{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from datetime import datetime\n", "import numpy as np\n", "import scipy.integrate as spi\n", "import matplotlib.pyplot as plt\n", "%matplotlib widget\n", "\n", "import ppigrf\n", "\n", "DEBUG = None # to be set later" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "## Some constants\n", "\n", "M = 5 # nuclear mass unit u\n", "# 1 u = 1.66e-27 kg\n", "\n", "CHARGE = 2 # charge of the nucleus in units of the elementary charge\n", "# 1 e = 1.6e-19 C\n", "\n", "SPEED_OF_LIGHT = 3e8 # m/s\n", "\n", "DATE = datetime(2021, 3, 28)\n", "\n", "## Conversion factor when computing the Lorentz force\n", "# F = gamma * q * v x B\n", "CONVERSION_FACTOR = 1.66e27 * 1.6e-19 * 1e-9\n", "# where we also converted from nT to T\n", "R_EARTH = 6.4e6 # m\n", "\n", "ABSOLUTE_TOLERANCE = 1e3" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Modelling the magnetic field\n", "- as a sanity check we can use a simple homogeneous magnetic field in the z direction\n", "$$\n", "\\mathbf{B} = B_0 \\mathbf{e}_z\n", "$$\n", "- In the simplest approximation, the magnetic field can be modelled as a dipole field. In cartesian coordinates, it is given by:\n", "$$\n", "\\mathbf{B}(\\mathbf{r}) = -B_0 \\cdot \\frac{R_{earth}^3}{r^5} * \\left( 3xz \\cdot \\mathbf{e_x} + 3yz\\cdot \\mathbf{e_y} + (2z^2 - x^2 - y^2)\\cdot \\mathbf{e_z}\\right)\n", "$$ \n", "TODO: check\n", "TODO: check reference\n", "- A far better approximation is given by the IGRF model. The IGRF model is given by a sum of spherical harmonics. The coefficients are fitted to measurements and account for time variations." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "## helpers for IGRF, since it is given in spherical coordinates\n", "def cartesian_to_spherical(v: np.ndarray) -> np.ndarray:\n", " return np.array([\n", " np.linalg.norm(v),\n", " np.degrees(np.arctan2(np.linalg.norm(v[:2]), v[2])),\n", " np.degrees(np.arctan2(v[1], v[0]))\n", " ])\n", "\n", "\n", "#I'm lazy, so I redefine\n", "cosd = lambda x: np.cos(np.deg2rad(x))\n", "sind = lambda x: np.sin(np.deg2rad(x))\n", "def B_to_cartesian(r_vec: np.ndarray, B: np.ndarray) -> np.ndarray:\n", " # express the spherical components of B in cartesian coordinates through the jacobian\n", " # (Bx, By, Bz) = J * (Br, Btheta, Bphi)\n", " r = r_vec[0] # though not needed\n", " theta = r_vec[1]\n", " phi = r_vec[2]\n", " J = np.array([\n", " [cosd(theta) * cosd(phi), - sind(theta) * cosd(phi), -cosd(theta) * sind(phi)],\n", " [cosd(theta) * sind(phi), sind(theta) * sind(phi), cosd(theta) * cosd(phi)],\n", " [sind(theta), cosd(theta), sind(theta)]\n", " ])\n", " B_cart = J @ B\n", " if DEBUG:\n", " print(f\"spherical B = {np.linalg.norm(B)}, cartesian B = {np.linalg.norm(B_cart)}\")\n", " return B_cart\n", "\n", "\n", "B_INTENSITY = 1e4 # nT # to be on par with the IGRF values\n", "## Different implementations of the magnetic field\n", "def simple_field(x):\n", " B = np.array([0, 0, 1]) * B_INTENSITY\n", " return B\n", "\n", "\n", "def dipole_field(x):\n", " intensity = B_INTENSITY * 1e-2\n", " r = np.linalg.norm(x)\n", " B = intensity * R_EARTH**3 / r**5 * np.array([\n", " 3 * x[2] * x[0],\n", " 3 * x[2] * x[1],\n", " 2 * x[2]**2 - x[0]**2 - x[1]**2\n", " ])\n", " return B\n", "\n", "\n", "def IGRF_field(x):\n", " r_vec = cartesian_to_spherical(x)\n", " r = r_vec[0] * 1e-3 # convert to km\n", " B = ppigrf.igrf_gc(r, r_vec[1], r_vec[2], DATE) # returns radial, south, east\n", " B = np.array(B).flatten()\n", " B_cart = B_to_cartesian(r_vec, B)\n", " if DEBUG:\n", " print(f\"B = {B}, B_cart = {B_cart}\")\n", " return B_cart\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Magnetic field and equation of motion\n", "We consider **only** the effect of the magnetic field, as given by the Lorentz force:\n", "\n", "$$\n", "F_L = q \\cdot \\vec{v} \\times \\vec{B}(r, \\theta, \\phi)\n", "$$\n", "TODO: comment on synchrotron radiation\n", "where:\n", "- v is the velocity of the particle\n", "- B is the magnetic field\n", "\n", "The equation of motion is still given by:\n", "$$\n", "m \\cdot \\frac{d^2 \\vec{r}}{dt^2} = F_L\n", "$$\n", "but in the relativistic case the mass is expressed as\n", "$$\n", "m = \\gamma m_0\n", "$$\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Integrating the equation of motion\n", "\n", "As a starting point we can integrate the EOM and track the particle **forward in time**. The procedure is as follows:\n", "- linearize the EOM\n", "- integrate the EOM\n", "- plot the trajectory\n", "\n", "=> Doing this for every incoming particle is not feasible!\n", "\n", "\n", "#### Backtracking\n", "We can also track the particle **backward in time**, from the detector (eg. AMS-01). The procedure is as follows:\n", "- modify the EOM to track the particle backward in time\n", " - treat the velocity as negative" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "\n", "## Functions to be integrated\n", "def gamma_inv(v: np.ndarray) -> float:\n", " v = np.linalg.norm(v)\n", " if v > SPEED_OF_LIGHT:\n", " print(f\"v = {v} > c, setting gamma = 0\")\n", " return 0\n", " return np.sqrt(1 - (v / SPEED_OF_LIGHT)**2)\n", "\n", "\n", "def force(x: np.ndarray, v: np.ndarray, b_field_func: callable) -> np.ndarray:\n", " B = b_field_func(x)\n", " # B is now in nT, but this is absorbed in the conversion factor\n", " F = CHARGE * np.cross(v, B) * CONVERSION_FACTOR\n", " if DEBUG:\n", " print(f\"B = {B}\")\n", " print(f\"x = {x}\")\n", " print(f\"v = {np.linalg.norm(v)}\")\n", " print(f\"F = {F}\")\n", " return F.flatten()\n", "\n", "\n", "# linearized equations of motion - forward\n", "def y_prime(t, y, b_field_func):\n", " # to be compatible with the scipy integrator, we need the following signature\n", " x = y[:3]\n", " v = y[3:]\n", " a = (gamma_inv(v) / M) * force(x, v, b_field_func)\n", " ydot = np.concatenate((v, a))\n", " if DEBUG:\n", " print(f\"1/gamma = {gamma_inv(v)}\")\n", " print(f\"a = {a}\")\n", " print(f\"ydot: {ydot}\")\n", " return np.concatenate((v, a))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "## Some more helpers\n", "def plot_trajectory(x: list[np.ndarray], labels: list[str], show_nth: int = 1, show_earth: bool = False, fix_limits: bool = True):\n", " fig = plt.figure()\n", " ax = fig.add_subplot(projection='3d')\n", " # show the trajectory (x)\n", " for trajectory, label in zip(x, labels):\n", " trajectory = trajectory / R_EARTH\n", " ax.plot3D(trajectory[0, ::show_nth], trajectory[1, ::show_nth], trajectory[2, ::show_nth], label=label)\n", " # show start and end points\n", " ax.scatter(trajectory[0, 0], trajectory[1, 0], trajectory[2, 0], color='green') #, label='start'\n", " ax.scatter(trajectory[0, -1], trajectory[1, -1], trajectory[2, -1], color='red') #, label='end'\n", " \n", " # show the earth\n", " if show_earth:\n", " u = np.linspace(0, 2 * np.pi, 100)\n", " v = np.linspace(0, np.pi, 100)\n", " x = np.outer(np.cos(u), np.sin(v))\n", " y = np.outer(np.sin(u), np.sin(v))\n", " z = np.outer(np.ones(np.size(u)), np.cos(v))\n", " ax.plot_surface(x, y, z, color='b', alpha=0.1)\n", "\n", " # set sensible view limits\n", " ax.set_box_aspect([1,1,1])\n", " if fix_limits:\n", " ax.set_xlim(-5, 5)\n", " ax.set_ylim(-5, 5)\n", " ax.set_zlim(-5, 5)\n", " # TODO: explain limit\n", " \n", " ax.set_xlabel('x [R_e]')\n", " ax.set_ylabel('y [R_e]')\n", " ax.set_zlabel('z [R_e]')\n", " # show small legend\n", " ax.legend(fontsize='small')\n", " # plt.show()\n", "\n", "\n", "def energy_to_speed(E: float) -> float:\n", " \"\"\"assumes energy given in eV and returns speed in m/s\"\"\"\n", " mass_kg = M * 1.66e-27\n", " energy_j = E * 1.6e-19\n", " return SPEED_OF_LIGHT * np.sqrt(1 - ((mass_kg * SPEED_OF_LIGHT**2) / (mass_kg * SPEED_OF_LIGHT**2 + energy_j))**2)\n", " \n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "## ODE solving parameters\n", "\n", "ABS_TOL = 1e2\n", "# setup of initial conditions\n", "# Cartesian coordinates, SI units: m and m/s\n", "X_0 = [6.5e6, 6.5e6, 0]\n", "V_0 = [-1e4, -1e4, 0]\n", "Y0 = np.concatenate((X_0, V_0))\n", "\n", "DEBUG = False\n", "# CONVERSION_FACTOR = 1e-1\n", "# TODO: remove this overwrite\n", "\n", "TIME_RANGE = [0, 100]\n", "# TODO: cite reference\n", "N_STEPS = 10000\n", "t = np.linspace(TIME_RANGE[0], TIME_RANGE[1], N_STEPS)\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Result has shape (6, 10000)\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "8b922d2cf91241bd88352745fc97b389", "version_major": 2, 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", 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