Euclid: The reduced shear approximation and magnification bias for Stage IV cosmic shear experiments

Euclid: The reduced shear approximation and magnification bias for Stage IV cosmic shear experiments

Authors: A.C. Deshpande, ..., S. Casas, M. Kilbinger, V. Pettorino, S. Pires, J.-L. Starck, F. Sureau, et al.
Journal: Astronomy and Astrophysics
Year: 2020
DOI:  10.1051/0004-6361/201937323
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Abstract

Stage IV weak lensing experiments will offer more than an order of magnitude leap in precision. We must therefore ensure that our analyses remain accurate in this new era. Accordingly, previously ignored systematic effects must be addressed. In this work, we evaluate the impact of the reduced shear approximation and magnification bias, on the information obtained from the angular power spectrum. To first-order, the statistics of reduced shear, a combination of shear and convergence, are taken to be equal to those of shear. However, this approximation can induce a bias in the cosmological parameters that can no longer be neglected. A separate bias arises from the statistics of shear being altered by the preferential selection of galaxies and the dilution of their surface densities, in high-magnification regions. The corrections for these systematic effects take similar forms, allowing them to be treated together. We calculated the impact of neglecting these effects on the cosmological parameters that would be determined from Euclid, using cosmic shear tomography. To do so, we employed the Fisher matrix formalism, and included the impact of the super-sample covariance. We also demonstrate how the reduced shear correction can be calculated using a lognormal field forward modelling approach. These effects cause significant biases in Omega_m, sigma_8, n_s, Omega_DE, w_0, and w_a of -0.53 sigma, 0.43 sigma, -0.34 sigma, 1.36 sigma, -0.68 sigma, and 1.21 sigma, respectively. We then show that these lensing biases interact with another systematic: the intrinsic alignment of galaxies. Accordingly, we develop the formalism for an intrinsic alignment-enhanced lensing bias correction. Applying this to Euclid, we find that the additional terms introduced by this correction are sub-dominant.

Euclid: The selection of quiescent and star-forming galaxies using observed colours

Euclid: The selection of quiescent and star-forming galaxies using observed colours

Authors: L. Bisigello, ..., V. Pettorino, S. Pires, F. Sureau, et al.
Journal: MNRAS
Year: 2020
DOI:  10.1093/mnras/staa885
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Abstract

The Euclid mission will observe well over a billion galaxies out to z6 and beyond. This will offer an unrivalled opportunity to investigate several key questions for understanding galaxy formation and evolution. The first step for many of these studies will be the selection of a sample of quiescent and star-forming galaxies, as is often done in the literature by using well known colour techniques such as the `UVJ' diagram. However, given the limited number of filters available for the Euclid telescope, the recovery of such rest-frame colours will be challenging. We therefore investigate the use of observed Euclid colours, on their own and together with ground-based u-band observations, for selecting quiescent and star-forming galaxies. The most efficient colour combination, among the ones tested in this work, consists of the (u-VIS) and (VIS-J) colours. We find that this combination allows users to select a sample of quiescent galaxies complete to above 70% and with less than 15% contamination at redshifts in the range 0.75<z<1. For galaxies at high-z or without the u-band complementary observations, the (VIS-Y) and (J-H) colours represent a valid alternative, with >65% completeness level and contamination below 20% at 1<z<2 for finding quiescent galaxies. In comparison, the sample of quiescent galaxies selected with the traditional UVJ technique is only 20% complete at z<3, when recovering the rest-frame colours using mock Euclid observations. This shows that our new methodology is the most suitable one when only Euclid bands, along with u-band imaging, are available.

Beyond self-acceleration: force- and fluid-acceleration

The notion of self acceleration has been introduced as a convenient way to theoretically distinguish cosmological models in which acceleration is due to modified gravity from those in which it is due to the properties of matter or fields. In this paper we review the concept of self acceleration as given, for example, by [1], and highlight two problems. First, that it applies only to universal couplings, and second, that it is too narrow, i.e. it excludes models in which the acceleration can be shown to be induced by a genuine modification of gravity, for instance coupled dark energy with a universal coupling, the Hu-Sawicki f(R) model or, in the context of inflation, the Starobinski model. We then propose two new, more general, concepts in its place: force-acceleration and field-acceleration, which are also applicable in presence of non universal cosmologies. We illustrate their concrete application with two examples, among the modified gravity classes which are still in agreement with current data, i.e. f(R) models and coupled dark energy.

As noted already for example in [35, 36], we further remark that at present non-universal couplings are among the (few) classes of models which survive gravitational wave detection and local constraints (see [12] for a review on models surviving with a universal coupling). This is because, by construction, baryonic interactions are standard and satisfy solar system constraints; furthermore the speed of gravitational waves in these models is  cT = 1 and therefore in agreement with gravitational wave detection. It has also been noted (see for example [37–39] and the update in [33]) that models in which a non-universal coupling between dark matter particles is considered would also solve the tension in the measurement of the Hubble parameter [40] due to the degeneracy beta - H0 first noted in Ref. [41].

Reference: L.Amendola, V.Pettorino  "Beyond self-acceleration: force- and fluid-acceleration", Physics Letters B, in press, 2020.

Non linear matter power spectrum and machine learning

Non linear matter power spectrum and machine learning

Position: Internship
Deadline:  1/02/2020
Contact: Santiago Casas, V. Pettorino, Jean-Luc Starck

Details about this position are provided in the following PDF.

If interested, please send an e-mail with CV and arrange for at least one reference letter to be sent to us separately. 

Cross-correlations between cosmological probes from Euclid, BOSS/e-BOSS, Planck and beyond

Cross-correlations between cosmological probes from Euclid, BOSS/e- BOSS, Planck and beyond

Position: PhD (starting Fall 2020) / internship
Deadline:  1/02/2020
Contact: V. Pettorino, M. Kilbinger

Details about this position are provided in the following PDF.

If interested, please send an e-mail with your CV and arrange for at least one reference letter to be sent to us separately. 

EuroPython 2019

Date: July 8-14 2019

Venue: Basel, CH

Website: https://ep2019.europython.eu/

Blog: http://blog.europython.eu/

Twitter: @europython

Conference App will be announced on the blog.

EuroPython is an annual conference hosting ~1200 participants from academia and companies, interested in development and applications of python programming language. It’s also a good opportunity for students and postdocs who wish to find a job outside academia.

For more info, contact: Valeria Pettorino


 

 

Cosmological Parameters Estimation within Growing Neutrinos

Position: Internship
Deadline:  28/02/2019
Contact: V. Pettorino and S.Casas

Dark energy may be triggered by neutrinos with varying mass (https://arxiv.org/abs/1608.02358). The internship is meant to use a MonteCarlo COSMOMC Boltzmann code to test a simplified framework for this scenario using a prescription we have developed already. The student will be able to use data to test theories, using MCMC simulations.  It will involve collaboration with IAP (F.Fuhrer) and Heidelberg (C.Wetterich), potentially leading to a scientific paper. Availability for 6 months is preferred.

Required skills: python and one language between C or fortran. Previous use of CAMB/CLASS/COSMOMC would be an asset.