Nova: Breakthrough Application of Microsoft's Innovative zk-SNARKs System

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Nova: An Innovative zk-SNARKs System

Nova is a new zk-SNARKs system developed by Microsoft. It employs the Relaxed R1CS( technology, which significantly improves the efficiency and flexibility of proofs. The main advantages of Nova are:

  1. By using relaxed R1CS technology, the randomness requirement in the proof process is reduced, improving efficiency.

  2. Support incremental computation, allowing complex functions to be calculated step by step without the need to process all calculations at once.

  3. Supports polynomial calculations and can handle more complex proof tasks.

  4. Improved the practicality of zk-SNARKs in large-scale applications.

Nova also has some limitations:

  1. Due to the use of relaxed R1CS, the proof strength may be slightly lower than that of traditional R1CS systems.

  2. Implementation is relatively complex, increasing the difficulty of use and maintenance.

Despite this, Nova still occupies an important position in the field of zk-SNARKs. It has opened new paths for the development of zk-SNARKs and expanded the scope of applications, especially suitable for scenarios that require handling large-scale data or complex computations.

The core implementation of Nova includes:

  1. R1CS-related data structures and algorithms
  2. Polynomial Computation and Evaluation
  3. Non-interactive folding scheme ) NIFS (
  4. Spartan Protocol
  5. Polynomial Commitment Scheme Based on Inner Product Argument

By combining these innovative technologies, Nova has achieved an efficient and flexible zk-SNARKs system, providing new solutions for blockchain, identity verification, and other fields.

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DecentralizedEldervip
· 22h ago
Far from it, it's still Microsoft.
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MelonFieldvip
· 08-15 06:18
Unique, without boundaries~?
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HashBanditvip
· 08-15 06:15
ngl this r1cs stuff reminds me of my eth mining rig days... way less power hungry at least lmao
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HypotheticalLiquidatorvip
· 08-15 06:13
Relaxation = Risk control loophole Beware of the domino effect
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