\n",
"q_0: ───────────────────■──────────────────────────────────────────────────\n",
" │ \n",
"q_1: ───────────────────┼─────────────■────────────────────────────────────\n",
" │ │ \n",
"q_2: ───────────────────┼─────────────┼─────────────■──────────────────────\n",
" │ │ │ \n",
"q_3: ───────────────────┼─────────────┼─────────────┼─────────────■────────\n",
" ┌───────────┐┌─────┴──────┐┌─────┴──────┐┌─────┴─────┐┌──────┴───────┐\n",
"q_4: ┤ RY(9π/16) ├┤ RY(-π/216) ├┤ RY(-π/108) ├┤ RY(-π/27) ├┤ RY(-0.23271) ├\n",
" └───────────┘└────────────┘└────────────┘└───────────┘└──────────────┘"
],
"text/plain": [
" \n",
"q_0: ───────────────────■──────────────────────────────────────────────────\n",
" │ \n",
"q_1: ───────────────────┼─────────────■────────────────────────────────────\n",
" │ │ \n",
"q_2: ───────────────────┼─────────────┼─────────────■──────────────────────\n",
" │ │ │ \n",
"q_3: ───────────────────┼─────────────┼─────────────┼─────────────■────────\n",
" ┌───────────┐┌─────┴──────┐┌─────┴──────┐┌─────┴─────┐┌──────┴───────┐\n",
"q_4: ┤ RY(9π/16) ├┤ RY(-π/216) ├┤ RY(-π/108) ├┤ RY(-π/27) ├┤ RY(-0.23271) ├\n",
" └───────────┘└────────────┘└────────────┘└───────────┘└──────────────┘"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fixed_income.draw()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" ┌───────┐┌────┐\n",
"q_0: ┤0 ├┤0 ├\n",
" │ ││ │\n",
"q_1: ┤1 ├┤1 ├\n",
" │ P(X) ││ │\n",
"q_2: ┤2 ├┤2 F ├\n",
" │ ││ │\n",
"q_3: ┤3 ├┤3 ├\n",
" └───────┘│ │\n",
"q_4: ─────────┤4 ├\n",
" └────┘"
],
"text/plain": [
" ┌───────┐┌────┐\n",
"q_0: ┤0 ├┤0 ├\n",
" │ ││ │\n",
"q_1: ┤1 ├┤1 ├\n",
" │ P(X) ││ │\n",
"q_2: ┤2 ├┤2 F ├\n",
" │ ││ │\n",
"q_3: ┤3 ├┤3 ├\n",
" └───────┘│ │\n",
"q_4: ─────────┤4 ├\n",
" └────┘"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"state_preparation = QuantumCircuit(fixed_income.num_qubits)\n",
"\n",
"# load probability distribution\n",
"state_preparation.append(u, range(u.num_qubits))\n",
"\n",
"# apply function\n",
"state_preparation.append(fixed_income, range(fixed_income.num_qubits))\n",
"\n",
"state_preparation.draw()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"ExecuteTime": {
"end_time": "2020-07-13T23:39:30.566677Z",
"start_time": "2020-07-13T23:39:30.561554Z"
}
},
"outputs": [],
"source": [
"# set target precision and confidence level\n",
"epsilon = 0.01\n",
"alpha = 0.05\n",
"\n",
"# set objective qubit\n",
"objective = u.num_qubits\n",
"\n",
"# construct amplitude estimation \n",
"ae = IterativeAmplitudeEstimation(epsilon=epsilon, alpha=alpha, \n",
" state_preparation=state_preparation,\n",
" objective_qubits=[objective],\n",
" post_processing=fixed_income.post_processing)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"ExecuteTime": {
"end_time": "2020-07-13T23:39:53.292025Z",
"start_time": "2020-07-13T23:39:30.882045Z"
}
},
"outputs": [],
"source": [
"result = ae.run(quantum_instance=Aer.get_backend('qasm_simulator'), shots=100)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"ExecuteTime": {
"end_time": "2020-07-13T23:39:53.298201Z",
"start_time": "2020-07-13T23:39:53.294221Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Exact value: \t2.1942\n",
"Estimated value: \t2.3404\n",
"Confidence interval:\t[2.3094, 2.3714]\n"
]
}
],
"source": [
"conf_int = np.array(result['confidence_interval'])\n",
"print('Exact value: \\t%.4f' % exact_value)\n",
"print('Estimated value: \\t%.4f' % (result['estimation']))\n",
"print('Confidence interval:\\t[%.4f, %.4f]' % tuple(conf_int))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"ExecuteTime": {
"end_time": "2020-07-13T23:39:53.845834Z",
"start_time": "2020-07-13T23:39:53.687281Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"| Qiskit Software | Version |
|---|---|
| Qiskit | 0.23.3 |
| Terra | 0.16.2 |
| Aer | 0.7.3 |
| Ignis | 0.5.1 |
| Aqua | 0.8.1 |
| IBM Q Provider | 0.11.1 |
| System information | |
| Python | 3.8.5 (default, Sep 4 2020, 07:30:14) \n", "[GCC 7.3.0] |
| OS | Linux |
| CPUs | 2 |
| Memory (Gb) | 3.736370086669922 |
| Thu Jan 28 13:33:57 2021 IST | |
© Copyright IBM 2017, 2021.
This code is licensed under the Apache License, Version 2.0. You may
obtain a copy of this license in the LICENSE.txt file in the root directory
of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
Any modifications or derivative works of this code must retain this
copyright notice, and modified files need to carry a notice indicating
that they have been altered from the originals.