Massive Neutrinos in Cosmological Structure Formation

Massive neutrinos play a subtle yet pivotal role in the evolution of cosmic structure. Unlike cold dark matter, neutrinos retain relativistic velocities for an extended epoch, producing a characteristic free-streaming effect that suppresses the growth of density fluctuations below a redshift-dependent scale. This leads to a scale-dependent damping of the matter power spectrum, alterations to the formation and clustering of dark matter haloes, and imprints on the cosmic web topology. The summed mass of the three neutrino species also influences key observational probes such as baryon acoustic oscillations, weak gravitational lensing and redshift-space distortions. As a result, precision measurements of large-scale structure from galaxy redshift surveys, the Lyman-α forest and cosmic microwave background lensing are now sensitive to neutrino masses at the sub-electronvolt level. Theoretical efforts combine linear perturbation theory, higher-order fluid approaches and non-linear N-body simulations to model these effects. In parallel, innovative methods—including topological analyses of the cosmic web and machine-learning emulators—are being developed to extract maximal information from forthcoming surveys such as Euclid, DESI and the Rubin Observatory. The determination of the absolute neutrino mass scale and hierarchy thus represents one of the key intersections of particle physics and cosmology, with implications for fundamental physics and the thermal history of the Universe.

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Massive Neutrinos in Cosmological Structure Formation publication trend

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Technical terms

Free-streaming length: The comoving scale below which neutrino thermal motions erase density perturbations, suppressing structure growth on small scales.

Matter power spectrum: A statistical measure of the distribution of density fluctuations as a function of spatial scale, sensitive to neutrino mass via scale-dependent suppression.

Critical points: Special locations in the cosmic density field (peaks, troughs and saddles) whose clustering encodes the topology of the large-scale structure.

Magnification bias: A lensing-induced correlation between foreground and background galaxy samples arising from flux magnification, used to probe mass distributions and neutrino effects.

Emulator: A data-driven surrogate model, often based on machine learning, that predicts cosmological observables (e.g. power spectra) across parameter space at minimal cost.

References

1. Signature of Massive Neutrinos from the Clustering of Critical Points. I. Density-threshold-based Analysis in Configuration Space. The Astrophysical Journal Supplement Series (2023).
2. Toward the measurement of neutrino masses: Performance of cosmic magnification with submillimeter galaxies. Astronomy & Astrophysics (2024).
3. Learning Neutrino Effects in Cosmology with Convolutional Neural Network. The Astrophysical Journal (2023).