{ "cells": [ { "cell_type": "markdown", "id": "181e61e3", "metadata": {}, "source": [ "# Spin-Orbit-Torque Demo\n" ] }, { "cell_type": "markdown", "id": "9329eba4", "metadata": {}, "source": [ "## Google Colab Link\n", "\n", "The demo can be run on Google Colab without any local installation.\n", "Use the following [link](https://colab.research.google.com/drive/1OWMH0_qqxM73rB5gK5pi7nFRtO4nO_N8) to try it out." ] }, { "cell_type": "code", "execution_count": 11, "id": "fec73e7b", "metadata": {}, "outputs": [], "source": [ "!pip install -q magnumnp numpy==1.22.4" ] }, { "cell_type": "markdown", "id": "22eb09dd", "metadata": {}, "source": [ "## Run Demo:" ] }, { "cell_type": "code", "execution_count": 12, "id": "cb7f7d51", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;32m[State] running on device: cpu (dtype = float64)\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;32m[Mesh] 1x1x1 (size= 1e-09 x 1e-09 x 1e-09)\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;32m[LLGSolver] using RKF45 solver (atol = 1e-05)\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] relax: t=1e-11 dE=0 E=-2.4e-22\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;32m[LLGSolver] using RKF45 solver (atol = 1e-05)\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1e-12\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2e-12\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3e-12\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4e-12\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5e-12\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6e-12\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7e-12\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8e-12\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9e-12\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.1e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.2e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.3e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.4e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.5e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.6e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.7e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.8e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.9e-11\u001b[0m\n", "2023-05-08 13:12:37 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.1e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.2e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.3e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.4e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.5e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.6e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.7e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.8e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.9e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.1e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.2e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.3e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.4e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.5e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.6e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.7e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.8e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.9e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.1e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.2e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.3e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.4e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.5e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.6e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.7e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.8e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.9e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.1e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.2e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.3e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.4e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.5e-11\u001b[0m\n", "2023-05-08 13:12:38 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.6e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.7e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.8e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.9e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.1e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.2e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.3e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.4e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.5e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.6e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.7e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.8e-11\u001b[0m\n", "2023-05-08 13:12:39 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.9e-11\u001b[0m\n", "2023-05-08 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step: dt= 1e-12 t=1e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.01e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.02e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.03e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.04e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.05e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.06e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.07e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.08e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.09e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.1e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.11e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.12e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.13e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.14e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.15e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.16e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.17e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.18e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.19e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.2e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.21e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.22e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.23e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.24e-10\u001b[0m\n", "2023-05-08 13:12:40 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.25e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.26e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.27e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.28e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.29e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.3e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.31e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.32e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.33e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.34e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.35e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.36e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.37e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.38e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.39e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.4e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.41e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.42e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.43e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.44e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.45e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.46e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.47e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.48e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.49e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.5e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.51e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.52e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.53e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.54e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.55e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.56e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.57e-10\u001b[0m\n", "2023-05-08 13:12:41 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.58e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.59e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.6e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.61e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.62e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.63e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.64e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.65e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.66e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.67e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.68e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.69e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.7e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.71e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.72e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.73e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.74e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.75e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.76e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.77e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.78e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.79e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.8e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.81e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.82e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.83e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.84e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.85e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.86e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.87e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.88e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.89e-10\u001b[0m\n", "2023-05-08 13:12:42 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.9e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.91e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.92e-10\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.93e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.94e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.95e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.96e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.97e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.98e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1.99e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.01e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.02e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.03e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.04e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.05e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.06e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.07e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.08e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.09e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.1e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.11e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.12e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.13e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.14e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.15e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.16e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.17e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.18e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.19e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.2e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.21e-10\u001b[0m\n", "2023-05-08 13:12:43 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.22e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.23e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.24e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.25e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.26e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.27e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.28e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.29e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.3e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.31e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.32e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.33e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.34e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.35e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.36e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.37e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.38e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.39e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.4e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.41e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.42e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.43e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.44e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.45e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.46e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.47e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.48e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.49e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.5e-10\u001b[0m\n", "2023-05-08 13:12:44 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.51e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.52e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.53e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.54e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.55e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.56e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.57e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.58e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.59e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.6e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.61e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.62e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.63e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.64e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.65e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.66e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.67e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.68e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.69e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.7e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.71e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.72e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.73e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.74e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.75e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.76e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.77e-10\u001b[0m\n", "2023-05-08 13:12:45 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.78e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.79e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.8e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.81e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.82e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.83e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.84e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.85e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.86e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.87e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.88e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.89e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.9e-10\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.91e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.92e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.93e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.94e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.95e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.96e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.97e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.98e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=2.99e-10\u001b[0m\n", "2023-05-08 13:12:46 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.01e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.02e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.03e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.04e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.05e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.06e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.07e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.08e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.09e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.1e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.11e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.12e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.13e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.14e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.15e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.16e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.17e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.18e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.19e-10\u001b[0m\n", "2023-05-08 13:12:47 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.2e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.21e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.22e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.23e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.24e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.25e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.26e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.27e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.28e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.29e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.3e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.31e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.32e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.33e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.34e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.35e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.36e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.37e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.38e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.39e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.4e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.41e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.42e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.43e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.44e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.45e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.46e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.47e-10\u001b[0m\n", "2023-05-08 13:12:48 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.48e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.49e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.5e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.51e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.52e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.53e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.54e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.55e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.56e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.57e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.58e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.59e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.6e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.61e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.62e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.63e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.64e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.65e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.66e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.67e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.68e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.69e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.7e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.71e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.72e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.73e-10\u001b[0m\n", "2023-05-08 13:12:49 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.74e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.75e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.76e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.77e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.78e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.79e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.8e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.81e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.82e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.83e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.84e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.85e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.86e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.87e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.88e-10\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.89e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.9e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.91e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.92e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.93e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.94e-10\u001b[0m\n", "2023-05-08 13:12:50 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.95e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.96e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.97e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.98e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=3.99e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.01e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.02e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.03e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.04e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.05e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.06e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.07e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.08e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.09e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.1e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.11e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.12e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.13e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.14e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.15e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.16e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.17e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.18e-10\u001b[0m\n", "2023-05-08 13:12:51 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.19e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.2e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.21e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.22e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.23e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.24e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.25e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.26e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.27e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.28e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.29e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.3e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.31e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.32e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.33e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.34e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.35e-10\u001b[0m\n", "2023-05-08 13:12:52 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.36e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.37e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.38e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.39e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.4e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.41e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.42e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.43e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.44e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.45e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.46e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.47e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.48e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.49e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.5e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.51e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.52e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.53e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.54e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.55e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.56e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.57e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.58e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.59e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.6e-10\u001b[0m\n", "2023-05-08 13:12:53 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.61e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.62e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.63e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.64e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.65e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.66e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.67e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.68e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.69e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.7e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.71e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.72e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.73e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.74e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.75e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.76e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.77e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.78e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.79e-10\u001b[0m\n", "2023-05-08 13:12:54 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.8e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.81e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.82e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.83e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.84e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.85e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.86e-10\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.87e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.88e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.89e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.9e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.91e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.92e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.93e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.94e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.95e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.96e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.97e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.98e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=4.99e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5e-10\u001b[0m\n", "2023-05-08 13:12:55 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.01e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.02e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.03e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.04e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.05e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.06e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.07e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.08e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.09e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.1e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.11e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.12e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.13e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.14e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.15e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.16e-10\u001b[0m\n", "2023-05-08 13:12:56 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.17e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.18e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.19e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.2e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.21e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.22e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.23e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.24e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.25e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.26e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.27e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO 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1e-12 t=5.38e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.39e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.4e-10\u001b[0m\n", "2023-05-08 13:12:57 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.41e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.42e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.43e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.44e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.45e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.46e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.47e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.48e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.49e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.5e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.51e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.52e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.53e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.54e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.55e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.56e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.57e-10\u001b[0m\n", "2023-05-08 13:12:58 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.58e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.59e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.6e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.61e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.62e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.63e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.64e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.65e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.66e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.67e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.68e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.69e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.7e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.71e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.72e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.73e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.74e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.75e-10\u001b[0m\n", "2023-05-08 13:12:59 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.76e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.77e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.78e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.79e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.8e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.81e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.82e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.83e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.84e-10\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.85e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.86e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.87e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=5.88e-10\u001b[0m\n", "2023-05-08 13:13:00 magnum.np:INFO 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1e-12 t=5.99e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.01e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.02e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.03e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.04e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.05e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.06e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.07e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.08e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.09e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.1e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.11e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.12e-10\u001b[0m\n", "2023-05-08 13:13:01 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.13e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.14e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.15e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.16e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.17e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.18e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.19e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.2e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.21e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.22e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.23e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.24e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.25e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.26e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.27e-10\u001b[0m\n", "2023-05-08 13:13:02 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.28e-10\u001b[0m\n", "2023-05-08 13:13:03 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.29e-10\u001b[0m\n", "2023-05-08 13:13:03 magnum.np:INFO 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1e-12 t=6.4e-10\u001b[0m\n", "2023-05-08 13:13:03 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.41e-10\u001b[0m\n", "2023-05-08 13:13:03 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.42e-10\u001b[0m\n", "2023-05-08 13:13:03 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.43e-10\u001b[0m\n", "2023-05-08 13:13:03 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.44e-10\u001b[0m\n", "2023-05-08 13:13:03 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.45e-10\u001b[0m\n", "2023-05-08 13:13:03 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.46e-10\u001b[0m\n", "2023-05-08 13:13:03 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.47e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.48e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.49e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.5e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.51e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.52e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.53e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.54e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.55e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.56e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.57e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.58e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.59e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.6e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.61e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.62e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.63e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.64e-10\u001b[0m\n", "2023-05-08 13:13:04 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.65e-10\u001b[0m\n", "2023-05-08 13:13:05 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.66e-10\u001b[0m\n", "2023-05-08 13:13:05 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.67e-10\u001b[0m\n", "2023-05-08 13:13:05 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.68e-10\u001b[0m\n", "2023-05-08 13:13:05 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.69e-10\u001b[0m\n", "2023-05-08 13:13:05 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.7e-10\u001b[0m\n", "2023-05-08 13:13:05 magnum.np:INFO 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1e-12 t=6.81e-10\u001b[0m\n", "2023-05-08 13:13:05 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.82e-10\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:13:06 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.83e-10\u001b[0m\n", "2023-05-08 13:13:06 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.84e-10\u001b[0m\n", "2023-05-08 13:13:06 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.85e-10\u001b[0m\n", "2023-05-08 13:13:06 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.86e-10\u001b[0m\n", "2023-05-08 13:13:06 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.87e-10\u001b[0m\n", "2023-05-08 13:13:06 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.88e-10\u001b[0m\n", "2023-05-08 13:13:06 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.89e-10\u001b[0m\n", "2023-05-08 13:13:06 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=6.9e-10\u001b[0m\n", "2023-05-08 13:13:06 magnum.np:INFO 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1e-12 t=7.01e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.02e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.03e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.04e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.05e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.06e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.07e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.08e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.09e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.1e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.11e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.12e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.13e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.14e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.15e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.16e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.17e-10\u001b[0m\n", "2023-05-08 13:13:07 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.18e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.19e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.2e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.21e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.22e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.23e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.24e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.25e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.26e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.27e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.28e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.29e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.3e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.31e-10\u001b[0m\n", "2023-05-08 13:13:08 magnum.np:INFO 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1e-12 t=7.42e-10\u001b[0m\n", "2023-05-08 13:13:09 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.43e-10\u001b[0m\n", "2023-05-08 13:13:09 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.44e-10\u001b[0m\n", "2023-05-08 13:13:09 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.45e-10\u001b[0m\n", "2023-05-08 13:13:09 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.46e-10\u001b[0m\n", "2023-05-08 13:13:09 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.47e-10\u001b[0m\n", "2023-05-08 13:13:09 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.48e-10\u001b[0m\n", "2023-05-08 13:13:09 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.49e-10\u001b[0m\n", "2023-05-08 13:13:09 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.5e-10\u001b[0m\n", "2023-05-08 13:13:09 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.51e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.52e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.53e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.54e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.55e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.56e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.57e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.58e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.59e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.6e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.61e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.62e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.63e-10\u001b[0m\n", "2023-05-08 13:13:10 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.64e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.65e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.66e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.67e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.68e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.69e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.7e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.71e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.72e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.73e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.74e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.75e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.76e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.77e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.78e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.79e-10\u001b[0m\n", "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.8e-10\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:13:11 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.81e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.82e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.83e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.84e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.85e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.86e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.87e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.88e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.89e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.9e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.91e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.92e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.93e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.94e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.95e-10\u001b[0m\n", "2023-05-08 13:13:12 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.96e-10\u001b[0m\n", "2023-05-08 13:13:13 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.97e-10\u001b[0m\n", "2023-05-08 13:13:13 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.98e-10\u001b[0m\n", "2023-05-08 13:13:13 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=7.99e-10\u001b[0m\n", "2023-05-08 13:13:13 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8e-10\u001b[0m\n", "2023-05-08 13:13:13 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.01e-10\u001b[0m\n", "2023-05-08 13:13:13 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.02e-10\u001b[0m\n", "2023-05-08 13:13:13 magnum.np:INFO 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1e-12 t=8.13e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.14e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.15e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.16e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.17e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.18e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.19e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.2e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.21e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.22e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.23e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.24e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.25e-10\u001b[0m\n", "2023-05-08 13:13:14 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.26e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.27e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.28e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.29e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.3e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.31e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.32e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.33e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.34e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.35e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.36e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.37e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.38e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.39e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.4e-10\u001b[0m\n", "2023-05-08 13:13:15 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.41e-10\u001b[0m\n", "2023-05-08 13:13:16 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.42e-10\u001b[0m\n", "2023-05-08 13:13:16 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.43e-10\u001b[0m\n", "2023-05-08 13:13:16 magnum.np:INFO 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1e-12 t=8.54e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.55e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.56e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.57e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.58e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.59e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.6e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.61e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.62e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.63e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.64e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.65e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.66e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.67e-10\u001b[0m\n", "2023-05-08 13:13:17 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.68e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.69e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.7e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.71e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.72e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.73e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.74e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.75e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.76e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.77e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.78e-10\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.79e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.8e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.81e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.82e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.83e-10\u001b[0m\n", "2023-05-08 13:13:18 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.84e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.85e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.86e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.87e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.88e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.89e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.9e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.91e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.92e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.93e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.94e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.95e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.96e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.97e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.98e-10\u001b[0m\n", "2023-05-08 13:13:19 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=8.99e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.01e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.02e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.03e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.04e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.05e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.06e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.07e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.08e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.09e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.1e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.11e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.12e-10\u001b[0m\n", "2023-05-08 13:13:20 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.13e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.14e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.15e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.16e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.17e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.18e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.19e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.2e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.21e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.22e-10\u001b[0m\n", "2023-05-08 13:13:21 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.23e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.24e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.25e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.26e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.27e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.28e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.29e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.3e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.31e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.32e-10\u001b[0m\n", "2023-05-08 13:13:22 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.33e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.34e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.35e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.36e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.37e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.38e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.39e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.4e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.41e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.42e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.43e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.44e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.45e-10\u001b[0m\n", "2023-05-08 13:13:23 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.46e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.47e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.48e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.49e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.5e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.51e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.52e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.53e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.54e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.55e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.56e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.57e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.58e-10\u001b[0m\n", "2023-05-08 13:13:24 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.59e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.6e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.61e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.62e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.63e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.64e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.65e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.66e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.67e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.68e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.69e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.7e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.71e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.72e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.73e-10\u001b[0m\n", "2023-05-08 13:13:25 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.74e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.75e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.76e-10\u001b[0m\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.77e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.78e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.79e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.8e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.81e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.82e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.83e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.84e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.85e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.86e-10\u001b[0m\n", "2023-05-08 13:13:26 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.87e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.88e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.89e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.9e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.91e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.92e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.93e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.94e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.95e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.96e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.97e-10\u001b[0m\n", "2023-05-08 13:13:27 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.98e-10\u001b[0m\n", "2023-05-08 13:13:28 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=9.99e-10\u001b[0m\n", "2023-05-08 13:13:28 magnum.np:INFO \u001b[1;37;34m[LLG] step: dt= 1e-12 t=1e-09\u001b[0m\n", "2023-05-08 13:13:28 magnum.np:WARNING \u001b[1;37;31mToo much time missing (52%). Add some Timers for more complete timing!\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "=======================================================================================\n", "TIMER REPORT\n", "=======================================================================================\n", "Operation No of calls Avg time [ms] Total time [s]\n", "------------------------------------- ------------- --------------- ----------------\n", "LLGSolver.relax 1 20923.3 20.9233\n", " ExchangeField.h 38 548.573 20.8458\n", " UniaxialAnisotropyField.h 38 0.626914 0.0238227\n", "SpinOrbitTorque.h 84 0.728035 0.061155\n", "LLGSolver.step 83 40.5836 3.36844\n", " ExchangeField.h 1021 0.606773 0.619515\n", " LLGSolver.relax 4 91.892 0.367568\n", " ExchangeField.h 152 0.976127 0.148371\n", " UniaxialAnisotropyField.h 152 0.360722 0.0548297\n", " SpinOrbitTorque.h 4000 0.601849 2.4074\n", " LLGSolver.step 4000 20.3233 81.2933\n", " ExchangeField.h 48072 0.266975 12.834\n", " SpinOrbitTorque.h 48072 0.346643 16.6638\n", " UniaxialAnisotropyField.h 48072 0.202435 9.73146\n", " SpinOrbitTorque.h 1021 0.676964 0.691181\n", " UniaxialAnisotropyField.h 1021 0.37927 0.387235\n", "------------------------------------- ------------- --------------- ----------------\n", "Total 50.7543\n", "Missing 26.4015\n", "=======================================================================================\n", "\n" ] } ], "source": [ "from magnumnp import *\n", "import torch\n", "\n", "Timer.enable()\n", "\n", "# initialize mesh\n", "eps = 1e-15\n", "#n = (2, 2, 2)\n", "n = (1, 1, 1)\n", "dx = (1.0e-9, 1.0e-9, 1e-9)\n", "\n", "mesh = Mesh(n, dx)\n", "state = State(mesh)\n", "\n", "# initialize polarization, p, and charge current amplitude\n", "# thickness of thin film on which the SOT acts\n", "p = state.Tensor((0, -1, 0))\n", "je = 6.9e10\n", "d = n[2] * dx[2]\n", "Keff = 1200e3*constants.mu_0*0.4/2./constants.mu_0\n", "\n", "state.material = {\n", " \"Ms\": 1200e3,\n", " \"A\": 15e-12,\n", " \"Ku\": Keff,\n", " \"Ku_axis\": [0, 0, 1],\n", " \"gamma\": 2.211e5,\n", " \"alpha\": 0.048,\n", " \"eta_damp\": -0.1, # both eta with opposite sign as magnum.af, same as magnum.pi\n", " \"eta_field\": 0.3,\n", " \"p\": p,\n", " \"d\": d,\n", " \"je\": je}\n", "\n", "# initialize field terms\n", "exchange = ExchangeField()\n", "aniso = UniaxialAnisotropyField()\n", "torque = SpinOrbitTorque()\n", "\n", "# initialize magnetization that relaxes into s-state\n", "state.m = state.Constant([0,0,1])\n", "\n", "# relax without external field\n", "llg = LLGSolver([exchange, aniso])\n", "llg.relax(state)\n", "\n", "# perform integration with external field\n", "state.t = 0.\n", "llg = LLGSolver([exchange, torque, aniso])\n", "slogger = ScalarLogger(\"data/log.dat\", ['t', 'm', torque.h])\n", "flogger = FieldLogger(\"data/fields.pvd\", ['m'])\n", "\n", "while state.t < 1e-9-eps:\n", " slogger << state\n", " flogger << state\n", " llg.step(state, 1e-12)\n", "\n", "Timer.print_report()" ] }, { "cell_type": "markdown", "id": "95c28257", "metadata": {}, "source": [ "## Plot Results:" ] }, { "cell_type": "code", "execution_count": 13, "id": "360f996c", "metadata": {}, "outputs": [], "source": [ "from os import path\n", "if not path.isdir(\"ref\"):\n", " !mkdir ref\n", " !wget -P ref https://gitlab.com/magnum.np/magnum.np/raw/main/demos/sot/ref/ref_magnumaf.dat\n", " !wget -P ref https://gitlab.com/nmagnum.np/magnum.np/raw/main/demos/sot/ref/ref_magnumnp.dat" ] }, { "cell_type": "code", "execution_count": 14, "id": "b7ad395e", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "data = np.loadtxt(\"data/log.dat\")\n", "ref_np = np.loadtxt(\"ref/ref_magnumnp.dat\")\n", "ref_af = np.loadtxt(\"ref/ref_magnumaf.dat\")\n", "\n", "fig, ax = plt.subplots(figsize=(10,5))\n", "cycle = plt.rcParams['axes.prop_cycle'].by_key()['color']\n", "\n", "ax.plot(data[:,1], data[:,2], '-', color = cycle[2], label = \"magnum.np\")\n", "ax.plot(ref_np[:,1], ref_np[:,2], '-', color = cycle[2], linewidth = 6, alpha = 0.4, label = \"reference magnum.np\")\n", "ax.plot(ref_af[:,1], ref_af[:,2], '--', color = cycle[2], linewidth = 1, alpha = 0.8, label = \"reference magnum.af\")\n", "\n", "#ax.set_xlim([4.82,5.0])\n", "#ax.set_ylim([0.99994,1.0])\n", "ax.set_title(\"Spin Orbit Torque\")\n", "ax.set_xlabel(\"Magnetization $m_x$\")\n", "ax.set_ylabel(\"Magnetization $m_y$\")\n", "ax.legend(ncol=3)\n", "ax.grid()\n", "fig.savefig(\"data/results.png\")" ] } ], "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": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 5 }