Vincent Desjacques

Dancing in the dark: galactic properties trace spin swings along the cosmic web

A large-scale hydrodynamical cosmological simulation, Horizon-AGN , is used to investigate the alignment between the spin of galaxies and the large-scale cosmic filaments above redshift one. The analysis of more than 150 000 galaxies with morphological diversity in a 100h −1 Mpc comoving box size shows that the spin of low-mass, rotationdominated, blue, star-forming galaxies is preferentially aligned with their neighbouring filaments. High-mass, dispersion-dominated, red, quiescent galaxies tend to have a spin perpendicular to nearby filaments. The reorientation of the spin of massive galaxies is provided by galaxy mergers which are significant in the mass build up of high-mass galaxies. We find that the stellar mass transition from alignment to misalignment happens around 3×10 10 M⊙. This is consistent with earlier findings of a dark matter mass transition for the orientation of the spin of halos (5 × 10 11 M⊙ at the same redshift from Codis et al. 2012). With these numerical evidence, we advocate a scenario in which galaxies form in the vorticity-rich neighbourhood of filaments, and migrate towards the nodes of the cosmic web as they convert their orbital angular momentum into spin. The signature of this process can be traced to the physical and morphological properties of galaxies, as measured relative to the cosmic web. We argue that a strong source of feedback such as Active Galactic Nuclei is mandatory to quench in situ star formation in massive galaxies. It allows mergers to play their key role by reducing post-merger gas inflows and, therefore, keeping galaxy spins misaligned with cosmic filaments. It also promotes diversity amongst galaxy properties.

Scale-dependent bias induced by local non-Gaussianity: A comparison to N-body simulations

We investigate the effect of primordial non-Gaussianity of the local fNL type on the auto- and cross-power spectra of dark matter haloes using simulations of the cold dark matter cosmology. We perform a series of large N-body simulations of both positive and negative fNL, spanning the range between 10 and 100. Theoretical models predict a scale-dependent bias correction b(k, fNL) that depends on the linear halo bias b(M). We measure the power spectra for a range of halo mass and redshifts covering the relevant range of existing galaxy and quasar populations. We show that auto- and cross-correlation analyses of bias are consistent with each other. We find that for low wavenumbers with k 1.5. We show that a scale-independent bias correction improves the comparison between theory and simulations on smaller scales, where the scale-dependent effect rapidly becomes negligible. The current limits on fNL from Slosar et al. come mostly from very large scales k < 0.01 h Mpc-1 and, therefore, remain valid. For the halo samples with b(M) < 1.5 - 2, we find that the scale-dependent bias from non-Gaussianity actually exceeds the theoretical predictions. Our results are consistent with the bias correction scaling linearly with fNL.

Signature of primordial non-Gaussianity of phi^3-type in the mass function and bias of dark matter haloes

We explore the effect of a cubic correction g{sub NL{phi}}{sup 3} on the mass function and bias of dark matter haloes extracted from a series of large N-body simulations and compare it to theoretical predictions. Such cubic terms can be motivated in scenarios like the curvaton model, in which a large cubic correction can be produced while simultaneously keeping the quadratic f{sub NL{phi}}{sup 2} correction small. The deviation from the Gaussian halo mass function is in reasonable agreement with the theoretical predictions. The scale-dependent bias correction {Delta}b{sub {kappa}}(k,g{sub NL}) measured from the auto- and cross-power spectrum of haloes, is similar to the correction in f{sub NL} models, but the amplitude is lower than theoretical expectations. Using the compilation of LSS data in [A. Slosar et al., J. Cosmol. Astropart. Phys. 08 (2008) 031], we obtain for the first time a limit on g{sub NL} of -3.5x10{sup 5}<g{sub NL}<+8.2x10{sup 5} (at 95% CL). This limit will improve with the future LSS data by 1-2 orders of magnitude, which should test many of the scenarios of this type.

Evidence for quadratic tidal tensor bias from the halo bispectrum

The relation between the clustering properties of luminous matter in the form of galaxies and the underlying dark matter distribution is of fundamental importance for the interpretation of ongoing and upcoming galaxy surveys. The so-called local bias model, where galaxy density is a function of local matter density, is frequently discussed as a means to infer the matter power spectrum or correlation function from the measured galaxy correlation. However, gravitational evolution generates a term quadratic in the tidal tensor and thus nonlocal in the Eulerian density field, even if this term is absent in the initial conditions (Lagrangian space). Because the term is quadratic, it contributes as a loop correction to the power spectrum, so the standard linear bias picture still applies on very large scales; however, it contributes at leading order to the bispectrum for which it is significant on all scales. Such a term could also be present in Lagrangian space if halo formation were influenced by the tidal field. We measure the corresponding coupling strengths from the matter-matter-halo bispectrum in numerical simulations and find a nonvanishing coefficient for the tidal tensor term. We find no scale dependence of the inferred bias parameters up to k∼0.1h  Mpc−1 and that the tidal effect is increasing with halo mass. While the local Lagrangian bias picture is a better description of our results than the local Eulerian bias picture, our results suggest that there might be a tidal tensor bias already in the initial conditions. We also find that the coefficients of the quadratic density term deviate quite strongly from the theoretical predictions based on the spherical collapse model and a universal mass function. Both quadratic density and tidal tensor bias terms must be included in the modeling of galaxy clustering of current and future surveys if one wants to achieve the high precision cosmology promise of these data sets.

Primordial non-Gaussianity from the large-scale structure

Primordial non-Gaussianity is a potentially powerful discriminant of the physical mechanisms that generate the cosmological fluctuations observed today. Any detection of non-Gaussianity would have profound implications for our understanding of cosmic structure formation. In this paper, we review past and current efforts in the search for primordial non-Gaussianity in the large-scale structure of the Universe.

High-performance P3M N-body code: cubep3m

This paper presents cubep3m, a publicly available high-performance cosmological N-body code and describes many utilities and extensions that have been added to the standard package. These include a memory-light runtime spherical overdensity halo finder, a non-Gaussian initial conditions generator and a system of unique particle identification. cubep3m is fast, its accuracy is tuneable to optimize speed or memory and has been run on more than 27 000 cores, achieving within a factor of 2 of ideal weak scaling even at this problem size. The code can be run in an extra-lean mode where the peak memory imprint for large runs is as low as 37 bytes per particles, which is almost two times leaner than other widely used N-body codes. However, load imbalances can increase this requirement by a factor of 2, such that fast configurations with all the utilities enabled and load imbalances factored in require between 70 and 120 bytes per particles. cubep3m is well designed to study large-scale cosmological systems, where imbalances are not too large and adaptive time-stepping not essential. It has already been used for a broad number of science applications that require either large samples of non-linear realizations or very large dark matter N-body simulations, including cosmological reionization, halo formation, baryonic acoustic oscillations, weak lensing or non-Gaussian statistics. We discuss the structure, the accuracy, known systematic effects and the scaling performance of the code and its utilities, when applicable.

Non-Gaussian Halo Bias Re-examined: Mass-dependent Amplitude from the Peak-Background Split and Thresholding

Recent results of N-body simulations have shown that current theoretical models are not able to correctly predict the amplitude of the scale-dependent halo bias induced by primordial non-Gaussianity, for models going beyond the simplest, local quadratic case. Motivated by these discrepancies, we carefully examine three theoretical approaches based on (1) the statistics of thresholded regions, (2) a peak-background split method based on separation of scales, and (3) a peak-background split method using the conditional mass function. We first demonstrate that the statistics of thresholded regions, which is shown to be equivalent at leading order to a local bias expansion, cannot explain the mass-dependent deviation between theory and N-body simulations. In the two formulations of the peak-background split on the other hand, we identify an important, but previously overlooked, correction to the non-Gaussian bias that strongly depends on halo mass. This new term is in general significant for any primordial non-Gaussianity going beyond the simplest local fNL model. In a separate paper (to be published in PRD rapid communication), the authors compare these new theoretical predictions with N-body simulations, showing good agreement for all simulated types of non-Gaussianity.

Redshift space correlations and scale-dependent stochastic biasing of density peaks

We calculate the redshift space correlation function and the power spectrum of density peaks of a Gaussian random field. Our derivation, which is valid on linear scales

Excursion set peaks: a self-consistent model of dark halo abundances and clustering

k\ensuremath{\lesssim}0.1\text{ }\text{ }h{\mathrm{Mpc}}^{\ensuremath{-}1}

Halo stochasticity from exclusion and nonlinear clustering

, is based on the peak biasing relation given by Desjacques [Phys. Rev. D, 78, 103503 (2008)]. In linear theory, the redshift space power spectrum is