Multibaseline gravitational wave radiometry

Journal Article · Tue Mar 15 04:00:00 EDT 2011 · Physical Review. D, Particles Fields

DOI:https://doi.org/10.1103/PHYSREVD.83.063002· OSTI ID:21537489

Talukder, Dipongkar; Bose, Sukanta ^[1]; Mitra, Sanjit ^[2]

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1. Department of Physics and Astronomy, Washington State University, Pullman, Washington 99164-2814 (United States)
2. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, California 91109 (United States)

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 [Classical Quantum Gravity 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.

• OSTI ID: 21537489
• Journal Information: Physical Review. D, Particles Fields, Journal Name: Physical Review. D, Particles Fields Journal Issue: 6 Vol. 83; ISSN PRVDAQ; ISSN 0556-2821
• Country of Publication: United States
• Language: English

Related Subjects

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
ACCURACY
BACKGROUND RADIATION
COMPARATIVE EVALUATIONS
CORRELATIONS
DETECTION
ERRORS
EVALUATION
FIELD THEORIES
GRAVITATIONAL WAVE DETECTORS
GRAVITATIONAL WAVES
MEASURING INSTRUMENTS
NOISE
QUANTUM FIELD THEORY
QUANTUM GRAVITY
RADIATION DETECTORS
RADIATIONS
SENSITIVITY
SIMULATION
STOCHASTIC PROCESSES