Plotting the solution to [4,5,7,4]

plot_oq.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "states kept: 16\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "q.results.plot_probabilities()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "feat_workflow_braket",
   "language": "python",
   "name": "feat_workflow_braket"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}