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find_capa.py
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# -*- coding: utf-8 -*-
"""
Created on Mon May 30 15:11:49 2016
@author: leghtas
"""
import scipy.constants as sc
import numpy as np
import matplotlib.pyplot as plt
import circuit
import circuit_find_capa as cp2s
import scipy.linalg as sl
import numpy.linalg as nl
from scipy.misc import factorial
import matplotlib
from matplotlib.animation import FuncAnimation
import sys
def move_figure(f, x, y):
"""Move figure's upper left corner to pixel (x, y)"""
backend = matplotlib.get_backend()
if backend == 'TkAgg':
f.canvas.manager.window.wm_geometry("+%d+%d" % (x, y))
elif backend == 'WXAgg':
f.canvas.manager.window.SetPosition((x, y))
else:
# This works for QT and GTK
# You can also use window.setGeometry
f.canvas.manager.window.move(x, y)
plt.show()
pi = np.pi
plt.close('all')
w, Z = [5.8e9*2*np.pi, 120]
Cc = 252e-15
LJ = 3000e-12
dLJ = 500e-12 #linear part for sna to be adjusted
wJ = 16.9*2*np.pi*1e9 #GHz without big_capa HFSS
CJ = 1/(LJ+dLJ)/wJ**2
print("CJ = "+str(CJ*1e15)+" fF\n")
_, _, EJ = circuit.get_E_from_w(1, 1, LJ+dLJ)
#EJ, LJ, I0 = circuit.convert_EJ_LJ_I0(I0=I0)
c = cp2s.CircuitPump2Snail(w, Z, Cc, EJ, CJ, wJ)
min_phi = 0*2*pi
max_phi = 1*2*pi
Npts = 1
phiVec = np.linspace(min_phi, max_phi, Npts)
ng_sweep = np.linspace(-1, 1, 21)
Xi2 = np.zeros((3, len(phiVec)))
Xi3 = np.zeros((4, len(phiVec)))
Xi4 = np.zeros((4, len(phiVec)))
check_Xi2 = np.zeros((4, len(phiVec)))
Xi_pa2pb = np.zeros(len(phiVec))
Xi_ac = np.zeros(len(phiVec))
Xi_bc = np.zeros(len(phiVec))
resx = np.zeros(len(phiVec))
resy = np.zeros(len(phiVec))
#Plot potential
if 1==0:
fig, ax = plt.subplots(figsize = (12,12))
ax.set_xlabel(r'$\varphi_r$', fontsize = fs)
ax.set_ylabel(r'$\varphi_s$', fontsize = fs)
min_i = 0
max_i = 10
def update(i):
Phi_ext = np.linspace(0,2*np.pi, max_i-min_i)
phi_ext= Phi_ext[i]
U = c.get_U(phi_ext_0=phi_ext)
shape=(40,20)
Ps = np.linspace(-8*np.pi, 8*np.pi, shape[0])
Pr = np.linspace(-8*np.pi, 8*np.pi, shape[1])
U_color = np.empty(shape)
for ii, ps in enumerate(Ps):
for jj, pr in enumerate(Pr):
U_color[ii, jj] = U(np.array([ps, pr]))
ax.pcolor(Pr, Ps, U_color, vmin=vmin, vmax=vmax)
return ax
# move_figure(fig, -1900, 10)
anim = FuncAnimation(fig, update, frames=np.arange(min_i, max_i), interval=200)
# if len(sys.argv) > 1 and sys.argv[1] == 'save':
anim.save('line.html', dpi=80, writer='imagemagick')
# Get freqs and Kerrs v.s. flux
if 1==1:
for kk, xx in enumerate(phiVec):
_res = c.get_freqs_kerrs(phi_ext_0=xx)
res1, res2, Xi2s, Xi3s, Xi4s, Xi_p = _res
Xi2[:, kk] = Xi2s
# Xi3[:, kk] = Xi3s
# Xi4[:, kk] = Xi4s
# Xi_pa2pb[kk] = Xi_p[0]
# Xi_ac[kk] = 4*Xi_p[1]
# Xi_bc[kk] = 4*Xi_p[2]
# resx[kk] = res1[0]
# resy[kk] = res1[1]
# PLOT
if 1==1:
# fig0, ax0 = plt.subplots(figsize=(12,6))
# ax0.plot(phiVec/2/pi, Xi2[0,:]/1e9, '.', label= 'f0')
# ax0.plot(phiVec/2/pi, Xi2[1,:]/1e9, '.', label= 'f1')
# ax0.plot(phiVec/2/pi, Xi2[2,:]/1e9, '.', label= 'f2')
# ax0.legend()
# ax0.set_ylabel('GHz')
print('\nf0 = %.3f GHz\n'%(Xi2[0,:]/1e9)+'f1 = %.3f GHz\n'%(Xi2[1,:]/1e9)+'f2 = %.3f GHz\n'%(Xi2[2,:]/1e9))
#
# fig, ax = plt.subplots(4, 4, figsize=(16,8))
# ax[0,0].plot(phiVec/2/pi, Xi2[0,:]/1e9, '.', label= 'f0')
# ax[1,0].plot(phiVec/2/pi, Xi2[1,:]/1e9, '.', label= 'f1')
# ax[2,0].plot(phiVec/2/pi, Xi2[2,:]/1e9, '.', label= 'f2')
# ax[3,0].plot(phiVec/2/pi, Xi2[3,:]/1e9, '.', label= 'f3')
# ax[0,0].set_title('freq')
#
# ax[0,0].legend()
# ax[1,0].legend()
# ax[2,0].legend()
# ax[3,0].legend()
#
# ax[0,1].plot(phiVec/2/pi, Xi3[0,:]/1e6)
# ax[1,1].plot(phiVec/2/pi, Xi3[1,:]/1e6)
# ax[2,1].plot(phiVec/2/pi, Xi3[2,:]/1e6)
# ax[3,1].plot(phiVec/2/pi, Xi3[3,:]/1e6)
# ax[0,1].set_title('c3')
#
# ax[0,2].plot(phiVec/2/pi, Xi4[0,:]/1e6)
# ax[1,2].plot(phiVec/2/pi, Xi4[1,:]/1e6)
# ax[2,2].plot(phiVec/2/pi, Xi4[2,:]/1e6)
# ax[3,2].plot(phiVec/2/pi, Xi4[3,:]/1e6)
# ax[0,2].set_title('c4')
#
# fig2, ax2 = plt.subplots(2,2, figsize=(16,8))
# ax2[0,0].plot(phiVec/2/pi, Xi_pa2pb/1e6, '.', label= '$a^2b^{+}$')
#
# dXi_pa2pb=np.diff(Xi_pa2pb)/(phiVec[1]-phiVec[0])*pi/10
# dphiVec = (phiVec[1:]+phiVec[:-1])/2
#
# ax2[0,0].plot(dphiVec/2/pi, dXi_pa2pb/1e6, '.', label= r'$\frac{\pi}{10}*da^2b^{+}$')
# ax2[0,0].legend()
# ax2[0,0].set_ylabel('MHz')
#
# Xi4_1 = (Xi4[1,1:]+Xi4[1,:-1])/2
# ax2[1,0].plot(dphiVec/2/pi, Xi4_1/1e6, '.', label= '$a^2a^{+2}$')
# ax2[1,0].plot([min(dphiVec/2/pi), max(dphiVec/2/pi)], [0,0])
# ax2[1,0].legend()
# ax2[1,0].set_ylabel('MHz')
#
# ax2[1,1].plot(phiVec/2/pi, Xi_ac/1e6, '.', label= r'$a^{+}ac^{+}c$')
# ax2[1,1].plot(phiVec/2/pi, Xi_bc/1e6, '.', label= r'$b^{+}bc^{+}c$')
# ax2[1,1].legend()
#
# ax2[0,1].plot(dphiVec/2/pi, dXi_pa2pb/Xi4_1, '.', label= '$a^2b^{+}/a^2a^{+2}$')
## ax[3,1].plot(phiVec/2/pi, Xi4[1,:]/1e6, label= '$b^2b^{+2}$')
# ax2[0,1].legend()
# ax[0,2].plot(phiVec/2/pi, Xi4[0,:]/1e6)
# ax[1,2].plot(phiVec/2/pi, Xi2[1,:]/1e9)
# ax[0,2].plot(np.array([min_phi, max_phi])/2/np.pi, [0,0])
# ax[1,2].plot(np.array([min_phi, max_phi])/2/np.pi, [0,0])
#
# fmin = min(Xi2[1,:]/1e9)
# fmax = max(Xi2[1,:]/1e9)
## ax[0,0].set_ylim([4, 8])
# ax[1,3].semilogy(Xi2[1,:]/1e9, np.abs(Xi3[1,:]/Xi4[1,:]))
# ax[1,3].semilogy([fmin, fmax], [10,10])
# ax[1,3].semilogy([fmin, fmax], [100,100])
# #ax[1,3].set_ylim([5,np.max(np.abs(Xi3[1,:]/Xi4[1,:]))])
#
# ax[0,0].set_title('frequency (GHz)')
# ax[0,1].set_title('$a^2a^{\dag}$ (MHz)')
# ax[0,2].set_title('$a^2a^{\dag 2}$ (MHz)')
# ax[0,3].set_title('$a^2a^{\dag}/a^2a^{\dag 2}$')
# ax[0,0].set_ylabel('Resonator')
# ax[1,0].set_ylabel('Plasma')
# fig2, ax2 = plt.subplots(2)
# ax2[0].scatter(k[1,:]/1e9, k[0,:]/1e9, 10, label='0 photon')
# ax2[0].scatter(k[1,:]/1e9+Xi4[3, :]/1e9, k[0,:]/1e9+Xi22[:]/1e9, 10, label='1 photon')
# ax2[0].scatter(wb/2/pi/1e9, wa/2/pi/1e9, marker='x')
# ax2[0].set_ylabel('MEMORY freq (GHz)')
# ax2[0].set_xlabel('BUFFER freq (GHz)')
# ax2[1].plot(phi_ext_sweep*BL/2/pi, k[1,:]/1e9, label='0 photon')
# ax2[1].plot(phi_ext_sweep*BL/2/pi, k[1,:]/1e9+Xi4[3, :]/1e9, label='1 photon')
# ax2[1].legend()
# ax2[0].legend()
if 1==0:
Nx = 21
Uab0 = np.zeros((Nx, Nx))
Uab = np.zeros((Nx, Nx))
Uac0 = np.zeros((Nx, Nx))
Uac = np.zeros((Nx, Nx))
Ubc0 = np.zeros((Nx, Nx))
Ubc = np.zeros((Nx, Nx))
Tab0 = np.zeros((Nx, Nx))
Tab = np.zeros((Nx, Nx))
Tac0 = np.zeros((Nx, Nx))
Tac = np.zeros((Nx, Nx))
Tbc0 = np.zeros((Nx, Nx))
Tbc = np.zeros((Nx, Nx))
phi_ext_s_0 = np.pi/2
phi_ext_l_0 = np.pi
U = c.get_U(phi_ext_s_0=phi_ext_s_0, phi_ext_l_0=phi_ext_l_0)
T = c.get_T(phi_ext_s_0=phi_ext_s_0, phi_ext_l_0=phi_ext_l_0)
res1, res2, P, U2 = c.get_normal_mode_frame(phi_ext_s_0=phi_ext_s_0,
phi_ext_l_0=phi_ext_l_0)
x1, _y, _z = (nl.inv(P)).dot(np.array([np.pi, 0, 0]))
_x, y1, _z = (nl.inv(P)).dot(np.array([0, np.pi, 0]))
x_grid = np.linspace(-x1, x1, Nx)
x_grid0 = np.linspace(-np.pi, np.pi, Nx)
y_grid = np.linspace(-x1, x1, Nx)
y_grid0 = np.linspace(-np.pi, np.pi, Nx)
for ikk, kk in enumerate(x_grid):
for iii, ii in enumerate(y_grid):
Uab[ikk, iii] = U(np.array([kk, ii, 0]), P=P)
Uac[ikk, iii] = U(np.array([kk, 0, ii]), P=P)
Ubc[ikk, iii] = U(np.array([0, kk, ii]), P=P)
Tab[ikk, iii] = T(np.array([kk, ii, 0]), P=P)
Tac[ikk, iii] = T(np.array([kk, 0, ii]), P=P)
Tbc[ikk, iii] = T(np.array([0, kk, ii]), P=P)
# Tbc[ikk, iii] = T(np.array([0, 1e8*kk,1e8*ii]), P=nl.inv(P))
for ikk, kk in enumerate(x_grid0):
for iii, ii in enumerate(y_grid0):
Uab0[ikk, iii] = U(np.array([kk, ii, 0]))
Uac0[ikk, iii] = U(np.array([kk, 0, ii]))
Ubc0[ikk, iii] = U(np.array([0, kk, ii]))
Tab0[ikk, iii] = T(np.array([kk, ii, 0]))
Tac0[ikk, iii] = T(np.array([kk, 0, ii]))
Tbc0[ikk, iii] = T(np.array([0, kk, ii]))
# Tbc0[ikk, iii] = T(np.array([kk, 0, ii]))
fig2, ax2 = plt.subplots(2,3)
ax2[0,0].pcolor(x_grid0, y_grid0, Uab0)
ax2[1,0].pcolor(x_grid, y_grid, Uab)
ax2[0,1].pcolor(x_grid0, y_grid0, Uac0)
ax2[1,1].pcolor(x_grid, y_grid, Uac)
ax2[0,2].pcolor(x_grid0, y_grid0, Ubc0)
ax2[1,2].pcolor(x_grid, y_grid, Ubc)
ax2[0,0].axis('equal')
ax2[0,1].axis('equal')
ax2[1,0].axis('equal')
ax2[1,1].axis('equal')
ax2[0,2].axis('equal')
ax2[1,2].axis('equal')
fig3, ax3 = plt.subplots(2,3)
ax3[0,0].pcolor(x_grid0, y_grid0, Tab0)
ax3[1,0].pcolor(x_grid, y_grid, Tab)
ax3[0,1].pcolor(x_grid0, y_grid0, Tac0)
ax3[1,1].pcolor(x_grid, y_grid, Tac)
ax3[0,2].pcolor(x_grid0, y_grid0, Tbc0)
ax3[1,2].pcolor(x_grid, y_grid, Tbc)
ax3[0,0].axis('equal')
ax3[0,1].axis('equal')
ax3[1,0].axis('equal')
ax3[1,1].axis('equal')
ax3[0,2].axis('equal')
ax3[1,2].axis('equal')
#ax2[1].plot(phi_ext_sweep/np.pi, gradUval_)
if 1==0:
fig, ax = plt.subplots(3, figsize=(12,8), sharex=True)
a=0.755e-3/3
ax[0].plot(a*phi_ext_sweep/np.pi, f[0,:]/1e9)
ax[1].plot(a*phi_ext_sweep/np.pi, f[1,:]/1e9)
ax[2].plot(a*phi_ext_sweep/np.pi, f[2,:]/1e9)
### data ###
folder = r'../no_squid/analyzed_data/'
filename_readout = r'sweep_DC_specVNA_DC2_in2outC_004.dat_'
readout_freq = np.load(folder+filename_readout+'freq.npy')
readout_flux = np.load(folder+filename_readout+'flux.npy')
filename_buffer = r'sweep_DC_specVNA_DC2_in4outD_003.dat_'
buffer_freq = np.load(folder+filename_buffer+'freq_fit.npy')
buffer_flux = np.load(folder+filename_buffer+'flux.npy')
filename_mem = r'VNA_sweep_DC_sweep_pump_freq_DC2_in2_outC_pump6_002.dat_'
mem_freq = np.load(folder+filename_mem+'freq_fit.npy')
mem_flux = np.load(folder+filename_mem+'flux.npy')
offs = 1.2e-4
ax[0].plot(mem_flux+1e-4-offs, mem_freq, 'o')
ax[1].plot(buffer_flux+1e-4- offs, buffer_freq, 'o')
ax[2].plot(readout_flux-offs, readout_freq/1e9, 'o')
ax[2].set_xlabel('DC (V)')
ax[0].set_ylabel('mem freq')
ax[1].set_ylabel('buff freq')
ax[2].set_ylabel('readout freq')
#fa = []
#fb = []
#
#for phi_ext_s in phi_ext_sweep:
# H = c.getH_overhbar_two_mode(phi_ext_l=phi_ext_s)
# E = H.eigenenergies()
# fa.append(E[1]-E[0])
# fb.append(E[2]-E[0])
#
#fig, ax = plt.subplots()
#ax.plot(phi_ext_sweep/np.pi, [f/2/np.pi/1e9 for f in fa])
#ax.plot(phi_ext_sweep/np.pi, [f/2/np.pi/1e9 for f in fb])
#c.pltElevels('phi_ext_s', phi_ext_sweep,
# phiVec=np.linspace(-pi, pi, 101),
# phi_ext_s_0=0, phi_ext_l_0=0, n_g_0=0)
#
# c.pltElevels('n_g', ng_sweep,
# phiVec=np.linspace(-pi, pi, 101),
# phi_ext_s_0=pi, phi_ext_l_0=0, n_g_0=0)
#fig, ax = plt.subplots()
#for ii in range(len(phi_ext_sweep)):
# ax.plot((np.diff(Elevels[ii,:])[0:298]/1e9/2/np.pi))
#ax.plot((np.diff(Elevels[0,:])[0:70]/1e9/2/np.pi))
#for ii in range(29):
# ax.plot(np.diff(Elevels)[:,ii]/1e9/2/np.pi)