{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#Simple example of transport properties of a coherent double quantum dot. The counting statistics functions used here\n", "#return the current, shot noise and noise spectrum (if required) for left and right junctions, and cross-correlations \n", "#between junctions\n", "\n", "#For the current and zero frequency shot noise comparisons are made to known analytical results.\n", "#I believe the frequency dependance is also analytical, but I cannot for the life of me find the formula in my thesis.\n", "\n", "\n", "#Author: Neill Lambert" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] } ], "source": [ "\n", "\n", "# setup the matplotlib graphics library and configure it to show \n", "# figures inline in the notebook\n", "%pylab inline" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# make qutip available in the rest of the notebook\n", "from qutip import *\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "#DDOT example, frequency dependance \n", "\n", "#number of data points:\n", "data = 500\n", "wmax = 2\n", "#list of frequencies\n", "w_vec = linspace(0., wmax, data)\n", "\n", "#Parameters\n", "eps = 0.5 # detuning\n", "Tc = 0.1 # tunnelling strength\n", "GammaR = 0.025\n", "GammaL = 0.025\n", "\n", "Lstate = basis(3,0)\n", "Rstate = basis(3,1)\n", "Empty = basis(3,2)\n", "\n", "H = 0.5*eps * (Lstate*Lstate.dag() - Rstate*Rstate.dag()) + Tc*(Lstate*Rstate.dag() + Rstate*Lstate.dag())\n", "\n", "c_ops = []\n", "rate = GammaL\n", "if rate > 0.0:\n", " c_ops.append(sqrt(rate)*Lstate*Empty.dag())\n", "\n", "rate = GammaR\n", "if rate > 0.0:\n", " c_ops.append(sqrt(rate)*Empty*Rstate.dag())" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "\n", "rho_ss = steadystate(H, c_ops)\n", "L = liouvillian(H, c_ops)\n", "I, S = countstat_current_noise(L, [], wlist=w_vec, rhoss=rho_ss, \n", " J_ops=[GammaR*sprepost(Empty*Rstate.dag(), Rstate*Empty.dag()), \n", " GammaL*sprepost(Lstate*Empty.dag(), Empty*Lstate.dag())], sparse=False) \n", " " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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OYGfFTi4cciHXHnltqpuUMucfcj4Aj7z/CFVeBaiHQUSkIQoM+4lxz43jk02fMLTrUH5/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\n55138te//pVBgwaxbt063n777cj6X/3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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axes = subplots(1, 1, sharex=True, figsize=(8,8))\n", "axes.plot(w_vec, S[0,0,:]/I[0], 'g', linewidth=2, label=\"Numerical noise spectrum in right junction\")\n", "\n", "axes.legend(loc=0, prop={\"size\":14})\n", "axes.set_xlabel(r'$\\omega$', fontsize=18)\n", "axes.set_ylabel(r'$F(\\omega)$', fontsize=18)\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "#DDOT example, Detuning dependance \n", "\n", "#number of data points:\n", "data = 200\n", "eps_max = 1\n", "#list of frequencies\n", "eps_vec = linspace(-eps_max, eps_max,data)\n", "\n", "#Parameters\n", "\n", "Tc = 0.1 # tunnelling strength\n", "GammaR = 0.0025\n", "GammaL = 0.1\n", "\n", "Lstate = basis(3,0)\n", "Rstate = basis(3,1)\n", "Empty = basis(3,2)\n", "\n", "c_ops = []\n", "rate = GammaL\n", "if rate > 0.0:\n", " c_ops.append(sqrt(rate) * Lstate*Empty.dag())\n", "\n", "rate = GammaR\n", "if rate > 0.0:\n", " c_ops.append(sqrt(rate) * Empty*Rstate.dag())\n", "\n", "Num_of_J_ops=2\n", "\n", "I_vec=[[] for N_ops in range(Num_of_J_ops)]\n", "F_vec=[[[] for N_ops in range(Num_of_J_ops)] for N_ops in range(Num_of_J_ops)]\n", "\n", "I_ana=[]\n", "F_ana=[]\n", "\n", "for eps in eps_vec:\n", " \n", " I_ana.append(4.*GammaR*GammaL*Tc**2/(4.*Tc**2*(2.*GammaL+GammaR)+GammaL*GammaR**2+4.*eps**2*GammaL)) #Analytical Current\n", " F_ana.append((1-8.*GammaL*Tc**2*(4*eps**2*(GammaR-GammaL) + GammaR*(3*GammaL*GammaR + GammaR**2 + \n", " 8*Tc**2))/(4.*Tc**2*(2.*GammaL+GammaR)+GammaL*GammaR**2+\n", " 4.*eps**2*GammaL)**2)) #Analytical Zero frequency Fano factor (noise normalized by current)\n", "\n", " H = 0.5*eps * (Lstate*Lstate.dag() - Rstate*Rstate.dag()) +Tc*(Lstate*Rstate.dag() + Rstate*Lstate.dag())\n", " \n", "\n", " rho_ss = steadystate(H, c_ops)\n", " L = liouvillian(H, c_ops)\n", " I, S = countstat_current_noise(L, [], rhoss=rho_ss, \n", " J_ops=[GammaR*sprepost(Empty*Rstate.dag(), Rstate*Empty.dag()), \n", " GammaL*sprepost(Lstate*Empty.dag(), Empty*Lstate.dag())],sparse=False) \n", " for i in range(Num_of_J_ops):\n", " I_vec[i].append(I[i])\n", " for j in range(Num_of_J_ops):\n", " \n", " F_vec[i][j].append(S[i,j]/sqrt(I[i]*I[j]))\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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9N++++y6TJ09m/fr1vPTSS7z//vt1nlTqJBUQIlLlzTff5IwzzqizcdBvfvMb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\nqzH/0TLFrRtjrU313t4NxPjw8zDGjDHGLDPGLEtPTy/5aERERCqRgD6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GwZVnt+E3wJuVqyXDweSNO4XfnephYaaXV+qKyU4KrjsXQhwJuTMghGYpawsB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UAAAI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\nQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "fig, axes = subplots(1, 1, sharex=True, figsize=(8,8))\n", "axes.plot(eps_vec, I_vec[0], 'g', linewidth=2, label=\"Numerical Current in right junction\")\n", "axes.plot(eps_vec, I_ana, 'r--', linewidth=2, label=\"Analytical Current in right junction\")\n", "\n", "\n", "axes.legend(loc=0,prop={\"size\":14})\n", "axes.set_xlabel(r'$\\epsilon$', fontsize=18)\n", "axes.set_ylabel(r'I', fontsize=18)\n", "\n", "fig1, axes1 = subplots(1, 1, sharex=True, figsize=(8,8))\n", "axes1.plot(eps_vec, F_vec[0][0], 'g', linewidth=2, label=\"Numerical Fano Factor in right junction\")\n", "axes1.plot(eps_vec, F_ana, 'r--', linewidth=2, label=\"Analytical Fano Factor in right junction\")\n", "\n", "axes1.legend(loc=0,prop={\"size\":14})\n", "axes1.set_xlabel(r'$\\epsilon$', fontsize=18)\n", "axes1.set_ylabel(r'F(0)', fontsize=18)\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
SoftwareVersion
QuTiP4.2.0
Numpy1.13.1
SciPy0.19.1
matplotlib2.0.2
Cython0.25.2
Number of CPUs2
BLAS InfoINTEL MKL
IPython6.1.0
Python3.6.1 |Anaconda custom (x86_64)| (default, May 11 2017, 13:04:09) \n", "[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)]
OSposix [darwin]
Wed Jul 19 22:15:11 2017 MDT
" ], "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from qutip.ipynbtools import version_table\n", "version_table()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "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": "3.6.1" } }, "nbformat": 4, "nbformat_minor": 1 }