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Article . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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Scale Dependent Memory in Cosmological Backreactions, From Local Viscosity to Global Information Drag

Authors: Atalebe, Stephen;

Scale Dependent Memory in Cosmological Backreactions, From Local Viscosity to Global Information Drag

Abstract

This work extends $\Lambda$CDM to a non--Markovian cosmological backreactionmodel by introducing a causal memory kernel that links the present expansion toa weighted history of nonlinear structure. In the Infinite TransformationPrinciple (ITP) framework, a negative, long--horizon kernel can fit late--timeexpansion and growth data while remaining compatible with early--timeinferences, and shifts the CMB--inferred Hubble rate by a few per cent. Separately, direct measurements in IllustrisTNG show that virialisation and bulk flows generate short--horizon, viscosity--like kernels on nonlinear coarse--graining scales. This paper unifies these results in a scale--dependent memory picture. A multiscale Volterra closure is formulated in which the backreaction term$\delta H^{2}(t;L)$ at coarse--graining scale $L$ is sourced by a structuralvariable $\Sigma(t;L)$ through a kernel $K_{L}(\Delta t)$. Under a mildseparability assumption for the structural source across scales,$\Sigma(t;L)\approx S(L)\Sigma_{\rm bg}(t)$, the background backreaction can bewritten as a convolution with an effective kernel$\Keff(\Delta t)=\int \dd\ln L\,W(L)S(L)K_{L}(\Delta t)$ that remains a kernelin the usual sense. Even if each $K_L$ is a short--horizon exponential, theirmixture need not be. Using TNG300--1 and TNG50--1, kernels are measured at multiple domain sizes tobuild a ladder of memory parameters $(\tau(L),A(L)\tau(L))$ with bootstrapuncertainties. The results show negative, viscosity--like kernels at allnonlinear scales, with $|A\tau|$ increasing towards smaller $L$ and$\tau(L)\lesssim 0.05$--$0.1\,{\rm Gyr}$. An SDSS DR8 domain analysis reproducesthe same sign and scale trend in the real Universe on$L\sim 60$--$240\,{\rm Mpc}/h$ scales. At the horizon, a Planck 2018 ITP fitfixes a long--memory kernel whose integrated drag$|A_{\rm hor}\tau_{\rm hor}|\simeq 0.03$ accounts for the few--percent reductionin $H_{0}$ relative to flat $\Lambda$CDM. Taken together, these measurements define a ``cosmic memory ladder'' frommicro-- to horizon scales. Simple power--law fits show that the effective memorytime grows roughly as $\tau(L)\propto L^{2/3}$ once the horizon point isincluded, while the integrated drag $|A\tau|$ becomes a slowly varying,scale--dependent coupling. A controlled kernel--mixture demonstration illustrateshow fitting a broad mixture of short--horizon kernels with a single exponentialcan inflate the inferred effective horizon. In this sense, the long--range``information drag'' in non--Markovian cosmology can be read as the infraredlimit of the same virial friction that couples structure and expansion insidethe cosmic web.

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Keywords

Physical cosmology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average