Search

The future 21 cm intensity mapping observations constitute a promising way to trace the matter distribution of the Universe and probe cosmology. Here we assess its capability for cosmological constraints using as a case study the BINGO radio telescope, that will survey the Universe at low redshifts ($0.13 < z < 0.45$). We use neural networks (NNs) to map summary statistics, namely, the angular power spectrum (APS) and the Minkowski functionals (MFs), calculated from simulations into cosmological parameters. Our simulations span a wide grid of cosmologies, sampled under the $\Lambda$CDM scenario, {$\Omega_c, h$}, and under an extension assuming the Chevallier-Polarski-Linder (CPL) parameterization, {$\Omega_c, h, w_0, w_a$}. In general, NNs trained over APS outperform those using MFs, while their combination provides 27% (5%) tighter error ellipse in the $\Omega_c-h$ plane under the $\Lambda$CDM scenario (CPL parameterization) compared to the individual use of the APS. Their combination allows predicting $\Omega_c$ and $h$ with 4.9% and 1.6% fractional errors, respectively, which increases to 6.4% and 3.7% under CPL parameterization. Although we find large bias on $w_a$ estimates, we still predict $w_0$ with 24.3% error. We also confirm our results to be robust to foreground contamination, besides finding the instrumental noise to cause the greater impact on the predictions. Still, our results illustrate the capability of future low redshift 21 cm observations in providing competitive cosmological constraints using NNs, showing the ease of combining different summary statistics., Comment: 17 pages, 13 figures

A new and promising technique for observing the Universe and study the dark sector is the intensity mapping of the redshifted 21cm line of neutral hydrogen (HI). The BINGO radio telescope will use the 21cm line to map the Universe in the redshift range $0.127 \le z \le 0.449$, in a tomographic approach, with the main goal of probing BAO. This work presents the forecasts of measuring the transversal BAO signal during the BINGO Phase 1 operation. We use two clustering estimators, the two-point angular correlation function (ACF) and the angular power spectrum (APS), and a template-based method to model the ACF and APS estimated from simulations of the BINGO region and extract the BAO information. The tomographic approach allows the combination of redshift bins to improve the template fitting performance. We find that each clustering estimator shows different sensitivities to specific redshift ranges, although both of them perform better at higher redshifts. In general, the APS estimator provides slightly better estimates, with smaller uncertainties and larger probability of detection of the BAO signal, achieving $\gtrsim 90$\% at higher redshifts. We investigate the contribution from instrumental noise and residual foreground signals and find that the former has the greater impact, getting more significant as the redshift increases, in particular the APS estimator. Indeed, including noise in the analysis increases the uncertainty up to a factor of $\sim 2.2$ at higher redshifts. Foreground residuals, in contrast, do not significantly affect our final uncertainties. In summary, our results show that, even including semi-realistic systematic effects, BINGO has the potential to successfully measure the BAO scale in radio frequencies. (Abridged), Comment: 18 pages, 6 figures. Submitted to A&A

To recover the 21 cm hydrogen line, it is essential to separate the cosmological signal from the much stronger foreground contributions at radio frequencies. The BINGO radio telescope is designed to measure the 21 cm line and detect BAOs using the intensity mapping technique. This work analyses the performance of the GNILC method, combined with a power spectrum debiasing procedure. The method was applied to a simulated BINGO mission, building upon previous work from the collaboration. It compares two different synchrotron emission models and different instrumental configurations, in addition to the combination with ancillary data to optimize both the foreground removal and recovery of the 21 cm signal across the full BINGO frequency band, as well as to determine an optimal number of frequency bands for the signal recovery. We have produced foreground emissions maps using the Planck Sky Model, the cosmological Hi emission maps are generated using the FLASK package and thermal noise maps are created according to the instrumental setup. We apply the GNILC method to the simulated sky maps to separate the Hi plus thermal noise contribution and, through a debiasing procedure, recover an estimate of the noiseless 21 cm power spectrum. We found a near optimal reconstruction of the Hi signal using a 80 bins configuration, which resulted in a power spectrum reconstruction average error over all frequencies of 3%. Furthermore, our tests showed that GNILC is robust against different synchrotron emission models. Finally, adding an extra channel with CBASS foregrounds information, we reduced the estimation error of the 21 cm signal. The optimisation of our previous work, producing a configuration with an optimal number of channels for binning the data, impacts greatly the decisions regarding BINGO hardware configuration before commissioning., Comment: Submitted to A&A