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PlotScript_voltVariation.py
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PlotScript_voltVariation.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Nov 27 16:20:13 2012
"""
import sympy.mpmath as mp
from sympy.mpmath import mpf
import time as time
import numpy as np
import matplotlib.pyplot as plt
import copy
import os
mp.mp.dps= 20
mp.mp.pretty = True
from Interface import Rfunc_constructor, Current
from InputParameters import base_parameters
plt.rc('font',**{'family':'sans-serif','sans-serif':['Helvetica'], 'size' : 16})
## for Palatino and other serif fonts use:
#rc('font',**{'family':'serif','serif':['Palatino']})
plt.rc('text', usetex=True)
_mp = np.vectorize(mp.mpf)
#===============================================================================
# MAIN PLOT (Current + Hmod vs Voltage)
#===============================================================================
def main_plot(saving = False):
"""Main plot:
Plots the mod-H function, the current with and without interference
# and transmission"""
Vpoints = mp.linspace(0, mpf('1.')/mpf(10**4), 201)
dist1 = mpf('2.0')/ mpf(10**(6))
dist2 = mpf('1.8')/mpf(10**(6))
genData = {
"v":[mpf(i) * mpf(10**j) for (i,j) in [(7,3),(7,3),(1,3),(1,3)]],
"c":[1,1,1,1],
"g":[mpf(1)/mpf(8),mpf(1)/mpf(8),mpf(1)/mpf(8),mpf(1)/mpf(8)],
"x":[-dist1, dist2, -dist1, dist2]}
mp.mp.dps= 60
A = base_parameters(genData, V = Vpoints, Q = 1/mpf(4), T = 1/mpf(10**4))
B = Rfunc_constructor(A, method = 'series')
B.setParameter(nterms = 450, maxA = 11, maxK = 11)
single, interference = Current(B)
fig = plt.figure()
xt = np.linspace(0, 1 * 10**(-4), 5)
xt_labels = [str(int(i * 10**6)) for i in xt]
ax = fig.add_subplot(211)
ax.plot(Vpoints,interference/np.max(single), label = r"With interference", linewidth=1.5)
ax.plot(Vpoints,single/np.max(single), label = r"Without interference", linewidth=1.5)
ax.get_lines()[1].set_dashes([5,2])
for i in ax.get_lines(): i.set_color('black')
ax.set_title(r'Tunnelling current for the Pfaffian state', fontsize=16)
ax.set_ylabel(r"$I_B/\mathrm{max}(I_B){}$", fontsize=16)
ax.set_ybound([0,1])
ax.set_yticks([.25, .5, .75, 1])
ax.set_yticklabels([0.25, 0.5, 0.75, 1])
ax.set_xticks(xt)
ax.set_xticklabels([])
ax.legend(loc = 'upper right', prop={'size':14})
plt.setp(ax.get_xticklabels(), fontsize = 14)
plt.setp(ax.get_yticklabels(), fontsize = 14)
ax.grid(True)
ax2 = fig.add_subplot(212)
ax2.plot(Vpoints, B.rrfunction, linewidth=1.5)
ax2.get_lines()[0].set_color('black')
ax2.set_title(r'Modulating function for the Pfaffian state', fontsize=16)
ax2.set_ylabel(r"$\mathrm{Re}[H_{ij}^{\mathrm{mod}}]{}$", fontsize=16)
ax2.set_xlabel(r'Voltage [$\mu$V]', fontsize=16)
ax2.xaxis.set_label_coords(.9, -0.12)
ax2.set_yticks([-0.25,0,.25,.5,.75,1])
ax2.set_yticklabels([-0.25,0,0.25,0.5,0.75,1])
ax2.set_xticks(xt)
ax2.set_xticklabels(xt_labels)
ax2.grid(True)
plt.setp(ax2.get_xticklabels(), fontsize=14)
plt.setp(ax2.get_yticklabels(), fontsize=14)
if saving: plt.savefig('main_plot.pdf', bbox_inches=0, dpi=300)
plt.subplots_adjust(hspace=0.3)
plt.show()
return B
#===============================================================================
# TEMPERATURE VARIATION (Hmod vs Voltage)
#===============================================================================
def temperature(saving = False):
Vpoints = mp.linspace(0, mpf('1.')/mpf(10**4), 201)
dist1 = np.array(mpf('3.5')/ mpf(10**(6)))
dist2 = np.array(mpf('3.5')/mpf(10**(6)))
genData = {
"v":[mpf(i) * mpf(10**j) for (i,j) in [(9,4),(9,4),(9,3),(9,3)]],
"c":[1,1,1,1],
"g":[1/mpf(8), 1/mpf(8), 1/mpf(8), 1/mpf(8)],
"x":[-dist1, dist2, -dist1, dist2]}
names = [0,10,18]
temperatureset = [mpf(i)/mpf(10**3) for i in names]
ans = []
fig = plt.figure()
ax = fig.add_subplot(111)
for i, j in enumerate(temperatureset):
A = base_parameters(genData, V = Vpoints, Q = 1/mpf(4), T = j)
if j < 9/mpf(10**3):
mp.mp.dps = 30
B = Rfunc_constructor(A, method = 'series')
B.setParameter(nterms = 500, maxA = 15, maxK = 15)
else:
mp.mp.dps = 20
B = Rfunc_constructor(A, method = 'fortran')
B.setParameter(nterms = 2*132000, maxA = 25, maxK = 25)
B.genAnswer()
ans.append(B)
ax.plot(Vpoints, B.rrfunction, \
label = str(names[i]) +' [mK]', linewidth=1.5)
dashstyle = [(None, None), [7,2], [3,4]]
for i in range(len(ax.get_lines())):
ax.get_lines()[i].set_color('black')
ax.get_lines()[i].set_dashes(dashstyle[i])
xt = np.linspace(0, 1 * 10**(-4), 5)
xt_labels = [str(int(i * 10**6)) for i in xt]
ax.set_title(r'The modulating function \\ for different temperature scales', fontsize=16)
ax.set_ylabel(r"$\mathrm{Re}[H_{ij}^{\mathrm{mod}}]{}$", fontsize=16)
ax.set_xlabel(r'Voltage [$\mu$V]', fontsize=16)
ax.xaxis.set_label_coords(.9, -0.06)
ax.set_ybound([-.25,1.125])
ax.set_yticks([-0.25,0,.25,.5,.75,1])
ax.set_yticklabels([-0.25,0,0.25,0.5,0.75,1])
ax.set_xticks(xt)
ax.set_xticklabels(xt_labels)
ax.grid(True)
ax.legend(loc='upper right', prop={'size':14})
plt.setp(ax.get_xticklabels(), fontsize=14)
plt.setp(ax.get_yticklabels(), fontsize=14)
if saving: plt.savefig('temperature.pdf', bbox_inches=0, dpi=300)
plt.show()
return ans
##===============================================================================
## PLOTS FOR 5/2 STATE
##===============================================================================
def particles_5_2(saving = False):
Vpoints = mp.linspace(0, mpf('1.')/mpf(10**4), 201)
dist1 = mpf('2.4')/ mpf(10**(6))
dist2 = mpf('2.1')/mpf(10**(6))
genData = {
"v":[mpf(i) * mpf(10**j) for (i,j) in [(5,3),(5,3),(1.4,3),(1.4,3)]],
"x":[-dist1, dist2, -dist1, dist2]}
pfaffE2 = {
"g":[mpf(1)/mpf(2),mpf(1)/mpf(2)],
"c":[1,1],
"x":[-dist1, dist2],
"v":[mpf(i) * mpf(10**j) for (i,j) in [(5,3),(5,3)]],"Q":1/mpf(2)}
pfaff = {
"g":[mpf(1)/mpf(8), mpf(1)/mpf(8),mpf(1)/mpf(8), mpf(1)/mpf(8)],
"c":[1,1,1,1],"Q":1/mpf(4)}
apf = {
"g":[mpf(1)/mpf(8),mpf(1)/mpf(8),mpf(3)/mpf(8), mpf(3)/mpf(8)],
"c":[1,1,-1,-1],"Q":1/mpf(4)}
state331 = {
"g":[mpf(1)/mpf(8), mpf(1)/mpf(8), mpf(1)/mpf(4), mpf(1)/mpf(4)],
"c":[1,1,1,1],"Q":1/mpf(4)}
particleset = [apf, state331, pfaff, pfaffE2]
names = [
"Anti-Pfaffian (e/4)",
"(3,3,1)-state (e/4)",
"Pfaffian (e/4)",
"Laughlin (e/2)"]
mp.mp.dps= 60
fig = plt.figure()
ax = fig.add_subplot(111)
ans = []
for i in range(0,4):
particle = genData.copy()
particle.update(particleset[i])
Qe = particle["Q"]
del particle["Q"]
A = base_parameters(particle, V = Vpoints, Q = Qe, T = 1/mpf(10**3))
B = Rfunc_constructor(A, method = 'series')
B.setParameter(nterms = 1200, maxA = 12, maxK = 12)
B.genAnswer()
### uncomment to return all instances
# ans.extend([copy.deepcopy(A),copy.deepcopy(B)])
###
if B.rrfunction.shape[1] > 1:
ax.plot(Vpoints, B.rrfunction[:,0], label = names[i], linewidth=1.5)
else:
ax.plot(Vpoints, B.rrfunction, label = names[i], linewidth=1.5)
dashstyle = [(None, None), [10,4], [5,3,1,3], [2,4]]
for i in range(len(ax.get_lines())):
ax.get_lines()[i].set_color('black')
ax.get_lines()[i].set_dashes(dashstyle[i])
ax.set_ylabel(r"$\mathrm{Re}[H_{ij}^{\mathrm{mod}}]{}$", fontsize=16)
ax.set_xlabel(r'Voltage [$\mu$V]', fontsize=16)
ax.xaxis.set_label_coords(.9, -0.06)
ax.set_ybound([-.5, 1])
ax.set_yticks([-0.25, 0, .25, .5, .75, 1])
ax.set_yticklabels([-0.25, 0, 0.25, 0.5, 0.75, 1])
xt = np.linspace(0, 1 * 10**(-4), 5)
xt_labels = [str(int(i * 10**6)) for i in xt]
ax.set_xticks(xt)
ax.set_xticklabels(xt_labels)
ax.set_title(r"Modulating function for $\nu = 5/2 $ candidates", fontsize=16)
ax.legend(loc='upper right', prop={'size':14})
ax.grid(True)
plt.setp(ax.get_xticklabels(), fontsize=14)
plt.setp(ax.get_yticklabels(), fontsize=14)
if saving: plt.savefig('particles_5_2.pdf', bbox_inches=0, dpi=300)
plt.show()
return ans
##===============================================================================
## PLOTS FOR 7/3 STATE
##===============================================================================
def particles_7_3(saving = False):
Vpoints = mp.linspace(0, mpf('1.')/mpf(10**4), 201)
dist1 = mpf('2.4')/ mpf(10**(6))
dist2 = mpf('2.1')/mpf(10**(6))
genData = {
"v":[mpf(i) * mpf(10**j) for (i,j) in [(5,3),(5,3),(1.4,3),(1.4,3)]],
"x":[-dist1, dist2, -dist1, dist2]}
LaughlinE3 = {
"g":[mpf(1)/mpf(2),mpf(1)/mpf(2)],
"c":[1,1],
"x":[-dist1, dist2],
"v":[mpf(i) * mpf(10**j) for (i,j) in [(5,3),(5,3)]],"Q":1/mpf(3)}
aBS23 = {
"g":[mpf(1)/mpf(3), mpf(1)/mpf(3),mpf(5)/mpf(8), mpf(5)/mpf(8)],
"c":[1,1,-1,-1],"Q":1/mpf(3)}
BS13 = {
"g":[mpf(1)/mpf(3),mpf(1)/mpf(3),mpf(3)/mpf(8), mpf(3)/mpf(8)],
"c":[1,1,1,1],"Q":1/mpf(3)}
aRR4 = {
"g":[mpf(1)/mpf(12), mpf(1)/mpf(12), mpf(1)/mpf(4), mpf(1)/mpf(4)],
"c":[1,1,-1,-1],"Q":1/mpf(6)}
particleset = [aBS23, BS13, aRR4, LaughlinE3]
names =[ r"$\overline{\mathrm{BS}}_{2/3}$ (e/3)",
r"$\mathrm{BS}_{1/3}^{\psi}$ (e/3)",
r"$\overline{\mathrm{RR}}_{k=4} $ (e/6)",
r"Laughlin (e/3)"]
mp.mp.dps= 60
fig = plt.figure()
ax = fig.add_subplot(111)
ans = []
for i in range(len(names)):
particle = genData.copy()
particle.update(particleset[i])
Qe = particle["Q"]
del particle["Q"]
A = base_parameters(particle, V = Vpoints, Q = Qe, T = 1/mpf(10**3))
B = Rfunc_constructor(A, method = 'series')
B.setParameter(nterms = 1200, maxA = 12, maxK = 12)
B.genAnswer()
#ans.append(B)
ax.plot(Vpoints, B.rrfunction, label = names[i], linewidth=1.5)
dashstyle = [(None, None), [10,4], [5,3,1,3], [2,4]]
for i in range(len(ax.get_lines())):
ax.get_lines()[i].set_color('black')
ax.get_lines()[i].set_dashes(dashstyle[i])
ax.set_ylabel(r"$\mathrm{Re}[H_{ij}^{\mathrm{mod}}]{}$", fontsize=16)
ax.set_xlabel(r'Voltage [$\mu$V]', fontsize=16)
ax.xaxis.set_label_coords(.9, -0.06)
ax.set_ybound([-.5, 1])
ax.set_yticks([-0.25, 0, .25, .5, .75, 1])
ax.set_yticklabels([-0.25, 0, 0.25, 0.5, 0.75, 1])
xt = np.linspace(0, 1 * 10**(-4), 5)
xt_labels = [str(int(i * 10**6)) for i in xt]
ax.set_xticks(xt)
ax.set_xticklabels(xt_labels)
ax.set_title(r"Modulating function for $\nu = 7/3 $ candidates", fontsize=16)
ax.legend(loc='upper right', prop={'size':14})
ax.grid(True)
plt.setp(ax.get_xticklabels(), fontsize=14)
plt.setp(ax.get_yticklabels(), fontsize=14)
if saving: plt.savefig('particles_7_3.pdf', bbox_inches=0, dpi=300)
plt.show()
return ans
def particles_12_5(saving = False):
Vpoints = mp.linspace(0, mpf('1.')/mpf(10**4), 201)
dist1 = mpf('2.4')/ mpf(10**(6))
dist2 = mpf('2.1')/mpf(10**(6))
genData = {
"v":[mpf(i) * mpf(10**j) for (i,j) in [(5,3),(5,3),(1.4,3),(1.4,3)]],
"x":[-dist1, dist2, -dist1, dist2]}
LaughlinE5 = {
"g":[mpf(2)/mpf(5),mpf(2)/mpf(5)],
"c":[1,1],
"x":[-dist1, dist2],
"v":[mpf(i) * mpf(10**j) for (i,j) in [(5,3),(5,3)]],"Q":1/mpf(3)}
BS25 = {
"g":[mpf(1)/mpf(10),mpf(1)/mpf(10),mpf(1)/mpf(8), mpf(1)/mpf(8)],
"c":[1,1,1,1],"Q":1/mpf(5)}
HH25 = {
"g":[mpf(1)/mpf(5),mpf(1)/mpf(5),mpf(2)/mpf(5), mpf(2)/mpf(5)],
"c":[1,1,1,1],"Q":1/mpf(5)}
aRR3 = {
"g":[mpf(1)/mpf(10), mpf(1)/mpf(10), mpf(3)/mpf(10), mpf(3)/mpf(10)],
"c":[1,1,-1,-1],"Q":mpf(1)/mpf(5)}
particleset = [HH25,aRR3, BS25, LaughlinE5]
names =[ r"$\mathrm{HH}_{2/5}$ (e/5)",
r"$\overline{\mathrm{RR}}_{k=3} $ (e/5)",
r"$\mathrm{BS}_{2/5}$ (e/5)",
r"Laughlin (2e/5)"]
mp.mp.dps= 60
fig = plt.figure()
ax = fig.add_subplot(111)
ans = []
for i in range(len(names)):
particle = genData.copy()
particle.update(particleset[i])
Qe = particle["Q"]
del particle["Q"]
A = base_parameters(particle, V = Vpoints, Q = Qe, T = 1/mpf(10**3))
B = Rfunc_constructor(A, method = 'series')
B.setParameter(nterms = 1000, maxA = 12, maxK = 12)
B.genAnswer()
ans.append(B)
ax.plot(Vpoints, B.rrfunction, label = names[i], linewidth=1.5)
xt = np.linspace(0, 1 * 10**(-4), 5)
xt_labels = [str(int(i * 10**6)) for i in xt]
dashstyle = [(None, None), [10,4], [6,3,1,3,1,3],[2,2] ,[2,6]]
for i in range(len(ax.get_lines())):
ax.get_lines()[i].set_color('black')
ax.get_lines()[i].set_dashes(dashstyle[i])
ax.set_ylabel(r"$\mathrm{Re}[H_{ij}^{\mathrm{mod}}]{}$", fontsize=16)
ax.set_xlabel(r'Voltage [$\mu$V]', fontsize=16)
ax.xaxis.set_label_coords(.9, -0.06)
ax.set_ybound([-.5, 1])
ax.set_yticks([-0.25, 0, .25, .5, .75, 1])
ax.set_yticklabels([-0.25, 0, 0.25, 0.5, 0.75, 1])
xt = np.linspace(0, 1 * 10**(-4), 5)
xt_labels = [str(int(i * 10**6)) for i in xt]
ax.set_xticks(xt)
ax.set_xticklabels(xt_labels)
ax.set_title(r"Modulating function for $\nu = 12/5 $ candidates", fontsize=16)
ax.legend(loc='upper right', prop={'size':14})
ax.grid(True)
plt.setp(ax.get_xticklabels(), fontsize=14)
plt.setp(ax.get_yticklabels(), fontsize=14)
if saving: plt.savefig('particles_12_5.pdf', bbox_inches=0, dpi=300)
plt.show()
return ans
#def plot_all(saveon = False):
# os.chdir('C:\\Science\\LaTeX\\Interferometer PRB')
# main_plot(saving = saveon)
# temperature(saving = saveon)
# particles_5_2(saving = saveon)
# particles_7_3(saving = saveon)
##A = RCNTC.RfuncCNTC(par = genData, nterms = 100000)
##A.updateParameters(par = {
## "v":[mpf('5.')* mpf(10**(4)),mpf('5.')*mpf(10**(3))],\
## "g":[1/mpf(8),1/mpf(8)],\
## "c":[1,1],\
## "a1":mpf('1.7')/ mpf(10**(6)), "a2":mpf('1.3')/mpf(10**(6)), \
## "T" :mpf(8) / mpf(10**(3)), "Q" :1/mpf(4)})
##A.updateParameters(par = pfaffData)
##A.genAnswer()
#===============================================================================
# MULTIPLE MODES -- NOT YET IMPLEMENTED
#===============================================================================
def multi_modes(saving = False):
"""Plots the modulating function and interference current for an edge with
3 modes."""
Vpoints = mp.linspace(0, mpf('2.')/mpf(10**4), 201)
dist1 = np.array(mpf('4.5')/ mpf(10**(6)))
dist2 = np.array(mpf('3.')/mpf(10**(6)))
genData = {
"v":[mpf(i) * mpf(10**j) for (i,j) in [(10,3),(10,3),(3,3),(3,3),(5,3),(5,3)]],
"x":[dist1, -dist2, dist1, -dist2,dist1, -dist2],
"g":[mpf(1)/mpf(10), mpf(1)/mpf(10), mpf(1)/mpf(10), mpf(1)/mpf(10),mpf(1)/mpf(10), mpf(1)/mpf(10)],
"c":[1,1,1,1,1,1]}
mp.mp.dps= 90
A = base_parameters(genData, V = Vpoints, Q = 1/mpf(4), T = mpf(0))
B = Rfunc_constructor(A, method = 'series')
B.setParameter(nterms = 800)
single, interference = Current(B)
fig = plt.figure()
xt = np.linspace(0, 2 * 10**(-4), 5)
xt_labels = [str(int(i * 10**6)) for i in xt]
ax = fig.add_subplot(211)
ax.plot(Vpoints,interference/np.max(single), label = r"With interference", linewidth=1.5)
ax.plot(Vpoints,single/np.max(single), label = r"With interference", linewidth=1.5)
ax.get_lines()[1].set_dashes([5,2])
for i in ax.get_lines(): i.set_color('black')
ax.set_title(r'Tunnelling current for edge with three modes')
ax.set_ylabel(r"$I_B/\mathrm{max}(I_B){}$")
ax.set_ybound([0,1])
ax.set_yticks([0,.25, .5, .75, 1])
ax.set_yticklabels([0,0.25, 0.5, 0.75, 1])
ax.set_xticks(xt)
ax.set_xticklabels([])
ax.legend(loc = 'upper right', prop={'size':14})
plt.setp(ax.get_xticklabels(), fontsize = 14)
plt.setp(ax.get_yticklabels(), fontsize = 14)
ax.grid(True)
ax2 = fig.add_subplot(212)
ax2.plot(Vpoints, B.rrfunction, linewidth=1.5)
ax2.get_lines()[0].set_color('black')
ax2.set_title(r'Modulating function for edge with three modes', fontsize=16)
ax2.set_ylabel(r"$\mathrm{Re}[H_{ij}^{\mathrm{mod}}]{}$", fontsize=16)
ax2.set_xlabel(r'Volt [$\mu$V]')
ax2.set_yticks([-0.25,0,.25,.5,.75,1])
ax2.set_yticklabels([-0.25,0,0.25,0.5,0.75,1])
ax2.set_xticks(xt)
ax2.set_xticklabels(xt_labels)
ax2.grid(True)
plt.setp(ax2.get_xticklabels(), fontsize=12.)
plt.setp(ax2.get_yticklabels(), fontsize=12.)
if saving: plt.savefig('main_plot.pdf', bbox_inches=0, dpi=300)
plt.show()
return B
if __name__ == '__main__':
pass