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Modelling the shapes of the largest gravitationally bound objects
Rossi, Graziano,Sheth, Ravi K.,Tormen, Giuseppe Blackwell Publishing Ltd 2011 MONTHLY NOTICES- ROYAL ASTRONOMICAL SOCIETY Vol.416 No.1
<P><B>ABSTRACT</B></P><P>We combine the physics of the ellipsoidal collapse model with the excursion set theory to study the shapes of dark matter haloes. In particular, we develop an analytic approximation to the non‐linear evolution that is more accurate than the Zeldovich approximation; we introduce a planar representation of halo axial ratios, which allows a concise and intuitive description of the dynamics of collapsing regions and allows one to relate the final shape of a halo to its initial shape; we provide simple physical explanations for some empirical fitting formulae obtained from numerical studies. Comparison with simulations is challenging, as there is no agreement about how to define a non‐spherical gravitationally bound object. Nevertheless, we find that our model matches the conditional minor‐to‐intermediate axial ratio distribution rather well, although it disagrees with the numerical results in reproducing the minor‐to‐major axial ratio distribution. In particular, the mass dependence of the minor‐to‐major axis distribution appears to be the opposite to what is found in many previous numerical studies, where low‐mass haloes are preferentially more spherical than high‐mass haloes. In our model, the high‐mass haloes are predicted to be more spherical, consistent with results based on a more recent and elaborate halo finding algorithm, and with observations of the mass dependence of the shapes of early‐type galaxies. We suggest that some of the disagreement with some previous numerical studies may be alleviated if we consider only isolated haloes.</P>
Excursion Set Statistics with Primordial Non-Gaussianity
Graziano Rossi,Pravabati Chingangbam,박창범 한국물리학회 2010 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.57 No.31
The statistics of regions above and below a temperature threshold (excursion sets), fully characterized in the contest of Gaussian random fields, is here extended to models with primordial non-Gaussianity of the local type and is used to analyze the cosmic microwave background (CMB) sky via simulated non-Gaussian maps. In particular, a positive value of the non-Gaussian parameter fNL is found to enhance the number density of the cold CMB excursion sets, along with their clustering strength, and to reduce that of the hot ones. This effect may be important to discriminate between the simpler Gaussian hypothesis and non-Gaussian scenarios, arising either from non-standard inflation or alternative early-universe models. However, while a distinct signature in the clustering of hot and cold pixels clearly emerges for large non-Gaussianity, particularly at angular scales of about 75 arcmin, the considered statistics appears to be less sensitive when fNL is relatively small and an additional smoothing is applied. This fact may pose a challenge if using the excursion set regions to constrain fNL, or the Gaussianity itself, from a real data set – in presence of noise and other observational artifacts.
Rossi, Graziano,Sheth, Ravi K.,Park, Changbom Blackwell Publishing Ltd 2010 MONTHLY NOTICES- ROYAL ASTRONOMICAL SOCIETY Vol.401 No.1
<P>ABSTRACT</P><P>Noisy distance estimates associated with photometric rather than spectroscopic redshifts lead to a biased estimate of the luminosity distribution, and produce a correlated misestimate of the sizes. We consider a sample of early-type galaxies from the Sloan Digital Sky Survey Data Release 6 for which both spectroscopic and photometric information is available, and apply the generalization of the <I>V</I><SUB>max</SUB> method to correct for these biases. We show that our technique recovers the true redshift, magnitude and size distributions, as well as the true size–luminosity relation. We find that using only 10 per cent of the spectroscopic information randomly spaced in our catalogue is sufficient for the reconstructions to be accurate within ∼3 per cent, when the photometric redshift error is δ<I>z</I>≃ 0.038. We then address the problem of extending our method to deep redshift catalogues, where only photometric information is available. In addition to the specific applications outlined here, our technique impacts a broader range of studies, when at least one distance-dependent quantity is involved. It is particularly relevant for the next generation of surveys, some of which will only have photometric information.</P>
COSMOLOGY WITH MASSIVE NEUTRINOS: CHALLENGES TO THE STANDARD ΛCDM PARADIGM
ROSSI, GRAZIANO The Korean Astronomical Society 2015 天文學論叢 Vol.30 No.2
Determining the absolute neutrino mass scale and the neutrino mass hierarchy are central goals in particle physics, with important implications for the Standard Model. However, the final answer may come from cosmology, as laboratory experiments provide measurements for two of the squared mass differences and a stringent lower bound on the total neutrino mass - but the upper bound is still poorly constrained, even when considering forecasted results from future probes. Cosmological tracers are very sensitive to neutrino properties and their total mass, because massive neutrinos produce a specific redshift-and scale-dependent signature in the power spectrum of the matter and galaxy distributions. Stringent upper limits on ${\sum}m_v$ will be essential for understanding the neutrino sector, and will nicely complement particle physics results. To this end, we describe here a series of cosmological hydrodynamical simulations which include massive neutrinos, specifically designed to meet the requirements of the Baryon Acoustic Spectroscopic Survey (BOSS) and focused on the Lyman-${\alpha}$ ($Ly{\alpha}$) forest - also a useful theoretical ground for upcoming surveys such as SDSS-IV/eBOSS and DESI. We then briefly highlight the remarkable constraining power of the $Ly{\alpha}$ forest in terms of the total neutrino mass, when combined with other state-of-the-art cosmological probes, leaving to a stringent upper bound on ${\sum}m_v$.