Probing the cosmic web: inter-cluster filament detection using
  gravitational lensing
  The problem of detecting dark matter filaments in the cosmic web is
considered. Weak lensing is an ideal probe of dark matter, and therefore forms
the basis of particularly promising detection methods. We consider and develop
a number of weak lensing techniques that could be used to detect filaments in
individual or stacked cluster fields, and apply them to synthetic lensing data
sets in the fields of clusters from the Millennium Simulation. These techniques
are multipole moments of the shear and convergence, mass reconstruction, and
parameterized fits to filament mass profiles using a Markov Chain Monte Carlo
approach. In particular, two new filament detection techniques are explored
(multipole shear filters and Markov Chain Monte Carlo mass profile fits), and
we outline the quality of data required to be able to identify and quantify
filament profiles. We also consider the effects of large scale structure on
filament detection. We conclude that using these techniques, there will be
realistic prospects of detecting filaments in data from future space-based
missions. The methods presented in this paper will be of great use in the
identification of dark matter filaments in future surveys.
