def profile( sequence, target, **keyword_args ):
"""
Makes a log-log scaling plot of a sequence infidelity relative to a target gate.
"""
# Parse keyword arguments.
if keyword_args.has_key('min_epsilon'):
min_epsilon = keyword_args['min_epsilon']
else:
min_epsilon = -1
if keyword_args.has_key('max_epsilon'):
max_epsilon = keyword_args['max_epsilon']
else:
max_epsilon = 1
if keyword_args.has_key('points'):
points = keyword_args['points']
else:
points = 500.0
if keyword_args.has_key('show'):
show = keyword_args['show']
else:
show = True
if keyword_args.has_key('label'):
label = keyword_args['label']
else:
label = None
if keyword_args.has_key('calculation'):
calculation = keyword_args['calculation']
else:
calculation = 'infidelity'
# Create a set of error amplitudes to measure scaling
dE = max_epsilon - min_epsilon
epsilon = qu.arange( min_epsilon, max_epsilon + dE/points, dE / points )
# Compute matrix representation of target gate
if hasattr( target, 'solve' ):
Ut = target.solve()
else:
Ut = target
# Perform calculation
err = sequence.error.copy()
y = []
for index in range( len(epsilon) ):
e = epsilon[index]
err.error_parameters = [ e ]
sequence.update_error(err)
if calculation == 'infidelity':
y.append( ro.infidelity(sequence.solve() , Ut) )
elif calculation == 'population':
p0 = qu.operator("0,0;0,1")
p1 = qu.operator("1,0;0,0")
U = sequence.solve()
y.append( qu.trace( U*p0*U.H*p1 ) )
if show:
# Create plot
if label == None:
plt.plot( qu.real(epsilon) , qu.real( y ) )
else:
plt.plot( qu.real(epsilon) , qu.real( y ), label = label )
plt.xlabel(r'Systematic Error')
if calculation == 'infidelity':
plt.ylabel(r'Infidelity')
elif calculation == 'population':
plt.ylabel(r'Population')
plt.xlim([min_epsilon, max_epsilon])
plt.show()
else:
# Return data to user
return [ qu.real(epsilon) , qu.real(y) ]
def scaling( sequence, target, **keyword_args ):
"""
Makes a log-log scaling plot of a sequence infidelity relative to a target gate.
"""
# Parse keyword arguments.
if keyword_args.has_key('min_epsilon'):
min_epsilon = keyword_args['min_epsilon']
else:
min_epsilon = 1e-5
if keyword_args.has_key('max_epsilon'):
max_epsilon = keyword_args['max_epsilon']
else:
max_epsilon = 1
if keyword_args.has_key('points'):
points = keyword_args['points']
else:
points = 500.0
if keyword_args.has_key('show'):
show = keyword_args['show']
else:
show = True
if keyword_args.has_key('calculation'):
calculation = keyword_args['calculation']
else:
calculation = 'infidelity'
# Create a set of error amplitudes to measure scaling
log_epsilon = qu.arange( qu.log10(min_epsilon), qu.log10(max_epsilon), \
(qu.log10(max_epsilon) -qu.log10(min_epsilon))/float(points) )
epsilon = []
err = sequence.error.copy()
for index in range( len(log_epsilon) ):
epsilon.append( 10**log_epsilon[index] )
# Compute matrix representation of target gate
try:
Ut = target.solve()
except AttributeError:
Ut = target
# Measure infidelities
y = []
for index in range( len(epsilon) ):
e = epsilon[index]
err.error_parameters = [ e ]
sequence.update_error(err)
if calculation == 'infidelity':
y.append( ro.infidelity(sequence.solve() , Ut) )
elif calculation == 'population':
p0 = qu.operator("0,0;0,1")
p1 = qu.operator("1,0;0,0")
U = sequence.solve()
y.append( qu.trace( U*p0*U.H*p1 ) )
if show:
# Create plot
plt.loglog( qu.real(epsilon) , qu.real( y ) )
plt.xlabel(r'Systematic Error')
if calculation == 'infidelity':
plt.ylabel(r'Infidelity')
elif calculation == 'population':
plt.ylabel(r'Population')
plt.xlim([min_epsilon, max_epsilon])
plt.show()
else:
# Return data to user
return [ qu.real(epsilon) , qu.real(infidelities) ]