Block et al. proposed a field-agnostic SNARK based on expand-accumulate codes in their paper, addressing the limitation of existing schemes that rely on specific finite fields, with proof generation time as low as 0.23 seconds, two orders of magnitude faster than non-field-agnostic SNARKs. Block等人在论文中提出了一种基于扩展累积码的域无关SNARK,解决了现有方案依赖特定有限域的问题,证明生成时间仅需0.23秒,比非域无关方案快两个数量级。
Notes
Proposed a field-agnostic SNARK based on expand-accumulate codes, independent of specific finite fields
Key technical contribution: proved these codes have constant rate and relative distance, solving an open problem
Prover time O(M log M), proof size O(√M), with significant concrete efficiency improvements
ECDSA verification on secp256k1 requires only 0.23s proof generation, 100x faster than non-field-agnostic SNARKs
Compared to Brakedown, proof size reduced by 1.9-2.8x with only 1.2x overhead in prover time
Features transparent setup and plausible post-quantum security, suitable for various practical applications
提出基于扩展累积码的域无关SNARK,不依赖特定有限域
主要技术贡献:证明这些码具有恒定速率和相对距离,解决先前开放问题
证明者时间为O(M log M),证明大小为O(√M),具体效率显著提升
ECDSA验证在secp256k1曲线上证明生成仅需0.23秒,比非域无关方案快100倍
相比Brakedown,证明大小减少1.9-2.8倍,证明者时间仅增加1.2倍开销
具有透明设置和潜在的后量子安全性,适用于多种实际应用场景
零知识证明zkDaily
Q&A Deep Dive 💬今日要点 深入解析 💬
Wed星期三
02.04
2026
Why is being field-agnostic an important property for SNARKs? 为什么“域无关”对 SNARK 来说是一个重要特性?
Many real-world cryptographic algorithms operate over specific finite fields or curve scalar fields. Traditional SNARKs often require costly field embeddings. Field-agnostic SNARKs work directly over the native field, significantly reducing overhead. 许多实际密码算法运行在特定有限域或椭圆曲线标量域上。传统 SNARK 若强制使用特定域,往往需要昂贵的域嵌入。域无关 SNARK 可以直接在原生域上工作,大幅降低证明开销。
Why is proving constant rate and relative distance for expand-accumulate codes important? 证明扩展累积码具有恒定速率和相对距离为何重要?
Constant rate and relative distance are crucial coding properties for efficient SNARKs. This result resolves a long-standing open problem and ensures proof size and soundness do not degrade as the system scales. 恒定速率和相对距离是构建高效 SNARK 的关键编码性质。该结果解决了一个长期开放问题,保证了在规模扩展时,证明大小和可靠性不会迅速恶化。
What does an O(M log M) prover complexity imply in practice? O(M log M) 的证明者复杂度在实践中意味着什么?
This complexity avoids reliance on field-specific FFTs, making implementations more general and engineering-friendly. With small constants, it enables sub-second proofs even for complex circuits like ECDSA verification. 该复杂度避免了对域特定 FFT 的依赖,使实现更通用且工程友好。在实际规模下,常数因子较小,使得在复杂电路如 ECDSA 验证中也能实现亚秒级证明。