{ "cells": [ { "cell_type": "markdown", "id": "a3db97c3", "metadata": { "id": "a3db97c3" }, "source": [ "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MeiraDavidson/math_module2/blob/main/notebooks/ch5_exponentials.ipynb)\n\n", "# Chapter 5 — Companion Notebook\n", "## The Function That Is Its Own Slope\n", "*Why one strange number between 2 and 3 refuses to change*\n", "\n", "Three live experiments on the number $e$. You will drag a base $a$ and watch the curve $y=a^x$ tilt away from the $y$-axis until its crossing slope $M(a)=\\ln a$ hits exactly $1$ — that base *is* $e$. Then you will see what \"its own derivative\" looks like, where the steepness of $y=e^x$ equals its height at every point. Finally you will run a decay simulator and watch a quantity halve, then halve again, at evenly spaced half-lives.\n", "\n", "> **How to use this notebook.** Run every cell from the top (Shift+Enter). Each widget below is live — drag the sliders and watch the picture respond. Requires `ipywidgets` and `matplotlib`." ] }, { "cell_type": "code", "execution_count": 1, "id": "7b0de8bc", "metadata": { "id": "7b0de8bc", "executionInfo": { "status": "ok", "timestamp": 1782335641240, "user_tz": 240, "elapsed": 38, "user": { "displayName": "Meira Davidson", "userId": "09448014842742744623" } } }, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from matplotlib import animation\n", "from ipywidgets import (interact, interactive, fixed, Dropdown, Checkbox,\n", " Button, Output, VBox, HBox,\n", " FloatSlider, IntSlider, FloatLogSlider)\n", "from IPython.display import HTML, display, Markdown\n", "\n", "# Book 2 palette — matches the printed figures in figures/png/\n", "BLUE=\"#1f4e79\"; RED=\"#c0392b\"; GREEN=\"#2e8b57\"; ORANGE=\"#e08e0b\"\n", "PURPLE=\"#6c3483\"; TEAL=\"#1b9e9e\"; GRAY=\"#7f8c8d\"; DARK=\"#2c3e50\"\n", "SHADE=\"#9fc5e8\"; SHADE2=\"#f4b6ad\"; SHADEG=\"#a9dfbf\"; LIGHT=\"#d6dbdf\"\n", "\n", "plt.rcParams.update({\n", " \"figure.figsize\": (7.2, 4.5), \"figure.dpi\": 96,\n", " \"font.family\": \"serif\", \"mathtext.fontset\": \"cm\", \"font.size\": 12,\n", " \"axes.spines.top\": False, \"axes.spines.right\": False,\n", " \"axes.grid\": True, \"grid.color\": LIGHT, \"grid.linewidth\": 0.7,\n", " \"lines.linewidth\": 2.2, \"lines.solid_capstyle\": \"round\",\n", "})\n", "\n", "def axes(ax=None, title=None):\n", " '''A clean axes with a light grid; returns the axes.'''\n", " if ax is None:\n", " _, ax = plt.subplots()\n", " if title:\n", " ax.set_title(title, color=DARK)\n", " return ax\n" ] }, { "cell_type": "markdown", "id": "bebf7ee2", "metadata": { "id": "bebf7ee2" }, "source": [ "## 1. Hunting for the base that leaves the axis at slope 1\n", "\n", "Take any exponential $y=a^x$ and differentiate it from scratch. The $a^x$ factors straight out of the difference quotient and *never changes as $h$ shrinks*, leaving one lonely number behind:\n", "\n", "$$\\frac{d}{dx}\\,a^{x} = M(a)\\,a^{x},\\qquad M(a)=\\lim_{h\\to 0}\\frac{a^{h}-1}{h}.$$\n", "\n", "Every exponential is *already* proportional to its own slope — off only by that constant $M(a)$. And $M(a)$ has a picture: plug in $x=0$ and, since $a^0=1$, the slope of $y=a^x$ right where it **crosses the $y$-axis** is exactly $M(a)$.\n", "\n", "So our whole quest reduces to one question: *for which base does the curve leave the axis at slope exactly $1$?* Drag $a$ below. The blue curve is $y=a^x$; the red line is its tangent at the crossing point $(0,1)$, and its slope is the live number $M(a)=\\ln a$. Push $a$ until that slope reads $1$ — you will be sitting on $a=e\\approx 2.718$, the base whose curve refuses to leave the axis at any slope but one." ] }, { "cell_type": "code", "execution_count": 2, "id": "020d6561", "metadata": { "id": "020d6561", "executionInfo": { "status": "ok", "timestamp": 1782335641993, "user_tz": 240, "elapsed": 751, "user": { "displayName": "Meira Davidson", "userId": "09448014842742744623" } }, "outputId": "28639167-3f8c-485f-ef29-a1bd06992da9", "colab": { "base_uri": "https://localhost:8080/", "height": 505, "referenced_widgets": [ "dc0da2d6a8b846a8901188ba636ee995", "5aceec7e6efa40f28aa7c9b484030e42", "dab74755b3a046228f2f829ce58f3188", "2b5b823a7c9d449fb3556dc535e5ec11", "33306188285b42c1a6b934e4446f89b9", "f9e307d941594a58a4e452b8426a25a3", "a10e00698c9f42d49cafd34c5e9118af", "1559740cb096499a8dc8facad38ce7af", "e589d6d29a0549058bc6e8b6498f275b", "1ac4b5581e5443b8aff57601680410c5" ] } }, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "interactive(children=(FloatSlider(value=2.0, continuous_update=False, description='base $a$', max=4.0, min=1.2…" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "dc0da2d6a8b846a8901188ba636ee995" } }, "metadata": {} } ], "source": [ "E = np.e # 2.71828..., the base we are hunting for\n", "\n", "def _base_slope(a=2.0, show_family=True):\n", " # M(a) = ln a is the slope of a^x at x=0 (the y-axis crossing).\n", " M = np.log(a)\n", " x = np.linspace(-2.2, 2.2, 400)\n", "\n", " fig, ax = plt.subplots()\n", " axes(ax)\n", "\n", " # Faint family of other bases, for context.\n", " if show_family:\n", " for b in (1.5, 2.0, E, 3.0, 4.0):\n", " ax.plot(x, b ** x, color=GRAY, lw=1.1, alpha=0.30, zorder=1)\n", "\n", " # The chosen curve y = a^x.\n", " ax.plot(x, a ** x, color=BLUE, lw=2.6, zorder=3,\n", " label=f'$y = a^x$, $a={a:.3f}$')\n", "\n", " # Tangent at the y-axis crossing (0, 1): slope = M(a) = ln a.\n", " xt = np.linspace(-1.4, 1.4, 2)\n", " ax.plot(xt, 1.0 + M * xt, color=RED, lw=2.2, ls='--', zorder=4,\n", " label=f'tangent at $(0,1)$, slope $= \\\\ln a = {M:.3f}$')\n", " ax.scatter([0], [1], s=46, color=RED, zorder=5)\n", "\n", " # Live verdict on whether we have found e.\n", " if abs(M - 1.0) < 0.01:\n", " verdict = (f'$M(a) = {M:.3f} \\\\approx 1$ \\u2014 '\n", " f'this is $e \\\\approx {E:.3f}$!')\n", " vcolor = GREEN\n", " elif M < 1.0:\n", " verdict = f'$M(a) = {M:.3f} < 1$ \\u2014 too gentle, push $a$ up'\n", " vcolor = DARK\n", " else:\n", " verdict = f'$M(a) = {M:.3f} > 1$ \\u2014 too steep, ease $a$ down'\n", " vcolor = DARK\n", " ax.set_title(verdict, color=vcolor, fontsize=13)\n", "\n", " ax.axhline(0, color=DARK, lw=0.8)\n", " ax.axvline(0, color=DARK, lw=0.8)\n", " ax.set_xlim(-2.2, 2.2)\n", " ax.set_ylim(-0.5, 8)\n", " ax.set_xlabel('$x$'); ax.set_ylabel('$y$')\n", " ax.legend(loc='upper left', framealpha=0.92)\n", " plt.show()\n", "\n", "interact(_base_slope,\n", " a=FloatSlider(value=2.0, min=1.2, max=4.0, step=0.01,\n", " description='base $a$', readout_format='.2f',\n", " continuous_update=False),\n", " show_family=Checkbox(value=True, description='show other bases'));" ] }, { "cell_type": "markdown", "id": "0c8f3992", "metadata": { "id": "0c8f3992" }, "source": [ "## 2. \"Its own derivative\" — slope equals height\n", "\n", "Setting $M(e)=1$ collapses the boxed rule to the headline of the whole chapter:\n", "\n", "$$\\frac{d}{dx}\\,e^{x} = e^{x}.$$\n", "\n", "That equation is a *geometric promise*: at any point $x_0$ the tangent to $y=e^x$ has slope $e^{x_0}$, which is the very height of the curve there. Where the curve sits at height $5$, it climbs at slope $5$. Slide $x_0$ along the curve and watch the green height and the red slope stay locked to the same number — the shaded triangle has rise equal to its run scaled by exactly that value." ] }, { "cell_type": "code", "execution_count": 3, "id": "25280ef1", "metadata": { "id": "25280ef1", "executionInfo": { "status": "ok", "timestamp": 1782335662956, "user_tz": 240, "elapsed": 324, "user": { "displayName": "Meira Davidson", "userId": "09448014842742744623" } }, "outputId": "41d1d7a4-997a-4640-f86b-d5f4229240d9", "colab": { "base_uri": "https://localhost:8080/", "height": 473, "referenced_widgets": [ "f3d1561b06164603979cc49042c3427a", "8c46774a408a48489b8f06b0aeec95ac", "fa6fb1baf25c4032a6af0a748bcc11fd", "03defe13a66f45b8aaab1456f6a69c88", "8a83a82abaf842c280ce7910f04110c3", "ff4a7e20383a4a829a22ed1328d3d195", "815b648b04b14cca8246261f9fbcf892" ] } }, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "interactive(children=(FloatSlider(value=0.6, continuous_update=False, description='point $x_0$', max=1.9, min=…" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "f3d1561b06164603979cc49042c3427a" } }, "metadata": {} } ], "source": [ "def _slope_equals_height(x0=0.6):\n", " x = np.linspace(-2.5, 2.0, 400)\n", " y = np.exp(x)\n", " h = np.exp(x0) # height = slope, the whole point\n", "\n", " fig, ax = plt.subplots()\n", " axes(ax, '$y=e^x$: slope at $x_0$ equals the height $e^{x_0}$')\n", " ax.plot(x, y, color=BLUE, lw=2.6, zorder=3, label='$y = e^x$')\n", "\n", " # Tangent line through (x0, h) with slope h.\n", " xt = np.linspace(x0 - 1.3, x0 + 1.3, 2)\n", " ax.plot(xt, h + h * (xt - x0), color=RED, lw=2.2, ls='--',\n", " zorder=4, label=f'tangent, slope $= {h:.3f}$')\n", "\n", " # Drop line showing the height, and a rise/run slope triangle.\n", " ax.vlines(x0, 0, h, color=GREEN, lw=2.0, zorder=2)\n", " ax.plot([x0, x0 + 1], [h, h], color=GRAY, lw=1.4, zorder=2)\n", " ax.plot([x0 + 1, x0 + 1], [h, h + h], color=GRAY, lw=1.4, zorder=2)\n", " ax.fill([x0, x0 + 1, x0 + 1], [h, h, h + h],\n", " color=SHADE2, alpha=0.55, zorder=1)\n", " ax.annotate(f'run $=1$', xy=(x0 + 0.5, h), xytext=(x0 + 0.5, h - 0.9),\n", " ha='center', color=GRAY, fontsize=11)\n", " ax.annotate(f'rise $= {h:.2f}$', xy=(x0 + 1, h + h / 2),\n", " xytext=(x0 + 1.1, h + h / 2), va='center',\n", " color=DARK, fontsize=11)\n", "\n", " ax.scatter([x0], [h], s=46, color=RED, zorder=5)\n", " ax.annotate(f'height $= e^{{{x0:.2f}}} = {h:.3f}$',\n", " xy=(x0, h), xytext=(x0 - 2.3, h + 0.6),\n", " color=GREEN, fontsize=12,\n", " arrowprops=dict(arrowstyle='->', color=GREEN, lw=1.4))\n", "\n", " ax.axhline(0, color=DARK, lw=0.8)\n", " ax.axvline(0, color=DARK, lw=0.8)\n", " ax.set_xlim(-2.5, 2.0)\n", " ax.set_ylim(-0.6, 8)\n", " ax.set_xlabel('$x$'); ax.set_ylabel('$y$')\n", " ax.legend(loc='upper left', framealpha=0.92)\n", " plt.show()\n", "\n", "interact(_slope_equals_height,\n", " x0=FloatSlider(value=0.6, min=-2.0, max=1.9, step=0.01,\n", " description='point $x_0$', readout_format='.2f',\n", " continuous_update=False));" ] }, { "cell_type": "markdown", "id": "89ee9715", "metadata": { "id": "89ee9715" }, "source": [ "## 3. Decay and half-life\n", "\n", "Flip the sign of the rate constant and the same function *decays*. Written in terms of its **half-life** $T$ — the time for the amount to fall to half of whatever it was — the model is\n", "\n", "$$N(t) = N_{0}\\left(\\tfrac12\\right)^{t/T} = N_0\\,e^{-\\lambda t},\\qquad \\lambda = \\frac{\\ln 2}{T}.$$\n", "\n", "The defining feature of exponential decay is that this halving is *memoryless*: it takes one half-life $T$ to go from $N_0$ to $N_0/2$, another $T$ to reach $N_0/4$, another to reach $N_0/8$ — no matter where you start counting. Drag the half-life $T$ (and the starting amount $N_0$). The dashed guides mark $t=T,2T,3T,4T$; at each one the quantity is exactly halved from the step before, and the labels read off the value." ] }, { "cell_type": "code", "execution_count": null, "id": "489f113c", "metadata": { "id": "489f113c" }, "outputs": [], "source": [ "def _decay(T=2.0, N0=400.0, n_halves=4):\n", " t = np.linspace(0, n_halves * T * 1.05, 400)\n", " N = N0 * 0.5 ** (t / T)\n", "\n", " fig, ax = plt.subplots()\n", " lam = np.log(2) / T\n", " axes(ax, f'$N(t)=N_0(1/2)^{{t/T}}$, half-life $T={T:.2f}$, '\n", " f'$\\\\lambda=\\\\ln 2/T={lam:.3f}$')\n", " ax.fill_between(t, 0, N, color=SHADE, alpha=0.35, zorder=0)\n", " ax.plot(t, N, color=BLUE, lw=2.6, zorder=3, label='$N(t)$')\n", "\n", " # Mark successive half-lives t = T, 2T, 3T, ... with guides.\n", " for k in range(0, n_halves + 1):\n", " tk = k * T\n", " Nk = N0 * 0.5 ** k # = N0 / 2^k\n", " # vertical guide up to the curve, horizontal guide to the axis\n", " ax.vlines(tk, 0, Nk, color=RED, lw=1.3, ls='--', zorder=2)\n", " ax.hlines(Nk, 0, tk, color=GREEN, lw=1.3, ls=':', zorder=2)\n", " ax.scatter([tk], [Nk], s=40, color=RED, zorder=4)\n", " label = f'{Nk:.4g}' if k else f'$N_0={Nk:.4g}$'\n", " ax.annotate(label, xy=(tk, Nk), xytext=(tk + 0.12 * T, Nk + 0.04 * N0),\n", " color=DARK, fontsize=11)\n", " if k:\n", " ax.annotate(f'${k}T$', xy=(tk, 0), xytext=(tk, -0.07 * N0),\n", " ha='center', color=RED, fontsize=11)\n", "\n", " ax.set_xlim(0, n_halves * T * 1.05)\n", " ax.set_ylim(-0.1 * N0, 1.12 * N0)\n", " ax.set_xlabel('time $t$'); ax.set_ylabel('amount $N$')\n", " ax.legend(loc='upper right', framealpha=0.92)\n", " plt.show()\n", "\n", "interact(_decay,\n", " T=FloatSlider(value=2.0, min=0.5, max=5.0, step=0.1,\n", " description='half-life $T$', readout_format='.1f',\n", " continuous_update=False),\n", " N0=FloatSlider(value=400.0, min=50.0, max=1000.0, step=50.0,\n", " description='start $N_0$', readout_format='.0f',\n", " continuous_update=False),\n", " n_halves=IntSlider(value=4, min=2, max=6, step=1,\n", " description='# half-lives'));" ] }, { "cell_type": "markdown", "id": "139fbee9", "metadata": { "id": "139fbee9" }, "source": [ "---\n", "\n", "*Three pictures, one idea.* The first widget shows that picking the base is the same as picking a crossing slope $M(a)=\\ln a$, and $e$ is the unique base that picks slope $1$. The second shows the payoff — at $a=e$ the curve's height *is* its slope everywhere. The third turns the same exponential, run with a negative rate, into the half-life arithmetic you can now derive rather than memorize: $t_{1/2} = \\ln 2/\\lambda$." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "name": "python", "pygments_lexer": "ipython3" }, "colab": { "provenance": [] }, "widgets": { "application/vnd.jupyter.widget-state+json": { "dc0da2d6a8b846a8901188ba636ee995": { "model_module": "@jupyter-widgets/controls", "model_name": "VBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [ "widget-interact" ], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "VBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "VBoxView", "box_style": "", "children": [ "IPY_MODEL_5aceec7e6efa40f28aa7c9b484030e42", "IPY_MODEL_dab74755b3a046228f2f829ce58f3188", "IPY_MODEL_2b5b823a7c9d449fb3556dc535e5ec11" ], "layout": "IPY_MODEL_33306188285b42c1a6b934e4446f89b9" } }, "5aceec7e6efa40f28aa7c9b484030e42": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatSliderModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatSliderModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "FloatSliderView", "continuous_update": false, "description": "base $a$", "description_tooltip": null, "disabled": false, "layout": "IPY_MODEL_f9e307d941594a58a4e452b8426a25a3", "max": 4, "min": 1.2, "orientation": "horizontal", "readout": true, "readout_format": ".2f", "step": 0.01, "style": "IPY_MODEL_a10e00698c9f42d49cafd34c5e9118af", "value": 2.18 } }, "dab74755b3a046228f2f829ce58f3188": { "model_module": "@jupyter-widgets/controls", "model_name": "CheckboxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "CheckboxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "CheckboxView", "description": "show other bases", "description_tooltip": null, "disabled": false, "indent": true, "layout": "IPY_MODEL_1559740cb096499a8dc8facad38ce7af", "style": "IPY_MODEL_e589d6d29a0549058bc6e8b6498f275b", "value": true } }, "2b5b823a7c9d449fb3556dc535e5ec11": { "model_module": "@jupyter-widgets/output", "model_name": "OutputModel", "model_module_version": "1.0.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/output", "_model_module_version": "1.0.0", "_model_name": "OutputModel", "_view_count": null, "_view_module": "@jupyter-widgets/output", "_view_module_version": "1.0.0", "_view_name": "OutputView", "layout": "IPY_MODEL_1ac4b5581e5443b8aff57601680410c5", "msg_id": "", "outputs": [ { "output_type": "display_data", "data": { "text/plain": "
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