AI 中文总结
研究系外行星探测中受散斑限制的问题，提出用梯度提升决策树的增强相干差分成像方法EPICX，将差分信号建模为高维回归问题，优化散斑噪声与行星信号区分，并用模拟数据验证了该方法。
AI 中文摘要
日冕仪成像系外行星时受到类似行星的残余散斑限制。先进的后处理对当前及未来地面或空间仪器至关重要。当前技术耗时且有限，如ADI需长序列且在小间距受限，RDI耗时且对散斑演化敏感。相干差分成像（CDI）利用散斑与行星间光的非相干性提供了更快的替代方案，但依赖精确仪器模型限制了其性能。本文引入EPICX，一种使用梯度提升决策树的增强CDI方法，将差分信号建模为高维回归问题，优化相干散斑噪声与非相干行星信号的区分。使用不同日冕仪的模拟数据验证了该增强方法，包括JWST和Roman上的。
英文摘要
Coronagraphic imaging of exoplanets is limited by residual speckles that mimic planets. Advanced post-processing is essential for current and future instruments on the ground or in space. Current techniques are time-intensive and limited. ADI requires long sequences and is limited at small separations. RDI is also time-consuming and sensitive to speckle evolution, leading to imperfect subtraction. Coherence Differential Imaging (CDI), which we successfully demonstrated on SPHERE, offers a faster alternative by using the light incoherence between speckles and planets. However, its reliance on accurate instrumental models limits its performance. In this work, we introduce EPICX, an enhanced CDI method using gradient-boosted decision trees. EPICX models the differential signal as a high-dimensional regression problem, optimizing the discrimination between coherent speckle noise and incoherent planet signal. We validate this enhanced CDI method using simulated data for different coronagraphs, including those aboard JWST and Roman.
Comments15 pages, 7 figures, proceedings of SPIE Astronomical Telescopes + Instrumentation 2026, 14145-99
