qom.solvers.stochastic module

Module to solve stochastic equations of motion.

class qom.solvers.stochastic.MCQTSolver(system, params: dict, num_trajs: int, cb_update=None, parallel: bool = False, p_index: int = 0, p_start: float = None)

Bases: object

Class to solve for the expectation values of operators using the Monte-Carlo quantum trajectories method.

Initializes system, num_trajs, T and updater.

Parameters:

• system (qom.systems.*) – Instance of the system. Requires predefined system methods get_ops_collapse, get_ops_expect, get_H_0 and get_ivc. For time-dependent Hamiltonians, the method get_H_t should also be defined. Refer to Notes below for their implementations.

• params (dict) –

  Parameters for the solver. Refer to Notes below for all available options. Required options are:

  key	value
  ’t_min’	(float) minimum time at which integration starts.
  ’t_max’	(float) maximum time at which integration stops.
  ’t_dim’	(int) number of values from 't_max' to 't_min', both inclusive.

• num_trajs (int) – Number of trajectories.

• cb_update (callable, optional) – Callback function to update status and progress, formatted as cb_update(status, progress, reset), where status is a string, progress is a float and reset is a boolean.

• parallel (bool, default=False) – Option to format outputs when running in parallel.

• p_index (int, default=0) – Index of the process.

• p_start (float, optional) – Time at which the process was started. If not provided, the value is initialized to current time.

Notes

The following system methods follow a strict formatting:

method	returns
get_H_0	the time-independent part of the Hamiltonian, formatted as get_H_0(c), where c is an array of the derived constants and controls of the system.
get_H_t	the time-dependent part of the Hamiltonian, formatted as get_H_t(c, t), where c is an array of the derived constants and controls of the system and t is the time at which the Hamiltonian is obtained.
get_ops_collapse	the collapse operators of the system. It follows the same formatting as get_H_0.
get_ops_expect	the operators of the system for which the expectation values are to be obtained. It follows the same formatting as get_H_0.
get_ivc	the initial state vector and the derived constants and controls, formatted as get_ivc().

The params dictionary currently supports the following keys:

key	value
‘show_progress’	(bool) option to display the progress of the solver. Default is False.
‘ode_method’	(str) method used to solve the ODEs. Available options are 'BDF', 'DOP853', 'LSODA', 'Radau', 'RK23', 'RK45' (fallback), 'dop853', 'dopri5', 'lsoda', 'vode' and 'zvode'. Refer to qom.solvers.differential.ODESolver for details of each method. Default is 'RK45'.
‘ode_is_stiff’	(bool) option to select whether the integration is a stiff problem or a non-stiff one. Default is False.
‘ode_atol’	(float) absolute tolerance of the integrator. Default is 1e-12.
‘ode_rtol’	(float) relative tolerance of the integrator. Default is 1e-6.
‘t_min’	(float) minimum time at which integration starts. Default is 0.0.
‘t_max’	(float) maximum time at which integration stops. Default is 1000.0.
‘t_dim’	(int) number of values from 't_max' to 't_min', both inclusive. Default is 10001.

desc = 'Monte-Carlo Quantum Trajectories Solver'

Description of the solver.

Type:

str

name = 'MCQTSolver'

Name of the solver.

Type:

str

set_params(params)

Method to set the solver parameters.

Parameters:

params (dict) – Parameters of the solver.

solve()

Method to solve for the quantum trajectories.

Sets the results with keys 'times', 'trajs', 'expects' and 'runtimes' for the time steps, individual trajectories of expectation values, pooled expectation values and execution times of each trajectory respectively.

solver_defaults = {'ode_atol': 1e-08, 'ode_is_stiff': False, 'ode_method': 'zvode', 'ode_rtol': 1e-06, 'show_progress': False, 't_dim': 10001, 't_max': 1000.0, 't_min': 0.0}

Default parameters of the solver.

Type:

dict