arXiv subjects

Carolina Cuesta-Lazaro

Publications and source records attributed to Carolina Cuesta-Lazaro.

39 records · Page 3Linked to original sources

arXiv2020

Towards a non-Gaussian model of redshift space distortions

To understand the nature of the accelerated expansion of the Universe, we need to combine constraints on the expansion rate and growth of structure. The growth rate is usually extracted from three dimensional galaxy maps by exploiting the effects of peculiar motions on galaxy clustering. However, theoretical models of the probability distribution function (PDF) of galaxy pairwise peculiar velocities are not accurate enough on small scales to reduce the error on theoretical predictions to the level required to match the precision expected for measurements from future surveys. Here, we improve the modelling of the pairwise velocity distribution by using the Skew-T PDF, which has nonzero skewness and kurtosis. Our model accurately reproduces the redshift-space multipoles (monopole, quadrupole and hexadecapole) predicted by N-body simulations, above scales of about $10\,h^{-1}{\rm Mpc}$. We illustrate how a Taylor expansion of the streaming model can reveal the contributions of the different moments to the clustering multipoles, which are independent of the shape of the velocity PDF. The Taylor expansion explains why the Gaussian streaming model works well in predicting the first two redshift-space multipoles, although the velocity PDF is non-Gaussian even on large scales. Indeed, any PDF with the correct first two moments would produce precise results for the monopole down to scales of about $10\,h^{-1}{\rm Mpc}$, and for the quadrupole down to about $30\,h^{-1}{\rm Mpc}$. An accurate model for the hexadecapole needs to include higher-order moments.

astro-ph.CO↗

arXiv2019

XNet: A convolutional neural network (CNN) implementation for medical X-Ray image segmentation suitable for small datasets

X-Ray image enhancement, along with many other medical image processing applications, requires the segmentation of images into bone, soft tissue, and open beam regions. We apply a machine learning approach to this problem, presenting an end-to-end solution which results in robust and efficient inference. Since medical institutions frequently do not have the resources to process and label the large quantity of X-Ray images usually needed for neural network training, we design an end-to-end solution for small datasets, while achieving state-of-the-art results. Our implementation produces an overall accuracy of 92%, F1 score of 0.92, and an AUC of 0.98, surpassing classical image processing techniques, such as clustering and entropy based methods, while improving upon the output of existing neural networks used for segmentation in non-medical contexts. The code used for this project is available online.

cs.CV↗

arXiv2018

Gravitational corrections to light propagation in a perturbed FLRW-universe and corresponding weak lensing spectra

When the gravitational lensing of the large-scale structure is calculated from a cosmological model a few assumptions enter: $(i)$ one assumes that the photons follow unperturbed background geodesics, which is usually referred to as the Born-approximation, $(ii)$ the lenses move slowly, $(iii)$ the source-redshift distribution is evaluated relative to the background quantities and $(iv)$ the lensing effect is linear in the gravitational potential. Even though these approximations are small individually they could sum up, especially since they include local effects such as the Sachs-Wolfe and peculiar motion, but also non-local ones like the Born-approximation and the integrated Sachs-Wolfe effect. In this work we will address all points mentioned and perturbatively calculate the effect on a tomographic cosmic shear power spectrum of each effect individually as well as all cross-correlations. Our findings show that each effect is at least 4 to 5 orders of magnitude below the leading order lensing signal. Finally we sum up all effects to estimate the overall impact on parameter estimation by a future cosmological weak lensing survey such as Euclid in a $w$CDM cosmology with parametrisation $Ω_\mathrm{m}$, $σ_8$,$n_\mathrm{s}$, $h$, $w_0$ and $w_\mathrm{a}$, using 5 tomographic bins. We consistently find a parameter bias of $10^{-5}$, which is therefore completely negligible for all practical purposes, confirming that other effects such as intrinsic alignments and magnification bias will be the dominant systematic source in future surveys.

astro-ph.CO↗