Erasing the Milky Way: new cleaning technique applied to GBT intensity mapping data

Wolz, Laura; Blake, Chris; Abdalla, F. B.; Anderson, Chris; Chang, Tzu-Ching; Li, Y.-C.; Masui, Kiyoshi; Switzer, Eric R.; Pen, Ue-Li; Voytek, Tabitha; Yadav, Jaswant K.

doi:10.1093/mnras/stw2556

Cited by 76 publications

(87 citation statements)

References 36 publications

(40 reference statements)

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“…Modelling and addressing the foreground removal problem with dedicated simulations is a very active area of research (see, for example, (Wolz et al 2014;Shaw et al 2015;Wolz et al 2017)). The conclusion of such work is that component separation methods can in principle be used to remove these foregrounds.…”

Section: Foregroundsmentioning

confidence: 99%

H iintensity mapping for clustering-based redshift estimation

Cunnington

Harrison

Pourtsidou

et al. 2018

Monthly Notices of the Royal Astronomical Society

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Precision cosmology requires accurate galaxy redshifts, but next generation optical surveys will observe unprecedented numbers of resolved galaxies, placing strain on the amount of spectroscopic follow-up required. We show how useful information can be gained on the redshift distributions of optical galaxy samples from spatial crosscorrelations with intensity maps of unresolved H i (21cm) spectral line emission. We construct a redshift distribution estimator, which we test using simulations. We utilise the S 3 -SAX catalogue which includes H i emission information for each galaxy, which we use to construct H i intensity maps. We also make use of simulated LSST and Euclid -like photometry enabling us to apply the H i clustering calibration to realistic simulated photometric redshifts. While taking into account important limitations to H i intensity mapping such as lost k-modes from foreground cleaning and poor angular resolution due to large receiver beams, we show that excellent constraints on redshift distributions can be provided for an optical photometric sample.

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Section: Foregroundsmentioning

confidence: 99%

H iintensity mapping for clustering-based redshift estimation

Cunnington

Harrison

Pourtsidou

et al. 2018

Monthly Notices of the Royal Astronomical Society

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“…Further blind component separation methods include Generalalized Morphological Component Analysis (GMCA) (Chapman et al 2013) and Generalized Internal Linear Combination (GnILC) (Remazeilles et al 2011). For this work we examine the FAS-TICA method (Hyvärinen 1999;Chapman et al 2012;Wolz et al 2014Wolz et al , 2017, which we describe in the following section. Alonso et al (2015) found there to be very little distinction between a PCA and ICA approach to foreground cleaning, so our choice of FASTICA as a foreground removal process should not affect the generality of our conclusions.…”

Section: Foreground Removalmentioning

confidence: 99%

Impact of foregrounds on H i intensity mapping cross-correlations with optical surveys

Cunnington

Wolz

Pourtsidou

et al. 2019

Monthly Notices of the Royal Astronomical Society

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The future of precision cosmology could benefit from cross-correlations between intensity maps of unresolved neutral hydrogen (Hi) and more conventional optical galaxy surveys. A major challenge that needs to be overcome is removing the 21cm foreground emission that contaminates the cosmological Hi signal. Using N-body simulations we simulate Hi intensity maps and optical catalogues which share the same underlying cosmology. Adding simulated foreground contamination and using state-of-the-art reconstruction techniques we investigate the impacts that 21cm foregrounds and other systematics have on these cross-correlations. We find that the impact a FASTICA 21cm foreground clean has on the cross-correlations with spectroscopic optical surveys with well-constrained redshifts is minimal. However, problems arise when photometric surveys are considered: we find that a redshift uncertainty σ z ≥ 0.04 causes significant degradation in the cross power spectrum signal. We diagnose the main root of these problems, which relates to arbitrary amplitude changes along the line-of-sight in the intensity maps caused by the foreground clean and suggest solutions which should be applicable to real data. These solutions involve a reconstruction of the line-of-sight temperature means using the available overlapping optical data along with an artificial extension to the Hi data through redshift to address edge effects. We then put these solutions through a further test in a mock experiment that uses a clustering-based redshift estimation technique to constrain the photometric redshifts of the optical sample. We find that with our suggested reconstruction, cross-correlations can be utilized to make an accurate prediction of the optical redshift distribution.

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“…Excepting the P TT monopole, all statistics and multipoles produce a satisfactory value of the χ 2 statistic with χ 2 /dof ∼ 1 for scales k < 0.2 h Mpc −1 . Current cross-correlation analyses of radio intensity mapping and galaxy surveys have produced ∼ 3-σ detections of the cross-power spectrum amplitude, and corresponding constraints on the neutral hydrogen density at intermediate redshifts (Chang et al 2010;Masui et al 2013;Wolz et al 2017;Anderson et al 2018). Analysis of the auto-power spectrum of intensity Figure 2.…”

Section: Simulation Testmentioning

confidence: 99%

Power spectrum modelling of galaxy and radio intensity maps including observational effects

Blake

2019

Monthly Notices of the Royal Astronomical Society

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Fluctuations in the large-scale structure of the Universe contain significant information about cosmological physics, but are modulated in survey datasets by various observational effects. Building on existing literature, we provide a general treatment of how fluctuation power spectra are modified by a position-dependent selection function, noise, weighting, smoothing, pixelization and discretization. Our work has relevance for the spatial power spectrum analysis of galaxy surveys with spectroscopic or accurate photometric redshifts, and radio intensity-mapping surveys of the sky brightness temperature including generic noise, telescope beams and pixelization. We consider the auto-power spectrum of a field, the cross-power spectrum between two fields and the multipoles of these power spectra with respect to a curved sky, deriving the corresponding power spectrum models, estimators, errors and optimal weights. We note that "FKP weights" for individual tracers do not in general provide the optimal weights when measuring the cross-power spectrum. We validate our models using mock datasets drawn from N-body simulations †. Our treatment should be useful for modelling and studying cosmological fluctuation fields in observed and simulated datasets.The power spectrum of the large-scale structure of the Universe -and its dependence on scale, redshift and direction -contains significant information about the composition of the Universe and the cosmological physics governing the growth of structure with time. Modern cosmological surveys can trace this large-scale structure over large volumes, by mapping the individual redshift-space positions of galaxies or quasars, the cumulative brightness temperature of spectral emission in a region of sky using intensity mapping in radio wavebands, or the spectral absorption of background light by intervening matter.One of the central problems in cosmological analysis is to relate these measured fluctuations in probes of large-scale structure, which are modulated by various observational effects and analysis approximations, to the underlying matter power spectrum which encodes the important cosmological information. Relevant observational effects may include a variation in the mean background level of the fields as a function of position (the survey selection function or mask), noise due to the sampling of discrete objects or in the measured brightness temperature, or smoothing of the fields in the mapping process due to the telescope resolution. Analysis approximations may involve the pixelization or gridding technique employed, and wide-angle corrections to the local plane-parallel approximation.Moreover, we may also utilize the cross-correlation between two different observed fields which trace the same underlying matter fluctuations. Such a multi-tracer analysis offers several benefits: (1) uncorrelated noise components in the two fields will bias the amplitude of their auto-power spectra, but not their cross-power spectrum; (2) an additive systematic component afflicting one of the...

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Erasing the Milky Way: new cleaning technique applied to GBT intensity mapping data

Cited by 76 publications

References 36 publications

H iintensity mapping for clustering-based redshift estimation

H iintensity mapping for clustering-based redshift estimation

Impact of foregrounds on H i intensity mapping cross-correlations with optical surveys

Power spectrum modelling of galaxy and radio intensity maps including observational effects

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