Briefing

The primary barrier to mass adoption of verifiable computation is the high asymptotic complexity of the prover, often quasi-linear, which makes proving large computations prohibitively slow. The Blaze SNARK proposes a new construction that achieves the theoretical optimum of $O(N)$ linear-time proving complexity and $O(log^2 N)$ verifier complexity. This is accomplished by encoding the witness using the highly efficient Repeat-Accumulate-Accumulate (RAA) codes and leveraging a novel code switching technique to transition to a Reed-Solomon-based polynomial commitment scheme. This fundamental efficiency gain transforms the scalability landscape, making it feasible to generate proofs for computations of unprecedented size, accelerating the path to universal verifiable computation.

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Context

Prior to this work, the state-of-the-art in transparent SNARKs, such as those based on the FRI protocol, typically achieved quasi-linear prover time, $O(N log N)$, or required complex trusted setups for better performance. The challenge was to break the quasi-linear barrier while maintaining a transparent setup and succinct verification, a theoretical bottleneck that limited the practical size of provable programs. This theoretical limitation presented a major obstacle to building general-purpose, high-throughput verifiable virtual machines.

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Analysis

The core mechanism of Blaze is a cryptographic code-switching technique. It begins by encoding the computation’s witness using Repeat-Accumulate-Accumulate (RAA) codes, which are known for their linear-time encoding complexity $O(N)$. The system then uses a novel transformation to convert the RAA-encoded data into a form compatible with a Reed-Solomon code.

This code-switching allows the system to use an efficient, polylogarithmic-time verifier, specifically one derived from the Basefold polynomial commitment scheme. This two-stage process effectively achieves the best asymptotic complexities for both the prover and the verifier in a single, transparent system, eliminating the quasi-linear overhead.

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Parameters

  • Prover Complexity → $O(N)$ field operations (The theoretical optimum for proving an $N$-sized computation)
  • Verifier Complexity → $O(log^2 N)$ (A polylogarithmic cost, making verification extremely fast)
  • Commitment Cost → Dominated by 8n field additions (Concretely efficient, dominated by simple XORs over binary fields)

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Outlook

This research establishes a new performance baseline for all future transparent SNARKs, shifting the focus from asymptotic complexity to concrete optimization of linear-time operations. The next step involves integrating this primitive into general-purpose zk-VMs, which could unlock decentralized applications requiring the verification of massive datasets or complex AI models on-chain. This advancement moves verifiable computation from a theoretical ideal to a practical reality within the next few years.

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Verdict

Blaze redefines the fundamental efficiency trade-off in zero-knowledge cryptography, establishing the asymptotic gold standard for transparent, scalable verifiable computation.

Zero knowledge proofs, Succinct arguments, Linear prover time, Polylogarithmic verifier, Coding theory, RAA codes, Reed Solomon codes, Polynomial commitment, Proof system efficiency, Trustless setup, Verifiable computation, zk-SNARK construction, Algebraic complexity, Cryptographic primitives, Proof aggregation Signal Acquired from → Cryptology ePrint Archive

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polynomial commitment scheme

Definition ∞ A polynomial commitment scheme is a cryptographic primitive that allows a prover to commit to a polynomial in a way that later permits opening the commitment at specific points, proving the polynomial's evaluation at those points without revealing the entire polynomial.

linear prover time

Definition ∞ Linear prover time refers to the computational time required for a prover to generate a cryptographic proof that scales linearly with the size of the computation being proven.

computation

Definition ∞ Computation refers to the process of performing calculations and executing algorithms, often utilizing specialized hardware or software.

polynomial commitment

Definition ∞ Polynomial commitment is a cryptographic primitive that allows a prover to commit to a polynomial in a concise manner.

theoretical optimum

Definition ∞ Theoretical Optimum represents the ideal or best possible performance, efficiency, or security level that a system or protocol could achieve under perfect conditions.

verifier complexity

Definition ∞ Verifier complexity refers to the computational resources, such as time and memory, required for a party to check the correctness of a given proof.

verifiable computation

Definition ∞ Verifiable computation is a cryptographic technique that allows a party to execute a computation and produce a proof that the computation was performed correctly.

efficiency

Definition ∞ Efficiency denotes the capacity to achieve maximal output with minimal expenditure of effort or resources.