A Fast and Simple Algorithm for Detecting Large Scale Structures
  Aims: we propose a gravitational potential method (GPM) as a supercluster
finder based on the analysis of the local gravitational potential distribution
measured by fast and simple algorithm applied to a spatial distribution of mass
tracers. Methodology: the GPM performs a two-step exploratory data analysis:
first, it measures the comoving local gravitational potential generated by
neighboring mass tracers at the position of a test point-like mass tracer. The
computation extended to all mass tracers of the sample provides a detailed map
of the negative potential fluctuations. The most negative gravitational
potential is provided by the highest mass density or, in other words, the
deeper is a potential fluctuations in a certain region of space and denser are
the mass tracers in that region. Therefore, from a smoothed potential
distribution, the deepest potential well detects unambiguously a high
concentration in the mass tracer distribution. Second, applying a density
contrast criterion to that mass concentration, a central bound core may be
identify and quantify in terms of memberships and total mass. Results: using a
complete volume-limited sample of galaxy clusters, a huge concentration of
galaxy clusters has been detected. In its central region, 35 clusters seem to
form a massive and bound core enclosed in a spherical volume of 51 Mpc radius.
Conclusions: the substantial agreement of our findings compared with those
obtained by different methodologies, confirms the GPM as a straightforward and
powerful as well as fast cluster finder useful for analyzing large datasets.
