scholarly journals Breaking the scale invariance of the primordial power spectrum in Hořava-Lifshitz cosmology

2009 ◽  
Vol 80 (6) ◽  
Author(s):  
Kazuhiro Yamamoto ◽  
Tsutomu Kobayashi ◽  
Gen Nakamura
2022 ◽  
Vol 2022 (01) ◽  
pp. 012
Author(s):  
Ki-Young Choi ◽  
Jinn-Ouk Gong ◽  
Su-beom Kang ◽  
Rathul Nath Raveendran

Abstract We suggest a new method to reconstruct, within canonical single-field inflation, the inflaton potential directly from the primordial power spectrum which may deviate significantly from near scale-invariance. Our approach relies on a more generalized slow-roll approximation than the standard one, and can probe the properties of the inflaton potential reliably. We give a few examples for reconstructing potential and discuss the validity of our method.


2010 ◽  
Vol 2010 (01) ◽  
pp. 016-016 ◽  
Author(s):  
Gavin Nicholson ◽  
Carlo R Contaldi ◽  
Paniez Paykari

2017 ◽  
Vol 95 (8) ◽  
Author(s):  
Gonzalo A. Palma ◽  
Bastián Pradenas ◽  
Walter Riquelme ◽  
Spyros Sypsas

2020 ◽  
Vol 102 (8) ◽  
Author(s):  
Shintaro Yoshiura ◽  
Masamune Oguri ◽  
Keitaro Takahashi ◽  
Tomo Takahashi

2019 ◽  
Vol 490 (3) ◽  
pp. 4237-4253 ◽  
Author(s):  
Florent Leclercq ◽  
Wolfgang Enzi ◽  
Jens Jasche ◽  
Alan Heavens

ABSTRACT We propose a new, likelihood-free approach to inferring the primordial matter power spectrum and cosmological parameters from arbitrarily complex forward models of galaxy surveys where all relevant statistics can be determined from numerical simulations, i.e. black boxes. Our approach, which we call simulator expansion for likelihood-free inference (selfi), builds upon approximate Bayesian computation using a novel effective likelihood, and upon the linearization of black-box models around an expansion point. Consequently, we obtain simple ‘filter equations’ for an effective posterior of the primordial power spectrum, and a straightforward scheme for cosmological parameter inference. We demonstrate that the workload is computationally tractable, fixed a priori, and perfectly parallel. As a proof of concept, we apply our framework to a realistic synthetic galaxy survey, with a data model accounting for physical structure formation and incomplete and noisy galaxy observations. In doing so, we show that the use of non-linear numerical models allows the galaxy power spectrum to be safely fitted up to at least kmax = 0.5 h Mpc−1, outperforming state-of-the-art backward-modelling techniques by a factor of ∼5 in the number of modes used. The result is an unbiased inference of the primordial matter power spectrum across the entire range of scales considered, including a high-fidelity reconstruction of baryon acoustic oscillations. It translates into an unbiased and robust inference of cosmological parameters. Our results pave the path towards easy applications of likelihood-free simulation-based inference in cosmology. We have made our code pyselfi and our data products publicly available at http://pyselfi.florent-leclercq.eu.


2016 ◽  
Vol 460 (2) ◽  
pp. 1577-1587 ◽  
Author(s):  
Rahul Kothari ◽  
Shamik Ghosh ◽  
Pranati K. Rath ◽  
Gopal Kashyap ◽  
Pankaj Jain

2011 ◽  
Vol 2011 (12) ◽  
pp. 008-008 ◽  
Author(s):  
Kohei Kumazaki ◽  
Shuichiro Yokoyama ◽  
Naoshi Sugiyama

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