paraqeet.model.closed_system.ClosedSystem#

class paraqeet.model.closed_system.ClosedSystem(hamiltonian, ode_propagation=False)#

Bases: EquationOfMotion

Model of a closed physical system, defined by a Hamiltonian.

Its dynamics is given by the Schrödinger equation.

Parameters:

hamiltonian (Hamiltonian) – Matrix representation of a Hamiltonian.
ode_propagation (bool)

__init__(hamiltonian, ode_propagation=False)#

Parameters:

hamiltonian (DifferentiableHamiltonian)
ode_propagation (bool)

Methods

`__init__`(hamiltonian[, ode_propagation])
`get_parameters`()	Get a list of optimizable parameters.
`get_right_hand_side`(time, state)	Return the right-hand side of the equations of motion.
`get_value`(times)	Get the matrix equations of motion.
`get_value_and_gradient`(times)	Compute the gradient of getMatrix.
`set_all_optimizable_parameters`(all_params)	Set all optimizable parameters in the optimization.
`set_optimizable_parameters`(params)	Set which parameters associated with the object shall be considered during optimization.

Attributes

`all_optimizable_parameters`	Get the optimizable parameters
`name`	Get the name of the parameter.
`ode_propagation`	Flag to set method of propagation to ODE.
`optimizable_parameters`	Get the optimizable parameters

property all_optimizable_parameters: list[Quantity]#

Get the optimizable parameters

Returns:: The list of all the optimizable parameters considered in the optimization
Return type:: list[Quantity]

get_parameters()#

Get a list of optimizable parameters.

Returns:: List of optimizable parameters of the system.
Return type:: List[Quantity]

get_right_hand_side(time, state)#

Return the right-hand side of the equations of motion.

The format depends on the implementation and could for example be a state vector or a matrix. Default implementation assumes a homogeneous ODE with matrix operator given by self.getMatrix().

Parameters:

time (Array) – Any one-dimensional vector of timestamps.
state (Array)

Returns:

The right-hand side of the equation of motion at each time stamp.

Return type:

Array

get_value(times)#

Get the matrix equations of motion.

Computes the right hand side of the Schrödinger equation without multiplying the state. Used for unitary solvers.

Parameters:: times (Array) – Vector of time samples.
Returns:: RHS with dimension [t, n, n] with ‘t’ as time and ‘n’ as Hilbert space dimension.
Return type:: Array

get_value_and_gradient(times)#

Compute the gradient of getMatrix.

Parameters:: times (Array) – Vector of time samples.
Returns:: Returns the gradient of getMatrix.
Return type:: Array

property name: str | None#

Get the name of the parameter.

Returns:: Name of the parameter.
Return type:: str | None

property ode_propagation: bool#

Flag to set method of propagation to ODE.

Returns:: Flag to use ODE propagation.
Return type:: bool

property optimizable_parameters: list[Quantity]#

Get the optimizable parameters

Returns:: The list of optimizable parameters associated with the object.
Return type:: list[Quantity]

set_all_optimizable_parameters(all_params)#

Set all optimizable parameters in the optimization.

Parameters:

params (List[Quantity]) – List of optimizable parameters to be set.
all_params (list[Quantity])

Return type:

None

set_optimizable_parameters(params)#

Set which parameters associated with the object shall be considered during optimization.

All quantities that are not in the response of get_parameters will be filtered out. This function is called by the optimizer before gradient based optimization to tell the layers which gradients to compute.

Parameters:: params (list[Quantity]) – List of optimizable parameters to be set.
Return type:: None