Sky reconstruction from transit visibilities: PAON-4 and Tianlai Dish Array

The spherical harmonics $m$-mode decomposition is a powerful sky map reconstruction method suitable for radio interferometers operating in transit mode. It can be applied to various configurations, including dish arrays and cylinders. We describe the computation of the instrument response function, the point spread function (PSF), transfer function, the noise covariance matrix and noise power spectrum. The analysis in this paper is focused on dish arrays operating in transit mode. We show that arrays with regular spacing have more pronounced side lobes as well as structures in their noise power spectrum, compared to arrays with irregular spacing, specially in the north-south direction. A good knowledge of the noise power spectrum $C^{\mathrm{noise}}(\ell)$ is essential for intensity mapping experiments as non uniform $C^{\mathrm{noise}}(\ell)$ is a potential problem for the measurement of the HI power spectrum. Different configurations have been studied to optimise the PAON-4 and Tianlai dish array layouts. We present their expected performance and their sensitivities to the 21-cm emission of the Milky Way and local extragalactic HI clumpsComment: 20 pages, 18 figures - Submitted to MNRAS ( the appendix A,B are not included in the accepted version

The SPL-Fr\'{e}jus physics potential

An optimization of the CERN-SPL beam line has been performed which leads to better sensitivities to the $\theta\_{13}$ mixing angle and to the $\delta\_{CP}$ violating phase than those advocated considering baseline scenario.Comment: 2 pages, 3 figures. To be published in Nuclear Physics B (Proceedings Supplement

Sky reconstruction for the Tianlai cylinder array

In this paper, we apply our sky map reconstruction method for transit type interferometers to the Tianlai cylinder array. The method is based on the spherical harmonic decomposition, and can be applied to cylindrical array as well as dish arrays and we can compute the instrument response, synthesised beam, transfer function and the noise power spectrum. We consider cylinder arrays with feed spacing larger than half wavelength, and as expected, we find that the arrays with regular spacing have grating lobes which produce spurious images in the reconstructed maps. We show that this problem can be overcome, using arrays with different feed spacing on each cylinder. We present the reconstructed maps, and study the performance in terms of noise power spectrum, transfer function and beams for both regular and irregular feed spacing configurations.Comment: 15 pages, 12 figures, accepted by RA

Stratégies pour l'accès rapide à des hétérocycles azotés à partir d'alcools propargyliques

La partie principale de ce manuscrit traite du développement de nouvelles méthodologies utilisant la substitution propargylique catalysée par des sels de fer(III), pour la formation de divers hétérocycles azotés ( 4-isoxazolines, isoxazoles, cis-acylaziridines et pyrimidines). En premier lieu, de nouvelles synthèses monotopes de 4-isoxazolines et d'isoxazoles diversement substitués impliquant des réactions de cyclisation catalysées par diverses espèces carbophiles ([Au], [Pd], [I+]) ont été développées. La fragilité de la liaison N-O des 4-isoxazolines a pu être ensuite exploitée pour conduire à la formation de cis-acylaziridines. De nouvelles voies d'accès aux (Z)-b-énaminones et aux pyrimidines trisubstituées ont été également développées.The main part of this manuscript deals with the development of new methodologies using iron(III)-catalyzed propargylic substitution, for the synthesis of various nitrogen-containing heterocycles ( 4-isoxazolines, isoxazoles, cis-acylaziridines and pyrimidines). Firstly, new one-pot syntheses of variously substituted 4-isoxazolines and isoxazoles involving cyclization reactions promoted by various carbophilic species ([Au], [Pd], [I+]) have been developed. The weakness of the 4-isoxazoline N-O bond has been then exploited, leading to the formation of cis-acylaziridines. New pathways to (Z)-b-enaminones and trisubstituted pyrimidines have also been developed.MONTPELLIER-Ecole Nat.Chimie (341722204) / SudocSudocFranceF

Core Cosmology Library: Precision Cosmological Predictions for LSST

The Core Cosmology Library (CCL) provides routines to compute basic cosmological observables to a high degree of accuracy, which have been verified with an extensive suite of validation tests. Predictions are provided for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias and the halo mass function through state-of-the-art modeling prescriptions available in the literature. Fiducial specifications for the expected galaxy distributions for the Large Synoptic Survey Telescope (LSST) are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. A rigorous validation procedure, based on comparisons between CCL and independent software packages, allows us to establish a well-defined numerical accuracy for each predicted quantity. As a result, predictions for correlation functions of galaxy clustering, galaxy-galaxy lensing and cosmic shear are demonstrated to be within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is an open source software package written in C, with a python interface and publicly available at https://github.com/LSSTDESC/CCL.Comment: 38 pages, 18 figures, matches ApJS accepted versio

Adversarial training applied to Convolutional Neural Network for photometric redshift predictions

The use of Convolutional Neural Networks (CNN) to estimate the galaxy photometric redshift probability distribution by analysing the images in different wavelength bands has been developed in the recent years thanks to the rapid development of the Machine Learning (ML) ecosystem. Authors have set-up CNN architectures and studied their performances and some sources of systematics using standard methods of training and testing to ensure the generalisation power of their models. So far so good, but one piece was missing : does the model generalisation power is well measured? The present article shows clearly that very small image perturbations can fool the model completely and opens the Pandora's box of \textit{adversarial} attack. Among the different techniques and scenarios, we have chosen to use the Fast Sign Gradient one-step Method and its Projected Gradient Descent iterative extension as adversarial generator tool kit. However, as unlikely as it may seem these adversarial samples which fool not only a single model, reveal a weakness both of the model and the classical training. A revisited algorithm is shown and applied by injecting a fraction of adversarial samples during the training phase. Numerical experiments have been conducted using a specific CNN model for illustration although our study could be applied to other models - not only CNN ones - and in other contexts - not only redshift measurements - as it deals with the complexity of the boundary decision surface