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Create smaoker #11

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{
"cells": [
{
"cell_type": "markdown",
"id": "722f92e3-4324-41b8-bebb-eb5c5c1c0f1a",
"metadata": {},
"source": [
"# Quantum Counting\n",
"\n",
"Here we count the number of solutions to the equation $x+y\\leq 7$ where x, y are integers of size `REG_SIZE` bits. "
]
},
{
"cell_type": "markdown",
"id": "3226860d-953f-4993-82fd-f629497d58c7",
"metadata": {},
"source": [
"## Using the `AmplitudeEstimation` function"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "0db8dd49-550a-419e-bce1-1a19a4a88ba7",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Opening: https://platform.classiq.io/circuit/388ff783-1868-4e26-b930-03b6eb01fd35?version=0.28.0\n"
]
}
],
"source": [
"from classiq import Model, Constraints, synthesize, show, execute\n",
"from classiq.builtin_functions import GroverOperator, ArithmeticOracle, AmplitudeEstimation\n",
"from classiq import RegisterUserInput\n",
"from classiq.execution import ExecutionPreferences\n",
"from classiq.execution import QaeWithQpeEstimationMethod\n",
"\n",
"REG_SIZE=3\n",
"NUM_PHASE_QUBITS=3\n",
"\n",
"arith_params = ArithmeticOracle(\n",
" expression = \"x + y <= 7\",\n",
" definitions=dict(\n",
" x = RegisterUserInput(size=REG_SIZE),\n",
" y = RegisterUserInput(size=REG_SIZE)),\n",
")\n",
"\n",
"grover_operator_params = GroverOperator(\n",
" oracle_params = arith_params,\n",
")\n",
"\n",
"ae_params = AmplitudeEstimation(\n",
" estimation_register_size=NUM_PHASE_QUBITS, grover_operator=grover_operator_params\n",
")\n",
"\n",
"model = Model()\n",
"\n",
"model.constraints = Constraints(max_width=12)\n",
"\n",
"qae_out = model.AmplitudeEstimation(ae_params)\n",
"\n",
"# necessary for the post-process to recognize the register\n",
"model.set_outputs({'ESTIMATED_AMPLITUDE_OUTPUT': qae_out['ESTIMATED_AMPLITUDE_OUTPUT']})\n",
"\n",
"# set execution instructions\n",
"model.sample()\n",
"model.post_process_amplitude_estimation(estimation_register_size=NUM_PHASE_QUBITS, estimation_method=QaeWithQpeEstimationMethod.MAXIMUM_LIKELIHOOD)\n",
"\n",
"quantum_program = synthesize(model.get_model())\n",
"show(quantum_program)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "21a9aef8-996d-4b92-92f7-616412985fb9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The probability estimation of the good states is: 0.14644660940672624\n"
]
}
],
"source": [
"qae_result = execute(quantum_program)\n",
"print(f\"The probability estimation of the good states is: {qae_result[1].value}\")"
]
},
{
"cell_type": "markdown",
"id": "93064d5d-25ba-4fd5-b3fd-eef55b7e07bd",
"metadata": {},
"source": [
"## Explicitly defining the amplitude estimation circuit"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "786636e3-91f8-42d8-8218-9caa5ac142ec",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Opening: https://platform.classiq.io/circuit/415ca5ff-63d5-485a-af16-1afaa6549cd7?version=0.28.0\n"
]
}
],
"source": [
"from classiq import Model, Constraints, synthesize, show, execute\n",
"from classiq.builtin_functions import GroverOperator, ArithmeticOracle, UniformDistributionStatePreparation, PhaseEstimation\n",
"from classiq import RegisterUserInput\n",
"from classiq.execution import ExecutionPreferences\n",
"from classiq.execution import QaeWithQpeEstimationMethod\n",
"\n",
"REG_SIZE=3\n",
"NUM_PHASE_QUBITS=3\n",
"\n",
"sp_params = UniformDistributionStatePreparation(num_qubits=REG_SIZE)\n",
"arith_params = ArithmeticOracle(\n",
" expression = \"x + y <= 7\",\n",
" definitions=dict(\n",
" x = RegisterUserInput(size=REG_SIZE),\n",
" y = RegisterUserInput(size=REG_SIZE)),\n",
")\n",
"\n",
"grover_operator_params = GroverOperator(\n",
" oracle_params = arith_params,\n",
")\n",
"\n",
"qpe_params = PhaseEstimation(\n",
" size=NUM_PHASE_QUBITS, unitary=\"GroverOperator\", unitary_params=grover_operator_params\n",
")\n",
"\n",
"model = Model()\n",
"model.constraints = Constraints(max_width=12)\n",
"\n",
"sp_x = model.UniformDistributionStatePreparation(sp_params)['OUT']\n",
"sp_y = model.UniformDistributionStatePreparation(sp_params)['OUT']\n",
"\n",
"qpe_out = model.PhaseEstimation(params=qpe_params, in_wires={'x': sp_x, 'y': sp_y})\n",
"\n",
"# necessary for the post-process to recognize the register\n",
"model.set_outputs({'ESTIMATED_AMPLITUDE_OUTPUT': qpe_out['PHASE_ESTIMATION']})\n",
"\n",
"# set execution instructions\n",
"model.sample()\n",
"model.post_process_amplitude_estimation(estimation_register_size=NUM_PHASE_QUBITS, estimation_method=QaeWithQpeEstimationMethod.MAXIMUM_LIKELIHOOD)\n",
"\n",
"quantum_program = synthesize(model.get_model())\n",
"show(quantum_program)"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "78f3ccab-1b22-42d5-a328-6ed44abcd88b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The probability estimation of the good states is: 0.5000000000000001\n"
]
}
],
"source": [
"qae_result = execute(quantum_program)\n",
"print(f\"The probability estimation of the good states is: {qae_result[1].value}\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
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"file_extension": ".py",
"mimetype": "text/x-python",
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"nbconvert_exporter": "python",
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"version": "3.11.4"
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