In Nomos DA v2, we currently have two viable options for securely performing data encoding, particularly when addressing small data sets (less than 1 MB).

Scenario 1: Variable Matrix Sizes

In this scenario, for datasets larger than 1 MB, we use a 1024x1024 matrix. However, for datasets smaller than 1 MB, smaller matrix sizes are necessary to satisfy the subspace distance check. For comparison, we assume a 256x256 matrix for small data.

In the existing Nomos DA v1, the protocol operates over 2048 subnetworks. Adhering to this constraint, we propose the following design:

Scenario 2: Using Field Extension

Alternatively, by employing field extension, a consistent 1024x1024 matrix can be used for all data sizes, both below and above 1 MB:

The main disadvantage of this scenario is the limitation to row-wise reconstruction only. However, this scenario reduces the total data per subnetwork, benefiting from the uniform 1024x1024 matrix size.

Below is a comparative analysis of the total data per subnetwork for both scenarios:

Scenario 1 (Variable Matrix Sizes)

Scenario 2 (Field Extension, 1024x1024 Matrix)