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some large ccts used in practice
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@Cryoris
Cryoris committed May 16, 2020
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from time import time"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"def print_stats(circuit):\n",
" print('Depth:', circuit.depth())\n",
" print('Num qubits:', circuit.num_qubits)\n",
" print('Ops:', circuit.count_ops())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# UCCSD"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"from qiskit.circuit import ParameterVector\n",
"from qiskit.chemistry.components.variational_forms import UCCSD\n",
"from qiskit.aqua.operators import Z2Symmetries\n",
"from qiskit.chemistry.drivers import PySCFDriver, UnitsType\n",
"from qiskit.chemistry import FermionicOperator"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"def get_qubit_op(dist, molecule=\"LiH\", basis=\"sto3g\"):\n",
" if molecule == \"LiH\":\n",
" driver = PySCFDriver(atom=\"Li .0 .0 .0; H .0 .0 \" + str(dist), unit=UnitsType.ANGSTROM, \n",
" charge=0, spin=0, basis=basis)\n",
" elif molecule == \"BeH2\":\n",
" driver = PySCFDriver(atom=\"Be .0 .0 .0; H .0 .0 -\" + str(dist) + \"; H .0 .0 \" + str(dist), \n",
" unit=UnitsType.ANGSTROM, \n",
" charge=0, spin=0, basis=basis)\n",
" molecule = driver.run()\n",
" freeze_list = [0]\n",
" remove_list = [-3, -2]\n",
" repulsion_energy = molecule.nuclear_repulsion_energy\n",
" num_particles = molecule.num_alpha + molecule.num_beta\n",
" num_spin_orbitals = molecule.num_orbitals * 2\n",
" remove_list = [x % molecule.num_orbitals for x in remove_list]\n",
" freeze_list = [x % molecule.num_orbitals for x in freeze_list]\n",
" remove_list = [x - len(freeze_list) for x in remove_list]\n",
" remove_list += [x + molecule.num_orbitals - len(freeze_list) for x in remove_list]\n",
" freeze_list += [x + molecule.num_orbitals for x in freeze_list]\n",
" ferOp = FermionicOperator(h1=molecule.one_body_integrals, h2=molecule.two_body_integrals)\n",
" ferOp, energy_shift = ferOp.fermion_mode_freezing(freeze_list)\n",
" num_spin_orbitals -= len(freeze_list)\n",
" num_particles -= len(freeze_list)\n",
" ferOp = ferOp.fermion_mode_elimination(remove_list)\n",
" num_spin_orbitals -= len(remove_list)\n",
" qubitOp = ferOp.mapping(map_type='parity', threshold=0.00000001)\n",
" qubitOp = Z2Symmetries.two_qubit_reduction(qubitOp, num_particles)\n",
" shift = energy_shift + repulsion_energy\n",
" return qubitOp, num_particles, num_spin_orbitals, shift\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Try `LiH` or `BeH2` as molecules, `sto-3g` for a small basis set and `3-21g` as large basis set.\n",
"To make the circuit deeper, you can set `reps` to a value larger than 1."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Constructed in 1.8730289936065674s\n"
]
}
],
"source": [
"molecule = 'LiH'\n",
"basis_set = '3-21g'\n",
"reps = 1\n",
"dist = 1.3\n",
"qubitOp, num_particles, num_spin_orbitals, shift = get_qubit_op(dist, molecule, basis_set)\n",
"var_form = UCCSD(\n",
" num_orbitals=num_spin_orbitals,\n",
" num_particles=num_particles,\n",
" reps=1,\n",
" qubit_mapping='parity'\n",
")\n",
"t0 = time()\n",
"circuit = var_form.construct_circuit(ParameterVector('P', length=var_form.num_parameters))\n",
"print('Constructed in {}s'.format(time() - t0))"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Depth: 2406\n",
"Num qubits: 10\n",
"Ops: OrderedDict([('u3', 1960), ('cx', 1312), ('cmp_dg', 14), ('cmp', 8), ('cLinRot', 8), ('cmp_dg_dg', 6), ('cLinRot_dg', 6), ('LinRot', 4), ('LinRot_dg', 3), ('h', 2), ('cu1', 1)])\n",
"Ops (decomposed): OrderedDict([('u3', 2156), ('cx', 1510), ('x', 280), ('ccx', 168), ('cry', 21), ('ry', 7), ('u1', 3), ('u2', 2)])\n"
]
}
],
"source": [
"print_stats(circuit.decompose())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# QAE"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"from qiskit.aqua.algorithms import AmplitudeEstimation\n",
"from qiskit.circuit.library import EfficientSU2\n",
"from qiskit.aqua.components.uncertainty_models import NormalDistribution\n",
"from qiskit.aqua.components.uncertainty_problems import UnivariatePiecewiseLinearObjective"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"class AFactory(CircuitFactory):\n",
" def __init__(self, objective, distribution):\n",
" super().__init__(distribution.num_target_qubits + 1)\n",
" self.objective = objective\n",
" self.distribution = distribution\n",
" self.i_state = list(range(distribution.num_target_qubits))\n",
" self.i_target = distribution.num_target_qubits\n",
" \n",
" def required_ancillas(self):\n",
" return self.objective.required_ancillas()\n",
" \n",
" def required_ancillas_controlled(self):\n",
" return self.objective.required_ancillas_controlled()\n",
" \n",
" def build(self, qc, q, q_ancillas=None, params=None):\n",
" qr_state = [q[i] for i in self.i_state]\n",
" qr_target = [q[self.i_target]]\n",
" \n",
" self.distribution.build(qc, qr_state)\n",
" self.objective.build(qc, q, q_ancillas=q_ancillas)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/jul/Work/Qiskit/qiskit-aqua/qiskit/aqua/components/uncertainty_problems/univariate_piecewise_linear_objective.py:164: DeprecationWarning: The qiskit.aqua.circuits.PiecewiseLinearRotation object is deprecated and will be removed no earlier than 3 months after the 0.7.0 release of Qiskit Aqua. You should use qiskit.circuit.library.PiecewiseLinearPauliRotations instead.\n",
" # create piecewise linear Y rotation\n"
]
}
],
"source": [
"num_state_qubits = 4\n",
"breakpoints = [0, 2, 5]\n",
"slopes = [1, 2, 5]\n",
"offsets = [-1, 0, 1]\n",
"f_min = 0\n",
"f_max = 12\n",
"c_approx = 0.1\n",
"distribution = NormalDistribution(num_state_qubits)\n",
"pwl = UnivariatePiecewiseLinearObjective(num_state_qubits, 0, 10, \n",
" breakpoints, slopes, offsets,\n",
" f_min, f_max, c_approx)\n",
"\n",
"a_factory = AFactory(pwl, distribution)"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Constructed in 16.878931999206543s\n"
]
}
],
"source": [
"m = 5\n",
"qae = AmplitudeEstimation(m, a_factory=a_factory)\n",
"t0 = time()\n",
"circuit = qae.construct_circuit()\n",
"print('Constructed in {}s'.format(time() - t0))"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Depth: 47750\n",
"Num qubits: 15\n",
"Ops: OrderedDict([('u1', 31139), ('cx', 27200), ('u2', 5771), ('u3', 2309), ('pw_lin', 32), ('pw_lin_dg', 31), ('iqft', 1)])\n"
]
}
],
"source": [
"print_stats(circuit)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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