We develop an estimator for the correlation function which, in the ensemble average, returns the shape of the correlation function, even for signals that have significant correlations on the scale of the survey region. Our estimator is general and works in any number of dimensions. We devel
We present a new statistical tool, called the triangle correlation function (TCF), inspired by the earlier work of Obreschkow et al. It is derived from the three-point correlation function and aims to probe the characteristic scale of ionized regions during the epoch of reionization from 21cm interferometric observations. Unlike most works, which focus on power spectrum, i.e. amplitude information, our statistic is based on the information we can extract from the phases of the Fourier transform of the ionization field. In this perspective, it may benefit from the well-known interferometric concept of closure phases. We find that this statistical estimator performs very well on simple ionization fields. For example, with well-defined fully ionized discs, there is a peaking scale, which we can relate to the radius of the ionized bubbles. We explore the robustness of the TCF when observational effects such as angular resolution and noise are considered. We also get interesting results on fields generated by more elaborate simulations such as 21CMFAST. Although the variety of sources and ionized morphologies in the early stages of the process make its interpretation more challenging, the nature of the signal can tell us about the stage of reionization. Finally, and in contrast to other bubble size distribution algorithms, we show that the TCF can resolve two different characteristic scales in a given map.
The presence of double-peaked/multicomponent emission line profiles in spectra of galaxies is commonly done by visual inspection. However, the identification of complex emission line profiles by eye is unapproachable for large databases such as the Sloan Digital Sky Survey (SDSS) or the integral field spectroscopy surveys of galaxies (e.g. CALIFA or MaNGA). We describe a quick method involving the cross-correlation technique for detecting the presence of complex (double-peaked or multiple components) profiles in the spectra of galaxies, deriving simultaneously a first estimation of the velocity dispersions and radial velocities of the dominant gaseous component. We illustrate the proposed procedure with the well-known complex [OIII]4959,5007 profiles of the central region of NGC1068.
We investigate how the shape of the galaxy two-point correlation function as measured in the zCOSMOS survey depends on local environment, quantified in terms of the density contrast on scales of 5 Mpc/h. We show that the flat shape previously observed at redshifts between z=0.6 and z=1 can be explained by this volume being simply 10% over-abundant in high-density environments, with respect to a Universal density probability distribution function. When galaxies corresponding to the top 10% tail of the distribution are excluded, the measured w_p(r_p) steepens and becomes indistinguishable from LCDM predictions on all scales. This is the same effect recognised by Abbas & Sheth in the SDSS data at z~0 and explained as a natural consequence of halo-environment correlations in a hierarchical scenario. Galaxies living in high-density regions trace dark matter halos with typically higher masses, which are more correlated. If the density probability distribution function of the sample is particularly rich in high-density regions because of the variance introduced by its finite size, this produces a distorted two-point correlation function. We argue that this is the dominant effect responsible for the observed peculiar clustering in the COSMOS field.
We present a set of tools to assess the capabilities of LISA to detect and reconstruct the spectral shape and amplitude of a stochastic gravitational wave background (SGWB). We first provide the LISA power-law sensitivity curve and binned power-law sensitivity curves, based on the latest updates on the LISA design. These curves are useful to make a qualitative assessment of the detection and reconstruction prospects of a SGWB. For a quantitative reconstruction of a SGWB with arbitrary power spectrum shape, we propose a novel data analysis technique: by means of an automatized adaptive procedure, we conveniently split the LISA sensitivity band into frequency bins, and fit the data inside each bin with a power law signal plus a model of the instrumental noise. We apply the procedure to SGWB signals with a variety of representative frequency profiles, and prove that LISA can reconstruct their spectral shape. Our procedure, implemented in the code SGWBinner, is suitable for homogeneous and isotropic SGWBs detectable at LISA, and it is also expected to work for other gravitational wave observatories.
Weak gravitational lensing is a very sensitive way of measuring cosmological parameters, including dark energy, and of testing current theories of gravitation. In practice, this requires exquisite measurement of the shapes of billions of galaxies over large areas of the sky, as may be obtained with the EUCLID and WFIRST satellites. For a given survey depth, applying image denoising to the data both improves the accuracy of the shape measurements and increases the number density of galaxies with a measurable shape. We perform simple tests of three different denoising techniques, using synthetic data. We propose a new and simple denoising method, based on wavelet decomposition of the data and a Wiener filtering of the resulting wavelet coefficients. When applied to the GREAT08 challenge dataset, this technique allows us to improve the quality factor of the measurement (Q; GREAT08 definition), by up to a factor of two. We demonstrate that the typical pixel size of the EUCLID optical channel will allow us to use image denoising.