2017
DOI: 10.1016/j.dark.2016.10.006
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Future constraints on angle-dependent non-Gaussianity from large radio surveys

Abstract: We investigate how well future large-scale radio surveys could measure different shapes of primordial non-Gaussianity; in particular we focus on angle-dependent non-Gaussianity arising from primordial anisotropic sources, whose bispectrum has an angle dependence between the three wavevectors that is characterized by Legendre polynomials PL and expansion coefficients cL. We provide forecasts for measurements of galaxy power spectrum, finding that Large-Scale Structure (LSS) data could allow measurements of prim… Show more

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Cited by 38 publications
(47 citation statements)
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“…Moreover, multi-tracer (MT) analyses [98,99], where one can divide the galaxy catalog into subsamples of different populations, can potentially improve the constraints from galaxy surveys by a factor of a few, depending on the assumptions on the number of distinguishable populations and their bias (for some first analyses using the MT technique, see Refs. [87,[100][101][102][103][104] We show the confidence ellipses for a DESI-like survey, as well as for a SKA-like survey, in Fig. 3, where we also include the information from Planck.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Moreover, multi-tracer (MT) analyses [98,99], where one can divide the galaxy catalog into subsamples of different populations, can potentially improve the constraints from galaxy surveys by a factor of a few, depending on the assumptions on the number of distinguishable populations and their bias (for some first analyses using the MT technique, see Refs. [87,[100][101][102][103][104] We show the confidence ellipses for a DESI-like survey, as well as for a SKA-like survey, in Fig. 3, where we also include the information from Planck.…”
Section: Resultsmentioning
confidence: 99%
“…, where σ v is the velocity dispersion and is modeled as in [87]. A real data analysis will need to take into account a variety of additional corrections, such as wide-angle effects [88][89][90], and cosmic magnification [91,92]; however none of these effects should be degenerate with modifications of the power spectrum spectral index or its runnings, so we will not include a detailed modeling of them.…”
Section: Formalismmentioning
confidence: 99%
“…They predict that a cosmic variance limited experiment would be able to measure fNL down to σ f NL ∼ 0.03, and thus able to constrain single-field slow-roll inflation (Maldacena 2003;Acquaviva et al 2003). Observations of PNG at lower redshifts rely on the scale dependence of the halo bias and can achieve competitive constraints for the primordial non-Gaussianity parameter D'Aloisio et al 2013;Li & Ma 2017;Raccanelli et al 2017;Karagiannis et al 2018). The prospects of constraining PNG with the cosmic 21cm signal are thus promising.…”
Section: Primordial Bispectrummentioning
confidence: 99%
“…More accurate analytical expressions for the scaledependent bias have been studied [17][18][19][20][21][22]. A widely used expression is derived by Matarrese and Verde [17],…”
Section: B the Scale-dependent Biasmentioning
confidence: 99%
“…Current measurements of the temperature and polarization of CMB from the Planck satellite provide state-of-the-art constraints on local, equilateral and orthogonal types of PNG [15] as f Besides the constraints from CMB, there have been many efforts to measure f NL through large-scale structure surveys. This is because the PNG induces a scale-dependent bias of the galaxy with respect to the underlying dark matter distribution tracer [16][17][18][19][20][21][22]. Reference [19] used spectroscopic and photometric luminous red galaxy samples and quasar samples * Electronic address: lixiating@gmail.com † Electronic address: ma@ukzn.ac.za from the SDSS survey to obtain the limit for local-type PNG as −31(−96) < f local NL < +70(+96) at 95% (99.7%) C.L., which was comparable to the measurements at the time from the Wilkinson Microwave Anisotropy Probe (WMAP) five-year results.…”
Section: Introductionmentioning
confidence: 99%