2010
DOI: 10.1051/0004-6361/200913514
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EvoL: the new Padova Tree-SPH parallel code for cosmological simulations

Abstract: Context. We present the new release of the Padova N-body code for cosmological simulations of galaxy formation and evolution, EvoL. The basic Tree + SPH code is presented and analysed, together with an overview of the software architectures. Aims. EvoL is a flexible parallel Fortran95 code, specifically designed for simulations of cosmological structure formations on cluster, galactic and sub-galactic scales. Methods. EvoL is a fully Lagrangian self-adaptive code, based on the classical oct-tree by Barnes & Hu… Show more

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Cited by 37 publications
(67 citation statements)
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“…This time step limiter is important when large differences in temperature occur between the pre-and post-shock media (Saitoh & Makino 2009;Merlin et al 2010). It is not critical in our case, as the net heating of the ISM caused by SNe explosions never exceeds a factor of 20.…”
Section: Feedbackmentioning
confidence: 95%
“…This time step limiter is important when large differences in temperature occur between the pre-and post-shock media (Saitoh & Makino 2009;Merlin et al 2010). It is not critical in our case, as the net heating of the ISM caused by SNe explosions never exceeds a factor of 20.…”
Section: Feedbackmentioning
confidence: 95%
“…The ability of the new AC formulation of SPH to follow the development of KH instabilities using this expression for the signal velocity was verified in a number of tests (Price 2008;Valcke et al 2010;Merlin et al 2010). However, the disadvantage of using the signal speed (24) is that it cannot be applied when self-gravity is considered because in that case a pressure gradient is present at hydrostatic equilibrium.…”
Section: Artificial Conductivitymentioning
confidence: 99%
“…Once the ANNs are instructed to reproduce the (robo) results as a function of the parameters, they should replace robo in the NB-TSPH simulator of galaxies. In our case the NB-TSPH model is EvoL by Merlin & Chiosi (2006 and Merlin et al (2010). The use of ANNs can greatly improve upon this point of difficulty.…”
Section: Introductionmentioning
confidence: 94%