Sublinear update complexity describes a computational characteristic where the time required to modify a data structure grows at a rate slower than linear with respect to the size of the structure. This means that as the data structure becomes larger, updating it remains relatively efficient. It is a desirable property for scalable systems.
Context
Sublinear update complexity is a crucial performance metric for authenticated data structures used in blockchains, such as Merkle trees or Verkle trees. Achieving this property allows for efficient state transitions and updates to the global ledger, even as the blockchain grows considerably. This efficiency is vital for improving the scalability and throughput of decentralized networks.
A new algebraic commitment primitive achieves sublinear state updates, fundamentally solving the efficiency bottleneck for large-scale stateless blockchain architecture.
A new vector commitment scheme achieves sublinear complexity for both global update size and local proof updates, solving the stateless client efficiency trade-off.
Research introduces a Dynamic Universal Accumulator that compresses massive data sets into a constant-size cryptographic proof, enabling efficient, constant-time verification for scalable systems.
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