healpy: equal area pixelization and spherical harmonics transforms for data on the sphere in Python

Zonca, A.; Singer, L. P.; Lenz, Daniel; Reinecke, M.; Rosset, C.; Hivon, E.; Górski, K. M.

doi:10.21105/joss.01298

Cited by 741 publications

(505 citation statements)

References 4 publications

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“…This ensures each foreground type has a spectral smoothness through frequency that we utilise in the foreground clean. The outputs from this and the GSM produce fullsky HEALPix 5 (Górski et al 2005;Zonca et al 2019) maps but we convert them into flat-sky Cartesian maps in order to add to our Hi data. To do this we define an angular coordinate for each pixel on the flat-sky map, which we match to a pixel in the HEALPix map with the closest angular coordinate.…”

Section: Simulating Foreground Contaminationmentioning

confidence: 99%

Multipole expansion for H i intensity mapping experiments: simulations and modelling

Cunnington

Pourtsidou

Soares

et al. 2020

Monthly Notices of the Royal Astronomical Society

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We present a framework and an open-source python toolkit to analyse the two-point statistics of 3D fluctuations in the context of H i intensity maps using the multipole expansion formalism. We include simulations of the cosmological H i signal using N-body and lognormal methods, foregrounds and their removal, as well as instrumental effects. Using these simulations and analytical modelling, we investigate the impact of foreground cleaning and the instrumental beam on the power spectrum multipoles as well as on the Fourier space clustering wedges. We find that both the instrumental beam and the foreground removal can produce a quadrupole (and a hexadecapole) signal, and demonstrate the importance of controlling and accurately modelling these effects for precision radio cosmology. We conclude that these effects can be modelled with reasonable accuracy using our multipole expansion technique. We also perform a Markov Chain Monte Carlo (MCMC) analysis to showcase the effect of foreground cleaning on the estimation of the H i abundance and bias parameters. The accompanying python toolkit is available at https://github.com/IntensityTools/MultipoleExpansion, and includes an interactive suite of examples to aid new users.

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Section: Simulating Foreground Contaminationmentioning

confidence: 99%

Multipole expansion for H i intensity mapping experiments: simulations and modelling

Cunnington

Pourtsidou

Soares

et al. 2020

Monthly Notices of the Royal Astronomical Society

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“…All the data products were obtained from the Planck Legacy Archive. 6 For most of the analysis, we used the healpy 7 implementation (Zonca et al 2019) of the HEALPix pixelization (Górski et al 2005). We refer to the 353-857 GHz data as intensity maps.…”

Section: Planck Datamentioning

confidence: 99%

Large-scale Maps of the Cosmic Infrared Background from Planck

Lenz

Doré

Lagache

2019

ApJ

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The cosmic infrared background (CIB) is a powerful probe of large-scale structure across a very large redshift range, and consists of unresolved redshifted infrared emission from dusty galaxies. It can be used to study the astrophysics of galaxies, the star formation history of the universe, and the connection between dark and luminous matter. It can furthermore be used as a tracer of the large-scale structure and thus assist in de-lensing of the cosmic microwave background. The major difficulty in its use lies in obtaining accurate and unbiased large-scale CIB images that are cleaned of the contamination by Galactic dust. We used data on neutral atomic hydrogen from the recently released HI4PI Survey to create template maps of Galactic dust, allowing us to remove this component from the Planck intensity maps from 353 to 857 GHz for approximately 25% of the sky. This allows us to constrain the CIB power spectrum down to ℓ  70. We present these CIB maps and the various processing and validation steps that we have performed to ensure their quality, as well as a comparison with previous studies. All our data products are made publicly available, 4 thereby enabling the community to investigate a wide range of questions related to the universe's large-scale structure.

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“…In the spatial domain (pixel space), the transformation does not encode all the information from a single Q or U pixel into that same pixel in E and B, but rather distributes the [Q, U ] pixel signal across multiple pixels in E and B. As an example, Figure 1 Throughout this paper, we utilize the healpy 2 (Zonca et al 2019) and HEALPix 3 (Górski et al 2005) analysis package. The package function map2alm is used to transform Q and U using the spin-2 spherical harmonic basis functions with coefficients a E lm and a B lm , and then the function alm2map is used to evaluate E and B maps from the a lm 's.…”

Section: Stokes [Qu] and Transformation To [Eb]mentioning

confidence: 99%

An Examination of Galactic Polarization with Application to the Planck TB Correlation

Weiland

Addison

Bennett

et al. 2020

ApJ

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Angular power spectra computed from Planck HFI 353 GHz intensity and polarization maps produce a TB correlation that can be approximated by a power-law (Planck Collaboration XI 2018). Whether the observed TB correlation is an induced systematic feature or a physical property of Galactic dust emission is of interest both for cosmological and Galactic studies. We investigate the large angular scale E and B-mode morphology of microwave polarized thermal dust emission, and relate it to physical quantities of polarization angle and polarization fraction. We use empirical models of polarized dust to show that dust polarization angle is a key factor in producing the TB correlation. A small sample of both simulated and observed polarization angle maps are combined with 353 GHz intensity and dust polarization fraction to produce a suite of maps from which we compute TB and EB. Model realizations that produce a positive TB correlation are common and can result from large-scale (> 5 • ) structure in the polarization angle. The TB correlation appears robust to introduction of individual intensity, polarization angle and polarization fraction model components that are independent of the 353 GHz observations. We conclude that the observed TB correlation is likely the result of large-scale Galactic dust polarization properties.

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healpy: equal area pixelization and spherical harmonics transforms for data on the sphere in Python

Cited by 741 publications

References 4 publications

Multipole expansion for H i intensity mapping experiments: simulations and modelling

Multipole expansion for H i intensity mapping experiments: simulations and modelling

Large-scale Maps of the Cosmic Infrared Background from Planck

An Examination of Galactic Polarization with Application to the Planck TB Correlation

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