\tcnot  aa, ab;\n",
       "\trz(2.0 * time)  ab;\n",
       "\tcnot  aa, ab;\n",
@@ -166,13 +166,13 @@
       "\n",
       "gate GQSP_3_TFIM(θa,θb,θc,θd,θe,θf,θg) aa,ab,ac,ad{\n",
       "\try(θa)  aa;\n",
-      "\tctrl(1) @ TFIM_3q_J100_h70(0.1)  aa, ab, ac, ad;\n",
+      "\tctrl(1) @ TFIM_3q_j100_h70(0.1)  aa, ab, ac, ad;\n",
       "\tp(θb)  aa;\n",
       "\try(θe)  aa;\n",
-      "\tctrl(1) @ TFIM_3q_J100_h70(0.1)  aa, ab, ac, ad;\n",
+      "\tctrl(1) @ TFIM_3q_j100_h70(0.1)  aa, ab, ac, ad;\n",
       "\tp(θc)  aa;\n",
       "\try(θf)  aa;\n",
-      "\tctrl(1) @ TFIM_3q_J100_h70(0.1)  aa, ab, ac, ad;\n",
+      "\tctrl(1) @ TFIM_3q_j100_h70(0.1)  aa, ab, ac, ad;\n",
       "\tp(θd)  aa;\n",
       "\try(θg)  aa;\n",
       "}\n",
@@ -288,7 +288,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "7c651bcd",
    "metadata": {},
    "outputs": [
@@ -300,13 +300,13 @@
       "Trotter Decomposition - Two vs Multi-Hamiltonian\n",
       "----------------------------------------------------\n",
       "Configuration 1: Two-Hamiltonian Trotter (Suzuki)\n",
-      "Two-Hamiltonian: 1858 characters\n",
+      "Two-Hamiltonian: 1864 characters\n",
       "\tMethod: Suzuki-Trotter, Depth: 2\n",
       "OPENQASM 3;\n",
       "include \"stdgates.inc\";\n",
       "qubit[3] qb;\n",
       "bit[3] cb;\n",
-      "gate TFIM_3q_J100_h70(time) aa,ab,ac{\n",
+      "gate TFIM_3q_j100_h70(time) aa,ab,ac{\n",
       "\tcnot  aa, ab;\n",
       "\trz(2.0 * time)  ab;\n",
       "\tcnot  aa, ab;\n",
@@ -321,7 +321,7 @@
       "\trx(1.4 * time)  ac;\n",
       "}\n",
       "\n",
-      "gate HeisenbergXYZ_3q_Jx100_Jy120_Jz80(time) aa,ab,ac{\n",
+      "gate HeisenbergXYZ_3q_j_x100_j_y120_j_z80(time) aa,ab,ac{\n",
       "\try(pi/2)  aa;\n",
       "\try(pi/2)  ab;\n",
       "\tcnot  aa, ab;\n",
@@ -360,9 +360,9 @@
       "\n",
       "def trot_suz_3_TFIM_HeisenbergXYZ_2(qubit[3] qubits,float time,int recursion_depth) {\n",
       "\tif (recursion_depth < 2){\n",
-      "\t\tTFIM_3q_J100_h70(time/2) qb[qubits[0]],qb[qubits[1]],qb[qubits[2]];\n",
-      "\t\tHeisenbergXYZ_3q_Jx100_Jy120_Jz80(time) qb[qubits[0]],qb[qubits[1]],qb[qubits[2]];\n",
-      "\t\tTFIM_3q_J100_h70(time/2) qb[qubits[0]],qb[qubits[1]],qb[qubits[2]];\n",
+      "\t\tTFIM_3q_j100_h70(time/2) qb[qubits[0]],qb[qubits[1]],qb[qubits[2]];\n",
+      "\t\tHeisenbergXYZ_3q_j_x100_j_y120_j_z80(time) qb[qubits[0]],qb[qubits[1]],qb[qubits[2]];\n",
+      "\t\tTFIM_3q_j100_h70(time/2) qb[qubits[0]],qb[qubits[1]],qb[qubits[2]];\n",
       "\t\treturn;\n",
       "\t}\n",
       "\tfloat suzuki_coeff = 1.0/(4.0 - pow(4.0, 1.0/(2.0*recursion_depth - 1.0)));\n",
@@ -377,16 +377,16 @@
       "\n",
       "\n",
       "Configuration 2: Multi-Hamiltonian Trotter\n",
-      "Multi-Hamiltonian: 3342 characters\n",
+      "Multi-Hamiltonian: 3351 characters\n",
       "\tHamiltonians: 3, Depth: 2\n",
       "\n",
       "Configuration 3: Linear Trotter Decomposition\n",
-      "Linear Trotter: 1769 characters\n",
+      "Linear Trotter: 1784 characters\n",
       "Method: First-order, Steps: 4\n",
       "Trotter Configuration Comparison:\n",
-      "\tTwo-Hamiltonian (Suzuki): 1858 chars\n",
-      "\tMulti-Hamiltonian:       3342 chars\n",
-      "\tLinear decomposition:     1769 chars\n"
+      "\tTwo-Hamiltonian (Suzuki): 1864 chars\n",
+      "\tMulti-Hamiltonian:       3351 chars\n",
+      "\tLinear decomposition:     1784 chars\n"
      ]
     }
    ],
@@ -492,7 +492,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "4b4b3bff",
    "metadata": {},
    "outputs": [
@@ -508,19 +508,13 @@
       "[('Z', np.complex128(1+0j))]\n",
       "Pauli-Z: 508 characters\n",
       "Testing Random 4x4 matrix (4, 4)...\n",
-      "[('II', np.complex128(0.4604637367120007+0.838946781387169j)), ('XI', np.complex128(0.5655598377382944+0.588833075307832j)), ('XX', np.complex128(0.4238844968885312+0.3326317061016123j)), ('IX', np.complex128(0.33106499350145013+0.33007330113196753j)), ('XY', np.complex128(-0.06002262495215413+0.2992097507618375j)), ('IY', np.complex128(-0.1797796889495182+0.20356340119461624j)), ('YI', np.complex128(-0.13521719508002197+0.19794667244217146j)), ('ZX', np.complex128(0.02442078075316162-0.23360780554666702j)), ('XZ', np.complex128(-0.18057751029366081-0.148700172760367j)), ('ZY', np.complex128(0.2184605953247674+0.03821255057383305j)), ('IZ', np.complex128(-0.095147349933698+0.07351264181838879j)), ('ZI', np.complex128(-0.11616413227155017+0.02567510247519522j)), ('YY', np.complex128(-0.05126587163767765+0.10703189572053626j)), ('YZ', np.complex128(-0.09614107149005136-0.02889548280897075j)), ('YX', np.complex128(-0.0870637778551501+0.04327330864487838j)), ('ZZ', np.complex128(0.0896637111235748-0.035398963079813106j))]\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Random 4x4: 2019 characters\n",
+      "[('IX', np.complex128(0.6312692451983448+0.7062795340748755j)), ('II', np.complex128(0.3312704466731056+0.6543110856138611j)), ('XX', np.complex128(0.48885549810002155+0.46708079988828466j)), ('XI', np.complex128(0.5064276643525388+0.42560849024074227j)), ('YI', np.complex128(-0.2209432140524214-0.32680593560317794j)), ('XY', np.complex128(0.3051770998894734-0.08729195918180288j)), ('YY', np.complex128(0.22903059831001216-0.17048096768847246j)), ('ZZ', np.complex128(-0.12674613849154037+0.09991843038070033j)), ('ZI', np.complex128(-0.14733787825849548+0.023772954678058178j)), ('IY', np.complex128(-0.13339759254293293-0.04272733136592735j)), ('IZ', np.complex128(-0.018907216413733607-0.13091360941091704j)), ('ZX', np.complex128(0.007991339043142087-0.10180140392762566j)), ('ZY', np.complex128(-0.05995761592784832-0.0542893312281765j)), ('XZ', np.complex128(-0.016121493337997672+0.07795486151092063j)), ('YZ', np.complex128(0.06407397205381465+0.006693388785256826j)), ('YX', np.complex128(0.03553879879197233-0.04432680229575253j))]\n",
+      "Random 4x4: 2023 characters\n",
       "\n",
       "Configuration 2: Operator Chain Input\n",
       "Testing Single Pauli chain (3 operators)...\n",
       "[('X', 0.5), ('Z', 0.3), ('Y', 0.2)]\n",
-      "\tSingle Pauli: 719 characters\n",
+      "\tSingle Pauli: 717 characters\n",
       "\tOperators: ['X', 'Z', 'Y']\n",
       "OPENQASM 3;\n",
       "include \"stdgates.inc\";\n",
@@ -545,7 +539,7 @@
       "\ty aa;\n",
       "}\n",
       "\n",
-      "gate SEL_8998145479025848162 aa,ab,ac,ad{\n",
+      "gate SEL_247308947824619046 aa,ab,ac,ad{\n",
       "\tctrl(2) @ X aa,ab,ac,ad;\n",
       "\tx aa;\n",
       "\tctrl(2) @ Z aa,ab,ac,ad;\n",
@@ -555,13 +549,13 @@
       "\tx ab;\n",
       "}\n",
       "\n",
-      "gate PS_2_8654309695166846104 aa,ab,ac,ad{\n",
+      "gate PS_2_8139876655021836051 aa,ab,ac,ad{\n",
       "\tPREP_3905172865891942725 aa,ab;\n",
-      "\tSEL_8998145479025848162 aa,ab,ac,ad;\n",
+      "\tSEL_247308947824619046 aa,ab,ac,ad;\n",
       "\tinv @ PREP_3905172865891942725 aa,ab;\n",
       "}\n",
       "\n",
-      "PS_2_8654309695166846104 qb[3],qb[4],qb[0],qb[1];\n",
+      "PS_2_8139876655021836051 qb[3],qb[4],qb[0],qb[1];\n",
       "cb[{3, 4}] = measure qb[{3, 4}];\n",
       "cb[{0, 1, 2, 3}] = measure qb[{0, 1, 2, 3}];\n",
       "\n",
@@ -573,9 +567,9 @@
       "Prep-Select Configuration Comparison:\n",
       "Matrix inputs:\n",
       "\tPauli-Z: 508 chars\n",
-      "\tRandom 4x4: 2019 chars\n",
+      "\tRandom 4x4: 2023 chars\n",
       "Operator chains:\n",
-      "\tSingle Pauli: 719 chars\n",
+      "\tSingle Pauli: 717 chars\n",
       "\tTwo-qubit Pauli: 756 chars\n"
      ]
     }
@@ -681,7 +675,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "a44b4a64",
    "metadata": {},
    "outputs": [
@@ -698,10 +692,10 @@
       "  Step 2: Applying GQSP...\n",
       "  Step 3: Applying prep-select...\n",
       "[('Z', np.complex128(1+0j))]\n",
-      "Integrated pipeline: 2465 characters\n",
-      "   Contains Trotter: True\n",
-      "   Contains GQSP: True\n",
-      "   Contains PrepSelect: True\n"
+      "Integrated pipeline: 2471 characters\n",
+      "\tContains Trotter: True\n",
+      "\tContains GQSP: True\n",
+      "\tContains PrepSelect: True\n"
      ]
     }
    ],
@@ -789,40 +783,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 7,
    "id": "22dfb86d",
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "OPENQASM 3;\n",
-      "include \"stdgates.inc\";\n",
-      "qubit[3] qb;\n",
-      "gate Z_on_two3 aa,ab,ac{\n",
-      "\tx  ac;\n",
-      "\tctrl(2) @ z  aa, ab, ac;\n",
-      "\tx  ac;\n",
-      "}\n",
-      "\n",
-      "def Grover3Z_on_two3(qubit[3] reg) {\n",
-      "\th  reg;\n",
-      "\tfor int i in [0:2] {\n",
-      "\t\t//Za\n",
-      "\t\tZ_on_two3  reg[0], reg[1], reg[2];\n",
-      "\t\th  reg;\n",
-      "\t\t//Z0\n",
-      "\t\tx  reg;\n",
-      "\t\tctrl(2) @ z  reg[0], reg[1], reg[0];\n",
-      "\t\tx  reg;\n",
-      "\t\th  reg;\n",
-      "\t}\n",
-      "}\n",
-      "\n",
-      "input angle[32] theta ;\n",
-      "Grover3Z_on_two3(qb[{0 ,1 ,2}]);\n",
-      "\n"
+     "ename": "TypeError",
+     "evalue": "GateLibrary.add_var() got an unexpected keyword argument 'type'. Did you mean 'qtype'?",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mTypeError\u001b[39m                                 Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[7]\u001b[39m\u001b[32m, line 51\u001b[39m\n\u001b[32m     47\u001b[39m         \u001b[38;5;28mself\u001b[39m.controlled_op(\u001b[38;5;28mself\u001b[39m.name, (qubits[-\u001b[32m1\u001b[39m], [control] + qubits[:-\u001b[32m1\u001b[39m]))\n\u001b[32m     50\u001b[39m \u001b[38;5;66;03m# Define input parameter\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m51\u001b[39m theta = \u001b[43mprogram\u001b[49m\u001b[43m.\u001b[49m\u001b[43madd_var\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtheta\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mtype\u001b[39;49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43minput angle[32]\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m     53\u001b[39m \u001b[38;5;66;03m# Apply Grover with custom gate\u001b[39;00m\n\u001b[32m     54\u001b[39m ampl.grover(Za, reg, \u001b[32m3\u001b[39m)\n",
+      "\u001b[31mTypeError\u001b[39m: GateLibrary.add_var() got an unexpected keyword argument 'type'. Did you mean 'qtype'?"
      ]
     }
    ],
@@ -901,7 +874,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "venv",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -915,7 +888,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.8"
+   "version": "3.13.9"
   }
  },
  "nbformat": 4,

qbraid_algorithms/qaoa/__init__.py

@@ -0,0 +1,20 @@
+# Copyright 2025 qBraid
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# 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.
+"""
+    Quantum Approximate Optimization Algorithm (QAOA) used to define cost and mixer Hamiltonians
+    and generate QASM programs accordingly.
+"""
+from .qaoa import QAOA
+
+__all__ = ["QAOA"]