NMF-based GPU accelerated coronagraphy pipeline

We present a generalized non-negative factorization (NMF)-based data reduction pipeline for circumstellar disk and exoplanet detection. By using an adaptable pre-processing routine that applies algorithmic masks and corrections to improper data, we are able to easily offload the computationally-intensive NMF algorithm to a Graphics Processing Unit (GPU), significantly increasing computational efficiency. NMF has been shown to better preserve disk structural features compared to other post-processing approaches and has demonstrated improvements in the analysis of archival data. The adaptive pre-processing routine of this pipeline, which automatically aligns and applies image corrections to the raw data, is shown to significantly improve chromatic halo suppression. Utilizing HST-STIS and JWST-MIRI coronagraphic datasets, we demonstrate a factor of five increase in real-time computational efficiency by using GPUs to perform NMF compared to using CPUs. Additionally, we demonstrate the usefulness of higher numbers of NMF components with SNR and contrast improvements, which necessitates the use of a more computationally efficient approach for data reduction.