kaira.channels.BinaryZChannel

Inheritance diagram for BinaryZChannel

class kaira.channels.BinaryZChannel(error_prob, *args: Any, **kwargs: Any)

Bases: BaseChannel

Z Channel (asymmetric binary channel) with one-sided error probability.

The Z Channel is an asymmetric binary channel where only one type of bit flip can occur: 1→0 errors happen with probability p, while 0→1 errors never occur. This models systems where one type of error is much more likely than the other [Verdú, 2002] [Golomb, 1980].

Mathematical Model:

P(y=0|x=1) = p (1→0 error probability) P(y=1|x=1) = 1-p P(y=0|x=0) = 1 (no errors) P(y=1|x=0) = 0

Parameters:

error_prob (float) – Probability of 1→0 bit flip (0 ≤ p ≤ 1)

Example

>>> channel = BinaryZChannel(error_prob=0.3)
>>> x = torch.tensor([0, 1, 0, 1], dtype=torch.float32)
>>> y = channel(x)  # Some 1s may flip to 0s, but 0s never flip to 1s

Methods

__init__	Initialize the Binary Z Channel.
forward	Apply Binary Z Channel errors to the input tensor.
get_config	Get a dictionary of the channel's configuration.

__init__(error_prob, *args: Any, **kwargs: Any)

Initialize the Binary Z Channel.

Parameters:

• error_prob (float) – Probability of 1→0 bit flip (0 ≤ p ≤ 1).

• *args – Variable length argument list passed to the base class.

• **kwargs – Arbitrary keyword arguments passed to the base class.

forward(x: Tensor, *args: Any, **kwargs: Any) → Tensor

Apply Binary Z Channel errors to the input tensor.

Parameters:

• x (torch.Tensor) – The input tensor (binary 0/1 or bipolar -1/1).

• *args – Additional positional arguments (unused).

• **kwargs – Additional keyword arguments (unused).

Returns:

The output tensor with potential 1 -> 0 flips.

Return type:

torch.Tensor

get_config() → Dict[str, Any]

Get a dictionary of the channel’s configuration.

This method returns a dictionary containing the channel’s parameters, which can be used to recreate the channel instance.

Returns:

Dictionary of parameter names and values

Return type:

Dict[str, Any]