cb.set_label('Noise (dB)')
#plot(pilier.freq, len(pilier.freq)*[1.], ':k')
show()
"""
figure('Optimize input coupler', figsize=(14, 10))
ax = gca()
input_transmissions = linspace(1e-6,150e-6, 100)
intra_powers = linspace(0.05, 500, 100)
#pilier.freq = linspace(3.99e6, 4.01e6, 100)
pilier.freq = array([4e6])
pilier.delta_hz = 0
plt.subplots_adjust(left=0.05, bottom=0.4)
axcolor = 'lightgoldenrodyellow'
axfreq = plt.axes([0.25, 0.1, 0.65, 0.03], axisbg=axcolor)
axamp = plt.axes([0.25, 0.15, 0.65, 0.03], axisbg=axcolor)
axtemp = plt.axes([0.25, 0.2, 0.65, 0.03], axisbg=axcolor)
axlength = plt.axes([0.25, 0.25, 0.65, 0.03], axisbg=axcolor)
temp = Slider(axtemp,
'Temp.',
0.,
10.,
valinit=1.,
o.n_photons = 1.1e8
o.freq = linspace(1.5e6, 1.56e6, 1000)
#o.right.output._get_losses = lambda:
if True:
figname = 'PRX Regal fig1'
close(figname)
figure(figname, figsize=(15,10))
dets = (3e3, 6e3, 13e3, 20e3)
for index, delta_hz in enumerate(dets):
subplot(len(dets),2,2*index+1)
o.delta_hz = delta_hz
o.n_photons = 1.1e8
title("$\Delta/2\pi$ = " + str(delta_hz) + ' hz')
ylabel('Intensity noise (vacua)')
plot(o.freq, abs(o.right.output.spectrum_sym(0)))
ylim(0.6,1.2)
xlabel('Frequency (Hz)')
subplot(122)
dets = linspace(0, 3000e3, 10)
opts = []
opts_all_quad = []
for det in dets:
o.delta_hz = det
o = OmR()
o.set_params(m=6.75e-12,
f_mech=1e6,
q=1000.,
lambda_nm = 1064.,
losses=1.e-6,
transmission_input=300e-6,
length=0.00764,
i_incident=1e-3,
delta_hz=1.)
tau = 1./(2*pi*1.7e6)
o.tau_in = tau/0.4
o.tau_ex = tau/0.6
o.n_th = 0
o.freq = linspace(0.99e6, 1.01e6, 400)
o.delta_hz = 0
figure('SB asymmetry on resonance', figsize=(10,13))
subplot(211)
o.n_th = 0
o.cooperativity = 0.1
title('Cooperativity = 0.1, n_th = 0')
plot(o.freq, o.right.output.spectrum_ss('upper'), '-r', label='Upper sideband')
plot(o.freq, o.right.output.spectrum_ss('lower'), '-b', label='Lower sideband')
xlabel('Frequency (Hz)')
ylabel('Single sided spectrum (Vacua)')
figure('mean_fields_omr', figsize=(12.9, 10.9))
last=None
for index, ((input_trans, out_trans, loss), title_) in enumerate((((1e-6,5e-6, 0), 'undercoupled'),
((5e-6, 5e-6,0), 'critically coupled'),
((5e-6, 0.5e-6,0), 'over coupled'),
((1e-6, 1e-6, 5e-6), 'loss dominated'))):
last = subplot(2, 2 ,index + 1, sharex=last)
cav.transmission_input = input_trans
cav.transmission_output = out_trans
cav.losses = loss
title(title_)
reflected = []
transmitted = []
deltas = linspace(-25*cav.bandwidth_hz, 25*cav.bandwidth_hz, 300)
for delta_hz in deltas:
cav.delta_hz = delta_hz
reflected.append(cav.left.output.mean_field)#/cav.intra.mean_field))
transmitted.append(cav.right.output.mean_field)#/cav.intra.mean_field))
reflected = array(reflected)
transmitted = array(transmitted)
plot(real(reflected), imag(reflected),'o', label='reflected')
plot(real(transmitted), imag(transmitted),'o', label='transmitted')
xlabel('Real')
ylabel('Imag')
legend()
gca().set_aspect('equal')
show()
transmission_output=1e-6,
length=0.0024,
i_incident=2e-4,
temp=300,
delta_hz=1.)
arcizet.freq=linspace(813.e3, 816.e3, 1000)
kappa_hz = arcizet.kappa_hz
name = "Arcizet2006"
figure(name)
for power in array((1.4,2.5,4.5,6.5,9.5)):
shifts = []
cooling = []
phis = linspace(-4,4,100)
arcizet.delta_hz = 0
arcizet.i_intra = power
for index, ph in enumerate(phis): #(0.03, 0.06, 0.09, 0.11, 0.13)):#
arcizet.delta_hz = ph*kappa_hz/2
y = arcizet.right.output.spectrum_sym(pi/2)#dummy_spec()
c = curve.Curve()
c.set_data(Series(abs(y), index=arcizet.freq))
f,a = c.fit('lorentz')
print f.params
shifts.append(f.params['x0'])#arcizet.freq[y.argmax()])
cooling.append(2*f.params['bandwidth'])#y.max())
#gca().set_yscale('log')
subplot(211)
plot(phis, array(shifts) - arcizet.omega_m/(2*pi),label=str(power) + ' W')
xlabel('phi')
ylabel('freq shift (Hz)')
