Partially Constrained Internal Linear Combination: a method for low-noise CMB foreground mitigation

Understand

Internal Linear Combination (ILC) methods are some of the most widely used multi-frequency cleaning techniques employed in CMB data analysis.

• These methods reduce foregrounds by minimizing the total variance in the coadded map (subject to a signal-preservation constraint), although often significant foreground residuals or biases remain.
• A modification to the ILC method is the constrained ILC (cILC), which explicitly nulls certain foreground components; however, this foreground nulling often comes at a high price for ground-based CMB datasets, with the map noise increasing significantly on small scales.
• In this paper we explore a new method, the partially constrained ILC (pcILC), which allows us to optimize the tradeoff between foreground bias and variance in ILC methods.