NP computation refers to problems solvable by a non-deterministic Turing machine in polynomial time, or problems whose solutions can be verified in polynomial time. This class of computational problems is a central topic in theoretical computer science, particularly in complexity theory. Many cryptographic protocols rely on the presumed difficulty of certain NP problems. It describes a class of hard problems.
Context
In the cryptographic underpinnings of digital assets, the hardness of certain NP computation problems forms the basis for the security of many blockchain systems. For instance, the difficulty of solving specific mathematical problems quickly ensures the integrity of cryptographic hashes and digital signatures. Advances in quantum computing pose a long-term theoretical challenge to the security reliant on these computational assumptions. This is vital for crypto security.
A new lattice-based commitment scheme enables the first quasi-optimal, quantum-resistant SNARKs, making secure, scalable verifiable computation practical.
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