Wang and Zhang proposed UltraFold, the first distributed BaseFold PCS supporting general polynomials, scaling to any number of workers while maintaining succinct proof size. Wang和Zhang在论文中提出了UltraFold,首个支持通用多项式、可扩展至任意数量工作节点且保持证明简洁性的分布式BaseFold多项式承诺方案。
Notes
Transparent, code-based PCS like BaseFold are suitable for large-scale ZKPs but limited by single-machine capacity.
Existing distributed approaches have limitations: specific polynomial structures, proof size growth with workers, poor scalability.
UltraFold uses interleaved Merkle leaf layout for efficient distributed commitment/opening with one all-to-all exchange.
Packed Merkle trees reduce hashing overhead, lowering prover time and proof size.
Scheme avoids trusted setup, relies on standard hash assumptions, offers post-quantum security.
BaseFold等透明、基于代码的PCS适合大规模ZKP,但单机处理能力有限
现有分布式方案存在限制:仅支持特定结构多项式、证明大小随工作节点增加、扩展性不足
UltraFold通过交错Merkle叶布局实现高效分布式承诺和打开,仅需一次部分编码值的全交换
采用打包Merkle树减少开销,降低证明者时间和证明大小
实验显示,256个单核工作节点可在2秒内处理1.34亿系数多项式,证明大小216KB
方案避免可信设置,基于标准哈希假设,提供后量子安全性
零知识证明zkDaily
Q&A Deep Dive 💬今日要点 深入解析 💬
Sun星期日
02.22
2026
What core limitations of prior distributed attempts does UltraFold address? UltraFold 相比以往分布式尝试解决了哪些核心问题?
It supports general polynomials, scales to any number of workers, and keeps proof size independent of worker count. This avoids communication blowup or proof inflation. 它支持一般多项式结构,可扩展到任意数量工作节点,并且证明大小不随节点数量增长。这避免了通信或证明膨胀的问题。
Why do packed Merkle trees reduce hashing overhead? 为什么使用 packed Merkle trees 能降低哈希开销?
Packed structures batch multiple leaf values per node, reducing tree depth and total hash computations, which lowers prover time and proof size. Packed 结构在单个节点中合并多个叶子值进行批量哈希,减少树层级与哈希次数,从而降低证明时间和证明大小。
Why is proof size independence from worker count a key property? 为何证明大小独立于工作节点数量是关键性质?
If proof size grew with worker count, horizontal scaling would increase verification cost. UltraFold preserves succinctness, ensuring scalability does not harm verifier efficiency. 若证明大小随节点数量增长,则横向扩展会导致验证成本上升。UltraFold 保持证明简洁性,使可扩展性不会牺牲验证效率。