Simulated multitracer analyses with H I intensity mapping

We use full sky simulations, including the effects of foreground contamination and removal, to explore multitracer synergies between a SKA-like 21cm intensity mapping survey and an LSST-like photometric galaxy redshift survey. In particular we study ratios of auto and cross-correlations between the two tracers as estimators of the ratio of their biases, a quantity that should benefit considerably from the cosmic variance (CV) cancellation of the multitracer approach. We show how well we should be able to measure the bias ratio on very large scales (down to ℓ ∼ 3), which is crucial to measure primordial non-Gaussianity and general relativistic effects on large-scale structure. We find that, in the absence of foregrounds but with realistic noise levels of such surveys, the multitracer estimators are able to improve on the sensitivity of a cosmic variance contaminated measurement by a factor of 2-4. When foregrounds are included, estimators using the 21cm autocorrelation become biased. However, we show that cross-correlation estimators are immune to this and do not incur in any significant penalty in terms of sensitivity from discarding the autocorrelation data. However, the loss of long-wavelength radial modes caused by foreground removal in combination with the low-redshift resolution of photometric surveys, reduces the sensitivity of the multitracer estimator, albeit still better than the cosmic variance contaminated scenario even in the noise free case. Finally we explore different alternative avenues to avoid this problem.