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Womanium Final Assignment - Karan Y Islur #399

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Womanium Final Assignment - Karan Y Islur #399

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223 changes: 223 additions & 0 deletions community/womanium/assignments/Karan_Islur_hw4.ipynb.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "wTqEQ9-Pvryc"
},
"source": [
"# Linear Graph with 16 nodes\n",
"\n",
"\n",
"\n",
"***Quantum Walk***"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"id": "nDsgok_g5uPq"
},
"outputs": [],
"source": [
"from classiq import *\n",
"\n",
"size = 4\n",
"\n",
"@qfunc\n",
"def prepare_minus(x: QBit):\n",
" X(x)\n",
" H(x)\n",
"\n",
"@qfunc\n",
"def diffuzer_oracle(aux: Output[QNum],x:QNum):\n",
" aux^=(x!=0)\n",
"\n",
"@qfunc\n",
"def zero_diffuzer(x: QNum):\n",
" aux = QNum('aux')\n",
" allocate(1,aux)\n",
" within_apply(compute=lambda: prepare_minus(aux),\n",
" action=lambda: diffuzer_oracle)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "hJvyxUGsxx6r"
},
"source": [
"# W Operator\n",
"\n",
"The superposition of all the adjacent vertices for all the vertices in the linear graph is created by this function. The first and the last vertex has only one adjacent verex compared to all other vertices, so the for loop is customized accordingly for these two vertices."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def W_iteration(i:int,vertices: QNum, adjacent_vertices:QNum):\n",
"\n",
" prob = [0]* 2**size\n",
" if i==0:\n",
" prob[i+1] = 1.0 #Probability\n",
" elif i==((2**size)-1):\n",
" prob[i-1] = 1.0 #Probability\n",
" else:\n",
" prob[i-1] = 0.5 #Probability\n",
" prob[i+1] = 0.5 #Probability\n",
" print(f'State={i}, prob vec ={prob}')\n",
"\n",
" control(ctrl=vertices==i,\n",
" operand=lambda: within_apply(\n",
" compute= lambda: inplace_prepare_state(probabilities=prob, bound=0.01, target=adjacent_vertices),\n",
" action= lambda: zero_diffuzer(adjacent_vertices)))\n",
"\n",
"@qfunc\n",
"def W_operator(vertices:QNum, adjacent_vertices: QNum):\n",
" for i in range(2**size):\n",
" W_iteration(i,vertices,adjacent_vertices)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Mz6umPX69jHl"
},
"source": [
"# S Operator\n",
"\n",
"Here, the qubit should result in a 1 state for the edges of two adjacent vertices, so the edge oracle is changed accordingly."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"id": "YhfGlIf_MdsV"
},
"outputs": [],
"source": [
"@qfunc\n",
"def edge_oracle(res:Output[QBit], vertices: QNum, adjacent_vertices: QNum):\n",
" res |= (((vertices-adjacent_vertices) == 1) | ((vertices-adjacent_vertices) == -1))\n",
"\n",
"@qfunc\n",
"def bitwise_swap(x: QArray[QBit], y:QArray[QBit]):\n",
" repeat(count= x.len,\n",
" iteration= lambda i: SWAP(x[i],y[i]))\n",
"\n",
"@qfunc\n",
"def S_operator(vertices:QNum, adjacent_vertices: QNum):\n",
" res = QNum('res')\n",
" edge_oracle(res,vertices,adjacent_vertices)\n",
" control(ctrl= res==1,\n",
" operand= lambda: bitwise_swap(vertices,adjacent_vertices))"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "0P8D2W7X997a"
},
"source": [
"# Main Function"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "9uQiPdVjMhfk",
"outputId": "28b9560b-293f-4769-fd40-bdae222c0441"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"State=0, prob vec =[0, 1.0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
"State=1, prob vec =[0.5, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
"State=2, prob vec =[0, 0.5, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
"State=3, prob vec =[0, 0, 0.5, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
"State=4, prob vec =[0, 0, 0, 0.5, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
"State=5, prob vec =[0, 0, 0, 0, 0.5, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
"State=6, prob vec =[0, 0, 0, 0, 0, 0.5, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0]\n",
"State=7, prob vec =[0, 0, 0, 0, 0, 0, 0.5, 0, 0.5, 0, 0, 0, 0, 0, 0, 0]\n",
"State=8, prob vec =[0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0.5, 0, 0, 0, 0, 0, 0]\n",
"State=9, prob vec =[0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0.5, 0, 0, 0, 0, 0]\n",
"State=10, prob vec =[0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0.5, 0, 0, 0, 0]\n",
"State=11, prob vec =[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0.5, 0, 0, 0]\n",
"State=12, prob vec =[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0.5, 0, 0]\n",
"State=13, prob vec =[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0.5, 0]\n",
"State=14, prob vec =[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0.5]\n",
"State=15, prob vec =[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.0, 0]\n"
]
}
],
"source": [
"@qfunc\n",
"def main(vertices:Output[QNum], adjacent_vertices:Output[QNum]):\n",
" '''function'''\n",
"\n",
" allocate(size,vertices)\n",
" hadamard_transform(vertices)\n",
" allocate(size,adjacent_vertices)\n",
"\n",
" W_operator(vertices,adjacent_vertices)\n",
" S_operator(vertices,adjacent_vertices)\n",
"\n",
"qmod = create_model(main)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"id": "-cENeHTsQzdA"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Opening: https://platform.classiq.io/circuit/9bfc927c-ffe6-431c-8011-c71f4d35b8bd?version=0.43.3\n"
]
}
],
"source": [
"qprog = synthesize(qmod)\n",
"show(qprog)"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"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": "3.11.4"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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