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Estimating major merger rates and spin parameters ab initio via the clustering of critical events

Cadiou, Corentin LU orcid ; Pichon-Pharabod, Eric ; Pichon, Christophe and Pogosyan, Dmitri (2024) In Monthly Notices of the Royal Astronomical Society 531(1). p.1385-1397
Abstract

We build a model to predict from first principles the properties of major mergers. We predict these from the coalescence of peaks and saddle points in the vicinity of a given larger peak, as one increases the smoothing scale in the initial linear density field as a proxy for cosmic time. To refine our results, we also ensure, using a suite of ∼400 power-law Gaussian random fields smoothed at ∼30 different scales, that the relevant peaks and saddles are topologically connected: They should belong to a persistent pair before coalescence. Our model allows us to (a) compute the probability distribution function of the satellite-merger separation in Lagrangian space: They peak at three times the smoothing scale; (b) predict the distribution... (More)

We build a model to predict from first principles the properties of major mergers. We predict these from the coalescence of peaks and saddle points in the vicinity of a given larger peak, as one increases the smoothing scale in the initial linear density field as a proxy for cosmic time. To refine our results, we also ensure, using a suite of ∼400 power-law Gaussian random fields smoothed at ∼30 different scales, that the relevant peaks and saddles are topologically connected: They should belong to a persistent pair before coalescence. Our model allows us to (a) compute the probability distribution function of the satellite-merger separation in Lagrangian space: They peak at three times the smoothing scale; (b) predict the distribution of the number of mergers as a function of peak rarity: haloes typically undergo two major mergers (>1:10) per decade of mass growth; (c) recover that the typical spin brought by mergers: it is of the order of a few tens of per cent.

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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
cosmology: Theory, large-scale structure of Universe
in
Monthly Notices of the Royal Astronomical Society
volume
531
issue
1
pages
13 pages
publisher
Oxford University Press
external identifiers
  • scopus:85193909579
ISSN
0035-8711
DOI
10.1093/mnras/stae1220
language
English
LU publication?
yes
id
0d498c8c-f884-4365-bd1b-f609362e6deb
date added to LUP
2024-05-31 13:58:01
date last changed
2024-05-31 13:59:01
@article{0d498c8c-f884-4365-bd1b-f609362e6deb,
  abstract     = {{<p>We build a model to predict from first principles the properties of major mergers. We predict these from the coalescence of peaks and saddle points in the vicinity of a given larger peak, as one increases the smoothing scale in the initial linear density field as a proxy for cosmic time. To refine our results, we also ensure, using a suite of ∼400 power-law Gaussian random fields smoothed at ∼30 different scales, that the relevant peaks and saddles are topologically connected: They should belong to a persistent pair before coalescence. Our model allows us to (a) compute the probability distribution function of the satellite-merger separation in Lagrangian space: They peak at three times the smoothing scale; (b) predict the distribution of the number of mergers as a function of peak rarity: haloes typically undergo two major mergers (&gt;1:10) per decade of mass growth; (c) recover that the typical spin brought by mergers: it is of the order of a few tens of per cent.</p>}},
  author       = {{Cadiou, Corentin and Pichon-Pharabod, Eric and Pichon, Christophe and Pogosyan, Dmitri}},
  issn         = {{0035-8711}},
  keywords     = {{cosmology: Theory; large-scale structure of Universe}},
  language     = {{eng}},
  month        = {{06}},
  number       = {{1}},
  pages        = {{1385--1397}},
  publisher    = {{Oxford University Press}},
  series       = {{Monthly Notices of the Royal Astronomical Society}},
  title        = {{Estimating major merger rates and spin parameters ab initio via the clustering of critical events}},
  url          = {{http://dx.doi.org/10.1093/mnras/stae1220}},
  doi          = {{10.1093/mnras/stae1220}},
  volume       = {{531}},
  year         = {{2024}},
}