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from numpy import *
from os import path, listdir
import plotly.plotly as py
from plotly.graph_objs import *
from plotly.offline import download_plotlyjs, init_notebook_mode, iplot
from myfunctions import analyze, plotS21
from plotlylayouts import *
First, let's find map out the dispersive shift due to the fixed qubit with the tunable qubit not biased.
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def plot_disp_shift(sample, show=False):
datapath = '\\\\128.230.72.36\labshare\Experiments\JPM\\' + sample
files = listdir(datapath)
data = []
layout, trace = spectrumPlot(title="Dispersive shift of " + sample)
for f in files:
if f.endswith('.s2p'):
result = analyze(path.join(datapath, f), show=show);
data.append(Scatter(
x = result['freq'],
y = result['dBm'],
name = f))
descr = "$F_0 = " + str(round(result['f0']/1e9, 6)) + "\\text{GHz}\quad "
descr = descr + "Q = " + str(round(result['Q'], 3)) + "\quad "
descr = descr + "\kappa = " + str(round(result['kappa']/(2*pi*1e6), 3)) + "\\text{MHz}$"
layout['annotations'].append(dict(
text=descr,
x=result['f0'],
y=max(result['dBm']),
xref='x',
yref='y'))
fig = Figure(data=data, layout=layout)
iplot(fig)
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plot_disp_shift("CH002_2")
Now let's look at the resonant frequency at various flux points to look for periodicity in resonance frequency.
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sample = "CH002_2\\flux"
datapath = '\\\\128.230.72.36\labshare\Experiments\JPM\\' + sample
files = listdir(datapath)
volts = []
freqs = []
errors = []
for f in files:
if f.endswith('.s2p'):
volt = float(path.splitext(f)[0])
volts.append(volt)
result = analyze(path.join(datapath, f), show=False)
freqs.append(result['f0'])
errors.append(result['f0err'])
layout = dict(
title="Flux Tuning",
xaxis=dict(title="Volts at SRS"),
yaxis=dict(title="Resonant Frequency (GHz)")
)
data = Scatter(
x=volts,
y=freqs,
mode='markers',
error_y=dict(
type='data',
array=errors,
visible=True
)
)
fig = Figure(data=[data], layout=layout)
iplot(fig)
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plot_disp_shift("CH003-Cooldown3")
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sample = "CH003-Cooldown3\Flux-45dBm"
datapath = '\\\\128.230.72.36\labshare\Experiments\JPM\\' + sample
files = listdir(datapath)
volts = []
freqs = []
errors = []
for f in files:
if f.endswith('.s2p'):
volt = float(path.splitext(f)[0])
volts.append(volt)
result = analyze(path.join(datapath, f), show=False)
freqs.append(result['f0'])
errors.append(result['f0err'])
layout = dict(
title="Flux Tuning of CH003",
xaxis=dict(title="Volts at SRS"),
yaxis=dict(title="Resonant Frequency (GHz)")
)
data = Scatter(
x=volts,
y=freqs,
mode='markers',
error_y=dict(
type='data',
array=errors,
visible=True
)
)
fig = Figure(data=[data], layout=layout)
iplot(fig)
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sample = "CH002-Cooldown3\Flux-60dBm2"
datapath = '\\\\128.230.72.36\labshare\Experiments\JPM\\' + sample
files = listdir(datapath)
volts = []
freqs = []
errors = []
for f in files:
if f.endswith('.s2p'):
volt = float(path.splitext(f)[0])
volts.append(volt)
result = analyze(path.join(datapath, f), show=False)
freqs.append(result['f0'])
errors.append(result['f0err'])
layout = dict(
title="Flux Tuning of CH002",
xaxis=dict(title="Volts at SRS"),
yaxis=dict(title="Resonant Frequency (GHz)")
)
data = Scatter(
x=volts,
y=freqs,
mode='markers',
error_y=dict(
type='data',
array=errors,
visible=True
)
)
fig = Figure(data=[data], layout=layout)
iplot(fig)
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