IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v116y2021i535p1088-1099.html
   My bibliography  Save this article

Nonparametric Estimation of Galaxy Cluster Emissivity and Detection of Point Sources in Astrophysics With Two Lasso Penalties

Author

Listed:
  • Jairo Diaz-Rodriguez
  • Dominique Eckert
  • Hatef Monajemi
  • Stéphane Paltani
  • Sylvain Sardy

Abstract

Astrophysicists are interested in recovering the three-dimensional gas emissivity of a galaxy cluster from a two-dimensional telescope image. Blurring and point sources make this inverse problem harder to solve. The conventional approach requires in a first step to identify and mask the point sources. Instead we model all astrophysical components in a single Poisson generalized linear model. To enforce sparsity on the parameters, maximum likelihood estimation is regularized with two l1 penalties with weights λ 1 for the radial emissivity and λ 2 for the point sources. The method has the advantage of not employing cross-validation to select λ 1 and λ 2. To judge the significance of interesting features, we quantify uncertainty with the bootstrap. We apply our method to two X-ray telescopes (XMM-Newton and Chandra) data to estimate gas emissivity. The results are more stable and seems less biased than the conventional method, in particular in the outskirt of galaxy clusters. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Suggested Citation

  • Jairo Diaz-Rodriguez & Dominique Eckert & Hatef Monajemi & Stéphane Paltani & Sylvain Sardy, 2021. "Nonparametric Estimation of Galaxy Cluster Emissivity and Detection of Point Sources in Astrophysics With Two Lasso Penalties," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(535), pages 1088-1099, July.
  • Handle: RePEc:taf:jnlasa:v:116:y:2021:i:535:p:1088-1099
    DOI: 10.1080/01621459.2020.1796676
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2020.1796676
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/01621459.2020.1796676?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jnlasa:v:116:y:2021:i:535:p:1088-1099. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UASA20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.