HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR

Michael D. Schneider, David W. Hogg, Philip J. Marshall, William A. Dawson, Joshua Meyers, Deborah J. Bard, Dustin Lang

    Research output: Contribution to journalArticle

    Abstract

    Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.

    Original languageEnglish (US)
    Article number87
    JournalAstrophysical Journal
    Volume807
    Issue number1
    DOIs
    StatePublished - Jul 1 2015

    Fingerprint

    COSMIC
    inference
    galaxies
    shear
    pixel
    specifications
    sampling
    forward modeling
    inverse problem
    estimators
    pixels
    ellipticity
    modeling
    distribution
    shearing

    Keywords

    • catalogs
    • cosmology: observations
    • gravitational lensing: weak
    • methods: data analysis
    • methods: statistical
    • surveys

    ASJC Scopus subject areas

    • Space and Planetary Science
    • Astronomy and Astrophysics

    Cite this

    Schneider, M. D., Hogg, D. W., Marshall, P. J., Dawson, W. A., Meyers, J., Bard, D. J., & Lang, D. (2015). HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR. Astrophysical Journal, 807(1), [87]. https://doi.org/10.1088/0004-637X/807/1/87

    HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR. / Schneider, Michael D.; Hogg, David W.; Marshall, Philip J.; Dawson, William A.; Meyers, Joshua; Bard, Deborah J.; Lang, Dustin.

    In: Astrophysical Journal, Vol. 807, No. 1, 87, 01.07.2015.

    Research output: Contribution to journalArticle

    Schneider, MD, Hogg, DW, Marshall, PJ, Dawson, WA, Meyers, J, Bard, DJ & Lang, D 2015, 'HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR', Astrophysical Journal, vol. 807, no. 1, 87. https://doi.org/10.1088/0004-637X/807/1/87
    Schneider MD, Hogg DW, Marshall PJ, Dawson WA, Meyers J, Bard DJ et al. HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR. Astrophysical Journal. 2015 Jul 1;807(1). 87. https://doi.org/10.1088/0004-637X/807/1/87
    Schneider, Michael D. ; Hogg, David W. ; Marshall, Philip J. ; Dawson, William A. ; Meyers, Joshua ; Bard, Deborah J. ; Lang, Dustin. / HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR. In: Astrophysical Journal. 2015 ; Vol. 807, No. 1.
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