Euclid preparation : LIII. LensMC, weak lensing cosmic shear measurement with forward modelling and Markov Chain Monte Carlo sampling

Abstract

<p> LENSMC is a weak lensing shear measurement method developed for <em>Euclid</em> and Stage-IV surveys. It is based on forward modelling in order to deal with convolution by a point spread function (PSF) with comparable size to many galaxies, sampling the posterior distribution of galaxy parameters via Markov chain Monte Carlo, and marginalisation over nuisance parameters for each of the 1.5 billion galaxies observed by <em>Euclid</em>. We quantified the scientific performance through high-fidelity images based on the <em>Euclid</em> Flagship simulations and emulation of the <em>Euclid</em> VIS images, realistic clustering with a mean surface number density of 250 arcmin⁻² (<em>I</em>_E < 29.5) for galaxies, and 6 arcmin⁻² (<em>I</em>_E < 26) for stars, and a diffraction-limited chromatic PSF with a full width at half maximum of 0′.′2 and spatial variation across the field of view. LENSMC measured objects with a density of 90 arcmin⁻² (<em>I</em>_E < 26.5) in 4500 deg². The total shear bias was broken down into measurement (our main focus here) and selection effects (which will be addressed in future work). We found measurement multiplicative and additive biases of <em>m</em>₁ = (−3.6 ± 0.2) × 10⁻³, <em>m</em>₂ = (−4.3 ± 0.2) × 10⁻³, <em>c</em>₁ = (−1.78 ± 0.03) × 10−⁴, and <em>c</em>₂ = (0.09 ± 0.03) × 10⁻⁴; a large detection bias with a multiplicative component of 1.2 × 10⁻² and an additive component of −3 × 10⁻⁴; and a measurement PSF leakage of <em>α</em>₁ = (−9 ± 3) × 10⁻⁴ and <em>α</em>₂ = (2 ± 3) × 10⁻⁴. When model bias is suppressed, the obtained measurement biases are close to <em>Euclid</em> requirement and largely dominated by undetected faint galaxies (−5 × 10⁻³). Although significant, model bias will be straightforward to calibrate given its weak sensitivity on galaxy morphology parameters. LENSMC is publicly available at gitlab.com/gcongedo/LensMC. <br></p>