The HI intensity mapping bispectrum including observational effects

Cunnington, Steven; Watkinson, Catherine; Pourtsidou, Alkistis

doi:10.48550/arxiv.2102.11153

Cited by 4 publications

(4 citation statements)

References 77 publications

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“…This relation dates back to local measurements performed by Zwaan et al (2005) and Keres et al (2003), which was incorporated in the H modelling in Baugh et al (2004) and Power et al (2010). This is the assumption made in previous IM studies (Cunnington et al 2020a(Cunnington et al , 2021a and will be our default option here (see discussion at the end of the subsection).…”

Section: From Dark Matter To Hmentioning

confidence: 99%

HI intensity mapping correlation function from UNIT simulations: BAO and observationally induced anisotropy

Avila,

Vos-Ginés,

Cunnington

et al. 2021

Preprint

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We study the clustering of H intensity maps produced from simulations with a focus on baryonic acoustic oscillations (BAO) and the effects induced by telescope beam smoothing and foreground cleaning. We start by creating a H catalogue at 𝑧 = 1.321 based on the Semi-Analytic Galaxy Evolution (SAGE) model applied to the UNIT simulations. With this catalogue we investigate the relation between model H and the dark matter haloes and we also study the abundance of H , Ω H , predicted by this model. We then create synthetic H intensity maps with a Nearest-Grid-Point approach. In order to simulate the telescope beam effect, a Gaussian smoothing is applied on the plane perpendicular to the line of sight. The effect of foreground removal methods is simulated by exponentially damping the largest wavelength Fourier modes on the radial direction. We study the anisotropic 2-point correlation function (2PCF) 𝜉 (𝑟 ⊥ , 𝑟 ) and how it is affected by the aforementioned observational effects. In order to better isolate the BAO signal, we study several 2PCF 𝜇-wedges (with a restricted range of orientations 𝜇) tailored to address the systematics effects and we compare them with different definitions of radial 2PCFs. Finally, we discuss our findings in the context of an SKA-like survey, finding a clear BAO signal in most of the estimators here proposed.

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Section: From Dark Matter To Hmentioning

confidence: 99%

HI intensity mapping correlation function from UNIT simulations: BAO and observationally induced anisotropy

Avila,

Vos-Ginés,

Cunnington

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…This relation dates back to local measurements performed by Zwaan et al (2005) and Keres et al (2003), which was incorporated in the H i modelling in Baugh et al (2004) and Power et al (2010). This is the assumption made in previous IM studies (Cunnington et al 2020a(Cunnington et al , 2021a and will be our default option here (see discussion at the end of the subsection).…”

Section: From Dark Matter To H Imentioning

confidence: 99%

H i IM correlation function from UNIT simulations: BAO and observationally induced anisotropy

Ávila

Vos-Ginés

Cunnington

et al. 2021

Monthly Notices of the Royal Astronomical Society

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We study the clustering of H i intensity maps produced from simulations with a focus on baryonic acoustic oscillations (BAO) and the effects induced by telescope beam smoothing and foreground cleaning. We start by creating a H i catalogue at z = 1.321 based on the Semi-Analytic Galaxy Evolution (SAGE) model applied to the UNIT simulations. With this catalogue we investigate the relation between model H i and the dark matter haloes and we also study the abundance of H i, $\Omega _\rm {H\,\small {I}}$, predicted by this model. We then create synthetic H i intensity maps with a Nearest-Grid-Point approach. In order to simulate the telescope beam effect, a Gaussian smoothing is applied on the plane perpendicular to the line of sight. The effect of foreground removal methods is simulated by exponentially damping the largest wavelength Fourier modes on the radial direction. We study the anisotropic 2-point correlation function (2PCF) ξ(r⊥, r∥) and how it is affected by the aforementioned observational effects. In order to better isolate the BAO signal, we study several 2PCF μ-wedges (with a restricted range of orientations μ) tailored to address the systematics effects and we compare them with different definitions of radial 2PCFs. Finally, we discuss our findings in the context of an SKA-like survey, finding a clear BAO signal in most of the estimators here proposed.

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“…The analysis of the simulations and the quality assessment for the residual maps after cleaning require estimators to compress the threedimensional information contained in the data-cubes. Although some studies have started to explore observational effects in higher-order statistics (Cunnington et al 2021a;Jolicoeur et al 2021), in this work, we focus on 2-point summary statistics, looking both at the angular and line-of-sight directions, keeping the two separated to distinguish features that could show up independently in each direction. In particular, we compute the angular power spectrum as a function of frequency 𝐶 ℓ (𝜈) (Section 4.1) and the one-dimensional line-of-sight power spectrum 𝑃 los (𝑘 𝜈 ) (Section 4.2).…”

Section: Summary Statisticsmentioning

confidence: 99%

SKAO HI Intensity Mapping: Blind Foreground Subtraction Challenge

Spinelli,

Carucci,

Cunnington

et al. 2021

Preprint

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Neutral Hydrogen Intensity Mapping (H IM) surveys will be a powerful new probe of cosmology. However, strong astrophysical foregrounds contaminate the signal and their coupling with instrumental systematics further increases the data cleaning complexity. In this work, we simulate a realistic single-dish H IM survey of a 5000 deg 2 patch in the 950 − 1400 MHz range, with both the MID telescope of the SKA Observatory (SKAO) and MeerKAT, its precursor. We include a state-of-the-art H simulations and explore different foreground models and instrumental effects such as non-homogeneous thermal noise and beam side-lobes. We perform the first Blind Foreground Subtraction Challenge for H IM on these synthetic data-cubes, aiming to characterise the performance of available foreground cleaning methods with no prior knowledge of the sky components and noise level. Nine foreground cleaning pipelines joined the Challenge, based on statistical source separation algorithms, blind polynomial fitting, and an astrophysical-informed parametric fit to foregrounds. We devise metrics to compare the pipeline performances quantitatively. In general, they can recover the input maps' 2-point statistics within 20 per cent in the range of scales least affected by the telescope beam. However, spurious artefacts appear in the cleaned maps due to interactions between the foreground structure and the beam side-lobes. We conclude that it is fundamental to develop accurate beam deconvolution algorithms and test data post-processing steps carefully before cleaning. This study was performed as part of SKAO preparatory work by the H IM Focus Group of the SKA Cosmology Science Working Group.

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The HI intensity mapping bispectrum including observational effects

Cited by 4 publications

References 77 publications

HI intensity mapping correlation function from UNIT simulations: BAO and observationally induced anisotropy

HI intensity mapping correlation function from UNIT simulations: BAO and observationally induced anisotropy

H i IM correlation function from UNIT simulations: BAO and observationally induced anisotropy

SKAO HI Intensity Mapping: Blind Foreground Subtraction Challenge

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