English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The forthcoming generation of galaxy redshift surveys will sample thelarge-scale structure of the Universe over unprecedented volumes withhigh-density tracers. This advancement will make robust measurements ofthree-point clustering statistics possible. In preparation for thisimprovement, we investigate how several methodological choices can influenceinferences based on the bispectrum about galaxy bias and shot noise. We firstmeasure the real-space bispectrum of dark-matter haloes extracted from 298N-body simulations covering a volume of approximately $1000 h^{-3}\mathrm{Gpc}^3$. We then fit a series of theoretical models based on tree-levelperturbation theory to the numerical data. To achieve this, we estimate thecovariance matrix of the measurement errors by using 10,000 mock cataloguesgenerated with the Pinocchio code. We study how the model constraints areinfluenced by the binning strategy for the bispectrum configurations and by theform of the likelihood function. We also use Bayesian model-selectiontechniques to single out the optimal theoretical description of our data. Wefind that a three-parameter bias model combined with Poissonian shot noise isnecessary to model the halo bispectrum up to scales of $k_\mathrm{max}\lesssim0.08 h \mathrm{Mpc}^{-1}$, although fitting formulae that relate the biasparameters can be helpful to reduce the freedom of the model withoutcompromising accuracy. Our data clearly disfavour local Eulerian and localLagrangian bias models and do not require corrections to Poissonian shot noise.We anticipate that model-selection diagnostics will be particularly useful toextend the analysis to smaller scales as, in this case, the number of modelparameters will grow significantly large.

Toward a robust inference method for the galaxy bispectrum: likelihood function and model selection