论文标题
WS-SNAPSHOT：用于宽场和大型成像的有效算法
WS-Snapshot: An effective algorithm for wide-field and large-scale imaging
论文作者
论文摘要
平方公里阵列（SKA）是世界上最大的无线电干涉仪。高精度，宽大和大型成像显着挑战了SKA科学数据处理器（SDP）的构建。我们提出了一种基于改进的W堆栈和快照的混合成像方法。通过拟合快照$ UV $平面来减少W范围，从而有效地增强了改进的W堆积算法的性能。我们提出了WS-Snapshot的详细实现。通过全尺度SKA1-LOW模拟，我们介绍了不同参数案例的成像性能和成像质量结果。结果表明，WS-SNAPSHOT方法可以实现更有效的分布处理处理，并大大减少了在可接受的精度范围内的计算时间开销，这对于随后的SKA科学研究至关重要。
The Square Kilometre Array (SKA) is the largest radio interferometer under construction in the world. The high accuracy, wide-field and large size imaging significantly challenge the construction of the Science Data Processor (SDP) of SKA. We propose a hybrid imaging method based on improved W-Stacking and snapshots. The w range is reduced by fitting the snapshot $uv$ plane, thus effectively enhancing the performance of the improved W-Stacking algorithm. We present a detailed implementation of WS-Snapshot. With full-scale SKA1-LOW simulations, we present the imaging performance and imaging quality results for different parameter cases. The results show that the WS-Snapshot method enables more efficient distributed processing and significantly reduces the computational time overhead within an acceptable accuracy range, which would be crucial for subsequent SKA science studies.
