Optimizing NILC Extractions of the Thermal Sunyaev–Zel’Dovich Effect with Deep Learning
Cameron T. Pratt,
Zhijie Qu,
Joel N. Bregman
et al.
Abstract:All-sky maps of the thermal Sunyaev–Zel’dovich effect (SZ) tend to suffer from systematic features arising from the component-separation techniques used to extract the signal. In this work, we investigate one of these methods, known as needlet internal linear combination (NILC), and test its performance on simulated data. We show that NILC estimates are strongly affected by the choice of the spatial localization parameter (Γ), which controls a bias-variance trade-off. Typically, NILC extractions assume a fixed… Show more
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