HW3 reveiwed submission

Classiq · Jun 13, 2024 · 4592469 · 4592469
1 parent 7fc063f
commit 4592469
Showing 1 changed file with 317 additions and 0 deletions.
diff --git a/community/QClass_2024/Submissions/HW3/Noah_Nzeki_William_HW3_VQE.ipynb b/community/QClass_2024/Submissions/HW3/Noah_Nzeki_William_HW3_VQE.ipynb
@@ -0,0 +1,317 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fc72d98f-8993-4bd4-a545-23d122f3df71",
+   "metadata": {},
+   "source": [
+    "# H₂ Molecule Homework Assignment\n",
+    "### Quantum Software Development Journey: From Theory to Application with Classiq - Part 3\n",
+    "\n",
+    "- Similarly to what we have done in class, in this exercise we will implement the VQE on H2 molecule.\n",
+    "- This time instead of using the built-in methods and functions (such as `Molecule` and `MoleculeProblem`) to difne and solve the problem, you will be provided with a two qubits Hamiltonian."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56eda6d8-76c4-4862-b914-0c4598d67274",
+   "metadata": {},
+   "source": [
+    "## Submission\n",
+    "- Submit the completed Jupyter notebook and report via GitHub. Ensure all files are correctly named and organized.\n",
+    "- Use the Typeform link provided in the submission folder to confirm your submission.\n",
+    "\n",
+    "## Additional Resources\n",
+    "- [Classiq Documentation](https://docs.classiq.io/latest/)\n",
+    "- The notebook from live session #3\n",
+    "\n",
+    "## Important Dates\n",
+    "- **Assignment Release:** 22.5.2024\n",
+    "- **Submission Deadline:** 3.6.2024 (7 A.M GMT+3)\n",
+    "\n",
+    "---\n",
+    "\n",
+    "Happy coding and good luck!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d41e969d-f6a7-4ff7-9660-19ce6c97ba6b",
+   "metadata": {},
+   "source": [
+    "### Part 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f710d6f4-d40b-42d5-b524-c6acb8059fe2",
+   "metadata": {},
+   "source": [
+    "Given the following Hamiltonian:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6ba8a6f1-3259-4492-a1ca-3abde7530cd4",
+   "metadata": {},
+   "source": [
+    "$$\n",
+    "\\hat{H} = -1.0523 \\cdot (I \\otimes I) + 0.3979 \\cdot (I \\otimes Z) - 0.3979 \\cdot (Z \\otimes I) - 0.0112 \\cdot (Z \\otimes Z) + 0.1809 \\cdot (X \\otimes X)\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "736d275c-9a5a-4c08-b891-3078430dc6c1",
+   "metadata": {},
+   "source": [
+    "Complete the following code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "19266c11-6acc-4edb-910f-2d0dfe80a6c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from typing import List\n",
+    "from classiq import *\n",
+    "\n",
+    "HAMILTONIAN = QConstant(\"HAMILTONIAN\", List[PauliTerm], #[...]) #TODO: Complete Hamiltonian\n",
+    "                        [           \n",
+    "            PauliTerm([Pauli.I, Pauli.I], -1.0523),\n",
+    "            PauliTerm([Pauli.I, Pauli.Z], 0.3979),\n",
+    "            PauliTerm([Pauli.Z, Pauli.I], -0.3979),\n",
+    "            PauliTerm([Pauli.Z, Pauli.Z], -0.0112),\n",
+    "            PauliTerm([Pauli.X, Pauli.X], 0.1809)])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "0bb68899-2076-45c0-8868-131f38aa3b78",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Opening: https://platform.classiq.io/circuit/53712c40-3bc3-46d5-a5a4-fe4b3a2aa001?version=0.42.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "@qfunc\n",
+    "def main(q: Output[QArray[QBit]], angles: CArray[CReal, 3]) -> None:\n",
+    "    # TODO: Create an ansatz which allows each qubit to have arbitrary rotation\n",
+    "    \n",
+    "    allocate(2, q)  \n",
+    "    U(angles[0], angles[1], angles[2], 0, q[0]) \n",
+    "    U(angles[0], angles[1], angles[2], 0, q[1]) \n",
+    "\n",
+    "@cfunc\n",
+    "def cmain() -> None:\n",
+    "    res = vqe(\n",
+    "        HAMILTONIAN, #.TODO: complete the missing argument\n",
+    "        False,\n",
+    "        [],\n",
+    "        optimizer=Optimizer.COBYLA,\n",
+    "        max_iteration=1000,\n",
+    "        tolerance=0.001,\n",
+    "        step_size=0,\n",
+    "        skip_compute_variance=False,\n",
+    "        alpha_cvar=1.0,\n",
+    "    )\n",
+    "    save({\"result\": res})\n",
+    "\n",
+    "qmod = create_model(main, classical_execution_function=cmain) #TODO: complete the line, use classical_execution_function\n",
+    "qprog = synthesize(qmod)\n",
+    "show(qprog)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "0563c1a8-7aec-4da9-9105-6b16c5c24382",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "execution = execute(qprog)\n",
+    "res = execution.result()\n",
+    "#execution.open_in_ide()\n",
+    "vqe_result = res[0].value #TODO: complete the line"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "de17cfc0-8e64-4493-b4c2-4a97fc9797a0",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Optimal energy: -1.06419619140625\n",
+      "Optimal parameters: {'angles_0': 6.111236674714585, 'angles_1': -0.887265255532695, 'angles_2': 3.112766526311032}\n",
+      "Eigenstate: {'01': (0.09110862335695782+0j), '10': (0.09110862335695782+0j), '00': (0.9916644782889019+0j)}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Optimal energy: {vqe_result.energy}\")\n",
+    "print(f\"Optimal parameters: {vqe_result.optimal_parameters}\")\n",
+    "print(f\"Eigenstate: {vqe_result.eigenstate}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5df11dfc-3e3a-4191-bd47-d522ca3dcbfa",
+   "metadata": {},
+   "source": [
+    "Does it similar to the `optimal energy` we calculated in class? \\\n",
+    "Does it similar to the `total energy` we calculated in class?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4f0e0bea-b12f-43ad-94e8-100fedf2b57f",
+   "metadata": {},
+   "source": [
+    "### Part 2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "66882248-de08-4a6e-b33c-647f015f7d79",
+   "metadata": {},
+   "source": [
+    "**Now, we want to have a more interesting ansatz in our `main`.**  \n",
+    "Add **one** line of code to the `main` function you created in Part 1 that creates **entanglement** between the two qubits.  \n",
+    "Which gate should you use?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "bb39be9e-4994-44e5-84d8-c99bc8b77145",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Opening: https://platform.classiq.io/circuit/1d523274-b861-41f3-9ad1-62c8d76927de?version=0.42.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "@qfunc\n",
+    "def main(q: Output[QArray[QBit]], angles: CArray[CReal, 3]) -> None:\n",
+    "    # TODO: Create an ansatz which allows each qubit to have arbitrary rotation\n",
+    "    \n",
+    "    allocate(2, q)  \n",
+    "    U(angles[0], angles[1], angles[2], 0, q[0]) \n",
+    "    U(angles[0], angles[1], angles[2], 0, q[1]) \n",
+    "    CX(q[1],q[0])\n",
+    "\n",
+    "@cfunc\n",
+    "def cmain() -> None:\n",
+    "    res = vqe(\n",
+    "        HAMILTONIAN, # TODO: complete the missing argument\n",
+    "        False,\n",
+    "        [],\n",
+    "        optimizer=Optimizer.COBYLA,\n",
+    "        max_iteration=1000,\n",
+    "        tolerance=0.001,\n",
+    "        step_size=0,\n",
+    "        skip_compute_variance=False,\n",
+    "        alpha_cvar=1.0,\n",
+    "    )\n",
+    "    save({\"result\": res})\n",
+    "\n",
+    "qmod = create_model(main, classical_execution_function=cmain) #TODO: complete the line, use classical_execution_function\n",
+    "qprog = synthesize(qmod)\n",
+    "show(qprog)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "112a1590-283c-4f79-8035-72936561102d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Opening in existing browser session.\n",
+      "Opening in existing browser session.\n"
+     ]
+    }
+   ],
+   "source": [
+    "execution = execute(qprog)\n",
+    "res = execution.result()\n",
+    "# execution.open_in_ide()\n",
+    "vqe_result = res[0].value #TODO: complete the line"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "06500e4c-a04b-4cfa-a84d-41f96a0c68eb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Optimal energy: -1.311106640625\n",
+      "Optimal parameters: {'angles_0': 5.243383358664046, 'angles_1': -0.362281429584872, 'angles_2': -3.9155584047002607}\n",
+      "Eigenstate: {'01': (0.4215855488510013+0j), '11': (0.4250459533979826+0j), '10': (0.2548360379734389+0j), '00': (0.7593814300139292+0j)}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Optimal energy: {vqe_result.energy}\")\n",
+    "print(f\"Optimal parameters: {vqe_result.optimal_parameters}\")\n",
+    "print(f\"Eigenstate: {vqe_result.eigenstate}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "30a635d7-2f15-4c94-a94b-f4270f17aed8",
+   "metadata": {},
+   "source": [
+    "Does it similar to the `optimal energy` we calculated in class? \\\n",
+    "Does it similar to the `total energy` we calculated in class? \\\n",
+    "What can we learn about the provided  form this result Hamiltonian?"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}