Weak-lensing detection of intracluster filaments with ground-based data
According to the current standard model of cosmology, matter in the Universe arranges itself along a network of filamentary structure. These filaments connect the main nodes of this so-called “cosmic web”, which are clusters of galaxies. Although its large-scale distribution is clearly characterized...
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
22 November 2013
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| In: |
Astronomy and astrophysics
Year: 2013, Jahrgang: 559, Pages: A112$p1-9 |
| ISSN: | 1432-0746 |
| DOI: | 10.1051/0004-6361/201322007 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1051/0004-6361/201322007 Verlag, lizenzpflichtig, Volltext: https://www.aanda.org/articles/aa/abs/2013/11/aa22007-13/aa22007-13.html 
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| Verfasserangaben: | Matteo Maturi and Julian Merten |
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| 520 | |a According to the current standard model of cosmology, matter in the Universe arranges itself along a network of filamentary structure. These filaments connect the main nodes of this so-called “cosmic web”, which are clusters of galaxies. Although its large-scale distribution is clearly characterized by numerical simulations, constraining the dark-matter content of the cosmic web in reality turns out to be difficult. The natural method of choice is gravitational lensing. However, the direct detection and mapping of the elusive filament signal is challenging and in this work we present two methods that are specifically tailored to achieve this task. A linear matched filter aims at detecting the smooth mass-component of filaments and is optimized to perform a shear decomposition that follows the anisotropic component of the lensing signal. Filaments clearly inherit this property due to their morphology. At the same time, the contamination arising from the central massive cluster is controlled in a natural way. The filament 1<i>σ<i/> detection is of about <i>κ<i/> ~ 0.01 − 0.005 according to the filter’s template width and length, enabling the detection of structures beyond reach with other approaches. The second, complementary method seeks to detect the clumpy component of filaments. The detection is determined by the number density of subclump identifications in an area enclosing the potential filament, as was found within the observed field with the filter approach. We tested both methods against mocked observations based on realistic <i>N<i/>-body simulations of filamentary structure and proved the feasibility of detecting filaments with ground-based data. | ||
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