H
Hendrik Hildebrandt
Researcher at University of Bonn
Publications - 216
Citations - 17738
Hendrik Hildebrandt is an academic researcher from University of Bonn. The author has contributed to research in topics: Galaxy & Weak gravitational lensing. The author has an hindex of 66, co-authored 178 publications receiving 15431 citations. Previous affiliations of Hendrik Hildebrandt include Leiden University & University of British Columbia.
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A blind test of photometric redshifts on ground-based data
TL;DR: In this paper, the German Ministry for Education and Science (BMBF) through the DLR under the 50 OR 0106, by the BMBF through DESY under the project 05 AV5PDA/3, and by the Deutsche Forschungsgemeinschaft (DFG) under the projects SCHN342/3-1 and ER327/2-1.
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The 2-degree Field Lensing Survey: design and clustering measurements
Chris Blake,Alexandra Amon,M. J. Childress,M. J. Childress,Thomas Erben,Karl Glazebrook,Joachim Harnois-Déraps,Joachim Harnois-Déraps,Catherine Heymans,Hendrik Hildebrandt,Samuel Hinton,Steven Janssens,Andrew Johnson,Shahab Joudaki,Dominik Klaes,Konrad Kuijken,Chris Lidman,Felipe A. Marín,David Parkinson,Gregory B. Poole,Christian Wolf +20 more
TL;DR: The 2dFLenS survey as mentioned in this paper is the first wide-area spectroscopic survey specifically targeting the area mapped by deep-imaging gravitational lensing fields, in this case the Kilo-Degree Survey.
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Strong and weak lensing united: II. The cluster mass distribution of the most X-ray luminous cluster RX J1347.5-1145
Marusa Bradac,Marusa Bradac,Marusa Bradac,Thomas Erben,Peter Schneider,Hendrik Hildebrandt,Marco Lombardi,Marco Lombardi,Marco Lombardi,Mischa Schirmer,J. M. Miralles,J. M. Miralles,Douglas Clowe,Sabine Schindler +13 more
TL;DR: In this paper, the authors applied the cluster-mass reconstruction method which combines strong and weak gravitational lensing data, developed in the first paper in the series, successfully reconstructs the mass distribution of a simulated cluster.
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3D-Matched-Filter Galaxy Cluster Finder I: Selection Functions and CFHTLS Deep Clusters
Martha Milkeraitis,L. van Waerbeke,Catherine Heymans,Hendrik Hildebrandt,J. P. Dietrich,T. Erben +5 more
TL;DR: The 3D-Matched-Filter (3D-MF) as mentioned in this paper is an optimized galaxy cluster finder, which utilizes galaxy cluster radial profiles, luminosity functions and redshift information to detect galaxy clusters in optical surveys.
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Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks
Maciej Bilicki,Henk Hoekstra,V. Amaro,C. Blake,Michael J. I. Brown,Stefano Cavuoti,J. T. A. de Jong,Hendrik Hildebrandt,Christian Wolf,Alexandra Amon,Massimo Brescia,Sarah Brough,M. V. Costa-Duarte,Thomas Erben,Karl Glazebrook,A. Grado,Catherine Heymans,Thomas H. Jarrett,Shahab Joudaki,Konrad Kuijken,Giuseppe Longo,Nicola R. Napolitano,David Parkinson,Civita Vellucci,G. A. Verdoes Kleijn,Lingyu Wang +25 more
TL;DR: In this paper, a machine-learning approach was proposed for image-z analysis of the Kilo-Degree Survey Data Release 3, using two neural-network based techniques: ANNz2 and MLPQNA.