未来高能物理实验对探测器技术提出了越来越高的要求。近年来，随着电子学技术的进步，粒子流技术得到了长足的发展。粒子流的核心思想是充分利用探测器记录的信息，分别重建出带电粒子和中性粒子，以此来提升喷注、tau子、轻子等重要物理标的物的重建效率和重建精度。粒子流算法在直线对撞机、CMS实验上取得了巨大成功。但另一方面，目前的粒子流算法普遍较为复杂、性能高度依赖给定探测器几何，难以对探测器几何进行有效优化。同时，粒子流探测器的物理潜力尚待进一步发掘。.. Arbor算法是目前CEPC探测器使用的基准粒子流算法之一。本项目计划将Arbor算法完善成为一个适应多种实验类型和原型机测试平台的通用算法框架。该框架将为我国自主研发、优化PFA探测器提供良好基础，并成为参与相关国际合作的有利条件。

With the development of the electronic technology, the Particle Flow Algorithm made significant progress in recent years. The key idea of Particle Flow Algorithm is to measure each individual final state particle in the most suited sub-detector systems. It could improve the reconstruction efficiency and measurement accuracy for different physics objects, such as jet, tau and leptons. PFA has achieved huge successes at the future linear collider experiments and the CMS experiments. However, the existing PFAs are always very complicated, and their performance strongly depends on the detector geometry. It is difficult to use the existing PFA tools to optimise the detector geometry for future experiments. On the other hand, the full physics potential of the PFA oriented detectors could should also be explored. .. Arbor is one of the default PFA algorithm for the CEPC conceptual detector. In this project, we proposed to develop an generic PFA toolkit from Arbor algorithm. This toolkit, should be easily adjusted to different detector geometry and collision environments. This toolkit is expected to provide technical support for the PFA oriented detector design/optimisation efforts at China.