def measureSCurve(self,voltages = None,ntimes = 40,microwaveOff = True):
self.notify("status","Measuring S curve...")
def getVoltageBounds(v0,jba,variable,ntimes):
v = v0
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = ntimes)
p = jba._acqiris.Psw()[variable]
while p > 0.03 and v < v0*2.0:
v*=1.05
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = ntimes)
p = jba._acqiris.Psw()[variable]
vmax = v
v = v0
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = ntimes)
p = jba._acqiris.Psw()[variable]
while p < 0.98 and v > v0/2.0:
v/=1.05
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = ntimes)
p = jba._acqiris.Psw()[variable]
vmin = v
return (vmin*0.95,vmax*1.2)
try:
v0 = self.voltage()
state = self._qubitmwg.output()
self._attenuator.turnOn()
data = Datacube("S Curve")
dataManager = DataManager()
dataManager.addDatacube(data)
if microwaveOff:
self._qubitmwg.turnOff()
if voltages == None:
self.notify("status","Searching for proper voltage range...")
(vmin,vmax) = getVoltageBounds(v0,self,self._params["variable"],ntimes)
voltages = arange(vmin,vmax,0.005)
self.notify("status","Measuring S curve in voltage range [%g - %g]..." % (vmin,vmax))
for v in voltages:
self.setVoltage(v)
self._acqiris.bifurcationMap(ntimes = ntimes)
data.set(v = v)
data.set(**(self._acqiris.Psw()))
data.commit()
self.notify("sCurve",(data.column("v"),data.column(self._params["variable"])))
finally:
self.notify("status","S curve complete.")
self.setVoltage(v0)
if state:
self._qubitmwg.turnOn()
##Imports...
import sys
from quantum.qulib import *
from quantum.plotting import *
from numpy.linalg import norm
from pyview.helpers.datamanager import DataManager
from pyview.lib.datacube import *
from pyview.gui.datamanager import startDataManager
import matplotlib
matplotlib.use("module://pyview.gui.mpl.backend_static")
from matplotlib.pylab import *
dataManager = DataManager()
startDataManager()
def integrate(rho, L, ts, dt=0.1):
t = 0
rhos = zeros((len(ts), rho.shape[0], rho.shape[1]), dtype=complex128)
def rungeKuttaIntegrate(rho, L, t, dt):
L2 = L(t + dt / 2.)
k1 = dt * L(t) * rho
k2 = dt * L2 * (rho + k1 / 2.)
k3 = dt * L2 * (rho + k2 / 2.)
k4 = dt * L(t + dt) * (rho + k3 / 2.)
return rho + 1. / 6. * (k1 + 2. * k2 + 2. * k3 + k4)
xlabel("fluxline I voltage [V]")
ylabel("drive frequency [GHz]")
plot(vs,ees[:,2]-ees[:,0],color = 'white',lw = 2,ls = 'solid')
plot(vs,ees[:,1]-ees[:,0],color = 'white',lw = 2,ls = 'solid')
xlim(1.26,1.29)
ylim(5.1,5.15)
figtext(0.02,0.02,gv.survey.filename()[:-4])
figtext(0.02,0.95,"$g = %g Mhz$\ncrosstalk = %g %%" % (g*1000,crosstalk * 100))
show()
##
from pyview.helpers.datamanager import DataManager
dataManager = DataManager()
fit = Datacube("fit")
dataManager.addDatacube(fit)
for i in range(0,len(gv.survey)):
fit.set(i= i,flux = gv.survey["flux"][i])
j = argmin(abs(vs-gv.survey["flux"][i]))
fqb1 = real(ees[j,2]-ees[j,0])
fqb2 = real(ees[j,1]-ees[j,0])
print gv.survey["flux"][i],vs[j]
import scipy.optimize
import numpy.linalg
fitfunc = lambda p, x: 1./math.pi*p[0]/((x-p[1])*(x-p[1])/p[3]/p[3]+1)+p[2]+1./math.pi*p[4]/((x-p[5])*(x-p[5])/p[6]/p[6]+1) # Target function
##curve
from config.instrumentsRSV import *
from matplotlib.pyplot import *
#from pyview.gui.mpl.backend import figure
import numpy
import scipy
from pyview.helpers.datamanager import DataManager
dataManager = DataManager()
instrumentManager=Manager()
vna=instrumentManager.getInstrument('vna')
print vna
coilVoltage=instrumentManager.getInstrument('Yoko1')
print coil
##
def setMyVNAPower(power):
atten=-20*math.modf(power/20.)[1]
pow=power+atten-5
vna.setAttenuation(atten)
vna.setPower(pow)
##
data=Datacube('VNAvsCoil1')
dataManager.addDatacube(data)
k=0
voltages=arange(-3,0.1,0.05)
for voltages in voltages:
print "voltages=%f V"%voltages
coilVoltage.setVoltage(voltages)
#time.sleep(4)
child=vna.getTrace(waitFullSweep=True)
def toDataManager(self): dataManager = DataManager() dataManager.addDatacube(self)
rhoMatData.setAt(i,errorimage=0)
if rhoMatData.column("errorimage")[i]!=1:
print "Plotting..."
try:
plotDensityMatrix(densityMatrix,export="film of swap/rhomats/rhomat_%.3d.png" % i,figureTitle = "t = %g ns" % rhoMatData.column("duration")[i])#,figureName="phibell = %s" % str(phibell))
except:
print "Failed!"
print sys.exc_info()
rhoMatData.setAt(i,errorimage=1)
rhoMatData.savetxt()
##
##
from pyview.helpers.datamanager import DataManager
dataManager = DataManager()3
##
phi_wit=Datacube()
dataManager.addDatacube(phi_wit)
phi_wit.setName("phi_wit")
phi_wit.createColumn("zPulseLength",real(rhoMatData.column("zPulseLength")))
phi_wit.createColumn("phibell",real(rhoMatData.column("phibell")))
phi_wit.createColumn("w_phi_minus",real(rhoMatData.column("w_phi_minus")))
phi_wit.createColumn("w_phi_plus",real(rhoMatData.column("w_phi_plus")))
phi_wit.savetxt()
##
#chshdata=Datacube()
#chshdata.setName("CHSH from rhoMat theory")
##Imports...
import sys
from quantum.qulib import *
from quantum.plotting import *
from numpy.linalg import norm
from pyview.helpers.datamanager import DataManager
from pyview.lib.datacube import *
from pyview.gui.datamanager import startDataManager
import matplotlib
matplotlib.use("module://pyview.gui.mpl.backend_static")
from matplotlib.pylab import *
dataManager = DataManager()
startDataManager()
def integrate(rho,L,ts,dt = 0.1):
t = 0
rhos = zeros((len(ts),rho.shape[0],rho.shape[1]),dtype = complex128)
def rungeKuttaIntegrate(rho,L,t,dt):
L2 = L(t+dt/2.)
k1 = dt*L(t)*rho
k2 = dt*L2*(rho+k1/2.)
k3 = dt*L2*(rho+k2/2.)
k4 = dt*L(t+dt)*(rho+k3/2.)
return rho+1./6.*(k1+2.*k2+2.*k3+k4)
import matplotlib
matplotlib.use('module://pyview.gui.mpl.backend')
from numpy import *
from matplotlib.pyplot import *
import csv
##
from pyview.lib.datacube import Datacube
from pyview.helpers.datamanager import DataManager
import re
filename = "qubit_chip_sonnet_model.csv"
dataManager = DataManager()
file = open(filename,"rb")
content = file.read()
file.close()
lines = content.split("\n")
curves = Datacube("curves")
dataManager.clear()
dataManager.addDatacube(curves)
i = 0
curve = None
while i < len(lines):
elements = lines[i].split(",")
if re.search("l1=(\d+\.\d+)",lines[i],re.I):
if curve != None and len(curve) == 0:
curves.removeChild(curve)
print lines[i]
lq = float(re.search("l1=(\d+\.\d+)",lines[i],re.I).group(1))
print lq
def measureSCurve(self,voltages = None,ntimes = 10,microwaveOff = True,data=None,fspPower=False,corelations=False,**extraInDatacube):
self.notify("status","Measuring S curve...")
def getVoltageBounds(v0,jba,variable,ntimes):
return (0.5,5)
v = v0
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = ntimes)
p = jba._acqiris.Psw()[variable]
while p > 0.03 and v < v0*2.0:
v*=1.05
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = ntimes)
p = jba._acqiris.Psw()[variable]
vmax = v
v = v0
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = ntimes)
p = jba._acqiris.Psw()[variable]
while p < 0.98 and v > v0/2.0:
v/=1.05
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = ntimes)
p = jba._acqiris.Psw()[variable]
vmin = v
return (vmin*0.95,vmax*1.2)
if fspPower:
self._pulseGenerator._mixer._fsp.setFrequency(self._frequency)
if data==None:
data = Datacube("%s S Curve - f=%f" %(self.name(),self._frequency))
dataManager = DataManager()
dataManager.addDatacube(data)
else:
data.setName("%s S Curve - f=%f" %(self.name(),self._frequency))
if voltages==None:
bounds=[self._vMaxAmplitude-2*max(self._vMaxAmplitude/5,abs(self._sCurveParams[0])),self._vMaxAmplitude+2*max(self._vMaxAmplitude/5,abs(self._sCurveParams[0]))]
voltages=linspace(bounds[0],bounds[1],200)
try:
for v in voltages:
self.setAmplitude(v)
data.set(v = v)
d=self.measure(nLoops=ntimes)
#d=self.getThisMeasure()
data.set(**d[1])
if corelations:
data.set(**d[4])
data.set(**extraInDatacube)
if fspPower:
time.sleep(1)
data.set(fspPower=self._pulseGenerator._mixer._fsp.getValueAtMarker())
#self.notify("histograms",d[2][self.bit][0])
#self.notify("iqdata",(d[2][self.bit][0],d[2][self.bit][1]))
##self.notify("iqP",(d[0][:,0],d[0][:,1],((0,0,0))))
data.commit()
#self.notify("sCurve",(data.column("v"),data.column("b%i"%self.bit)))
data.createColumn("p-0.5",abs(data["b%i"%self.bit]-0.5))
data.sortBy("p-0.5")
self._p50fromS=data['v'][0]
data.sortBy('v')
#data.sortBy("b%i"%self.bit)
#p=data["b%i"%self.bit]
#v=data['v']
#p=p[p>0]
#v=v[p>0]
##p=p[p<1]
#v=v[p<1]
#self.sInterpolateVP=scipy.interpolate.interp1d(p,v)
#data.sortBy('v')
except:
raise
finally:
data.savetxt()
self.notify("status","S curve complete.")
self.setAmplitude(self._vMaxAmplitude)
return data
ylabel("drive frequency [GHz]")
plot(vs, ees[:, 2] - ees[:, 0], color='white', lw=2, ls='solid')
plot(vs, ees[:, 1] - ees[:, 0], color='white', lw=2, ls='solid')
xlim(1.26, 1.29)
ylim(5.1, 5.15)
figtext(0.02, 0.02, gv.survey.filename()[:-4])
figtext(0.02, 0.95,
"$g = %g Mhz$\ncrosstalk = %g %%" % (g * 1000, crosstalk * 100))
show()
##
from pyview.helpers.datamanager import DataManager
dataManager = DataManager()
fit = Datacube("fit")
dataManager.addDatacube(fit)
for i in range(0, len(gv.survey)):
fit.set(i=i, flux=gv.survey["flux"][i])
j = argmin(abs(vs - gv.survey["flux"][i]))
fqb1 = real(ees[j, 2] - ees[j, 0])
fqb2 = real(ees[j, 1] - ees[j, 0])
print gv.survey["flux"][i], vs[j]
import scipy.optimize
import numpy.linalg
fitfunc = lambda p, x: 1. / math.pi * p[0] / (
##Imports... import sys from quantum.qulib import * from quantum.plotting import * import matplotlib from scipy.optimize import fmin_powell from numpy.linalg import norm from pyview.helpers.datamanager import DataManager from pyview.gui.datamanager import startDataManager dataManager = DataManager() ##Parameter definitions... alpha = -2.0*math.pi*0.24 beta = -2.0*math.pi*0.24 gamma10_1 = 0*1.0/353.4 gamma10_2 = 0*1.0/368.7 gammaphi10_1 = 0*1.0/500.0 gammaphi10_2 = 0*1.0/650.0 ##Some more definitions... sm10 = matrix([[0,1,0],[0,0,0],[0,0,0]]) sp10 = matrix([[0,0,0],[1,0,0],[0,0,0]]) sm21 = matrix([[0,0,0],[0,0,1],[0,0,0]]) sp21 = matrix([[0,0,0],[0,0,0],[0,1,0]]) sm20 = matrix([[0,0,1],[0,0,0],[0,0,0]]) sp20 = matrix([[0,0,0],[0,0,0],[1,0,0]]) id3 = matrix([[1,0,0],[0,1,0],[0,0,1]]) sz10 = matrix([[1,0,0],[0,-1,0],[0,0,0]])
def measureSCurve(self,voltages = None,nLoops = 5,microwaveOff = True,data=None,fspPower=False,corelations=False,**extraInDatacube):
self.notify("status","Measuring S curve...")
def getVoltageBounds(v0,jba,variable,ntimes):
return (0.5,5)
v = v0
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = nLoops)
p = jba._acqiris.Psw()[variable]
while p > 0.03 and v < v0*2.0:
v*=1.05
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = nLoops)
p = jba._acqiris.Psw()[variable]
vmax = v
v = v0
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = nLoops)
p = jba._acqiris.Psw()[variable]
while p < 0.98 and v > v0/2.0:
v/=1.05
jba.setVoltage(v)
jba._acqiris.bifurcationMap(ntimes = nLoops)
p = jba._acqiris.Psw()[variable]
vmin = v
return (vmin*0.95,vmax*1.2)
if fspPower:
self._pulseGenerator._mixer._fsp.setFrequency(self._frequency)
if data==None:
data = Datacube("%s S Curve - f=%f" %(self.name(),self._frequency))
dataManager = DataManager()
dataManager.addDatacube(data)
else:
data.setName("%s S Curve - f=%f" %(self.name(),self._frequency))
if voltages==None:
bounds=[self.center-self.width*1,self.center+self.width*1]
# voltages=linspace(bounds[0],bounds[1],200)
voltages=SmartLoop(bounds[0],(bounds[1]-bounds[0])/50, bounds[1], name="Scurve voltages")
print "entering in loop"
try:
for v in voltages:
print "voltage :",v
self.setAmplitude(v)
data.set(v = v)
print "measuring"
d=self.measure(nLoops=nLoops)
print "got point"
#d=self.getThisMeasure()
#data.set(**d[1])
data.set(**d[-1])
print "in datacube"
#data.set(**extraInDatacube)
print "extra in datacube"
if fspPower:
time.sleep(1)
data.set(fspPower=self._pulseGenerator._mixer._fsp.getValueAtMarker())
#self.notify("histograms",d[2][self.bit][0])
#self.notify("iqdata",(d[2][self.bit][0],d[2][self.bit][1]))
##self.notify("iqP",(d[0][:,0],d[0][:,1],((0,0,0))))
print "commiting"
data.commit()
print "commited"
#self.notify("sCurve",(data.column("v"),data.column("b%i"%self.bit)))
print "first loop over"
#data.sortBy('v')
#data.sortBy("b%i"%self.bit)
#p=data["b%i"%self.bit]
#v=data['v']
#p=p[p>0]
#v=v[p>0]
##p=p[p<1]
#v=v[p<1]
#self.sInterpolateVP=scipy.interpolate.interp1d(p,v)
#data.sortBy('v')
print "first loop over"
except:
raise
finally:
data.savetxt()
self.notify("status","S curve complete.")
self.setAmplitude(self._vMaxAmplitude)
return data
##Imports... import sys from quantum.qulib import * from quantum.plotting import * import matplotlib from scipy.optimize import fmin_powell from numpy.linalg import norm from pyview.helpers.datamanager import DataManager from pyview.gui.datamanager import startDataManager dataManager = DataManager() ##Parameter definitions... alpha = -2.0 * math.pi * 0.24 beta = -2.0 * math.pi * 0.24 gamma10_1 = 0 * 1.0 / 353.4 gamma10_2 = 0 * 1.0 / 368.7 gammaphi10_1 = 0 * 1.0 / 500.0 gammaphi10_2 = 0 * 1.0 / 650.0 ##Some more definitions... sm10 = matrix([[0, 1, 0], [0, 0, 0], [0, 0, 0]]) sp10 = matrix([[0, 0, 0], [1, 0, 0], [0, 0, 0]]) sm21 = matrix([[0, 0, 0], [0, 0, 1], [0, 0, 0]]) sp21 = matrix([[0, 0, 0], [0, 0, 0], [0, 1, 0]]) sm20 = matrix([[0, 0, 1], [0, 0, 0], [0, 0, 0]]) sp20 = matrix([[0, 0, 0], [0, 0, 0], [1, 0, 0]]) id3 = matrix([[1, 0, 0], [0, 1, 0], [0, 0, 1]]) sz10 = matrix([[1, 0, 0], [0, -1, 0], [0, 0, 0]])