发表机构
Offchain Labs（Offchain Labs）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究Base将优先级燃气拍卖从2秒拆分为十个200毫秒子拍卖后，搜索者有效费用下降0.187 gwei，费用压缩显著，并揭示延迟影响排序，为Rollup拍卖节奏治理提供依据。
AI 中文摘要
Flashblocks将区块的优先级燃气拍卖划分为更短的顺序拍卖，在区块完成前提交交易顺序。我们研究这种拍卖节奏如何影响自动化套利者（即搜索者）的出价与竞争。2025年7月，Base将单一的2秒拍卖替换为十个200毫秒的拍卖。我们利用这一变化，仅从链上数据估计搜索者的反应。在一个包含3,032名搜索者和8,053个活动匹配对照的地址-日面板上，双重差分设计估计有效优先级费用下降0.187 gwei（占搜索者前期均值的59%）。搜索者优先级费用价值中在区块燃气前十分之一内支付的比例从0.98降至0.28。这种费用压缩是识别出的效应。回滚率响应未被（因果地）识别，仅作描述性报告。在单个机会层面，获胜费用分为一个近似不变的底价和一个竞争溢价。在高竞争下，溢价随拍卖时长近似线性增长，在低竞争下增长较缓。一个具有不确定到达时间和失败搜索者部分支付的第一价格拍卖模型解释了这一模式。我们将尝试匹配到其竞争的池。在按价值计算的1.9%至2.7%的竞争机会中，较高费用的交易在较早落地的较低费用获胜者之后回滚，这是一个上界。因此，延迟决定了部分排序。一个微观拍卖模型预测，当出价接近非零底价时，将窗口缩短至200毫秒以下会产生递减的回报。诸如Arbitrum One等Rollup现在将拍卖节奏设为治理可调参数，因此这些估计为如何设置该参数提供了信息。
英文摘要
Flashblocks divide a block's priority gas auction into shorter sequential auctions that commit transaction order before the block is complete. We ask how this auction cadence affects bidding and competition among automated arbitrageurs, or searchers. In July 2025 Base replaced a single 2 s auction with ten 200 ms auctions. We use this change to estimate the searcher response from on-chain data alone. On an address-day panel of 3,032 searchers and 8,053 activity-matched controls, a difference-in-differences design estimates a 0.187 gwei fall in the effective priority fee (59% of the searcher pre-period mean). The share of searcher priority-fee value paid in the first tenth of block gas falls from 0.98 to 0.28. This fee compression is the identified effect. The revert-rate response is not (causally) identified and is reported descriptively. At the level of a single opportunity, the winning fee splits into an approximately invariant floor and a competitive premium. The premium scales about linearly with auction duration at high contention and less steeply at low contention. A first-price auction model with uncertain arrival and partial payments by losing searchers accounts for this pattern. We match attempts to the pool they contest. A higher-fee transaction reverts behind a lower-fee winner that landed earlier in 1.9 to 2.7% of contested opportunities by value, an upper bound. Latency therefore decides part of the ordering. A micro-auction model projects diminishing returns from shortening the window below 200 ms, as bids approach a nonzero floor. Rollups such as Arbitrum One now make auction cadence a governance tunable parameter, so these estimates inform how it is set.
Comments32 pages, 5 figures, includes appendices
