Cat-state-even-loss-animation.gif (220 × 128 pixels, file size: 217 KB, MIME type: image/gif, looped, 40 frames, 5.0 s)
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Summary
DescriptionCat-state-even-loss-animation.gif |
English: Animated Wigner function of an even cat state. The animation shows the distribution for different values of the amplitude α and relative fractional loss. |
Date | |
Source | Own work |
Author | Geek3 |
GIF development InfoField | This plot was created with Matplotlib. |
Source code InfoField | Python code#!/usr/bin/python
# -*- coding: utf8 -*-
import numpy as np
from math import *
import matplotlib.pyplot as plt
from matplotlib import animation, ticker
import os
# settings
plt.rc('path', snap=False)
plt.rc('mathtext', default='regular')
fname = 'Cat-state-even-loss-animation'
width, height = 220, 128
dpi = 65.
nframes = 40
fps = 10
alpha0 = 2.
xlim = -4, 4
ylim = -2, 2
res = 40.
x_range = np.linspace(xlim[0], xlim[1], res*4+1)
y_range = np.linspace(ylim[0], ylim[1], res*2+1)
x_pixels = (x_range[1:] + x_range[:-1]) / 2.
y_pixels = (y_range[1:] + y_range[:-1]) / 2.
X, Y = np.meshgrid(x_pixels, y_pixels)
delays = [100 // fps for i in range(nframes)]
delays[0] = delays[20] = 60
plt.close('all')
def cat_state(x, y, alpha, theta, L):
# Eq. (64), Phys. Rev. A 80, 032318 (2009)
gaussm = np.exp(-(x + sqrt(2 * (1-L)) * alpha)**2 - y**2)
gaussp = np.exp(-(x - sqrt(2 * (1-L)) * alpha)**2 - y**2)
gauss0 = np.exp(-x**2 - y**2)
fringe = np.cos(sqrt(8 * (1-L)) * alpha * y + theta)
damp = exp(-2 * L * alpha**2)
norm = 2 * pi * (1. + exp(-2 * alpha**2) * cos(theta))
return (gaussm + gaussp + 2. * gauss0 * fringe * damp) / norm
def animate(nframe):
print 'frame', nframe+1, '/', nframes
t = nframe / float(nframes)
plt.clf()
if t < 0.5:
alpha = alpha0
L = t / 0.5
else:
alpha = alpha0 * (t - 0.5) / 0.5
L = 0.
img = cat_state(X, Y, alpha, 0., L)
plt.imshow(img, cmap='RdBu', vmin=-1/pi, vmax=1/pi, origin='lower',
extent=(xlim[0], xlim[1], ylim[0], ylim[1]))
plt.title(r'$\alpha={:.1f}$ loss$={:.2f}$'.format(alpha, L))
plt.gca().set_aspect('equal', adjustable='box')
plt.gca().yaxis.set_major_locator(ticker.MultipleLocator(1))
plt.subplots_adjust(left=0.1, right=1-0.06, bottom=0.1)
fig = plt.figure(figsize=(width/float(dpi), height/float(dpi)))
# start animation
if 0 != os.system('convert -version > ' + os.devnull):
print 'imagemagick not installed!'
# warning: imagemagick produces dithered and therefore large gifs
anim = animation.FuncAnimation(fig, animate, frames=nframes)
anim.save(fname + '.gif', writer='imagemagick', fps=fps, dpi=dpi)
else:
# unfortunately the matplotlib imagemagick backend does not support
# options which are necessary to generate high quality output without
# framewise color palettes. Therefore save all frames and convert then.
if not os.path.isdir(fname):
os.mkdir(fname)
fnames = []
for frame in range(nframes):
animate(frame)
imgname = os.path.join(fname, fname + '{:03d}'.format(frame) + '.png')
fig.savefig(imgname, dpi=dpi)
fnames.append(imgname)
# compile optimized animation with ImageMagick
cmd = 'convert -loop 0 '
nameslist = ['-delay ' + str(delays[i]) + ' ' + n for i,n in enumerate(fnames)]
cmd += ' '.join(nameslist)
cmd += ' +dither -colors 255 '
cmd += fname + '.gif'
os.system(cmd)
for fnamei in fnames:
os.remove(fnamei)
os.rmdir(fname)
|
Licensing
I, the copyright holder of this work, hereby publish it under the following license:
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Items portrayed in this file
depicts
1 September 2018
image/gif
10d8e924308168223f271146f734019be12de1ea
222,375 byte
4.999999999999998 second
128 pixel
220 pixel
File history
Click on a date/time to view the file as it appeared at that time.
Date/Time | Thumbnail | Dimensions | User | Comment | |
---|---|---|---|---|---|
current | 20:12, 1 September 2018 | 220 × 128 (217 KB) | Geek3 | User created page with UploadWizard |
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