Interpreting the Unresolved Intensity of Cosmologically Redshifted Line Radiation

Abstract

Intensity mapping experiments survey the spectrum of diffuse line radiation rather than detect individual objects at high signal-to-noise ratio. Spectral maps of unresolved atomic and molecular line radiation contain threedimensional information about the density and environments of emitting gasand efficiently probe cosmological volumes out to high redshift. Intensity mapping survey volumes also contain all other sources of radiation at the frequencies of interest. Continuum foregrounds are typically~10 2 -10 3 times brighter than the cosmological signal. The instrumental response to bright foregrounds will produce new spectral degrees of freedom that are not known in advance, nor necessarily spectrally smooth. The intrinsic spectra of foregrounds may also not be wellknown in advance. We describe a general class of quadratic estimators to analyze data from single-dish intensity mapping experimentsand determine contaminated spectral modes from the data themselves. The key attribute of foregrounds is not that they are spectrally smooth, but instead that they have fewer bright spectral degrees of freedom than the cosmological signal. Spurious correlations between the signal and foregrounds produce additional bias. Compensation for signal attenuation must estimate and correct this bias. A successful intensity mapping experiment will control instrumental systematics that spread variance into new modes, and it must observe a large enough volume that contaminant modes can be determined independently from the signal on scales of interest.

Erasing the Milky Way: new cleaning technique applied to GBT intensity mapping data

“…The foregrounds for intensity mapping have fewer existing observational constraints than the microwave sky, however, the data contains more line-of-sight information as it extends over a wider frequency interval. Most foreground separation methods utilise the power-law dependence of the foregrounds in the frequency direction, where the techniques can be divided into parametric methods (Ansari et al 2008;Shaw et al 2014Shaw et al , 2015Zhang et al 2016) and blind methods (Wolz et al 2014;Switzer et al 2015;Olivari et al 2016). In this work, we perform foreground subtraction using an Independent Component Analysis (fastica, Hyvärinen 1999) motivated by its previous successful applications to CMB simulations (Maino et al 2002), epoch of reionization studies (Chapman et al 2012) and intensity mapping simulations (Wolz et al 2014).…”

Extracting H i cosmological signal with generalized needlet internal linear combination

“…Parametric methods use a model to describe some physical properties of the foregrounds. Others, such as Principal Component Analysis (PCA) (Masui et al 2013;Switzer et al 2013;Alonso et al 2015;Bigot-Sazy et al 2015), Independent Component Analysis (ICA) (Alonso et al 2015), FASTICA (Wolz et al 2014), inverse variance (Liu & Tegmark 2011), and quadratic estimators (Switzer et al 2015), use only the observed data to recover the HI signal and therefore do not assume a specific parametric model for the foregrounds.…”

Searching for H i imprints in cosmic web filaments with 21-cm intensity mapping

“…At these frequencies the radio foregrounds, mainly Galactic and extra-Galactic synchrotron emission, are two to three orders of magnitude brighter than the 21-cm emission. As mentioned, these maps are already foreground-cleaned; the identification and removal of these foregrounds at the map level is described in A18 and is based on the algorithm detailed in Switzer et al (2015). Given the dominant amplitude of the foregrounds, and their expected frequency smoothness compared to the 21-cm signal (Liu & Tegmark 2012), the cleaning is based on a Principal Component Analysis (PCA) in which the higher frequency correlated modes are removed.…”