hide
Free keywords:
General Relativity and Quantum Cosmology, gr-qc,Astrophysics, Cosmology and Extragalactic Astrophysics, astro-ph.CO,High Energy Physics - Theory, hep-th
Abstract:
We present a statistic for the detection of stochastic gravitational-wave
backgrounds (SGWBs) using radiometry with a network of multiple baselines. We
also quantitatively compare the sensitivities of existing baselines, and their
network, to SGWBs. We assess how the measurement accuracy of signal parameters,
e.g., the sky position of a localized source, can improve when using a network
of baselines as compared to any of the single participating baselines. The
search statistic itself is derived from the likelihood ratio of the
cross-correlation of the data across all possible baselines in a detector
network, and is optimal in Gaussian noise. Specifically, it is the
likelihood-ratio maximized over the strength of the SGWB, and is called the
maximized likelihood ratio (MLR). One of the main advantages of using the MLR
over past search strategies for inferring the presence or absence of a signal
is that the former does not require the deconvolution of the cross-correlation
statistic. Therefore, it does not suffer from errors inherent to the
deconvolution procedure and is, especially, useful for detecting weak sources.
In the limit of a single baseline, it reduces to the detection statistic
studied by Ballmer [Class. Quant. Grav. 23, S179 (2006)] and Mitra et al.
[Phys. Rev. D 77, 042002 (2008)]. Unlike past studies, here the MLR statistic
enables us to compare quantitatively the performances of a variety of baselines
searching for a SGWB signal in (simulated) data. Although we use simulated
noise and SGWB signals for making these comparisons, our method can be
straightforwardly applied on real data.
