On the Onset of Stochasticity in $\Lambda$CDM Cosmological Simulations
Jerome Thiebaut (IAP), Christophe Pichon (IAP), Thierry Sousbie (IAP),, Simon Prunet (IAP), D. Pogosyan

TL;DR
This paper investigates the onset of stochasticity in $\Lambda$CDM cosmological simulations, identifying a critical scale and mass where chaos emerges, affecting certain properties of cosmic structures while others remain robust.
Contribution
It introduces a novel measurement of chaos onset in cosmological simulations and links it to specific scales and masses, enhancing understanding of non-linear structure formation.
Findings
Chaos appears at small, non-linear scales (~3.5 Mpc/h).
Critical mass for sensitivity scales as perturbation amplitude to the 0.15 power.
Some halo properties are sensitive to initial conditions, others are robust.
Abstract
The onset of stochasticity is measured in CDM cosmological simulations using a set of classical observables. It is quantified as the local derivative of the logarithm of the dispersion of a given observable (within a set of different simulations differing weakly through their initial realization), with respect to the cosmic growth factor. In an Eulerian framework, it is shown here that chaos appears at small scales, where dynamic is non-linear, while it vanishes at larger scales, allowing the computation of a critical transition scale corresponding to ~ 3.5 Mpc/h. This picture is confirmed by Lagrangian measurements which show that the distribution of substructures within clusters is partially sensitive to initial conditions, with a critical mass upper bound scaling roughly like the perturbation's amplitude to the power 0.15. The corresponding characteristic mass, $M_{\rm…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCosmology and Gravitation Theories · Stochastic processes and financial applications · advanced mathematical theories
