Constraining single-field inflation with MegaMapper
Constraining single-field inflation with MegaMapper
复制标题
使用 MegaMapper 限制单字段膨胀
DOI:
10.1016/j.physletb.2023.137912
复制
发表时间:
2023
影响因子:
4.4
通讯作者:
Zaldarriaga, Matias
中科院分区:
文献类型:
--
作者:
Cabass, Giovanni;Ivanov, Mikhail M.;Philcox, Oliver H.E.;Simonović, Marko;Zaldarriaga, Matias
We forecast the constraints on single-field inflation from the bispectrum of future high-redshift surveys such as MegaMapper. Considering non-local primordial non-Gaussianity (NLPNG), we find that current methods will yield constraints of order σ (f NL eq)≈ 23, σ (f NL orth)≈ 12 in a joint power-spectrum and bispectrum analysis, varying both nuisance parameters and cosmology, including a conservative range of scales. Fixing cosmological parameters and quadratic bias parameter relations, the limits tighten significantly to σ (f NL eq)≈ 17, σ (f NL orth)≈ 8. These compare favorably with the forecasted bounds from CMB-S4: σ (f NL eq)≈ 21, σ (f NL orth)≈ 9, with a combined constraint of σ (f NL eq)≈ 14, σ (f NL orth)≈ 7; this weakens only slightly if one instead combines with data from the Simons Observatory. We additionally perform a range of Fisher analyses for the error, forecasting the dependence on nuisance parameter marginalization, scale cuts, and survey strategy. Lack of knowledge of bias and counterterm parameters is found to significantly limit the information content; this could be ameliorated by tight simulation-based priors on the nuisance parameters. The error-bars decrease significantly as the number of observed galaxies and survey depth is increased: as expected, deep dense surveys are the most constraining, though it will be difficult to reach σ (f NL)≈ 1 with current methods. The NLPNG constraints will tighten further with improved theoretical models (incorporating higher-loop corrections and improved understanding of nuisance parameters), as well as the inclusion of additional higher-order statistics.
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DOI:
10.1088/1475-7516/2020/05/005
发表时间:
2020-05-01
影响因子:
6.4
作者:
d'Amico, Guido;Gleyzes, Jerome;Gil-Marin, Hector
通讯作者:
Gil-Marin, Hector
影响因子:
4.8
作者:
D. Karagiannis;A. Lazanu;M. Liguori;A. Raccanelli;N. Bartolo;L. Verde
通讯作者:
L. Verde
DOI:
--
发表时间:
2006
期刊:
--
影响因子:
--
作者:
Iroon Polytechniou-
通讯作者:
Iroon Polytechniou-
影响因子:
4.8
作者:
Naonori S. Sugiyama;S. Saito;F. Beutler;H. Seo
通讯作者:
H. Seo