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Mapping with Probability – The Fortunate Isles Anthony Smith, Andrew Hopkins, Dick Hunstead
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Galaxy Clusters Morphology-Density SFR-Density Mass Tracers Galaxy Cluster Abell 1689 (Hubble)
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Detecting Clusters - Tricks Colour Clustering, Miller et al. 2005 BCG Colour-Redshift, Koester et al. 2007... not so good for finding things you don’t expect
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Detecting Clusters – Geometry (1) Smoothing Different scales, and filters, give different answers
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Detecting Clusters - Geometry (2) Minimal Spanning Tree (Barrow, Bhavsar & Sonoda 1985) Delaunay Tessellation Field Estimator (van de Weygaert & Schaap 2007)
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Probability Smoothing Smoothing on many scales (no filter) Take Maximum Values
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Scale Selection Smoothing on many scales Remember Scales that admit Maximum Probabilities
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Probability and Scale Maps Probability Map (P) Comparison with Average Scale Map (S) Comparison with Surrounding Locations P – S Equal weighting of both Probability map for density threshold, scale map for substructure
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Structure Identification Probability Map finds Islands Scale Map finds Banks Set threshold in P - S Bank Island
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Adaptive Contouring
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Application to Sloan DR7 Spectroscopic Survey, all galaxies with r < 17.77 (~ 620 000), median redshift ~ 0.1 Use galaxies as an adaptive grid Sample scales 0.25 – 1 h -1 Mpc in steps of 0.05 Line-of-sight Redshift radius 50 h -1 Mpc Threshold in Probability minus Scale of 0.5 Minimum Membership of 4
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Scaling Redshift Radii 100 h -1 Mpc Relative Galaxy Density z < 0.1 z > 0.1 -50 h -1 Mpc50 h -1 Mpc Line-of-Sight
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Running it for Real Catalogue contains 3475 clusters 0.025 < z < 0.22 Mean cluster radius 0.65 h -1 Mpc Raising the P – S threshold in the 0.025 < z < 0.05 redshift slice
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Sky Positions (0.05 < z < 0.075)
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Occupation Values Low Occupation Value; Filamentary High Occupation Value; Clustery Occupation Value01 Number
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Scale Distribution Berlind et al. 2006 Yoon et al. 2008 Radius (h -1 Mpc)01.50 0 Us Radius (h -1 Mpc) r
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3D Visualisation Clusters from 0.025 < z < 0.05 70 h -1 Mpc
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Summary Have designed and implemented a multi- scale structure identification algorithm Minimal assumptions made about cluster properties Identified ~3500 clusters in the Sloan Digital Sky Survey to z = 0.22 Positions and Scale distribution are consistent with previous studies
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Further Work Comparisons with other catalogues Quantify cluster properties; refine occupation statistic Examine intracluster galaxy populations Use photometric data Extend to larger scales
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