InjectNoiseNode

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

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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

Column 1	Column 2
`outgoing_register_type`	The virtual gate type of outgoing registers.

Methods Summary

Column 1	Column 2
`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

get_style()

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Return the style of this node when plotted.

instantiates

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

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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

sample(registers, rng, inputs, num_randomizations)

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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.

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