Target Detection Framework for Lobster Eye X-Ray Telescopes with Machine Learning Algorithms
This work addresses data processing for astronomers using lobster eye X-ray telescopes, offering a practical solution for detecting X-ray transients, though it appears incremental as it builds on existing methods.
The paper tackled the challenge of detecting celestial targets in images from lobster eye X-ray telescopes, which are distorted by unique point spread functions, by integrating machine learning algorithms into a detection framework. The result was a framework achieving over 94% purity and over 90% completeness for targets with flux above 3 mCrab, and over 94% purity for lower flux targets at acceptable time costs.
Lobster eye telescopes are ideal monitors to detect X-ray transients, because they could observe celestial objects over a wide field of view in X-ray band. However, images obtained by lobster eye telescopes are modified by their unique point spread functions, making it hard to design a high efficiency target detection algorithm. In this paper, we integrate several machine learning algorithms to build a target detection framework for data obtained by lobster eye telescopes. Our framework would firstly generate two 2D images with different pixel scales according to positions of photons on the detector. Then an algorithm based on morphological operations and two neural networks would be used to detect candidates of celestial objects with different flux from these 2D images. At last, a random forest algorithm will be used to pick up final detection results from candidates obtained by previous steps. Tested with simulated data of the Wide-field X-ray Telescope onboard the Einstein Probe, our detection framework could achieve over 94% purity and over 90% completeness for targets with flux more than 3 mCrab (9.6 * 10-11 erg/cm2/s) and more than 94% purity and moderate completeness for targets with lower flux at acceptable time cost. The framework proposed in this paper could be used as references for data processing methods developed for other lobster eye X-ray telescopes.