c3.libraries.tasks

Module Contents

c3.libraries.tasks.task_deco(cl)[source]

Decorator for task classes list.

class c3.libraries.tasks.Task(name: str = ' ', desc: str = ' ', comment: str = ' ', params: dict = None)[source]

Bases: c3.c3objs.C3obj

Inheritance diagram of c3.libraries.tasks.Task

Task that is part of the measurement setup.

__str__(self) → str

Return str(self).

class c3.libraries.tasks.InitialiseGround(name: str = 'init_ground', desc: str = ' ', comment: str = ' ', init_temp: c3.c3objs.Quantity = None, params=None)[source]

Bases: Task

Inheritance diagram of c3.libraries.tasks.InitialiseGround

Initialise the ground state with a given thermal distribution.

initialise(self, drift_ham, lindbladian=False, init_temp=None)[source]

Prepare the initial state of the system. At the moment finite temperature requires open system dynamics.

Parameters

  • drift_ham (tf.Tensor) – Drift Hamiltonian.

  • lindbladian (boolean) – Whether to include open system dynamics. Required for Temperature > 0.

  • init_temp (Quantity) – Temperature of the device.

Returns

State or density vector

Return type

tf.Tensor

__str__(self) → str

Return str(self).

class c3.libraries.tasks.ConfusionMatrix(name: str = 'conf_matrix', desc: str = ' ', comment: str = ' ', params=None, **confusion_rows)[source]

Bases: Task

Inheritance diagram of c3.libraries.tasks.ConfusionMatrix

Allows for misclassificaiton of readout measurement.

confuse(self, pops)[source]

Apply the confusion (or misclassification) matrix to populations.

Parameters

pops (list) – Populations

Returns

Populations after misclassification.

Return type

list

__str__(self) → str

Return str(self).

class c3.libraries.tasks.MeasurementRescale(name: str = 'meas_rescale', desc: str = ' ', comment: str = ' ', meas_offset: c3.c3objs.Quantity = None, meas_scale: c3.c3objs.Quantity = None, params=None)[source]

Bases: Task

Inheritance diagram of c3.libraries.tasks.MeasurementRescale

Rescale the result of the measurements. This is usually done to account for preparation errors.

Parameters

  • meas_offset (Quantity) – Offset added to the measured signal.

  • meas_scale (Quantity) – Factor multiplied to the measured signal.

rescale(self, pop1)[source]

Apply linear rescaling and offset to the readout value.

Parameters

pop1 (tf.float64) – Population in first excited state.

Returns

Population after rescaling.

Return type

tf.float64

__str__(self) → str

Return str(self).