Lugovtsov/4.2.1-hewton-rings/measurements.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e16deb44-1094-4981-b3b2-9170816472e9",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# %load ../processing_tools.py\n",
    "import numpy as np\n",
    "from scipy.optimize import curve_fit\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "import scienceplots\n",
    "\n",
    "plt.style.use(['science', 'russian-font'])\n",
    "\n",
    "matplotlib.rcParams.update({\n",
    "    'figure.figsize': [6, 4],\n",
    "    'savefig.facecolor': 'white',\n",
    "    'figure.dpi': 150.0,\n",
    "    'font.size': 12.0,\n",
    "})\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18f7eaab-03eb-44de-ac72-ad4c1908b33a",
   "metadata": {},
   "source": [
    "### Калибровка шкалы"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "b7d28cdc-bfae-4af9-8fb3-11509f9ffab5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.4353070925719702"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l = 700 # +-10\n",
    "dels = 96 + 700 - 76 # +-1\n",
    "k_mean = l / dels\n",
    "k_err = np.sqrt(10**2 * (1/dels)**2 + (-l/(dels**2))**2)\n",
    "k = (k_mean, k_err) # цена деления в микронах\n",
    "\n",
    "k_err / k_mean * 100 # %ошибки"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52600d36-efe5-460f-acb2-6538c76b0361",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Расстояния от центра до колец"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "06aec23a-bfc1-4a32-a4bf-2abb6158f070",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "center_pos = 482 # +- 1\n",
    "dark_dot = (482 - 435) * k[0]\n",
    "\n",
    "dist = np.genfromtxt('iii-data.csv', skip_header=True) - center_pos\n",
    "dist_si = (-dist)[::-1] * k[0]\n",
    "dark_distances = dist_si[1::2]\n",
    "light_distances = dist_si[::2]\n",
    "m = np.arange(0, len(dist) / 2)\n",
    "\n",
    "# dist_si**2 = (dist * k)**2\n",
    "err = lambda dist : np.sqrt((k[0]**2 * 2*dist*1)**2 + (dist**2 * 2*k[0]*k[1])**2)\n",
    "plt.errorbar(m+1, dark_distances**2, yerr=err(dark_distances), label='Тёмные кольца')\n",
    "plt.errorbar(m, light_distances**2, yerr=err(light_distances), label='Светлые кольца')\n",
    "plt.scatter(0, dark_dot**2, marker='o', label='Граница тёмного пятна')\n",
    "\n",
    "plt.ylabel('Квадрат расстояния до центра, $\\\\text{мкм}^2$')\n",
    "plt.xlabel('Порядковый номер m')\n",
    "plt.legend()\n",
    "\n",
    "plt.savefig(r'images/dark-light.svg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2adad890-f5df-4a1f-ac51-10126ec6f233",
   "metadata": {},
   "source": [
    "**Тёмный проходит через (0,0)**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "718516ca-f89a-490e-aa08-92635336ae3e",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Рассчёт кривизны"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0ca07e96-9b37-4615-b120-f95e610f525a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def line1(x, k):\n",
    "    return k*x\n",
    "\n",
    "([lR1], [[lR1_err]]) = curve_fit(line1, m+1, dark_distances**2)\n",
    "\n",
    "plt.fill_between(m+1, line1(m+1, lR1+lR1_err), line1(m+1, lR1-lR1_err), alpha=.15, edgecolor='none', label='Случайная ошибка')\n",
    "plt.plot(m+1, line1(m+1, lR1), alpha=.65, label=r'Аппроксимация $r=\\sqrt{m\\lambda R}$', color='C0')\n",
    "plt.errorbar(m+1, dark_distances**2, yerr=err(dark_distances), label='Эксперимент', marker='.', linestyle='none', color='C0')\n",
    "\n",
    "plt.ylabel('Квадрат расстояния до центра, $\\\\text{мкм}^2$')\n",
    "plt.xlabel('Порядковый номер m')\n",
    "plt.legend()\n",
    "\n",
    "plt.savefig(r'images/dark-approx.svg')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b5626fb-4cc1-4f4b-add9-ac390d645812",
   "metadata": {},
   "source": [
    "$R = k / \\lambda\\\\\n",
    "\\delta R = \\sqrt{\\left(\\dfrac{1}{\\lambda}\\right)^2 \\delta k^2 + \\left(\\dfrac{k}{\\lambda^2}\\right)^2 \\delta \\lambda^2}$ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82838ffe-5fdb-4b52-a79a-b38eaa2c5973",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R = 12.7 +- 0.9 мм\n"
     ]
    }
   ],
   "source": [
    "R = lR1 / lamb\n",
    "R_err = np.sqrt((1/lamb)**2 * lR1_err**2 + (lR1/(lamb**2))**2 * lamb_err**2)\n",
    "print(f'R = {R*1e-3:.3} +- {R_err*1e-3:.1} мм')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19a36a5f-d7ad-4720-9d5c-cbaecaf59636",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Разность длин волн, полученная при наблюдении биений"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "1e23db39-56a0-4a1d-b2bf-8d77f6d7e8d8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "38.714285714285715"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delta = 1/14 * lamb * 1e3 # нм\n",
    "delta"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b220cdb-e764-443e-9f18-834132439e24",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Лабораторный журнал"
   ]
  },
  {
   "cell_type": "raw",
   "id": "87504042-278d-43b9-82d3-e10518bd63f1",
   "metadata": {
    "tags": []
   },
   "source": [
    "81 (темн)\n",
    "84 (светл)\n",
    "89\n",
    "94\n",
    "98\n",
    "\n",
    "104\n",
    "108\n",
    "113\n",
    "119\n",
    "124\n",
    "128\n",
    "132\n",
    "137\n",
    "144\n",
    "154\n",
    "160\n",
    "165\n",
    "171\n",
    "177\n",
    "183\n",
    "189\n",
    "195\n",
    "\n",
    "202\n",
    "209\n",
    "214\n",
    "222\n",
    "229\n",
    "236\n",
    "243\n",
    "252\n",
    "259\n",
    "268\n",
    "276\n",
    "285\n",
    "295\n",
    "\n",
    "303\n",
    "313\n",
    "324\n",
    "336\n",
    "351\n",
    "364\n",
    "378\n",
    "399 (темн)\n",
    "\n",
    "424 (светл) -- последнее кольцо\n",
    "далее тёмное пятно радиусом 435\n",
    "центр -- 482"
   ]
  },
  {
   "cell_type": "raw",
   "id": "a9da40b4-e2b7-4943-9f76-098686d1824c",
   "metadata": {},
   "source": [
    "14 полос между системами"
   ]
  }
 ],
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