{ "metadata": { "name": "", "signature": "sha256:442ec51d8b46cd8f77b8d3a9f5ed58fdcd50891cc7bfc9f355b4005d60dc5837" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# QuTiP lecture: Quantum Monte-Carlo Trajectories" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Author: J. R. Johansson (robert@riken.jp), http://dml.riken.jp/~rob/\n", "\n", "The latest version of this [IPython notebook](http://ipython.org/ipython-doc/dev/interactive/htmlnotebook.html) lecture is available at [http://github.com/jrjohansson/qutip-lectures](http://github.com/jrjohansson/qutip-lectures).\n", "\n", "The other notebooks in this lecture series are indexed at [http://jrjohansson.github.com](http://jrjohansson.github.com).\n", "\n", "The example in this lecture is based on an example by P.D. Nation." ] }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import numpy as np" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "from qutip import *" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Introduction to the Quantum Monte-Carlo trajectory method\n", "\n", "The Quantum Monte-Carlo trajectory method is an equation of motion for a single realization of the state vector $\\left|\\psi(t)\\right>$ for a quantum system that interacts with its environment. The dynamics of the wave function is given by the Schrodinger equation,\n", "\n", "
Software | Version |
---|---|
QuTiP | 3.0.0.dev-5a88aa8 |
Numpy | 1.8.1 |
Python | 3.4.1 (default, Jun 9 2014, 17:34:49) \n", "[GCC 4.8.3] |
IPython | 2.0.0 |
SciPy | 0.13.3 |
matplotlib | 1.3.1 |
Cython | 0.20.1post0 |
OS | posix [linux] |
Thu Jun 26 15:01:46 2014 JST |