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Parameter sensitivity of cosmic pairwise velocities in the nonlinear regime of structure formation

Jorge Enrique García-Farieta*

Héctor J. Hortúa

  • Laboratorio de Inteligencia Artificial (SavIA Lab), Grupo Signos, Departamento de Matemáticas, Universidad El Bosque, Bogotá, Colombia

  • Laboratorio de Inteligencia Artificial (SavIA Lab), Grupo Signos, Departamento de Matemáticas, Universidad El Bosque, Bogotá, Colombia Instituto de Neurociencias, Universidad El Bosque, Bogotá, Colombia

  • *Contact author: jegarciaf@unbosque.edu.co
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Phys. Rev. D 113, 103519 – Published 12 May, 2026

DOI: https://doi.org/10.1103/f8rq-llf2

Abstract

The peculiar velocities of dark matter tracers drive the growth of cosmic structures, providing a sensitive test of cosmological models and strengthening constraints on the nature of dark energy. In this work, we investigate the mean pairwise velocities, v12, of dark matter tracers as a cosmological probe in the nonlinear regime of cosmic structure formation. Using N-body dark matter-only simulations, we measure v12 for pair separations up to 50 h−1  Mpc and model it by solving the pair conservation equation for a self-gravitating particle system, along with various prescriptions of the nonlinear matter power spectrum. We quantified the sensitivity of v12 to variations in key cosmological parameters such as Ωm, σ8, h, Mν, and w. Our parameter inference analysis using Markov chain Monte Carlo (MCMC) shows sub-11% agreement with simulation data, with notable degeneracies, particularly between Ωm and σ8. We further compute the stable clustering crossing scale across redshifts z=0, 0.5, and 1, assessing its dependence on cosmology. Among the tested power spectrum modeling approaches, we find that the csstemu emulator provides the most accurate predictions, with deviations below 5% for r>10 h−1  Mpc at z=0.5. Our results are validated using independent simulation suites, demonstrating that our framework offers a robust method for extracting cosmological constraints from upcoming peculiar velocity data.

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Phys. Rev. D 113, 103519– Published 12 May, 2026
  • Received 22 September 2025
  • Accepted 20 April 2026
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