import numbers
from collections.abc import Iterable
from copy import deepcopy
import numpy as np
from qutip.qobjevo import QobjEvo
from qutip.qip.operations import expand_operator
from qutip.qobj import Qobj
from qutip.operators import sigmaz, destroy, num
from qutip.qip.pulse import Pulse
__all__ = ["Noise", "DecoherenceNoise", "RelaxationNoise",
"ControlAmpNoise", "RandomNoise", "process_noise"]
def process_noise(pulses, noise_list, dims, t1=None, t2=None,
device_noise=False):
"""
Apply noise to the input list of pulses. It does not modify the input
pulse, but return a new one containing the noise.
Parameters
----------
pulses: list of :class:`.Pulse`
The input pulses, on which the noise object will be applied.
noise_list: list of :class:`.Noise`
A list of noise objects.
dims: int or list
Dimension of the system.
If int, we assume it is the number of qubits in the system.
If list, it is the dimension of the component systems.
t1: list or float, optional
Characterize the decoherence of amplitude damping for
each qubit. A list of size `N` or a float for all qubits.
t2: list of float, optional
Characterize the decoherence of dephasing for
each qubit. A list of size `N` or a float for all qubits.
device_noise: bool
If pulse independent noise such as relaxation are included.
Default is False.
Returns
-------
noisy_pulses: list of :class:`qutip.qip.Pulse`
The noisy pulses, including the system noise.
"""
noisy_pulses = deepcopy(pulses)
systematic_noise = Pulse(None, None, label="systematic_noise")
if (t1 is not None) or (t2 is not None):
noise_list.append(RelaxationNoise(t1, t2))
for noise in noise_list:
if isinstance(noise, (DecoherenceNoise, RelaxationNoise)) \
and not device_noise:
pass
else:
noisy_pulses, systematic_noise = noise._apply_noise(
dims=dims, pulses=noisy_pulses,
systematic_noise=systematic_noise)
if device_noise:
return noisy_pulses + [systematic_noise]
else:
return noisy_pulses
[docs]class Noise(object):
"""
The base class representing noise in a processor.
The noise object can be added to :class:`.Processor` and
contributes to evolution.
"""
def __init__(self):
pass
[docs] def get_noisy_dynamics(self, dims, pulses, systematic_noise):
"""
Return a pulses list added with noise and
the pulse independent noise in a dummy Pulse object.
Parameters
----------
dims: list, optional
The dimension of the components system, the default value is
[2,2...,2] for qubits system.
pulses: list of :class:`.Pulse`
The input pulses, on which the noise object is to be applied.
systematic_noise: :class:`.Pulse`
The dummy pulse with no ideal control element.
Returns
-------
noisy_pulses: list of :class:`.Pulse`
Noisy pulses.
systematic_noise: :class:`.Pulse`
The dummy pulse representing pulse independent noise.
"""
raise NotImplementedError(
"Subclass error needs a method"
"`get_noisy_dynamics` to process the noise.")
def _apply_noise(self, pulses=None, systematic_noise=None, dims=None):
"""
For backward compatibility, in case the method has no return value
or only return the pulse.
"""
result = self.get_noisy_dynamics(
pulses=pulses, systematic_noise=systematic_noise, dims=dims)
if result is None: # in-place change
pass
elif isinstance(result, tuple) and len(result) == 2:
pulses, systematic_noise = result
# only pulse
elif isinstance(result, list) and len(result) == len(pulses):
pulses = result
else:
raise TypeError(
"Returned value of get_noisy_dynamics not understood.")
return pulses, systematic_noise
[docs]class DecoherenceNoise(Noise):
"""
The decoherence noise in a processor. It generates lindblad noise
according to the given collapse operator `c_ops`.
Parameters
----------
c_ops: :class:`qutip.Qobj` or list
The Hamiltonian representing the dynamics of the noise.
targets: int or list, optional
The indices of qubits that are acted on. Default is on all
qubits
coeff: list, optional
A list of the coefficients for the control Hamiltonians.
tlist: array_like, optional
A NumPy array specifies the time of each coefficient.
all_qubits: bool, optional
If `c_ops` contains only single qubits collapse operator,
``all_qubits=True`` will allow it to be applied to all qubits.
Attributes
----------
c_ops: :class:`qutip.Qobj` or list
The Hamiltonian representing the dynamics of the noise.
targets: int or list
The indices of qubits that are acted on.
coeff: list
A list of the coefficients for the control Hamiltonians.
tlist: array_like
A NumPy array specifies the time of each coefficient.
all_qubits: bool
If `c_ops` contains only single qubits collapse operator,
``all_qubits=True`` will allow it to be applied to all qubits.
"""
def __init__(self, c_ops, targets=None, coeff=None, tlist=None,
all_qubits=False):
if isinstance(c_ops, Qobj):
self.c_ops = [c_ops]
else:
self.c_ops = c_ops
self.coeff = coeff
self.tlist = tlist
self.targets = targets
if all_qubits:
if not all([c_op.dims == [[2], [2]] for c_op in self.c_ops]):
raise ValueError(
"The operator is not a single qubit operator, "
"thus cannot be applied to all qubits")
self.all_qubits = all_qubits
[docs] def get_noisy_dynamics(
self, dims=None, pulses=None, systematic_noise=None):
if systematic_noise is None:
systematic_noise = Pulse(None, None, label="system")
N = len(dims)
# time-independent
if (self.coeff is None) and (self.tlist is None):
self.coeff = True
for c_op in self.c_ops:
if self.all_qubits:
for targets in range(N):
systematic_noise.add_lindblad_noise(
c_op, targets, self.tlist, self.coeff)
else:
systematic_noise.add_lindblad_noise(
c_op, self.targets, self.tlist, self.coeff)
return pulses, systematic_noise
[docs]class RelaxationNoise(Noise):
"""
The decoherence on each qubit characterized by two time scales t1 and t2.
Parameters
----------
t1: float or list, optional
Characterize the decoherence of amplitude damping for
each qubit.
t2: float or list, optional
Characterize the decoherence of dephasing for
each qubit.
targets: int or list, optional
The indices of qubits that are acted on. Default is on all
qubits
Attributes
----------
t1: float or list
Characterize the decoherence of amplitude damping for
each qubit.
t2: float or list
Characterize the decoherence of dephasing for
each qubit.
targets: int or list
The indices of qubits that are acted on.
"""
def __init__(self, t1=None, t2=None, targets=None):
self.t1 = t1
self.t2 = t2
self.targets = targets
def _T_to_list(self, T, N):
"""
Check if the relaxation time is valid
Parameters
----------
T: list of float
The relaxation time
N: int
The number of component systems.
Returns
-------
T: list
The relaxation time in Python list form
"""
if (isinstance(T, numbers.Real) and T > 0) or T is None:
return [T] * N
elif isinstance(T, Iterable) and len(T) == N:
return T
else:
raise ValueError(
"Invalid relaxation time T={},"
"either the length is not equal to the number of qubits, "
"or T is not a positive number.".format(T))
[docs] def get_noisy_dynamics(
self, dims=None, pulses=None, systematic_noise=None):
if systematic_noise is None:
systematic_noise = Pulse(None, None, label="system")
N = len(dims)
self.t1 = self._T_to_list(self.t1, N)
self.t2 = self._T_to_list(self.t2, N)
if len(self.t1) != N or len(self.t2) != N:
raise ValueError(
"Length of t1 or t2 does not match N, "
"len(t1)={}, len(t2)={}".format(
len(self.t1), len(self.t2)))
if self.targets is None:
targets = range(N)
else:
targets = self.targets
for qu_ind in targets:
t1 = self.t1[qu_ind]
t2 = self.t2[qu_ind]
if t1 is not None:
op = 1/np.sqrt(t1) * destroy(dims[qu_ind])
systematic_noise.add_lindblad_noise(op, qu_ind, coeff=True)
if t2 is not None:
# Keep the total dephasing ~ exp(-t/t2)
if t1 is not None:
if 2*t1 < t2:
raise ValueError(
"t1={}, t2={} does not fulfill "
"2*t1>t2".format(t1, t2))
T2_eff = 1./(1./t2-1./2./t1)
else:
T2_eff = t2
op = 1/np.sqrt(2*T2_eff) * 2 * num(dims[qu_ind])
systematic_noise.add_lindblad_noise(op, qu_ind, coeff=True)
return pulses, systematic_noise
[docs]class ControlAmpNoise(Noise):
"""
The noise in the amplitude of the control pulse.
Parameters
----------
coeff: list
A list of the coefficients for the control Hamiltonians.
For available choices, see :class:`qutip.QobjEvo`.
tlist: array_like, optional
A NumPy array specifies the time of each coefficient.
indices: list of int, optional
The indices of target pulse in the list of pulses.
Attributes
----------
coeff: list
A list of the coefficients for the control Hamiltonians.
For available choices, see :class:`qutip.QobjEvo`.
tlist: array_like
A NumPy array specifies the time of each coefficient.
indices: list of int
The indices of target pulse in the list of pulses.
"""
def __init__(self, coeff, tlist=None, indices=None):
self.coeff = coeff
self.tlist = tlist
self.indices = indices
[docs] def get_noisy_dynamics(
self, dims=None, pulses=None, systematic_noise=None):
if pulses is None:
pulses = []
if self.indices is None:
indices = range(len(pulses))
else:
indices = self.indices
for i in indices:
pulse = pulses[i]
if isinstance(self.coeff, (int, float)):
coeff = pulse.coeff * self.coeff
else:
coeff = self.coeff
if self.tlist is None:
tlist = pulse.tlist
else:
tlist = self.tlist
pulses[i].add_coherent_noise(
pulse.qobj, pulse.targets, tlist, coeff)
return pulses, systematic_noise
[docs]class RandomNoise(ControlAmpNoise):
"""
Random noise in the amplitude of the control pulse. The arguments for
the random generator need to be given as key word arguments.
Parameters
----------
dt: float, optional
The time interval between two random amplitude. The coefficients
of the noise are the same within this time range.
rand_gen: numpy.random, optional
A random generator in numpy.random, it has to take a ``size``
parameter as the size of random numbers in the output array.
indices: list of int, optional
The indices of target pulse in the list of pulses.
**kwargs:
Key word arguments for the random number generator.
Attributes
----------
dt: float, optional
The time interval between two random amplitude. The coefficients
of the noise are the same within this time range.
rand_gen: numpy.random, optional
A random generator in numpy.random, it has to take a ``size``
parameter.
indices: list of int
The indices of target pulse in the list of pulses.
**kwargs:
Key word arguments for the random number generator.
Examples
--------
>>> gaussnoise = RandomNoise( \
dt=0.1, rand_gen=np.random.normal, loc=mean, scale=std) \
# doctest: +SKIP
"""
def __init__(
self, dt, rand_gen, indices=None, **kwargs):
super(RandomNoise, self).__init__(coeff=None, tlist=None)
self.rand_gen = rand_gen
self.kwargs = kwargs
if "size" in kwargs:
raise ValueError("size is preditermined inside the noise object.")
self.dt = dt
self.indices = indices
[docs] def get_noisy_dynamics(
self, dims=None, pulses=None, systematic_noise=None):
if pulses is None:
pulses = []
if self.indices is None:
indices = range(len(pulses))
else:
indices = self.indices
t_max = -np.inf
t_min = np.inf
for pulse in pulses:
t_max = max(max(pulse.tlist), t_max)
t_min = min(min(pulse.tlist), t_min)
# create new tlist and random coeff
num_rand = int(np.floor((t_max - t_min) / self.dt)) + 1
tlist = (np.arange(0, self.dt*num_rand, self.dt)[:num_rand] + t_min)
# [:num_rand] for round of error like 0.2*6=1.2000000000002
for i in indices:
pulse = pulses[i]
coeff = self.rand_gen(**self.kwargs, size=num_rand)
pulses[i].add_coherent_noise(
pulse.qobj, pulse.targets, tlist, coeff)
return pulses, systematic_noise