Mapa do Site
Contactos
Siga-nos no Facebook Siga-nos no Twitter Canal YouTube
Centro de Astrofísica da Universidade do Porto

MAMPOSSt: Modelling Anisotropy and Mass Profiles of Observed Spherical Systems - I. Gaussian 3D velocities

G. A. Mamon, A. Biviano, G. Boué

Resumo
Mass modelling of spherical systems through internal kinematics is hampered by the mass–velocity anisotropy degeneracy inherent in the Jeans equation, as well as the lack of techniques that are both fast and adaptable to realistic systems. A new fast method, called Modelling Anisotropy and Mass Profiles of Observed Spherical Systems (MAMPOSSt), is developed and thoroughly tested. MAMPOSSt performs a maximum-likelihood fit of the distribution of observed tracers in projected phase space (projected radius and line-of-sight velocity). As in other methods, MAMPOSSt assumes a shape for the gravitational potential (or equivalently the total mass profile). However, instead of postulating a shape for the distribution function in terms of energy and angular momentum, or supposing Gaussian line-of-sight velocity distributions, MAMPOSSt assumes a velocity anisotropy profile and a shape for the 3D velocity distribution. The formalism is presented for the case of a Gaussian 3D velocity distribution. In contrast to most methods based on moments, MAMPOSSt requires no binning, differentiation, nor extrapolation of the observables. Tests on cluster-mass haloes from ?CDM dissipationless cosmological simulations indicate that, with 500 tracers, MAMPOSSt is able to jointly recover the virial radius, tracer scale radius, dark matter scale radius and outer or constant velocity anisotropy with small bias (<10% on scale radii and <2% on the two other quantities) and inefficiencies of 10%, 27%, 48% and 20%, respectively. MAMPOSSt does not perform better when some parameters are frozen, and even particularly worse when the virial radius is set to its true value, which appears to be the consequence of halo triaxiality. The accuracy of MAMPOSSt depends weakly on the adopted interloper removal scheme, including an efficient iterative Bayesian scheme that we introduce here, which can directly obtain the virial radius with as good precision as MAMPOSSt. Additional tests are made on the number of tracers, the stacking of haloes, the chosen aperture, and the density and velocity anisotropy models. Our tests show that MAMPOSSt with Gaussian 3D velocities is very competitive with other methods that are either currently restricted to constant velocity anisotropy or 3 orders of magnitude slower. These tests suggest that MAMPOSSt can be a very powerful and rapid method for the mass and anisotropy modelling of systems such as clusters and groups of galaxies, elliptical and dwarf spheroidal galaxies.

Palavras chave
methods: analytical - galaxies: clusters: general - galaxies: haloes - galaxies: kinematics and dynamics - dark matter

Monthly Notices of the Royal Astronomical Society
Volume 429, Página 3079
março 2013

>> ADS>> DOI

Instituto de Astrofísica e Ciências do Espaço

O Instituto de Astrofísica e Ciências do Espaço (IA) é uma nova, mas muito aguardada, estrutura de investigação com uma dimensão nacional. Ele concretiza uma visão ousada, mas realizável para o desenvolvimento da Astronomia, Astrofísica e Ciências Espaciais em Portugal, aproveitando ao máximo e realizando plenamente o potencial criado pela participação nacional na Agência Espacial Europeia (ESA) e no Observatório Europeu do Sul (ESO). O IA é o resultado da fusão entre as duas unidades de investigação mais proeminentes no campo em Portugal: o Centro de Astrofísica da Universidade do Porto (CAUP) e o Centro de Astronomia e Astrofísica da Universidade de Lisboa (CAAUL). Atualmente, engloba mais de dois terços de todos os investigadores ativos em Ciências Espaciais em Portugal, e é responsável por uma fração ainda maior da produtividade nacional em revistas internacionais ISI na área de Ciências Espaciais. Esta é a área científica com maior fator de impacto relativo (1,65 vezes acima da média internacional) e o campo com o maior número médio de citações por artigo para Portugal.

Continuar no sítio do CAUP|Seguir para o sítio do IA