Noise bias in weak lensing shape measurements

Alexandre Refregier, Tomasz Kacprzak, Adam Amara, Sarah Bridle, Barnaby Rowe

    Research output: Contribution to journalArticlepeer-review


    Weak lensing experiments are a powerful probe into cosmology through their measurement of the mass distribution of the universe. A challenge for this technique is to control systematic errors that occur when measuring the shapes of distant galaxies. In this paper, we investigate noise bias, a systematic error that arises from second-order noise terms in the shape measurement process. We first derive analytical expressions for the bias of general maximum-likelihood estimators in the presence of additive noise. We then find analytical expressions for a simplified toy model in which galaxies are modelled and fitted with a Gaussian with its size as a single free parameter. Even for this very simple case we find a significant effect. We also extend our analysis to a more realistic six-parameter elliptical Gaussian model. We find that the noise bias is generically of the order of the inverse-squared signal-to-noise ratio (SNR) of the galaxies and is thus of the order of a percent for galaxies of SNR 10, i.e. comparable to the weak lensing shear signal. This is nearly two orders of magnitude greater than the systematic requirements for future all-sky weak lensing surveys. We discuss possible ways to circumvent this effect, including a calibration method using simulations discussed in an associated paper. © 2012 The Authors Monthly Notices of the Royal Astronomical Society © 2012 RAS.
    Original languageEnglish
    Pages (from-to)1951-1957
    Number of pages6
    JournalMonthly Notices of the Royal Astronomical Society
    Issue number3
    Publication statusPublished - 21 Sept 2012


    • Cosmology: observations
    • Dark energy
    • Dark matter
    • Gravitational lensing: weak
    • Methods: statistical
    • Techniques: image processing


    Dive into the research topics of 'Noise bias in weak lensing shape measurements'. Together they form a unique fingerprint.

    Cite this