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91探花
Black Hole

Lensing of space time around a black hole. At 91探花 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.

Adrianne Slyz

Professor of Astrophysics

Sub department

  • Astrophysics

Research groups

  • Beecroft Institute for Particle Astrophysics and Cosmology
Adrianne.Slyz@physics.ox.ac.uk
Telephone: 01865 (2)83013
Denys Wilkinson Building, room 555D
  • About
  • Publications

The Horizon-AGN simulation: evolution of galaxy properties over cosmic time

Monthly Notices of the Royal Astronomical Society 91探花 University Press 467:4 (2017) 4739-4752

Authors:

S Kaviraj, C Laigle, T Kimm, Julien Devriendt, Y Dubois, C Pichon, A Slyz, E Chisari, S Peirani

Abstract:

We compare the predictions of Horizon-AGN, a hydrodynamical cosmological simulation that uses an adaptive mesh refinement code, to observational data in the redshift range 0 < z < 6. We study the reproduction, by the simulation, of quantities that trace the aggregate stellar-mass growth of galaxies over cosmic time: luminosity and stellar-mass functions, the star formation main sequence, rest-frame UV鈥搊ptical鈥搉ear-infrared colours and the cosmic star formation history. We show that Horizon-AGN, which is not tuned to reproduce the local Universe, produces good overall agreement with these quantities, from the present day to the epoch when the Universe was 5 per cent of its current age. By comparison to Horizon-noAGN, a twin simulation without active galactic nuclei feedback, we quantify how feedback from black holes is likely to help shape galaxy stellar-mass growth in the redshift range 0 < z < 6, particularly in the most massive galaxies. Our results demonstrate that Horizon-AGN successfully captures the evolutionary trends of observed galaxies over the lifetime of the Universe, making it an excellent tool for studying the processes that drive galaxy evolution and making predictions for the next generation of galaxy surveys.

Cosmic evolution of stellar quenching by AGN feedback: clues from the Horizon-AGN simulation

(2017)

Authors:

RS Beckmann, J Devriendt, A Slyz, S Peirani, MLA Richardson, Y Dubois, C Pichon, NE Chisari, S Kaviraj, C Laigle, M Volonteri

Feedback-regulated star formation and escape of LyC photons from mini-haloes during reionization

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 466:4 (2017) 4826-4846

Authors:

T Kimm, H Katz, M Haehnelt, J Rosdahl, J Devriendt, A Slyz

How the cosmic web induces intrinsic alignments of galaxies

Proceedings of the International Astronomical Union Cambridge University Press 11:S308 (2016) 437-442

Authors:

S Codis, Y Dubois, C Pichon, Julien Devriendt, Adrianne Slyz

Abstract:

Intrinsic alignments are believed to be a major source of systematics for future generation of weak gravitational lensing surveys like Euclid or LSST. Direct measurements of the alignment of the projected light distribution of galaxies in wide field imaging data seem to agree on a contamination at a level of a few per cent of the shear correlation functions, although the amplitude of the effect depends on the population of galaxies considered. Given this dependency, it is difficult to use dark matter-only simulations as the sole resource to predict and control intrinsic alignments. We report here estimates on the level of intrinsic alignment in the cosmological hydrodynamical simulation Horizon-AGN that could be a major source of systematic errors in weak gravitational lensing measurements. In particular, assuming that the spin of galaxies is a good proxy for their ellipticity, we show how those spins are spatially correlated and how they couple to the tidal field in which they are embedded. We also present theoretical calculations that illustrate and qualitatively explain the observed signals.

Feedback-regulated star formation and escape of LyC photons from mini-haloes during reionisation

(2016)

Authors:

Taysun Kimm, Harley Katz, Martin Haehnelt, Joakim Rosdahl, Julien Devriendt, Adrianne Slyz

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