Two dimensional sampling is a data verification technique used in some distributed systems. This method involves structuring data in a two-dimensional matrix and then randomly sampling cells from both rows and columns to verify data availability. By checking a sufficient number of these intersecting samples, a node can probabilistically confirm that the entire dataset is present and correctly formed. It enhances the efficiency of data integrity checks without requiring full data download.
Context
Two dimensional sampling is a advanced concept being explored for data availability layers in modular blockchain architectures, particularly for optimistic and zero-knowledge rollups. It aims to provide stronger data availability guarantees than one-dimensional sampling while maintaining efficiency for light clients. Future research will focus on refining the cryptographic proofs and practical implementations to further secure and scale these systems.
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