paraqeet.model.transmon.Transmon#

class paraqeet.model.transmon.Transmon(dimension, frequency, anharmonicity, drives=None, t1=None, temp=None, t2star=None)[source]#

Bases: DifferentiableHamiltonian

Hamiltonian of an anharmonic oscillator.

Optimizable parameters are the ground frequency and the anharmonicity.

Parameters:

dimension (int) – Dimension of the anharmonic oscillator.
frequency (Quantity) – Frequency of the anharmonic oscillator.
anharmonicity (Quantity) – Anharmonicity of the oscillator.
drives (list[Drive]) – List of time-dependent drives of the subsystem.
t1 (Quantity | None)
temp (Quantity | None)
t2star (Quantity | None)

__init__(dimension, frequency, anharmonicity, drives=None, t1=None, temp=None, t2star=None)[source]#

Parameters:

dimension (int)
frequency (Quantity)
anharmonicity (Quantity)
drives (list[Drive] | None)
t1 (Quantity | None)
temp (Quantity | None)
t2star (Quantity | None)

Methods

`__init__`(dimension, frequency, anharmonicity)
`dimension`()	Get the dimension of the Transmon system.
`get_collapseops`()	Return a list tuples of decay rates and collapse operators for each subsystem.
`get_decay_rates`()	Return decay rate for T1, T2star and Temp respectively.
`get_gradient_at_timestep`(time)	Get the gradient of the drive.
`get_parameters`()	Get parameters of the model.
`get_value`(times)	Return the matrix representation of the Hamiltonian.
`get_value_and_gradient`(times)	Compute value and gradient for given timesteps.
`get_value_at_timestep`(timestep)	Get the drive matrix.
`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
`anharmonicity`	Get the anharmonicity of the Transmon system.
`drives`	Return the list of Drives of the system.
`frequency`	Get the frequency of the Transmon system.
`name`	Get the name of the parameter.
`optimizable_parameters`	Get the optimizable parameters
`t1`	Get the t1 of the resonator.
`t2star`	Get the t2star of the resonator.
`temp`	Get the temp of the resonator.

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]

property anharmonicity: Quantity#: Get the anharmonicity of the Transmon system.

dimension()[source]#

Get the dimension of the Transmon system.

Return type:: int

property drives: list[Drive]#

Return the list of Drives of the system.

Returns:: Returns a list of time-dependent drives of the system.
Return type:: list[Drive]

property frequency: Quantity#: Get the frequency of the Transmon system.

get_collapseops()[source]#

Return a list tuples of decay rates and collapse operators for each subsystem.

Returns:: List of collapse operators
Return type:: list[tuple[Array, Array]]

get_decay_rates()[source]#

Return decay rate for T1, T2star and Temp respectively.

Return type:: list[Array]

get_gradient_at_timestep(time)[source]#

Get the gradient of the drive.

Parameters:

t (Array) – Single time stamp.
time (float)

Returns:

Returns the gradients of the drive.

Return type:

Array

get_parameters()[source]#

Get parameters of the model.

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

get_value(times)[source]#

Return the matrix representation of the Hamiltonian.

The default implementation calls get_value_at_timestep for each time step. Subclasses can override this function for a more efficient implementation.

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

get_value_and_gradient(times)[source]#

Compute value and gradient for given timesteps. The gradient call uses vmap over at_timestep methods.

Parameters:: times (Array)
Return type:: tuple[Array, Array]

get_value_at_timestep(timestep)[source]#

Get the drive matrix.

Parameters:: timestep (Array) – Vector of time samples.
Returns:: The repeated drive matrix.
Return type:: Array

property name: str | None#

Get the name of the parameter.

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

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)[source]#

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)[source]#

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

property t1: Quantity | None#: Get the t1 of the resonator.

property t2star: Quantity | None#: Get the t2star of the resonator.

property temp: Quantity | None#: Get the temp of the resonator.