Journal Article

<span class="smallCaps">orca</span>: The Overdense Red-sequence Cluster Algorithm

D. N. A. Murphy, J. E. Geach and R. G. Bower

in Monthly Notices of the Royal Astronomical Society

Published on behalf of The Royal Astronomical Society

Volume 420, issue 3, pages 1861-1881
Published in print March 2012 | ISSN: 0035-8711
Published online February 2012 | e-ISSN: 1365-2966 | DOI:
orca: The Overdense Red-sequence Cluster Algorithm

More Like This

Show all results sharing this subject:

  • Astronomy and Astrophysics


Show Summary Details


We present a new cluster-detection algorithm designed for the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) survey but with generic application to any multiband data. The method makes no prior assumptions about the properties of clusters other than (i) the similarity in colour of cluster galaxies (the ‘red sequence’); and (ii) an enhanced projected surface density. The detector has three main steps: (i) it identifies cluster members by photometrically filtering the input catalogue to isolate galaxies in colour–magnitude space; (ii) a Voronoi diagram identifies regions of high surface density; and (iii) galaxies are grouped into clusters with a Friends-of-Friends technique. Where multiple colours are available, we require systems to exhibit sequences in two colours. In this paper, we present the algorithm and demonstrate it on two data sets. The first is a 7-deg2 sample of the deep Sloan Digital Sky Survey (SDSS) equatorial stripe (Stripe 82), from which we detect 97 clusters with z≤ 0.6. Benefitting from deeper data, we are 100 per cent complete in the maxBCG optically selected cluster catalogue (based on shallower single-epoch SDSS data) and find an additional 78 previously unidentified clusters. The second data set is a mock Medium Deep Survey Pan-STARRS catalogue, based on the Λ cold dark matter (ΛCDM) model and a semi-analytic galaxy formation recipe. Knowledge of galaxy–halo memberships in the mock catalogue allows for the quantification of algorithm performance. We detect 305 mock clusters in haloes with mass >1013h−1 M at z≲ 0.6 and determine a spurious detection rate of <1 per cent, consistent with tests on the Stripe 82 catalogue. The detector performs well in the recovery of model ΛCDM clusters. At the median redshift of the catalogue, the algorithm achieves >75 per cent completeness down to halo masses of 1013.4h−1 M and recovers >75 per cent of the total stellar mass of clusters in haloes down to 1013.8h−1 M. A companion paper presents the complete cluster catalogue over the full 270-deg2 Stripe 82 catalogue.

Keywords: catalogues; galaxies: clusters: general; cosmology: observations; large-scale structure of Universe

Journal Article.  14891 words.  Illustrated.

Subjects: Astronomy and Astrophysics

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.