2.3.Measuring_Ic_Vc_and_Rn_at_402ohm.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d8a8a37e-f395-405f-a07d-0349694b422d",
   "metadata": {},
   "source": [
    "# Measuring the Josephson Current, the gap voltage and the normal state resistance at 402ohm \n",
    "** **\n",
    " * This project uses the lmfit package. Lmfit provides curve fiting using non-linear least squares minimization and was developed by Matt Newville: https://github.com/newville."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99bc9cd0-0ca7-4229-bb2d-1414a58bec04",
   "metadata": {},
   "source": [
    "## Install and import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fe638614-0386-4845-b482-4cf89c0a7ec4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#uncomment the following line to install lmfit\n",
    "#!pip install lmfit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "04360f36-197c-420b-8d71-f2df94a17d09",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from lmfit.models import LinearModel\n",
    "import math"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0754b065-979d-4761-ae32-c4f0e97c6630",
   "metadata": {},
   "source": [
    "## Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b466b556-6609-46cb-ace8-4d4f8e8be730",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-7.866</td>\n",
       "      <td>-61.4747</td>\n",
       "      <td>0.00311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-7.725</td>\n",
       "      <td>-59.5667</td>\n",
       "      <td>0.00301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-7.358</td>\n",
       "      <td>-56.8905</td>\n",
       "      <td>0.00288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-7.040</td>\n",
       "      <td>-54.1489</td>\n",
       "      <td>0.00274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-6.694</td>\n",
       "      <td>-51.4086</td>\n",
       "      <td>0.00261</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0        1        2\n",
       "0 -7.866 -61.4747  0.00311\n",
       "1 -7.725 -59.5667  0.00301\n",
       "2 -7.358 -56.8905  0.00288\n",
       "3 -7.040 -54.1489  0.00274\n",
       "4 -6.694 -51.4086  0.00261"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Load the data\n",
    "df = pd.read_csv(\"./Data/402_one_pass.csv\", sep = \" \", header = None)\n",
    "\n",
    "#Preview the data\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69f59ccf-9d58-428a-aba2-80e58fb89e31",
   "metadata": {},
   "source": [
    "## Data wrangling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1a2fbb4d-0b59-4083-9449-2fd37d3709f1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.268</td>\n",
       "      <td>3.3406</td>\n",
       "      <td>0.00020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1.822</td>\n",
       "      <td>5.2718</td>\n",
       "      <td>0.00030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1.878</td>\n",
       "      <td>6.9896</td>\n",
       "      <td>0.00038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1.921</td>\n",
       "      <td>8.7230</td>\n",
       "      <td>0.00047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1.935</td>\n",
       "      <td>10.6706</td>\n",
       "      <td>0.00057</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        0        1        2\n",
       "30  0.268   3.3406  0.00020\n",
       "31  1.822   5.2718  0.00030\n",
       "32  1.878   6.9896  0.00038\n",
       "33  1.921   8.7230  0.00047\n",
       "34  1.935  10.6706  0.00057"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Focus on the positive side of the graph\n",
    "df = df[(df[0] >= 0.268)]\n",
    "\n",
    "#Preview the subset\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e0e46b58-f661-4940-a460-22838f6fb379",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V =  [0.268, 1.822, 1.878, 1.921, 1.935, 2.005, 2.161, 2.401, 2.613, 2.839, 3.065, 3.305, 3.587, 3.827, 4.081, 4.322, 4.59, 4.894, 5.134, 5.48, 5.762, 6.045, 6.306, 6.652, 6.913, 7.294, 7.577, 7.93, 8.241, 8.015, 7.824, 7.591, 7.379, 7.196, 7.019, 6.814, 6.616, 6.419, 6.256, 6.045, 5.861, 5.649, 5.473, 5.331, 5.141, 4.957, 4.802, 4.618, 4.435, 4.307, 4.11, 3.968, 3.785, 3.644, 3.495, 3.333, 3.213, 3.072, 2.909, 2.761, 2.613, 2.486, 2.309, 2.147, 2.048, 2.02, 2.013, 1.977, 1.977, 1.956, 1.928, 1.794, 0.96]\n",
      "I =  [3.3406, 5.2718, 6.9896, 8.723, 10.6706, 12.5383, 14.3584, 16.0856, 18.124, 20.1391, 22.011, 24.1905, 25.9294, 28.0974, 30.133, 32.5615, 34.5207, 36.9936, 38.9289, 41.2742, 43.4797, 46.1204, 48.3811, 50.7742, 53.0826, 55.5098, 57.7753, 60.4631, 62.294, 60.5279, 59.0155, 57.3762, 56.0951, 54.5063, 53.0192, 51.4024, 49.9801, 48.4016, 46.8824, 45.3857, 44.0691, 42.4789, 41.1507, 39.5176, 38.3122, 36.999, 35.415, 34.2437, 32.8657, 31.5758, 30.1821, 28.8982, 27.5134, 26.1661, 24.9478, 23.7151, 22.3234, 21.1903, 19.8901, 18.7059, 17.4439, 16.235, 14.9792, 13.8843, 12.61, 11.5171, 10.2299, 9.2257, 7.9698, 6.9452, 5.6081, 4.5979, 3.5296]\n"
     ]
    }
   ],
   "source": [
    "#Ascribe the columns to the V and I varibles \n",
    "V = list(df[0])\n",
    "I = list(df[1])\n",
    "\n",
    "#Preview the data\n",
    "print(\"V = \", V)\n",
    "print(\"I = \", I )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "419268da-b862-48c9-b78a-420d552c4f6d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Identify the index of an arbitrary upper limit to enhance the plots \n",
    "V.index(4.894)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d68cd360-3b84-4be3-968d-8d77562286e7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V =  [0.268 1.822 1.878 1.921 1.935 2.005 2.161 2.401 2.613 2.839 3.065 3.305\n",
      " 3.587 3.827 4.081]\n",
      "I =  [ 3.3406  5.2718  6.9896  8.723  10.6706 12.5383 14.3584 16.0856 18.124\n",
      " 20.1391 22.011  24.1905 25.9294 28.0974 30.133 ]\n"
     ]
    }
   ],
   "source": [
    "#Remove the data above the chosen upper limit to enhance the view and focus on the single forward pass\n",
    "V = np.array(V[0:15])\n",
    "\n",
    "I = np.array(I[0:15])\n",
    "\n",
    "#Preview the new subsets\n",
    "print(\"V = \", V)\n",
    "print(\"I = \", I)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "aede1c1b-543e-4e7f-bd18-2cac0aa30847",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f7e98cc62d0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Uncomment the line below to make the graph interactive\n",
    "#%matplotlib widget\n",
    "\n",
    "#Preview the data\n",
    "sns.relplot(x = V, y = I, kind = \"line\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6909a570-bf72-4f1b-b00d-4e955bfc4a82",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1600x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Uncomment the line below to make the graph interactive\n",
    "#%matplotlib widget\n",
    "\n",
    "#Set figure size\n",
    "plt.figure(figsize=(16,10))\n",
    "\n",
    "#Take the second derivatove of the data\n",
    "d2I_dV2 = np.gradient(np.gradient(I, V), V)\n",
    "\n",
    "# Set a threshold to identify inflection points\n",
    "threshold = 0.2  # Adjust this threshold as needed\n",
    "inflection_points = V[d2I_dV2 > threshold]\n",
    "\n",
    "# Create a line plot using seaborn\n",
    "sns.lineplot(x=V, y=I, label='Data')\n",
    "sns.lineplot(x=V, y=I, label='Data')\n",
    "\n",
    "# Annotate inflection points on the graph\n",
    "for point in inflection_points:\n",
    "    plt.annotate(f'Inflection Point\\n(V={point:.3f})\\n(I = {np.interp(point, V, I):3f})', xy=(point, np.interp(point, V, I)),\n",
    "                 xytext=(point -1, np.interp(point, V, I) + 5),\n",
    "                 arrowprops={'facecolor': 'red', 'shrink': 0.05})\n",
    "\n",
    "# Set plot labels and title\n",
    "plt.xlabel('V')\n",
    "plt.ylabel('I')\n",
    "plt.title('Inflection Points Detection')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "05975d96-f651-48b2-9092-5704b0f5936c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.268, 1.822, 1.878, 1.921, 1.935, 2.613, 3.587, 3.827])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Preview the inflection points array\n",
    "inflection_points"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc785054-bd2d-4230-86b4-fa6440d296cd",
   "metadata": {},
   "source": [
    "### Clear the graph above to focus on Ic and Vc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1311acd9-0417-4089-a690-7627baaf5f39",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Uncomment the line below to make the graph interactive\n",
    "#%matplotlib widget\n",
    "\n",
    "#Set figure size\n",
    "plt.figure(figsize=(9,6))\n",
    "\n",
    "#Take the second derivative of the data\n",
    "d2I_dV2 = np.gradient(np.gradient(I, V), V)\n",
    "\n",
    "# Set a threshold to identify inflection points\n",
    "threshold = 0.5  # Adjust this threshold as needed\n",
    "inflection_points = V[d2I_dV2 > threshold]\n",
    "\n",
    "# Create a line plot using seaborn\n",
    "sns.lineplot(x=V, y=I, label='Data', color = \"orange\")\n",
    "\n",
    "# Annotate inflection points on the graph\n",
    "for idx, point in enumerate(inflection_points):\n",
    "    if idx in [1, 4]:\n",
    "        plt.annotate(f'Inflection Point\\n(V={point:.3f}mV)\\n(I = {np.interp(point, V, I):3f}$\\mu A$)', \n",
    "                     xy=(point, np.interp(point, V, I)),\n",
    "                     xytext=(point - 1, np.interp(point, V, I) + 5),\n",
    "                     arrowprops={'facecolor': 'red', 'shrink': 0.05})\n",
    "\n",
    "\n",
    "# Set plot labels and title\n",
    "plt.xlabel('V')\n",
    "plt.ylabel('I')\n",
    "plt.title('Inflection Points Detection')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e85392e7-7fdc-4476-805f-665973b49608",
   "metadata": {},
   "source": [
    "# Estimating the normal state resistance (Rn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "59c0fa22-6aaf-4859-b923-3ff6aa7fe6de",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.268, 1.822, 1.878, 1.921, 1.935, 2.005, 2.161, 2.401, 2.613, 2.839, 3.065, 3.305, 3.587, 3.827, 4.081, 4.322, 4.59, 4.894, 5.134, 5.48, 5.762, 6.045, 6.306, 6.652, 6.913, 7.294, 7.577, 7.93, 8.241, 8.015, 7.824, 7.591, 7.379, 7.196, 7.019, 6.814, 6.616, 6.419, 6.256, 6.045, 5.861, 5.649, 5.473, 5.331, 5.141, 4.957, 4.802, 4.618, 4.435, 4.307, 4.11, 3.968, 3.785, 3.644, 3.495, 3.333, 3.213, 3.072, 2.909, 2.761, 2.613, 2.486, 2.309, 2.147, 2.048, 2.02, 2.013, 1.977, 1.977, 1.956, 1.928, 1.794, 0.96]\n"
     ]
    }
   ],
   "source": [
    "#Preview the main dataset\n",
    "print(list(df[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "78ae52f8-aafc-41de-a28e-b7e91c22e3e3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "28\n"
     ]
    }
   ],
   "source": [
    "#The dataset includes points from two complete sweeps\n",
    "#Identify the index of the approximate limits of the normal state on the positive side of the graph \n",
    "print(list(df[0]).index(1.935))\n",
    "print(list(df[0]).index(df[0].max()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b864c5cd-63be-4c90-ba23-6d975b3d44c4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.935 2.005 2.161 2.401 2.613 2.839 3.065 3.305 3.587 3.827 4.081 4.322\n",
      " 4.59  4.894 5.134 5.48  5.762 6.045 6.306 6.652 6.913 7.294 7.577 7.93 ]\n",
      "[10.6706 12.5383 14.3584 16.0856 18.124  20.1391 22.011  24.1905 25.9294\n",
      " 28.0974 30.133  32.5615 34.5207 36.9936 38.9289 41.2742 43.4797 46.1204\n",
      " 48.3811 50.7742 53.0826 55.5098 57.7753 60.4631]\n"
     ]
    }
   ],
   "source": [
    "#Select data from the first pass\n",
    "V_n = np.array(df[0][4:28])\n",
    "I_n = np.array(df[1][4:28])\n",
    "\n",
    "#Preview the data\n",
    "print(V_n)\n",
    "print(I_n)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85c19d83-70af-4459-979f-865a26a9e202",
   "metadata": {},
   "source": [
    "## Define the model and fit the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "14e579a1-d903-42ee-9b29-f3b31a16d046",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[Model]]\n",
      "    Model(linear)\n",
      "[[Fit Statistics]]\n",
      "    # fitting method   = leastsq\n",
      "    # function evals   = 7\n",
      "    # data points      = 24\n",
      "    # variables        = 2\n",
      "    chi-square         = 22.0995672\n",
      "    reduced chi-square = 1.00452578\n",
      "    Akaike info crit   = 2.02010067\n",
      "    Bayesian info crit = 4.37620833\n",
      "    R-squared          = 1.00000000\n",
      "[[Variables]]\n",
      "    slope:      8395.88321 +/- 112.738379 (1.34%) (init = 8124.482)\n",
      "    intercept: -4379065.70 +/- 366631.037 (8.37%) (init = -3224332)\n",
      "[[Correlations]] (unreported correlations are < 0.100)\n",
      "    C(slope, intercept) = -0.9097\n"
     ]
    }
   ],
   "source": [
    "#Define the variables and convert to Volts and Amps\n",
    "x = V_n / 0.001\n",
    "y = I_n / 0.000001\n",
    "\n",
    "#Use builtin NameModel, specify prefix for each:\n",
    "mod = LinearModel(prefix='') \n",
    "\n",
    "#Set the initial parameters to 'guess' mode\n",
    "pars  = mod.guess(y, x = x)\n",
    "\n",
    "#Fit with weights=1/yerr\n",
    "result = mod.fit(y, pars, x = x, weights= 1. / (y * 0.0318))\n",
    "\n",
    "#Print the fit results\n",
    "print(result.fit_report())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e2b31af-3b9f-41ff-bab6-429b46e63cd5",
   "metadata": {},
   "source": [
    "## Plot the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b562e985-269d-4d96-9741-543a4bb1a329",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Set the figure size\n",
    "plt.figure(figsize = (9,6))\n",
    "\n",
    "#Plot the data and the model\n",
    "plt.scatter(x, y, linewidth=2)\n",
    "plt.plot(x, result.best_fit, 'r-', linewidth=2.5)\n",
    "\n",
    "# Set plot labels and title\n",
    "plt.xlabel('V ($V$)')\n",
    "plt.ylabel('I ($A$)')\n",
    "plt.title('Normal State IVC')\n",
    "\n",
    "#Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4bf727c-9b28-4da8-b6c6-4fb66078c772",
   "metadata": {},
   "source": [
    "# Calculating the theoretical Ic and V_gap\n",
    "\n",
    "![](./img/Ic_formula.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9c3f054f-0b07-4f8f-b3de-a8fdd96668ba",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'slope': 8395.883205536935, 'intercept': -4379065.700491861}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Access the model parameters\n",
    "varys = result.params.valuesdict()\n",
    "\n",
    "varys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b00cd57a-cc33-4faf-a5ee-3ae6e148bd15",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Normal state resistance: R_n =  0.000119 Ohm\n"
     ]
    }
   ],
   "source": [
    "#The slope is equal to 1 / R \n",
    "R_n = 1 / varys.get(\"slope\")\n",
    "\n",
    "print('Normal state resistance: R_n = ', round(R_n, 6), 'Ohm') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9447a90f-624a-41a4-9975-06e5b6d0a2b4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Temperature = 7.38123653 K\n",
      "-----------------------------\n",
      "-----------------------------\n",
      "Weak Coupling Formula\n",
      "-----------------------------\n",
      "delta_t = 1.7619565250962866e-22 J\n",
      "Gap Energy = 3.523913050192573e-22 J\n",
      "Gap Voltage = 2.199421451874031 mV\n",
      "Josephson Current = 10.131088057326222 uA\n",
      "______________________________\n",
      "______________________________\n",
      "------------------------------\n",
      "Strong Coupling Approximation\n",
      "------------------------------\n",
      "delta_t = 1.6557101604313494e-22 J\n",
      "Gap Energy =  3.311420320862699e-22 J\n",
      "Gap Voltage = 2.066795856236861 mV\n",
      "Josephson Current = 9.143029962049823 uA\n",
      "________________________________\n",
      "________________________________\n",
      "________________________________\n"
     ]
    }
   ],
   "source": [
    "#Define the terms for the strong and weak coupling formulas \n",
    "t_c = 9.25 #critical temperature\n",
    "delta_0 = 2.25288819E-22 # from 1.764 * k_B * t_c,  [check eqn. 1 on the report paper] \n",
    "t = 7.38123653 #from the calibration curve in notebook 2\n",
    "e = 1.6022E-19 #elementay charge\n",
    "pi = 3.14159265358979323846264338327950 \n",
    "t_red = t / t_c #the reduced temperature\n",
    "k_B = 1.3807E-23 #Boltzmann constant\n",
    "R_n = 1 / varys.get(\"slope\") #from the slope of the IVC\n",
    "\n",
    "\n",
    "#weak coupling formula\n",
    "\n",
    "delta_weak = delta_0 * 1.74 * math.sqrt(1.0 - t_red)\n",
    "\n",
    "E_weak = delta_weak * 2\n",
    "\n",
    "V_weak = (E_weak / e) * 1000\n",
    "\n",
    "#The Ambegaokar-Baratoff formula\n",
    "Ic_weak = (pi / 2) * (delta_weak / (e * R_n)) * math.tanh(delta_weak / (2 * k_B * t))\n",
    "\n",
    "\n",
    "#strong coupling approximation\n",
    "\n",
    "delta_strong = (delta_0) * math.sqrt(math.cos((pi * t_red**2)  / 2 )) \n",
    "\n",
    "E_strong = delta_strong * 2\n",
    "\n",
    "V_strong = (E_strong / e) * 1000\n",
    "\n",
    "#The Ambegaokar-Baratoff formula\n",
    "Ic_strong = (pi / 2) * (delta_strong / (e * R_n)) * math.tanh(delta_strong / (2 * k_B * t))\n",
    "\n",
    "\n",
    "#Print the results\n",
    "print('Temperature =', t, 'K')\n",
    "print('-----------------------------')\n",
    "print('-----------------------------')\n",
    "                         \n",
    "print('Weak Coupling Formula')\n",
    "print('-----------------------------')\n",
    "\n",
    "\n",
    "print('delta_t =', delta_weak, 'J')\n",
    "print('Gap Energy =', E_weak, 'J')\n",
    "print('Gap Voltage =', V_weak, 'mV')\n",
    "print('Josephson Current =', Ic_weak, 'uA')\n",
    "print('______________________________')\n",
    "print('______________________________')\n",
    "print('------------------------------')\n",
    "print('Strong Coupling Approximation')\n",
    "print('------------------------------')\n",
    "\n",
    "print('delta_t =', delta_strong, 'J')\n",
    "print('Gap Energy = ', E_strong, 'J')\n",
    "print('Gap Voltage =', V_strong, 'mV')\n",
    "print('Josephson Current =', Ic_strong, 'uA')\n",
    "print('________________________________')\n",
    "print('________________________________')\n",
    "print('________________________________')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ef1804d8-51d9-4eea-ac5c-b806b800994a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Ic': 10.6706, 'Ic_weak': 10.131088057326222, 'Ic_strong': 9.143029962049823, 'V_gap': 1.822, 'Vg_weak': 2.199421451874031, 'Vg_strong': 2.066795856236861, 'Temp': 7.38123653}\n"
     ]
    }
   ],
   "source": [
    "#Add all the collected results to a dictionary\n",
    "Josephson_data = {\"Ic\" : np.interp(inflection_points[4], V, I) , \"Ic_weak\" : Ic_weak, \"Ic_strong\" : Ic_strong, \"V_gap\" : inflection_points[1], \"Vg_weak\" : V_weak, \"Vg_strong\" : V_strong, \"Temp\" : t}\n",
    "\n",
    "#Preview the newly created row of data\n",
    "print(Josephson_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c29b131a-d29f-4f75-ba01-4e28fbbc0548",
   "metadata": {},
   "source": [
    "## Export the results to a csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "565be433-d8b5-44ea-a793-bbf072ae75c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import csv\n",
    "\n",
    "# with open(r'./Data/Josephson_data.csv', 'a', newline='') as csvfile:\n",
    "#     fieldnames = ['Ic','Ic_weak', 'Ic_strong', 'V_gap', 'Vg_weak', 'Vg_strong', 'Temp']\n",
    "#     writer = csv.DictWriter(csvfile, fieldnames=fieldnames)\n",
    "\n",
    "#     writer.writerow(Josephson_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55f9e1ba-ea28-4854-8b64-a7ac34c3ddf8",
   "metadata": {},
   "source": [
    "## Author\n",
    "** **\n",
    "\n",
    "### <a href=\"https://www.linkedin.com/in/alin-airinei/\">Alin Airinei</a>"
   ]
  }
 ],
 "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": "3.11.4"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}