Technical Announcement: The Self-Organizing Order Book (SOOB)

README: Empirical Validation of O(1) Complexity in SOOB Dataset: UKE_Gradual_Stress_Test.csv Author: Rayan S. Hammad Version: 2.1 (Performance & Complexity Validation) 1. Overview This dataset contains the raw telemetry for the Self-Organizing Order Book (SOOB) during a massive-scale gradual stress test. The objective was to determine if the SOOB's spiral architecture maintains constant-time complexity (O(1)) as volume scales toward 2 billion transactions, bypassing the logarithmic degradation (O(\log N)) inherent in legacy FIFO/PTP tree-based matching engines. 2. Methodology Test Environment: High-frequency execution manifold. Volume Range: 50,000 to 2,000,000,000 transactions. Metric Captured: elapsed_sec (cumulative time) and throughput_tx_ms (transactions processed per millisecond). Logic Applied: Adaptive Manifold with Golden Ratio decay function for order prioritization. 3. Key Observations & Proof of O(1) The data demonstrates that after an initial "geometric alignment" phase (warm-up), throughput stabilizes at a peak of approximately 922,000 tx/ms. Complexity Signature: Unlike legacy systems where throughput drops as the database grows, the SOOB maintains a flat performance curve from $N = 1.2B$ to $N = 2.0B$. This suggests that the cost of placing/matching an order is independent of the total volume in the book. Stability Shocks: Vertical shifts in the time-domain reflect the SOOB's self-reorganization triggers, which ensure market stability and prevent flash-crashing without compromising execution speed. 4. Column Descriptions volume: The total number of transactions processed. elapsed_sec: The cumulative time taken to reach the corresponding volume. throughput_tx_ms: Calculated as $(\Delta Volume / \Delta Time)$ in milliseconds, representing the real-time efficiency of the spiral architecture. 5. Usage for Researchers This data is provided to validate the scalability claims of the SOOB. Researchers can utilize this CSV to model the efficiency of the Hammad-Arrhenius Proof within financial kinetics.README: 自组织订单簿（Self-Organizing Order Book，SOOB）O(1)复杂度实证验证 数据集：UKE_Gradual_Stress_Test.csv 作者：雷扬·S·哈马德（Rayan S. Hammad） 版本：2.1（性能与复杂度验证） 1. 概述 本数据集包含自组织订单簿（Self-Organizing Order Book，SOOB）在大规模渐进压力测试中的原始遥测数据。本次测试的核心目标为验证：当交易量规模扩张至20亿笔交易时，SOOB的螺旋架构能否维持恒定时间复杂度（O(1)），从而规避传统基于先进先出（FIFO）/点对点（PTP）树型撮合引擎固有的对数级复杂度退化（O(log N)）问题。 2. 测试方法 测试环境：高频执行流形 交易量范围：50,000至2,000,000,000笔交易 采集指标：elapsed_sec（累计耗时）与throughput_tx_ms（每毫秒处理交易数） 应用逻辑：采用自适应流形与黄金比例衰减函数实现订单优先级排序 3. 关键观测与O(1)复杂度验证 本次数据显示，在经历初始“几何对齐”预热阶段后，系统吞吐量稳定在约922,000笔/毫秒的峰值水平。 复杂度特征：与传统系统随数据库规模扩大而吞吐量下降的情况不同，SOOB在交易量N从12亿至20亿区间内始终保持平坦的性能曲线。这表明订单的挂单与撮合成本与订单簿总交易量无关。 稳定性扰动：时域中的垂直偏移对应SOOB的自重组触发机制，该机制可在不牺牲执行速度的前提下保障市场稳定性，避免闪崩问题。 4. 字段说明 volume：累计处理的总交易笔数 elapsed_sec：完成对应交易量所需的累计耗时 throughput_tx_ms：以毫秒为单位计算的(Δ交易量 / Δ耗时)，用于表征螺旋架构的实时执行效率 5. 科研用途 本数据集用于验证SOOB的可扩展性宣称，研究人员可借助该CSV文件建模金融动力学中的哈马德-阿伦尼乌斯证明（Hammad-Arrhenius Proof）。