Improved reconstruction of a stochastic gravitational wave background with LISA. (arXiv:2009.11845v2 [astro-ph.CO] UPDATED)
<a href="http://arxiv.org/find/astro-ph/1/au:+Flauger_R/0/1/0/all/0/1">Raphael Flauger</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Karnesis_N/0/1/0/all/0/1">Nikolaos Karnesis</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Nardini_G/0/1/0/all/0/1">Germano Nardini</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Pieroni_M/0/1/0/all/0/1">Mauro Pieroni</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Ricciardone_A/0/1/0/all/0/1">Angelo Ricciardone</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Torrado_J/0/1/0/all/0/1">Jesús Torrado</a>
We present a data analysis methodology for a model-independent reconstruction
of the spectral shape of a stochastic gravitational wave background with LISA.
We improve a previously proposed reconstruction algorithm that relied on a
single Time-Delay-Interferometry (TDI) channel by including a complete set of
TDI channels. As in the earlier work, we assume an idealized equilateral
configuration. We test the improved algorithm with a number of case studies,
including reconstruction in the presence of two different astrophysical
foreground signals. We find that including additional channels helps in
different ways: it reduces the uncertainties on the reconstruction; it makes
the global likelihood maximization less prone to falling into local extrema;
and it efficiently breaks degeneracies between the signal and the instrumental
noise.
We present a data analysis methodology for a model-independent reconstruction
of the spectral shape of a stochastic gravitational wave background with LISA.
We improve a previously proposed reconstruction algorithm that relied on a
single Time-Delay-Interferometry (TDI) channel by including a complete set of
TDI channels. As in the earlier work, we assume an idealized equilateral
configuration. We test the improved algorithm with a number of case studies,
including reconstruction in the presence of two different astrophysical
foreground signals. We find that including additional channels helps in
different ways: it reduces the uncertainties on the reconstruction; it makes
the global likelihood maximization less prone to falling into local extrema;
and it efficiently breaks degeneracies between the signal and the instrumental
noise.
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