Speaker
Fabio Del Sordo
(NoRDITA/Yale University)
Description
The radial velocity method is a powerful way to search for
exoplanetary systems and it led to many discoveries of
exoplanets in the last 20 years. Nowadays, understanding
stellar activity and noise is a key factor for achieving a
substantial improvement in such technique. Radial-velocity
data are time-series containing the effect of both planets
and stellar disturbances: the detection of Earth-like
planets requires to improve the signal-to-noise ratio, i.e.
it is central to understand the noise present in the data.
Noise is caused by physical processes which operate on
different time-scales, oftentimes acting in a non-periodic
fashion. We present here an approach to such problem: to
look for multifractal structures in the time-series coming
from radial velocity measurements, identifying the
underlying long-range correlations and fractal scaling
properties, connecting them to the underlying physical
processes (stellar oscillations, stellar wind, granulation,
rotation, magnetic activity). This method has been
previously applied to satellite data related to Arctic sea
albedo, relevant for identify trends and noise in the Arctic
sea ice (Agarwal, Moon, Wettlaufer, 2012). Here we suggest
to use such analysis for exoplanetary data related to
possible Earth-like planets.
