Bernstein-Vazirani-Algo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f45d7135-a5cf-4ace-9287-f9083398e276",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-02T16:37:44.506465Z",
     "iopub.status.busy": "2022-03-02T16:37:44.504481Z",
     "iopub.status.idle": "2022-03-02T16:37:46.403003Z",
     "shell.execute_reply": "2022-03-02T16:37:46.402001Z"
    },
    "papermill": {
     "duration": 1.977086,
     "end_time": "2022-03-02T16:37:46.407064",
     "exception": false,
     "start_time": "2022-03-02T16:37:44.429978",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<frozen importlib._bootstrap>:219: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject\n"
     ]
    }
   ],
   "source": [
    "from qiskit import *\n",
    "%matplotlib inline\n",
    "from qiskit.tools.visualization import plot_histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bbd3bf7f-31ff-44d4-8055-8253409392f7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-02T16:37:46.561629Z",
     "iopub.status.busy": "2022-03-02T16:37:46.561062Z",
     "iopub.status.idle": "2022-03-02T16:37:46.570700Z",
     "shell.execute_reply": "2022-03-02T16:37:46.569338Z"
    },
    "papermill": {
     "duration": 0.089533,
     "end_time": "2022-03-02T16:37:46.574807",
     "exception": false,
     "start_time": "2022-03-02T16:37:46.485274",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "secretnumber = '1101001'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e2994272-1579-4910-93da-fceb225cde18",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-02T16:37:46.758941Z",
     "iopub.status.busy": "2022-03-02T16:37:46.758426Z",
     "iopub.status.idle": "2022-03-02T16:37:46.780218Z",
     "shell.execute_reply": "2022-03-02T16:37:46.779051Z"
    },
    "papermill": {
     "duration": 0.100465,
     "end_time": "2022-03-02T16:37:46.782360",
     "exception": false,
     "start_time": "2022-03-02T16:37:46.681895",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f2a93ddcd40>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit = QuantumCircuit(len(secretnumber)+1, len(secretnumber))\n",
    "circuit.h(range(len(secretnumber)))\n",
    "circuit.x(len(secretnumber))\n",
    "circuit.h(len(secretnumber))\n",
    "\n",
    "circuit.barrier()\n",
    "\n",
    "for i, on_off in enumerate(reversed(secretnumber)):\n",
    "    if on_off == '1':\n",
    "        circuit.cx(i, len(secretnumber))\n",
    "\n",
    "circuit.barrier()\n",
    "\n",
    "circuit.h(range(len(secretnumber)))\n",
    "\n",
    "circuit.barrier()\n",
    "\n",
    "circuit.measure(range(len(secretnumber)), range(len(secretnumber)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9dc53d1a-2716-422e-9aed-3c04969a2e4c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-02T16:37:46.952318Z",
     "iopub.status.busy": "2022-03-02T16:37:46.951787Z",
     "iopub.status.idle": "2022-03-02T16:37:47.765141Z",
     "shell.execute_reply": "2022-03-02T16:37:47.764698Z"
    },
    "papermill": {
     "duration": 0.924771,
     "end_time": "2022-03-02T16:37:47.770822",
     "exception": false,
     "start_time": "2022-03-02T16:37:46.846051",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1110x565.88 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9b218cb0-a23a-48e2-8216-b5f433f81455",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-02T16:37:47.932937Z",
     "iopub.status.busy": "2022-03-02T16:37:47.931011Z",
     "iopub.status.idle": "2022-03-02T16:37:48.474926Z",
     "shell.execute_reply": "2022-03-02T16:37:48.474239Z"
    },
    "papermill": {
     "duration": 0.627275,
     "end_time": "2022-03-02T16:37:48.476434",
     "exception": false,
     "start_time": "2022-03-02T16:37:47.849159",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'1101001': 1}\n"
     ]
    }
   ],
   "source": [
    "simulator = Aer.get_backend('qasm_simulator')\n",
    "result = execute(circuit, backend = simulator, shots = 1).result()\n",
    "count = result.get_counts()\n",
    "print(count)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Qiskit v0.34.2 (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": "3.8.12"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 7.887969,
   "end_time": "2022-03-02T16:37:49.083942",
   "environment_variables": {},
   "exception": null,
   "input_path": "/home/jovyan/QiskitSeason1/Bernstein-Vazirani-Algo.ipynb",
   "output_path": "/home/jovyan/QiskitSeason1/Bernstein-Vazirani-Algo-background-results.ipynb",
   "parameters": {},
   "start_time": "2022-03-02T16:37:41.195973",
   "version": "2.3.3"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "070be110d0bb47dc908def3a3fcf9592": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "249a6622bc5f42e7825427c957d49bc0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "GridBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_422731b0f7284cfe861efa203d872731"
       ],
       "layout": "IPY_MODEL_bd46727e302643e9ac662a9ce8ff7c26"
      }
     },
     "251d7245de5e4b9c9c0ebc698b01d352": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_68dbc2f5838b4980a4151947d4bf3e56",
       "style": "IPY_MODEL_a4eebedd6de243e19999b3505a31aec2",
       "value": "<h5>Status</h5>"
      }
     },
     "3a45396060184b58a2989ab617f49bc2": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "margin": "0px 0px 10px 0px"
      }
     },
     "422731b0f7284cfe861efa203d872731": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "primary",
       "description": "Clear",
       "layout": "IPY_MODEL_c2b9b154fa38447fbc4b7d0cc1c4f32d",
       "style": "IPY_MODEL_070be110d0bb47dc908def3a3fcf9592"
      }
     },
     "4e205a93c4e74ef9aa4ac1c95e3e6386": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "5f071114fbd04e7b90d454911b1cdafb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "68dbc2f5838b4980a4151947d4bf3e56": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "95px"
      }
     },
     "6a311cf1d67844e5a4d34f0f23e1b08a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_9b807e4804be408cb55f85f328c7466d",
       "style": "IPY_MODEL_f067bec5ef1b424f90997d3c272421cb",
       "value": "<h5>Backend</h5>"
      }
     },
     "6c771e2b89d3405dbd1384795ef2e180": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_71c8b677b99f4d3e80c7be5493d6aa30",
       "style": "IPY_MODEL_f1afd13e0f4a4c45bf22ac8bff7ea3b3",
       "value": "<h5>Job ID</h5>"
      }
     },
     "71c8b677b99f4d3e80c7be5493d6aa30": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "190px"
      }
     },
     "9b807e4804be408cb55f85f328c7466d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "145px"
      }
     },
     "a4eebedd6de243e19999b3505a31aec2": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "b3bd6cd1887e45dda32170332d70c3a4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_eaec52c2ea854c4c9879d30ea498cabf",
       "style": "IPY_MODEL_e7328c8d6fea42f2b9a067ad56b7f130",
       "value": "<h5>Queue</h5>"
      }
     },
     "bd46727e302643e9ac662a9ce8ff7c26": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_template_areas": "\n                                       \". . . . right \"\n                                        ",
       "grid_template_columns": "20% 20% 20% 20% 20%",
       "width": "100%"
      }
     },
     "bef730e36ee34d75a477959fe7e29890": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "margin": "0px 0px 0px 37px",
       "width": "600px"
      }
     },
     "c2b9b154fa38447fbc4b7d0cc1c4f32d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "right",
       "padding": "0px 0px 0px 0px",
       "width": "70px"
      }
     },
     "c9429ad1d493401c80eaff447fde5d28": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_6c771e2b89d3405dbd1384795ef2e180",
        "IPY_MODEL_6a311cf1d67844e5a4d34f0f23e1b08a",
        "IPY_MODEL_251d7245de5e4b9c9c0ebc698b01d352",
        "IPY_MODEL_b3bd6cd1887e45dda32170332d70c3a4",
        "IPY_MODEL_f372db395274422fbb9221c127e9a486"
       ],
       "layout": "IPY_MODEL_bef730e36ee34d75a477959fe7e29890"
      }
     },
     "cbeb34410a124eb6ae47c8c13ba1f944": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_3a45396060184b58a2989ab617f49bc2",
       "style": "IPY_MODEL_4e205a93c4e74ef9aa4ac1c95e3e6386",
       "value": "<p style='font-family: IBM Plex Sans, Arial, Helvetica, sans-serif; font-size: 20px; font-weight: medium;'>Circuit Properties</p>"
      }
     },
     "e7328c8d6fea42f2b9a067ad56b7f130": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "eaec52c2ea854c4c9879d30ea498cabf": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "ed697741485b4b98b43c7edc5249c239": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f067bec5ef1b424f90997d3c272421cb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "f1afd13e0f4a4c45bf22ac8bff7ea3b3": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "f372db395274422fbb9221c127e9a486": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_ed697741485b4b98b43c7edc5249c239",
       "style": "IPY_MODEL_5f071114fbd04e7b90d454911b1cdafb",
       "value": "<h5>Message</h5>"
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}