┌────┐\n",
"q_0: ┤0 ├\n",
" │ │\n",
"q_1: ┤1 ├\n",
" │ │\n",
"q_2: ┤2 F ├\n",
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" │ │\n",
"q_4: ┤4 ├\n",
" └────┘"
],
"text/plain": [
" ┌────┐\n",
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" │ │\n",
"q_3: ┤3 ├\n",
" │ │\n",
"q_4: ┤4 ├\n",
" └────┘"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fixed_income._objective.draw()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"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",
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" │ P(X) ││ │\n",
"q_2: ┤2 ├┤2 F ├\n",
" │ ││ │\n",
"q_3: ┤3 ├┤3 ├\n",
" └───────┘│ │\n",
"q_4: ─────────┤4 ├\n",
" └────┘"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fixed_income_circ = QuantumCircuit(fixed_income._objective.num_qubits)\n",
"\n",
"# load probability distribution\n",
"fixed_income_circ.append(u, range(u.num_qubits))\n",
"\n",
"# apply function\n",
"fixed_income_circ.append(fixed_income._objective, range(fixed_income._objective.num_qubits))\n",
"\n",
"fixed_income_circ.draw()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"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",
"# construct amplitude estimation\n",
"problem = fixed_income.to_estimation_problem()\n",
"\n",
"ae = IterativeAmplitudeEstimation(\n",
" epsilon_target=epsilon, alpha=alpha, sampler=Sampler(run_options={\"shots\": 100, \"seed\": 75})\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"ExecuteTime": {
"end_time": "2020-07-13T23:39:53.292025Z",
"start_time": "2020-07-13T23:39:30.882045Z"
}
},
"outputs": [],
"source": [
"result = ae.estimate(problem)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"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: \t2.3437\n",
"Confidence interval:\t[2.3101, 2.3772]\n"
]
}
],
"source": [
"conf_int = np.array(result.confidence_interval_processed)\n",
"print(\"Exact value: \\t%.4f\" % exact_value)\n",
"print(\"Estimated value: \\t%.4f\" % (fixed_income.interpret(result)))\n",
"print(\"Confidence interval:\\t[%.4f, %.4f]\" % tuple(conf_int))"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"ExecuteTime": {
"end_time": "2020-07-13T23:39:53.845834Z",
"start_time": "2020-07-13T23:39:53.687281Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"| Software | Version |
|---|---|
qiskit | None |
qiskit-terra | 0.45.0.dev0+c626be7 |
qiskit_finance | 0.4.0 |
qiskit_algorithms | 0.2.0 |
qiskit_ibm_provider | 0.6.1 |
qiskit_optimization | 0.6.0 |
qiskit_aer | 0.12.0 |
| System information | |
| Python version | 3.9.7 |
| Python compiler | GCC 7.5.0 |
| Python build | default, Sep 16 2021 13:09:58 |
| OS | Linux |
| CPUs | 2 |
| Memory (Gb) | 5.778430938720703 |
| Fri Aug 18 16:21:18 2023 EDT | |
© Copyright IBM 2017, 2023.
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.