Simulations of binary galaxy mergers and the link with Fast Rotators, Slow Rotators, and Kinematically Distinct Cores
Maxime Bois, Eric Emsellem, Fr\'ed\'eric Bournaud, Katherine Alatalo,, Leo Blitz, Martin Bureau, Michele Cappellari, Roger L. Davies, Timothy A., Davis, P. T. de Zeeuw, Pierre-Alain Duc, Sadegh Khochfar, Davor Krajnovi\'c,, Harald Kuntschner, Pierre-Yves Lablanche

TL;DR
This study uses high-resolution simulations to explore how binary galaxy mergers produce different types of early-type galaxies, revealing the roles of mass ratios and initial spins in forming Fast and Slow Rotators with or without Kinematically Distinct Cores.
Contribution
It provides detailed insights into how specific merger parameters influence the kinematic classification and internal structures of resulting early-type galaxies.
Findings
Mass ratios of 3:1 and 6:1 typically produce Fast Rotators.
Major mergers (2:1 and 1:1) can produce both Fast and Slow Rotators.
Most Slow Rotators contain Kinematically Distinct Cores formed from progenitor stars.
Abstract
We study the formation of early-type galaxies (ETGs) through mergers with a sample of 70 high-resolution numerical simulations of binary mergers of disc galaxies. These simulations encompass various mass ratios, initial conditions and orbital parameters. We find that binary mergers of disc galaxies with mass ratios of 3:1 and 6:1 are nearly always classified as Fast Rotators according to the Atlas3D criterion: they preserve the structure of the input fast rotating spiral progenitors. Major disc mergers (mass ratios of 2:1 and 1:1) lead to both Fast and Slow Rotators. Most of the Slow Rotators hold a stellar Kinematically Distinct Core (KDC) in their 1-3 central kilo-parsec: these KDCs are built from the stellar components of the progenitors. The mass ratio of the progenitors is a fundamental parameter for the formation of Slow Rotators in binary mergers, but it also requires a…
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Taxonomy
TopicsAstronomical Observations and Instrumentation · Pulsars and Gravitational Waves Research · Modeling, Simulation, and Optimization
