An information theoretic lower bound represents the absolute minimum amount of information that must be communicated or processed to accomplish a specific computational task. This bound is determined by the inherent information content of the problem, independent of any particular algorithm or computational model. It establishes a theoretical limit on the efficiency achievable for a given task. This limit guides cryptographic research.
Context
In cryptography and blockchain research, establishing information theoretic lower bounds helps assess the ultimate efficiency of protocols for tasks like data storage, proof generation, or consensus mechanisms. News reports on breakthroughs in cryptographic primitives or scaling solutions might refer to how close a new system comes to these theoretical limits. Understanding this concept aids in evaluating the fundamental performance capabilities of digital asset systems and their future potential.
A new vector commitment scheme achieves sublinear complexity for both global update size and local proof updates, solving the stateless client efficiency trade-off.
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