Galaxy Kinematics with VIRUS-P: The Dark Matter Halo of M87

Astronomy and Astrophysics – Astrophysics – Cosmology and Extragalactic Astrophysics

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15 figures, 29 pages, Accepted for publication in ApJ

Scientific paper

We present 2-D stellar kinematics of M87 out to R = 238" taken with the integral field spectrograph VIRUS-P. We run a large set of axisymmetric, orbit-based dynamical models and find clear evidence for a massive dark matter halo. While a logarithmic parameterization for the dark matter halo is preferred, we do not constrain the dark matter scale radius for an NFW profile and therefore cannot rule it out. Our best-fit logarithmic models return an enclosed dark matter fraction of 17.2 +/- 5.0 % within one effective radius (R_e ~ 100"), rising to 49.4 (+7.2,-8.8) % within 2 R_e. Existing SAURON data (R < 13"), and globular cluster kinematic data covering 145" < R < 540" complete the kinematic coverage to R = 47 kpc. At this radial distance the logarithmic dark halo comprises 85.3 (+2.5,-2.4) % of the total enclosed mass of 5.7^(+1.3)_(-0.9) X 10^(12) M_sun making M87 one of the most massive galaxies in the local universe. Our best-fit logarithmic dynamical models return a stellar mass-to-light ratio of 9.1^(+0.2)_(-0.2) (V-band), a dark halo circular velocity of 800^(+75)_(-25) kms, and a dark halo scale radius of 36^(+7)_(-3) kpc. The stellar M/L, assuming an NFW dark halo, is well constrained to 8.20^(+0.05)_(-0.10) (V-band). The stars in M87 are found to be radially anisotropic out to R ~ 0.5 R_e then isotropic or slightly tangentially anisotropic to our last stellar data point at R = 2.4 R_e where the anisotropy of the stars and globular clusters are in excellent agreement. The globular clusters then become radially anisotropic in the last two modeling bins at R = 3.4 R_e and R = 4.8 R_e. As one of the most massive galaxies in the local universe, constraints on both the mass distribution of M87 and anisotropy of its kinematic components strongly informs our theories of early-type galaxy formation and evolution in dense environments.

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