{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Simulation of Widget-Adjustable Parametric Circuit\n", "\n", "Suppose you are interested in printing out the state vector\n", "of a quantum circuit at various times (points) in its evolution, as well\n", "as at the end of the circuit. Qubiter can do that.\n", "\n", "Furthermore, suppose that the circuit is a parametric one, and you want to\n", "vary its parameters using sliders on a gui (graphical user interface).\n", "Qubiter can do that too, via a jupyter notebook with widgets.\n", "This notebook is one such notebook. \n", "\n", "\n", "A jupyter\n", "notebook with widgets gives you\n", "the best of both worlds, the gui world and the notebooks world.\n", "\n", "Gui's excel at reducing the possibility of user errors, increasing the ease of use for the user,\n", "and reducing the amount of understanding of the code \n", "that is demanded from the user in order for him or her to use \n", "the code correctly.\n", "\n", "Notebooks excel at providing a robust, flexible, ready made, familiar method of documenting\n", "and saving your work for multiple use cases. They are also great for \n", "explaining your work to others with great detail and precision." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/home/rrtucci/PycharmProjects/qubiter/qubiter/jupyter_notebooks\n", "/home/rrtucci/PycharmProjects/qubiter\n" ] } ], "source": [ "# cd to the Qubiter directory and add it to your path environmental variable\n", "import os\n", "import sys\n", "print(os.getcwd())\n", "os.chdir('../../')\n", "print(os.getcwd())\n", "sys.path.insert(0,os.getcwd())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will first construct the quantum\n", "circuit that we are interested in studying.\n", "\n", "Note that we insert a PRINT statement at each point \n", "at which we want a printout of\n", "the state vector (except at the end point which has an implicit PRINT\n", "statement). \n", "\n", "Note also that \n", "the angles for some gates are special strings \n", "with hash characters in them instead of floats.\n", "These placeholder variable or parameter\n", "strings have been explained elsewhere,\n", "in another jupyter notebook." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A PRINT statement in the 'ALL' style will\n", "print out a bunch of text info about the state vector\n", "at the point in the evolution where the print statement is located.\n", "The 'ALL+' style will printout\n", "everything that the 'ALL' style prints out, plus it\n", "prints a bar graph of the probability \n", "associated with each component of the state vector." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "loaded OneQubitGate, WITHOUT autograd.numpy\n" ] } ], "source": [ "from qubiter.jupyter_notebooks.utilities_nb import run_sim_gui\n", "from qubiter.SEO_writer import *" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "num_qbits = 3\n", "file_prefix = 'widgets_simulation_test'\n", "\n", "emb = CktEmbedder(num_qbits, num_qbits)\n", "wr = SEO_writer(file_prefix, emb)\n", "wr.write_Ry(0, rads='#1*.5')\n", "wr.write_Ry(1, rads='#2*.5')\n", "wr.write_cnot(0, 1)\n", "wr.write_PRINT('ALL+')\n", "wr.write_Ry(0, rads='#3*.5')\n", "wr.write_Ry(1, rads='#4*.5')\n", "wr.write_cnot(0, 1)\n", "wr.write_PRINT('ALL+')\n", "\n", "trols = Controls(num_qbits)\n", "trols.bit_pos_to_kind = {0:True, 1:False}\n", "trols.refresh_lists()\n", "wr.write_controlled_one_qbit_gate(2, trols,\n", " OneQubitGate.rot_ax, ['fun#1#3', 1])\n", "\n", "wr.close_files()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# We can ask wr to print the English file just created\n", "wr.print_eng_file(jup=True)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# We can ask wr to print the Picture file just created\n", "wr.print_pic_file(jup=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "All the gui code is prepackaged and\n", "included in a method called `run_sim_gui()`\n", "included in the file `utilities_nb.py`" ] }, { "attachments": { "gui-qubiter-sim.jpeg": { "image/jpeg": 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "This is a static jpeg showing what the widgets look like. A new, different interactive javascript rendering of the widgets will be generated when you run the notebook. To generate this cell, I: \n", "1. printed the computer screen, and then cropped the image with Gimp to produce the final jpeg\n", "2. made this cell a markdown cell, and then drag&dropped the final jpeg into this cell\n", "3. added these instructions at the top of the cell\n", "4. ran this cell\n", "![gui-qubiter-sim.jpeg](attachment:gui-qubiter-sim.jpeg)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "a3c81a6ebfbb43ffa9dd9a89237d7f71", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(VBox(children=(FloatSlider(value=130.0, max=1080.0, orientation='vertical', step=10.0), FloatTe…" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "degs_1 = 130.000000 (2.268928 rads)\n", "degs_2 = 240.000000 (4.188790 rads)\n", "degs_3 = 380.000000 (6.632251 rads)\n", "degs_4 = 70.000000 (1.221730 rads)\n", "\n", "*************************beginning PRINT output\n", "PRINT line number=4\n", "*********branch= pure\n", "state vector:\n", "ZL convention (Zero bit Last in state tuple)\n", "(000)ZL (-0.211309 + 0.000000j)\t prob=0.044652\n", "(010)ZL (-0.365998 + 0.000000j)\t prob=0.133955\n", "(001)ZL ( 0.784886 + 0.000000j)\t prob=0.616045\n", "(011)ZL ( 0.453154 + 0.000000j)\t prob=0.205348\n", "total probability of state vector (=one if no measurements)= 1.000000\n", "dictionary with key=qubit, value=(Prob(0), Prob(1))\n", "{0: (0.178606, 0.821394), 1: (0.660697, 0.339303), 2: (1.0, 0.0)}\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "****************************ending PRINT output\n", "\n", "*************************beginning PRINT output\n", "PRINT line number=8\n", "*********branch= pure\n", "state vector:\n", "ZL convention (Zero bit Last in state tuple)\n", "(000)ZL ( 0.220423 + 0.000000j)\t prob=0.048586\n", "(010)ZL ( 0.189609 + 0.000000j)\t prob=0.035952\n", "(001)ZL ( 0.046775 + 0.000000j)\t prob=0.002188\n", "(011)ZL (-0.955654 + 0.000000j)\t prob=0.913274\n", "total probability of state vector (=one if no measurements)= 1.000000\n", "dictionary with key=qubit, value=(Prob(0), Prob(1))\n", "{0: (0.084538, 0.915462), 1: (0.050774, 0.949226), 2: (1.0, 0.0)}\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "****************************ending PRINT output\n", "\n", "-----------------------------beginning final results\n", "*********branch= pure\n", "state vector:\n", "ZL convention (Zero bit Last in state tuple)\n", "(000)ZL ( 0.220423 + 0.000000j)\t prob=0.048586\n", "(010)ZL ( 0.189609 + 0.000000j)\t prob=0.035952\n", "(001)ZL ( 0.015154 + 0.000000j)\t prob=0.000230\n", "(101)ZL ( 0.000000 + 0.044252j)\t prob=0.001958\n", "(011)ZL (-0.955654 + 0.000000j)\t prob=0.913274\n", "total probability of state vector (=one if no measurements)= 1.000000\n", "dictionary with key=qubit, value=(Prob(0), Prob(1))\n", "{0: (0.084538, 0.915462), 1: (0.050774, 0.949226), 2: (0.998042, 0.001958)}\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-----------------------------ending final results\n", "\n" ] } ], "source": [ "all_var_nums = [1, 2, 3, 4]\n", "def fun(a, b):\n", " return a*b*.5\n", "fun_name_to_fun = {'fun': fun}\n", "\n", "# re-run this cell if you change the arguments of run_sim_gui()\n", "%matplotlib inline\n", "run_sim_gui(file_prefix, num_qbits, all_var_nums, fun_name_to_fun=fun_name_to_fun, \n", " append_new=True, sty_fin_desc='ALL+')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.10.9" 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