paper

Bayesian Multi-line Intensity Mapping

arXiv:2403.19740 · doi:10.3847/1538-4357/ad57b9

Abstract

Line intensity mapping (LIM) has emerged as a promising tool for probing the 3D large-scale structure through the aggregate emission of spectral lines. The presence of interloper lines poses a crucial challenge in extracting the signal from the target line in LIM. In this work, we introduce a novel method for LIM analysis that simultaneously extracts line signals from multiple spectral lines, utilizing the covariance of native LIM data elements defined in the spectral--angular space. We leverage correlated information from different lines to perform joint inference on all lines simultaneously, employing a Bayesian analysis framework. We present the formalism, demonstrate our technique with a mock survey setup resembling the SPHEREx deep field observation, and consider four spectral lines within the SPHEREx spectral coverage in the near infrared: H, \ion{O}{3}, H, and \ion{O}{2}. We demonstrate that our method can extract the power spectrum of all four lines at the level at . For the brightest line, H, the sensitivity can be achieved out to . Our technique offers a flexible framework for LIM analysis, enabling simultaneous inference of signals from multiple line emissions while accommodating diverse modeling constraints and parameterizations.

27 pages, 18 figures, accepted by ApJ

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