qutip/solver/brmesolve.py
"""
This module provides solvers for the Lindblad master equation and von Neumann
equation.
"""
__all__ = ['brmesolve', 'BRSolver']
import numpy as np
import inspect
from time import time
from .. import Qobj, QobjEvo, coefficient, Coefficient
from ..core.blochredfield import bloch_redfield_tensor, SpectraCoefficient
from ..core.cy.coefficient import InterCoefficient
from ..core import data as _data
from .solver_base import Solver, _solver_deprecation
from .options import _SolverOptions
from ._feedback import _QobjFeedback, _DataFeedback
def brmesolve(H, psi0, tlist, a_ops=(), e_ops=(), c_ops=(),
args=None, sec_cutoff=0.1, options=None, **kwargs):
"""
Solves for the dynamics of a system using the Bloch-Redfield master
equation, given an input Hamiltonian, Hermitian bath-coupling terms and
their associated spectral functions, as well as possible Lindblad collapse
operators.
Parameters
----------
H : :obj:`.Qobj`, :obj:`.QobjEvo`
Possibly time-dependent system Liouvillian or Hamiltonian as a Qobj or
QobjEvo. list of [:obj:`.Qobj`, :obj:`.Coefficient`] or callable that
can be made into :obj:`.QobjEvo` are also accepted.
psi0: Qobj
Initial density matrix or state vector (ket).
tlist : array_like
List of times for evaluating evolution
a_ops : list of (a_op, spectra)
Nested list of system operators that couple to the environment,
and the corresponding bath spectra.
a_op : :obj:`.Qobj`, :obj:`.QobjEvo`
The operator coupling to the environment. Must be hermitian.
spectra : :obj:`.Coefficient`, str, func
The corresponding bath spectral responce.
Can be a `Coefficient` using an 'w' args, a function of the
frequence or a string. Coefficient build from a numpy array are
understood as a function of ``w`` instead of ``t``. Function are
expected to be of the signature ``f(w)`` or ``f(t, w, **args)``.
The spectra function can depend on ``t`` if the corresponding
``a_op`` is a :obj:`.QobjEvo`.
Example:
.. code-block::
a_ops = [
(a+a.dag(), ('w>0', args={"w": 0})),
(QobjEvo(a+a.dag()), 'w > exp(-t)'),
(QobjEvo([b+b.dag(), lambda t: ...]), lambda w: ...)),
(c+c.dag(), SpectraCoefficient(coefficient(array, tlist=ws))),
]
.. note:
``Cubic_Spline`` has been replaced by :obj:`.Coefficient`:
``spline = qutip.coefficient(array, tlist=times)``
Whether the ``a_ops`` is time dependent is decided by the type of
the operator: :obj:`.Qobj` vs :obj:`.QobjEvo` instead of the type
of the spectra.
e_ops : list of :obj:`.Qobj` / callback function, optional
Single operator or list of operators for which to evaluate
expectation values or callable or list of callable.
Callable signature must be, `f(t: float, state: Qobj)`.
See :func:`expect` for more detail of operator expectation
c_ops : list of (:obj:`.QobjEvo`, :obj:`.QobjEvo` compatible format), optional
List of collapse operators.
args : dict, optional
Dictionary of parameters for time-dependent Hamiltonians and
collapse operators. The key ``w`` is reserved for the spectra function.
sec_cutoff : float, default: 0.1
Cutoff for secular approximation. Use ``-1`` if secular approximation
is not used when evaluating bath-coupling terms.
options : dict, optional
Dictionary of options for the solver.
- | store_final_state : bool
| Whether or not to store the final state of the evolution in the
result class.
- | store_states : bool, None
| Whether or not to store the state vectors or density matrices.
On `None` the states will be saved if no expectation operators are
given.
- | normalize_output : bool
| Normalize output state to hide ODE numerical errors. Only normalize
the state if the initial state is already normalized.
- | progress_bar : str {'text', 'enhanced', 'tqdm', ''}
| How to present the solver progress.
'tqdm' uses the python module of the same name and raise an error
if not installed. Empty string or False will disable the bar.
- | progress_kwargs : dict
| kwargs to pass to the progress_bar. Qutip's bars use `chunk_size`.
- | tensor_type : str ['sparse', 'dense', 'data']
| Which data type to use when computing the brtensor.
With a cutoff 'sparse' is usually the most efficient.
- | sparse_eigensolver : bool {False}
Whether to use the sparse eigensolver
- | method : str ["adams", "bdf", "lsoda", "dop853", "vern9", etc.]
Which differential equation integration method to use.
- | atol, rtol : float
| Absolute and relative tolerance of the ODE integrator.
- | nsteps : int
| Maximum number of (internally defined) steps allowed in one
``tlist`` step.
- | max_step : float, 0
| Maximum lenght of one internal step. When using pulses, it should
be less than half the width of the thinnest pulse.
Other options could be supported depending on the integration method,
see `Integrator <./classes.html#classes-ode>`_.
Returns
-------
result: :obj:`.Result`
An instance of the class :obj:`qutip.solver.Result`, which contains
either an array of expectation values, for operators given in e_ops,
or a list of states for the times specified by ``tlist``.
"""
options = _solver_deprecation(kwargs, options, "br")
args = args or {}
H = QobjEvo(H, args=args, tlist=tlist)
c_ops = c_ops if c_ops is not None else []
if not isinstance(c_ops, (list, tuple)):
c_ops = [c_ops]
c_ops = [QobjEvo(c_op, args=args, tlist=tlist) for c_op in c_ops]
new_a_ops = []
for (a_op, spectra) in a_ops:
aop = QobjEvo(a_op, args=args, tlist=tlist)
if isinstance(spectra, str):
new_a_ops.append(
(aop, coefficient(spectra, args={**args, 'w':0})))
elif isinstance(spectra, InterCoefficient):
new_a_ops.append((aop, SpectraCoefficient(spectra)))
elif isinstance(spectra, Coefficient):
new_a_ops.append((aop, spectra))
elif callable(spectra):
sig = inspect.signature(spectra)
if tuple(sig.parameters.keys()) == ("w",):
spec = SpectraCoefficient(coefficient(spectra))
else:
spec = coefficient(spectra, args={**args, 'w':0})
new_a_ops.append((aop, spec))
else:
raise TypeError("a_ops's spectra not known")
solver = BRSolver(H, new_a_ops, c_ops, sec_cutoff, options=options)
return solver.run(psi0, tlist, e_ops=e_ops)
class BRSolver(Solver):
"""
Bloch Redfield equation evolution of a density matrix for a given
Hamiltonian and set of bath coupling operators.
Parameters
----------
H : :obj:`.Qobj`, :obj:`.QobjEvo`
Possibly time-dependent system Liouvillian or Hamiltonian as a Qobj or
QobjEvo. list of [:obj:`.Qobj`, :obj:`.Coefficient`] or callable that
can be made into :obj:`.QobjEvo` are also accepted.
a_ops : list of (a_op, spectra)
Nested list of system operators that couple to the environment,
and the corresponding bath spectra.
a_op : :obj:`.Qobj`, :obj:`.QobjEvo`
The operator coupling to the environment. Must be hermitian.
spectra : :obj:`.Coefficient`
The corresponding bath spectra. As a `Coefficient` using an 'w'
args. Can depend on ``t`` only if a_op is a :obj:`.QobjEvo`.
:obj:`SpectraCoefficient` can be used to conver a coefficient
depending on ``t`` to one depending on ``w``.
Example:
.. code-block::
a_ops = [
(a+a.dag(), coefficient('w>0', args={'w':0})),
(QobjEvo([b+b.dag(), lambda t: ...]),
coefficient(lambda t, w: ...), args={"w": 0}),
(c+c.dag(), SpectraCoefficient(coefficient(array, tlist=ws))),
]
c_ops : list of :obj:`.Qobj`, :obj:`.QobjEvo`
Single collapse operator, or list of collapse operators, or a list
of Lindblad dissipator. None is equivalent to an empty list.
options : dict, optional
Options for the solver, see :obj:`BRSolver.options` and
`Integrator <./classes.html#classes-ode>`_ for a list of all options.
sec_cutoff : float {0.1}
Cutoff for secular approximation. Use ``-1`` if secular approximation
is not used when evaluating bath-coupling terms.
Attributes
----------
stats: dict
Diverse diagnostic statistics of the evolution.
"""
name = "brmesolve"
solver_options = {
"progress_bar": "",
"progress_kwargs": {"chunk_size":10},
"store_final_state": False,
"store_states": None,
"normalize_output": False,
'method': 'adams',
'tensor_type': 'sparse',
'sparse_eigensolver': False,
}
_avail_integrators = {}
def __init__(self, H, a_ops, c_ops=None, sec_cutoff=0.1, *, options=None):
_time_start = time()
self.rhs = None
self.sec_cutoff = sec_cutoff
self.options = options
if not isinstance(H, (Qobj, QobjEvo)):
raise TypeError("The Hamiltonian must be a Qobj or QobjEvo")
H = QobjEvo(H)
c_ops = c_ops or []
c_ops = [c_ops] if isinstance(c_ops, (Qobj, QobjEvo)) else c_ops
for c_op in c_ops:
if not isinstance(c_op, (Qobj, QobjEvo)):
raise TypeError("All `c_ops` must be a Qobj or QobjEvo")
a_ops = a_ops or []
if not hasattr(a_ops, "__iter__"):
TypeError("`a_ops` must be a list of (operator, spectra)")
if a_ops and isinstance(a_ops[0], (Qobj, QobjEvo)):
a_ops = [a_ops]
for oper, spectra in a_ops:
if not isinstance(oper, (Qobj, QobjEvo)):
raise TypeError("All `a_ops` operators "
"must be a Qobj or QobjEvo")
if not isinstance(spectra, Coefficient):
raise TypeError("All `a_ops` spectra "
"must be a Coefficient.")
self._system = H, a_ops, c_ops
self._num_collapse = len(c_ops)
self._num_a_ops = len(a_ops)
self.rhs = self._prepare_rhs()
self._integrator = self._get_integrator()
self._state_metadata = {}
self.stats = self._initialize_stats()
self.rhs._register_feedback({}, solver=self.name)
def _initialize_stats(self):
stats = super()._initialize_stats()
stats.update({
"solver": "Bloch Redfield Equation Evolution",
"init time": stats["init time"] + self._init_rhs_time,
"num_collapse": self._num_collapse,
"num_a_ops": self._num_a_ops,
})
return stats
def _prepare_rhs(self):
_time_start = time()
rhs = bloch_redfield_tensor(
*self._system,
fock_basis=True,
sec_cutoff=self.sec_cutoff,
sparse_eigensolver=self.options['sparse_eigensolver'],
br_dtype=self.options['tensor_type']
)
self._init_rhs_time = time() - _time_start
return rhs
@property
def options(self):
"""
Options for bloch redfield solver:
store_final_state: bool, default: False
Whether or not to store the final state of the evolution in the
result class.
store_states: bool, default: None
Whether or not to store the state vectors or density matrices.
On `None` the states will be saved if no expectation operators are
given.
normalize_output: bool, default: False
Normalize output state to hide ODE numerical errors.
progress_bar: str {'text', 'enhanced', 'tqdm', ''}, default: ""
How to present the solver progress.
'tqdm' uses the python module of the same name and raise an error if
not installed. Empty string or False will disable the bar.
progress_kwargs: dict, default: {"chunk_size":10}
Arguments to pass to the progress_bar. Qutip's bars use
``chunk_size``.
tensor_type: str ['sparse', 'dense', 'data'], default: "sparse"
Which data type to use when computing the brtensor.
With a cutoff 'sparse' is usually the most efficient.
sparse_eigensolver: bool, default: False
Whether to use the sparse eigensolver
method: str, default: "adams"
Which ODE integrator methods are supported.
"""
return self._options
@options.setter
def options(self, new_options):
Solver.options.fset(self, new_options)
def _apply_options(self, keys):
need_new_rhs = self.rhs is not None and not self.rhs.isconstant
need_new_rhs &= (
'sparse_eigensolver' in keys or 'tensor_type' in keys
)
if need_new_rhs:
self.rhs = self._prepare_rhs()
if self._integrator is None or not keys:
pass
elif 'method' in keys or need_new_rhs:
state = self._integrator.get_state()
self._integrator = self._get_integrator()
self._integrator.set_state(*state)
else:
self._integrator.options = self._options
self._integrator.reset(hard=True)
@classmethod
def StateFeedback(cls, default=None, raw_data=False):
"""
State of the evolution to be used in a time-dependent operator.
When used as an args:
``QobjEvo([op, func], args={"state": BRMESolver.StateFeedback()})``
The ``func`` will receive the density matrix as ``state`` during the
evolution.
.. note::
The state will not be in the lab basis, but in the evolution basis.
Parameters
----------
default : Qobj or qutip.core.data.Data, default : None
Initial value to be used at setup of the system.
raw_data : bool, default : False
If True, the raw matrix will be passed instead of a Qobj.
For density matrices, the matrices can be column stacked or square
depending on the integration method.
"""
if raw_data:
return _DataFeedback(default, open=True)
return _QobjFeedback(default, open=True)