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The Manticore Project I: a digital twin of our cosmic neighbourhood from Bayesian field-level analysis

Title: The Manticore Project I: a digital twin of our cosmic neighbourhood from Bayesian field-level analysis
Authors: McAlpine, S; Jasche, J; Ata, M; Lavaux, G; Stiskalek, R; Frenk, CS; Jenkins, A
Publisher Information: Oxford University Press
Publication Year: 2025
Collection: Oxford University Research Archive (ORA)
Description: We present the first results from the Manticore Project, dubbed Manticore-Local, a suite of Bayesian constrained simulations of the nearby Universe, generated by fitting a physical structure formation model to the 2M++ galaxy catalogue using the borg algorithm. This field-level inference yields physically consistent realizations of cosmic structure, leveraging a non-linear gravitational solver, a refined galaxy bias model, and physics-informed priors. The Manticore-Local posterior realizations evolve within a parent cosmological volume statistically consistent with Lambda-cold dark matter, demonstrated through extensive posterior predictive tests of power spectra, bispectra, initial condition Gaussianity, and the halo mass function. The inferred local supervolume ( Mpc, or ) shows no significant deviation from cosmological expectations; notably, we find no evidence for a large local underdensity, with the mean density suppressed by only per cent relative to the cosmic mean. Our model identifies high-significance counterparts for 14 prominent galaxy clusters – including Virgo, Coma, and Perseus – each within 1 deg of its observed sky position. Across the posterior ensemble, these counterparts are consistently detected with 2σ–4 significance, and their reconstructed masses and redshifts agree closely with observational estimates, confirming the inference’s spatial and dynamical fidelity. The peculiar velocity field recovered by Manticore-Local achieves the highest Bayesian evidence across five independent data sets, surpassing state-of-the-art non-linear models, linear theory, Wiener filtering, and machine learning approaches. Unlike methods yielding only point estimates or using simplified dynamics, Manticore-Local provides a full Bayesian posterior over cosmic structure and evolution, enabling rigorous uncertainty quantification. These results establish Manticore-Local as the most advanced constrained realization suite of the local Universe to date, offering a robust statistical foundation for future studies of ...
Document Type: article in journal/newspaper
Language: English
Relation: https://doi.org/10.1093/mnras/staf767
DOI: 10.1093/mnras/staf767
Availability: https://doi.org/10.1093/mnras/staf767; https://ora.ox.ac.uk/objects/uuid:220c32b5-b253-4b91-aa85-facdbae47e1f
Rights: info:eu-repo/semantics/openAccess ; CC Attribution (CC BY)
Accession Number: edsbas.AC9124F1
Database: BASE