Partially constrained internal linear combination: A method for low-noise CMB foreground mitigation
Abylkairov Y.S. Darwish O. Hill J.C. Sherwin B.D.
11 May 2021American Physical Society
Physical Review D
2021#103Issue 10
Internal linear combination (ILC) methods are some of the most widely used multifrequency cleaning techniques employed in cosmic microwave background (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, 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, which allows us to optimize the tradeoff between foreground bias and variance in ILC methods. In particular, this method allows us to minimize the variance subject to an inequality constraint requiring that the constrained foregrounds are reduced by at least a fixed factor, which can be chosen based on the foreground sensitivity of the intended application. We test our method on simulated sky maps for a Simons Observatory-like experiment; we find that for cleaning thermal Sunyaev-Zeldovich contamination at [3000,4800], if a small thermal Sunyaev-Zeldovich residual of 20% of the standard ILC residual can be tolerated, the variance of the CMB temperature map is reduced by at least 50% over the constrained ILC value. We also demonstrate an application of this method to reduce noise in CMB lensing reconstruction.
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Physics Department, Nazarbayev University, Nur-Sultan, 010000, Kazakhstan
Energetic Cosmos Laboratory, Nazarbayev University, Nur-Sultan, 010000, Kazakhstan
Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, CB3 0WA, United Kingdom
Department of Physics, Columbia University, New York, 10027, NY, United States
Center for Computational Astrophysics, Flatiron Institute, New York, 10010, NY, United States
Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge, CB3 OHA, United Kingdom
Physics Department
Energetic Cosmos Laboratory
Department of Applied Mathematics and Theoretical Physics
Department of Physics
Center for Computational Astrophysics
Kavli Institute for Cosmology
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