InjectNoiseNode

class samplomatic.samplex.nodes.InjectNoiseNode(register_name: str, sign_register_name: str, noise_ref: str, num_subsystems: int, modifier_ref: str = '')

Bases: SamplingNode

A node that produces samples for injecting noise.

The node uses a qiskit.quantum_info.PauliLindbladMap as the distribution to draw samples from. This map can be modified at sample time:

• noise_scales, a dictionary from StrRef to floats. If modifier_ref is in the dictionary, the distribution is replaced with the one generated by by qiskit.quantum_info.PauliLindbladMap.scale_rates().

• local_scales, a dictionary from StrRef to lists of floats. If modifier_ref is in the dictionary, the rates of qiskit.quantum_info.PauliLindbladMap are scaled individually.

Parameters:

• register_name – The name of the register to store the samples.

• sign_register_name – The name of the register to store the signs.

• noise_ref – Unique identifier of the Pauli Lindblad map to draw samples from.

• num_subsystems – The number of subsystems this node generates gates for.

• modifier_ref – Unique identifier for modifiers applied to the Pauli Lindblad map before sampling.

Attributes Summary

outgoing_register_type

The virtual gate type of outgoing registers.

Methods Summary

get_style()	Return the style of this node when plotted.
instantiates()	Return a manifest of new virtual registers that this node instantiates.
sample(registers, rng, inputs, ...)	Sample this node.

Attributes Documentation

outgoing_register_type

Methods Documentation

get_style()

Return the style of this node when plotted.

instantiates() → dict[str, tuple[int, VirtualType]]

Return a manifest of new virtual registers that this node instantiates.

Note

• To change the type or size of a register, both instantiate and remove it.

• Do not specify reads_from() or writes_to() for an instantiated register, these powers are implicit.

sample(registers, rng, inputs, num_randomizations)

Sample this node.

Parameters:

• registers – Where to sample into.

• rng – A randomness generator.

• inputs – Inputs of the sampling program.

• num_randomizations – How many randomizations to draw.