Reducing noise in cosmological N-body simulations with neutrinos

Banerjee, Arka; Powell, Devon; Abel, Tom; Villaescusa-Navarro, Francisco

doi:10.1088/1475-7516/2018/09/028

Cited by 67 publications

(84 citation statements)

References 79 publications

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“…We note that our void finding procedure in the CDM case only uses CDM particles and does not include the neutrino particles. A different approach is to locate voids in the total matter field, such as in the work of Banerjee & Dalal (2016) that included neutrino particles and CDM particles. In our work, we have established that the inversion is unique to voids derived from halos because the effective halo bias drives the inversion.…”

Section: Discussionmentioning

confidence: 99%

“…Massara et al (2015) focused on how neutrinos affect void abundance, density profiles, ellipticities, the correlation function, and velocity profiles with N-body simulations that included massive neutrinos as an additional collisionless particle component. Banerjee & Dalal (2016) observed that neutrinos affect the scale-dependent void bias for voids traced by the CDM particle field. They use a spherical void finder and a small volume simulation (700 h −1 Mpc box length).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Massive neutrinos leave fingerprints on cosmic voids

Kreisch

Pisani

Carbone

et al. 2019

Monthly Notices of the Royal Astronomical Society

113

123

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Do void statistics contain information beyond the tracer 2-point correlation function? Yes! As we vary the sum of the neutrino masses, we find void statistics contain information absent when using just tracer 2-point statistics. Massive neutrinos uniquely affect cosmic voids. We explore their impact on void clustering using both the DEMNUni and MassiveNuS simulations. For voids, neutrino effects depend on the observed void tracers. As the neutrino mass increases, the number of small voids traced by cold dark matter particles increases and the number of large voids decreases. Surprisingly, when massive, highly biased, halos are used as tracers, we find the opposite effect. The scale at which voids cluster, as well as the void correlation, is similarly sensitive to the sum of neutrino masses and the tracers. This scale dependent trend is not due to simulation volume or halo density. The interplay of these signatures in the void abundance and clustering leaves a distinct fingerprint that could be detected with observations and potentially help break degeneracies between different cosmological parameters. This paper paves the way to exploit cosmic voids in future surveys to constrain the mass of neutrinos.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Massive neutrinos leave fingerprints on cosmic voids

Kreisch

Pisani

Carbone

et al. 2019

Monthly Notices of the Royal Astronomical Society

113

123

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“…Several approaches have been followed in the literature to account for the effect of massive neutrinos in the non-linear regime, most of them relying on N-body cosmological simulations, which have been upgraded to include the effects of neutrino clustering in the evolution of the cosmological structures. Methods range from perturbative attempts [114][115][116][117][118][119][120][121] to the fully non-linear inclusion [121][122][123][124][125][126] of neutrinos as an extra set of particles. A conservative alternative consists on using exclusively power spectrum measurements within the linear regime (i.e., k < 0.1 h Mpc −1 ).…”

Section: B Large Scale Structure Of the Universementioning

confidence: 99%

Neutrino Mass Ordering from Oscillations and Beyond: 2018 Status and Future Prospects

Salas

Gariazzo

Mena

et al. 2018

Front. Astron. Space Sci.

193

197

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The ordering of the neutrino masses is a crucial input for a deep understanding of flavor physics, and its determination may provide the key to establish the relationship among the lepton masses and mixings and their analogous properties in the quark sector. The extraction of the neutrino mass ordering is a data-driven field expected to evolve very rapidly in the next decade. In this review, we both analyze the present status and describe the physics of subsequent prospects. Firstly, the different current available tools to measure the neutrino mass ordering are described. Namely, reactor, long-baseline (accelerator and atmospheric) neutrino beams, laboratory searches for beta and neutrinoless double beta decays and observations of the cosmic background radiation and the large scale structure of the universe are carefully reviewed. Secondly, the results from an up-to-date comprehensive global fit are reported: the Bayesian analysis to the 2018 publicly available oscillation and cosmological data sets provides strong evidence for the normal neutrino mass ordering versus the inverted scenario, with a significance of 3.5 standard deviations. This preference for the normal neutrino mass ordering is mostly due to neutrino oscillation measurements. Finally, we shall also emphasize the future perspectives for unveiling the neutrino mass ordering. In this regard, apart from describing the expectations from the aforementioned probes, we also focus on those arising from alternative and novel methods, as 21 cm cosmology, core-collapse supernova neutrinos and the direct detection of relic neutrinos.10 Here, σ 8 corresponds to the normalization of the matter power spectrum on scales of 8h −1 Mpc, see Equation (13). 11 The thermal SZ thermal effect consists on a spectral distortion on CMB photons which arrive along the line of sight of a cluster.

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“…To these tree forces we add a particle-mesh (PM) field for the fluctuations due to massive neutrinos, photons, DE and the metric field in order to study their effect on cosmological structure growth at linear level (for simulations treating neutrinos fully nonlinearly see e.g. Banerjee et al 2018;Bird et al 2018). This aspect is one of the key differences between EuclidEm-ulator1 and EuclidEmulator2.…”

Section: N-body Simulationmentioning

confidence: 99%

Euclid preparation: IX. EuclidEmulator2 – power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations

Knabenhans

Stadel

Potter

et al. 2021

Monthly Notices of the Royal Astronomical Society

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We present a new, updated version of the EuclidEmulator (called EuclidEmulator2), a fast and accurate predictor for the nonlinear correction of the matter power spectrum. 2 per cent-level accurate emulation is now supported in the eight-dimensional parameter space of w0waCDM+∑mν models between redshift z = 0 and z = 3 for spatial scales within the range 0.01 h Mpc−1 ≤ k ≤ 10 h Mpc−1. In order to achieve this level of accuracy, we have had to improve the quality of the underlying N-body simulations used as training data: (i) we use self-consistent linear evolution of non-dark matter species such as massive neutrinos, photons, dark energy and the metric field, (ii) we perform the simulations in the so-called N-body gauge, which allows one to interpret the results in the framework of general relativity, (iii) we run over 250 high-resolution simulations with 30003 particles in boxes of 1(h−1 Gpc)3 volumes based on paired-and-fixed initial conditions and (iv) we provide a resolution correction that can be applied to emulated results as a post-processing step in order to drastically reduce systematic biases on small scales due to residual resolution effects in the simulations. We find that the inclusion of the dynamical dark energy parameter wa significantly increases the complexity and expense of creating the emulator. The high fidelity of EuclidEmulator2 is tested in various comparisons against N-body simulations as well as alternative fast predictors like HALOFIT, HMCode and CosmicEmu. A blind test is successfully performed against the Euclid Flagship v2.0 simulation. Nonlinear correction factors emulated with EuclidEmulator2 are accurate at the level of $1{{\ \rm per\ cent}}$ or better for 0.01 h Mpc−1 ≤ k ≤ 10 h Mpc−1 and z ≤ 3 compared to high-resolution dark matter only simulations. EuclidEmulator2 is publicly available at https://github.com/miknab/EuclidEmulator2.

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Reducing noise in cosmological N-body simulations with neutrinos

Cited by 67 publications

References 79 publications

Massive neutrinos leave fingerprints on cosmic voids

Massive neutrinos leave fingerprints on cosmic voids

Neutrino Mass Ordering from Oscillations and Beyond: 2018 Status and Future Prospects

Euclid preparation: IX. EuclidEmulator2 – power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations

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