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Black Hole

Lensing of space time around a black hole. At Oxford we study black holes observationally and theoretically on all size and time scales - it is some of our core work.

Credit: ALAIN RIAZUELO, IAP/UPMC/CNRS. CLICK HERE TO VIEW MORE IMAGES.

Michele Cappellari

Professor of Astrophysics

Research theme

  • Astronomy and astrophysics

Sub department

  • Astrophysics

Research groups

  • Galaxy formation and evolution
  • Extremely Large Telescope
michele.cappellari@physics.ox.ac.uk
Telephone: 01865 (2)73647
Denys Wilkinson Building, room 755
  • About
  • Publications

UV Central Spikes in Early Type Galaxies

Chapter in Stellar Populations, Springer Nature (1995) 445-445

Authors:

F Bertola, M Cappellari, D Burstein, L Greggio, A Renzini, S Di Serego Alighieri
More details from the publisher

Dynamical modeling of SAURON galaxies

Proceedings of IUTAM Symposia and Summer Schools IUTAM 3

Authors:

Michele Cappellari, RCEVD Bosch, EK Verolme, R Bacon, Martin Bureau, Y Copin, RL Davies, E Emsellem, D Krajnovic, H Kuntschner, R McDermid, BW Miller, RF Peletier, PTD Zeeuw

Abstract:

We describe our program for the dynamical modeling of early-type galaxies observed with the panoramic integral-field spectrograph SAURON. We are using Schwarzschild's numerical orbit superposition method to reproduce in detail all kinematical and photometric observables, and recover the intrinsic orbital structure of the galaxies. Since catastrophes are the most prominent features in the orbital observables, two-dimensional kinematical coverage is essential to constrain the dynamical models.

Details from ORA
More details
Details from ArXiV

Voronoi binning: Optimal adaptive tessellations of multi-dimensional data

Abstract:

We review the concepts of the Voronoi binning technique (Cappellari & Copin 2003), which optimally solves the problem of preserving the maximum spatial resolution of general two-dimensional data, given a constraint on the minimum signal-to-noise ratio (S/N). This is achieved by partitioning the data in an adaptive fashion using a Voronoi tessellation with nearly hexagonal lattice. We review astrophysical applications of the method to X-ray data, integral-field spectroscopy, Fabry-Perot interferometry, N-body simulations, standard images and other regularly or irregularly sampled data. Voronoi binning, unlike adaptive smoothing, produces maps where the noise in the data can be visually assessed and spurious artifacts can be recognized. The method can be used to bin data according to any general criterion and not just S/N. It can be applied to higher dimensions and it can be used to generate optimal adaptive meshes for numerical simulations.
Details from ArXiV

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