English
Related papers

Related papers: Relation between standard perturbation theory and …

200 papers

I discuss the evolution of the redshift-space bispectrum via perturbation theory (PT) and large high-resolution numerical simulations. At large scales, we give the multipole expansion of the bispectrum in PT, which provides a natural way to…

Astrophysics · Physics 2007-05-23 Roman Scoccimarro

We explore the Lagrangian perturbation theory (LPT) at 1-loop order with Gaussian initial conditions. We present an expansion method to approximately compute the power spectrum in LPT. Our approximate solution has good convergence in the…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-17 Naonori S. Sugiyama

The large-scale matter distribution in the late-time Universe exhibits gravity-induced non-Gaussianity, and the bispectrum, three-point cumulant is expected to contain significant cosmological information. In particular, the measurement of…

Cosmology and Nongalactic Astrophysics · Physics 2017-09-06 Ichihiko Hashimoto , Yann Rasera , Atsushi Taruya

Perturbation theory (PT) calculation of large-scale structure has been used to interpret the observed non-linear statistics of large-scale structure at the quasi-linear regime. In particular, the so-called standard perturbation theory (SPT)…

Cosmology and Nongalactic Astrophysics · Physics 2018-12-05 Atsushi Taruya , Takahiro Nishimichi , Donghui Jeong

Target Propagation (TP) algorithms compute targets instead of gradients along neural networks and propagate them backward in a way that is similar yet different than gradient back-propagation (BP). The idea was first presented as a…

Machine Learning · Computer Science 2021-12-03 Vincent Roulet , Zaid Harchaoui

In the last three decades, Numerical Stochastic Perturbation Theory (NSPT) has proven to be an excellent tool for calculating perturbative expansions in theories such as Lattice QCD, for which standard, diagrammatic perturbation theory is…

High Energy Physics - Lattice · Physics 2025-02-05 P. Baglioni , F. Di Renzo

General and explicit predictions from the integrated perturbation theory (iPT) for power spectra and correlation functions of biased tracers are derived and presented in the one-loop approximation. The iPT is a general framework of the…

Cosmology and Nongalactic Astrophysics · Physics 2014-09-05 Takahiko Matsubara

We derive a perturbation theory (PT) for the Lorentz boost operator in the space of two-nucleon wave functions. The latter is expressed in terms of the nucleon-nucleon ($NN$) potentials, developed so far in great detail for their use in the…

Nuclear Theory · Physics 2025-09-15 Alexander N. Kvinikhidze , Hagop Sazdjian , Boris Blankleider

This is part two in a series of papers in which we investigate an approach based on Lagrangian perturbation theory (LPT) to study the non-linear evolution of the large-scale structure distribution in the universe. Firstly, we compute the…

Cosmology and Nongalactic Astrophysics · Physics 2012-06-15 Cornelius Rampf , Yvonne Y. Y. Wong

We present a specific prescription for the calculation of cosmological power spectra, exploited here at two-loop order in perturbation theory (PT), based on the multi-point propagator expansion. In this approach power spectra are…

Cosmology and Nongalactic Astrophysics · Physics 2013-05-30 Atsushi Taruya , Francis Bernardeau , Takahiro Nishimichi , Sandrine Codis

The integrated perturbation theory (iPT) is a set of methods in nonlinear perturbation theory for the structure formation in the Universe. In Papers I and II [arXiv:2210.10435, arXiv:2210.11085], the basic formalism and technical methods of…

Cosmology and Nongalactic Astrophysics · Physics 2024-09-23 Takahiko Matsubara

A recently developed variant of the so-called optimized perturbation theory (OPT), making it perturbatively consistent with renormalization group (RG) properties, RGOPT, was shown to drastically improve its convergence for zero temperature…

High Energy Physics - Phenomenology · Physics 2015-12-30 J. -L. Kneur , M. B. Pinto

We show here how Renormalized Perturbation Theory (RPT) calculations applied to the quasi-linear growth of the large-scale structure can be carried on in presence of primordial non-Gaussian (PNG) initial conditions. It is explicitly…

Cosmology and Nongalactic Astrophysics · Physics 2011-01-31 Francis Bernardeau , Martin Crocce , Emiliano Sefusatti

We present a perturbative approach within the scope of Kohn-Sham density functional theory (DFT). The method is based on the exact exchange-only optimized effective potential method, and correlation is included via perturbation expansion…

Chemical Physics · Physics 2007-05-23 P. Sule

Based on the multi-point propagator expansion, we present resummed perturbative calculations for cosmological power spectra and correlation functions in the context of modified gravity. In a wide class of modified gravity models that have a…

Cosmology and Nongalactic Astrophysics · Physics 2014-12-17 Atsushi Taruya , Takahiro Nishimichi , Francis Bernardeau , Takashi Hiramatsu , Kazuya Koyama

Perturbative renormalization group theory is developed as a unified tool for global asymptotic analysis. With numerous examples, we illustrate its application to ordinary differential equation problems involving multiple scales, boundary…

High Energy Physics - Theory · Physics 2008-11-26 Lin-Yuan Chen , Nigel Goldenfeld , Y. Oono

Galaxy surveys demand fast large-scale structure forward models that preserve large-scale phases while providing realistic nonlinear morphology at fixed force resolution. Single-step Lagrangian Perturbation Theory (LPT) solvers are…

Cosmology and Nongalactic Astrophysics · Physics 2026-03-26 Francisco-Shu Kitaura , Francesco Sinigaglia

We introduce the concept of multi-point propagators between linear cosmic fields and their nonlinear counterparts in the context of cosmological perturbation theory. Such functions express how a non-linearly evolved Fourier mode depends on…

Astrophysics · Physics 2009-02-23 Francis Bernardeau , Martin Crocce , Roman Scoccimarro

The success of deep learning, a brain-inspired form of AI, has sparked interest in understanding how the brain could similarly learn across multiple layers of neurons. However, the majority of biologically-plausible learning algorithms have…

Machine Learning · Computer Science 2020-12-17 Alexander Meulemans , Francesco S. Carzaniga , Johan A. K. Suykens , João Sacramento , Benjamin F. Grewe