Sensitivity tests of cosmic velocity fields to massive neutrinos

Massive neutrinos are well-known to cause a characteristic suppression in the growth of structures at scales below the neutrino free-streaming length. A detailed understanding of this suppression is essential in the era of precision cosmology we are entering into, enabling us to better constrain the total neutrino mass and possibly probe (beyond)-ΛCDM cosmological model(s). Instead of the usual N-body simulation or Boltzmann solver, in this article we consider a two-fluid framework at the linear scales, where the neutrino fluid perturbations are coupled to the CDM (+ baryon) fluid via gravity at redshifts of interest. Treating the neutrino mass fraction f ν as a perturbative parameter, we find solutions to the system with redshift-dependent neutrino free-streaming length in ΛCDM background via two separate approaches. The perturbative scale-dependent solution is shown to be in excellent agreement with numerical solution of the two-fluid equations valid to all orders in f ν, and also agrees with results from CLASS to a good accuracy. We further generalize the framework to incorporate different evolving dark energy backgrounds and found sub-percent level differences in the suppression, all of which lie within the observational uncertainty of BOSS-like surveys. We also present a brief discussion on the prospects of the current analysis in the context of upcoming missions.

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confidence: 75%

Revisiting coupled CDM-massive neutrino perturbations in diverse cosmological backgrounds

Pal,

Samanta,

Pal

2023

“…Nonetheless, we emphasise that novel astronomical observations have been proposed that may reveal more about nonlinear neutrino evolution than do conventional N -point statistics. These include a dipole distortion in galaxy cross-correlations induced by relative velocities [33][34][35][36], a long-range correlation in galactic rotation directions [37], wakes [38], non-Gaussianity [39], suppressed mass accretion by dark matter halos [40], and an environment-dependence of the halo mass function [41]. From the particle physics perspective, β-decay endpoint spectrum measurements [42] and high-energy astroparticle probes [43][44][45] too are sensitive to relic neutrino clustering in the Milky Way and elsewhere in the universe through direct particle interactions.…”

Section: Introductionmentioning

confidence: 99%

Hybrid multi-fluid-particle simulations of the cosmic neutrino background

Chen

Mosbech

Upadhye

et al. 2023

Simulation of the cosmic clustering of massive neutrinos is a daunting task, due both to their large velocity dispersion and to their weak clustering power becoming swamped by Poisson shot noise. We present a new approach, the multi-fluid hybrid-neutrino simulation, which partitions the neutrino population into multiple flows, each of which is characterised by its initial momentum and treated as a separate fluid. These fluid flows respond initially linearly to nonlinear perturbations in the cold matter, but slowest flows are later converted to a particle realisation should their clustering power exceed some threshold. After outlining the multi-fluid description of neutrinos, we study the conversion of the individual flows into particles, in order to quantify transient errors, as well as to determine a set of criteria for particle conversion. Assembling our results into a total neutrino power spectrum, we demonstrate that our multi-fluid hybrid-neutrino simulation is convergent to < 3% if conversion happens at z = 19 and agrees with more expensive simulations in the literature for neutrino fractions as high as Ω νh 2 = 0.005. Moreover, our hybrid-neutrino approach retains fine-grained information about the neutrinos' momentum distribution. However, the momentum resolution is currently limited by free-streaming transients excited by missing information in the neutrino particle initialisation procedure, which restricts the particle conversion to z ≳ 19 if percent-level resolution is desired.

“…Neutrinos, especially those with larger masses, present several unique cosmic signatures which may allow for their definitive detection. They introduce a scale-dependence into the dark matter halo bias [25][26][27][28]; a dipole distortion in galaxy cross-correlations due to their relative velocities [29][30][31][32]; a long-range correlation in galactic rotation directions [33]; "wakes" caused by neutrinos coherently free-streaming past collapsed halos [34,35]; non-Gaussianity due to their clustering in voids [36]; a suppression in mass accretion by dark matter halos [37]; and an environment-dependence of the halo mass function due to differential capture of neutrinos by halos [38]. Quantifying these effects requires accurate computations of the formation of large-scale structure in the non-linear regime.…”

Section: Jcap05(2023)046 1 Introductionmentioning

confidence: 99%

Flows for the masses: A multi-fluid non-linear perturbation theory for massive neutrinos

Chen

Upadhye

Wong

2023

Velocity dispersion of the massive neutrinos presents a daunting challenge for non-linear cosmological perturbation theory. We consider the neutrino population as a collection of non-linear fluids, each with uniform initial momentum, through an extension of the Time Renormalization Group perturbation theory. Employing recently-developed Fast Fourier Transform techniques, we accelerate our non-linear perturbation theory by more than two orders of magnitude, making it quick enough for practical use. After verifying that the neutrino mode-coupling integrals and power spectra converge, we show that our perturbation theory agrees with N-body neutrino simulations to within 10% for neutrino fractions Ω ν,0 h 2 ≤ 0.005 up to wave numbers of k = 1 h/Mpc, an accuracy consistent with ≤ 2.5% errors in the neutrino mass determination. Non-linear growth represents a > 10% correction to the neutrino power spectrum even for density fractions as low as Ω ν,0 h 2 = 0.001, demonstrating the limits of linear theory for accurate neutrino power spectrum predictions. Our code FlowsForTheMasses is avaliable online at github.com/upadhye/FlowsForTheMasses.