Astrophysical constraints from future measurements of the kinetic Sunyaev-Zel'dovich power spectrum

Abstract

High-precision measurements of the Cosmic Microwave Background (CMB) will soon allow for the unprecedented detection of small-scale secondary anisotropies, such as the kinetic Sunyaev-Zel'dovich (kSZ) effect. Linking the kSZ power spectrum to the properties of ionising sources would provide an opportunity to use such observations to access astrophysical and cosmological information from the Epoch of Reionisation, including the morphology of ionised regions, while simultaneously improving CMB analyses. The aim of this work is to assess this potential of the kSZ power spectrum to measure reionisation-era galaxy properties. We repurpose the publicly available LoReLi II simulations, which track the evolution of neutral hydrogen during reionisation, to generate a training set of patchy kSZ angular power spectra. We then train an emulator using neural network regression in order to allow for efficient Bayesian inference, and conduct forecasts assuming mock observations from current and future CMB experiments. We find that measurements of the kSZ power spectrum from such surveys can provide meaningful constraints on several of the astrophysical model parameters of the LoReLi II suite, including the ionising escape fraction for which we expect a 14% relative error, on average. They also provide an independent measurement of the CMB optical depth, marginalised over the astrophysics and with error bars competitive with the cosmic variance limit from large scale surveys. The kSZ power spectrum offers a promising avenue for probing the properties of reionisation-era galaxies and providing an independent measurement of the CMB optical depth with upcoming CMB experiments. Since the error budget of our mock observations is dominated by emulator reconstruction errors, we expect our results could be further improved with a more extended simulation training set.

Figures (11)

• Figure 1: Electron overdensity power spectra derived from the LoReLi II database shown at the midpoint of reionisation, $x_\mathrm{HII}(z) = 0.5$. The spectra are coloured by the value of the three astrophysical parameters varied in our analysis.
• Figure 2: Ionisation histories $x_e(z)$, defined as the volume-averaged ionisation fraction, for all simulations used in our analysis, coloured by the value of $f_\mathrm{esc}$, the parameter with the greatest observed impact on the kSZ power spectrum.
• Figure 3: Emulated pkSZ spectra from the validation dataset, overlaid with the true values (marked with $+$) of each spectrum (top panel). The residual of the averaged emulator outputs (predicted $-$ true) is shown both unnormalised (middle panel) and normalised (bottom panel) by the cosmic variance of our fiducial kSZ signal. The estimated emulator $1\sigma$ error, as given by Eq. \ref{['eq:emu_err']} overlaid in yellow.
• Figure 4: Mock data points (red) and observational uncertainties for the two survey configurations considered in this work. Each individual contribution, consisting of sample variance (loose dotted), instrumental noise (loose dashed), and foreground residuals (dense dash-dotted), to the total assumed uncertainty (solid line) are shown for each survey. We also show the emulator error (violet long-dash-dotted line) -- identical between surveys. Both the patchy (gold dense dashed) and the homogeneous spectra (pink dense dotted) contribute to the total kSZ signal (red solid).
• Figure 5: The catalogue of patchy kSZ angular power spectra reconstructed from the LoReLi II simulations, coloured by the value of each fitted astrophysical parameter.