{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Investigating Noise\n", "\n", "In this example, we investigate how a program might behave on a near-term device that is subject to noise using the convenience function `add_decoherence_noise`." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from pyquil import Program\n", "from pyquil.paulis import PauliSum, PauliTerm, exponentiate, exponential_map\n", "from pyquil.gates import MEASURE, H, Z, RX, RZ, CZ\n", "import numpy as np" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The task\n", "We want to prepare $e^{i \\theta XY}$ and measure it in the $Z$ basis." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from numpy import pi\n", "theta = pi/3\n", "xy = PauliTerm('X', 0) * PauliTerm('Y', 1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The idiomatic Pyquil program" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "H 0\n", "RX(pi/2) 1\n", "CNOT 0 1\n", "RZ(2*pi/3) 1\n", "CNOT 0 1\n", "H 0\n", "RX(-pi/2) 1\n", "\n" ] } ], "source": [ "prog = exponential_map(xy)(theta)\n", "print(prog)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The compiled program\n", "To run on a real device, we must compile each program to the native gate set for the device. The high-level noise model is similarly constrained to use a small, native gate set. In particular, we can use\n", "\n", " - $I$\n", " - $RZ(\\theta)$\n", " - $RX(\\pm \\pi/2)$\n", " - $CZ$\n", "\n", "For simplicity, the compiled program is given below but generally you will want to use a compiler to do this step for you." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "def get_compiled_prog(theta):\n", " return Program([\n", " RZ(-pi/2, 0),\n", " RX(-pi/2, 0),\n", " RZ(-pi/2, 1),\n", " RX( pi/2, 1),\n", " CZ(1, 0),\n", " RZ(-pi/2, 1),\n", " RX(-pi/2, 1),\n", " RZ(theta, 1),\n", " RX( pi/2, 1),\n", " CZ(1, 0),\n", " RX( pi/2, 0),\n", " RZ( pi/2, 0),\n", " RZ(-pi/2, 1),\n", " RX( pi/2, 1),\n", " RZ(-pi/2, 1),\n", " ])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Scan over noise parameters\n", "We perform a scan over three levels of noise each at 20 theta points.\n", "\n", "Specifically, we investigate T1 values of 1, 3, and 10 us. By default, T2 = T1 / 2, 1 qubit gates take 50 ns, and 2 qubit gates take 150 ns. \n", "\n", "In alignment with the device, $I$ and parametric $RZ$ are noiseless while $RX$ and $CZ$ gates experience 1q and 2q gate noise, respectively." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from pyquil import get_qc\n", "qc = get_qc('8q-qvm')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([ 1. , 3.16227766, 10. ])" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t1s = np.logspace(-6, -5, num=3)\n", "thetas = np.linspace(-pi, pi, num=20)\n", "t1s * 1e6 # us" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "from pyquil.noise import add_decoherence_noise\n", "records = []\n", "for theta in thetas:\n", " for t1 in t1s:\n", " prog = get_compiled_prog(theta)\n", " ro = prog.declare(\"ro\", memory_size=2)\n", " noisy = add_decoherence_noise(prog, T1=t1, T2=t1/2).inst([\n", " MEASURE(0, ro[0]),\n", " MEASURE(1, ro[1]),\n", " ])\n", " bitstrings = np.array(qc.run(noisy.wrap_in_numshots_loop(1000)))\n", " \n", " # Expectation of Z0 and Z1\n", " z0, z1 = 1 - 2*np.mean(bitstrings, axis=0)\n", " \n", " # Expectation of ZZ by computing the parity of each pair\n", " zz = 1 - (np.sum(bitstrings, axis=1) % 2).mean() * 2 \n", " \n", " record = {\n", " 'z0': z0,\n", " 'z1': z1,\n", " 'zz': zz,\n", " 'theta': theta,\n", " 't1': t1,\n", " }\n", " records += [record]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot the results" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "from matplotlib import pyplot as plt\n", "import seaborn as sns\n", "sns.set(style='ticks', palette='colorblind')" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "df_all = pd.DataFrame(records)\n", "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(12,4))\n", "\n", "for t1 in t1s:\n", " df = df_all.query('t1 == @t1')\n", " \n", " ax1.plot(df['theta'], df['z0'], 'o-') \n", " ax2.plot(df['theta'], df['z1'], 'o-') \n", " ax3.plot(df['theta'], df['zz'], 'o-', label='T1 = {:.0f} us'.format(t1*1e6))\n", " \n", "ax3.legend(loc='best')\n", "\n", "ax1.set_ylabel('Z0')\n", "ax2.set_ylabel('Z1')\n", "ax3.set_ylabel('ZZ')\n", "ax2.set_xlabel(r'$\\theta$')\n", "fig.tight_layout()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "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": "3.6.3" } }, "nbformat": 4, "nbformat_minor": 2 }