2009
DOI: 10.1111/j.1365-2966.2009.14590.x
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On measuring the gravitational-wave background using Pulsar Timing Arrays

Abstract: The long-term precise timing of Galactic millisecond pulsars holds great promise for measuring the long-period (months to years) astrophysical gravitational waves. Several gravitationalwave observational programs, called Pulsar Timing Arrays (PTA), are being pursued around the world.Here, we develop a Bayesian algorithm for measuring the stochastic gravitational-wave background (GWB) from the PTA data. Our algorithm has several strengths: (i) it analyses the data without any loss of information; (ii) it trivia… Show more

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Cited by 161 publications
(193 citation statements)
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“…The most common method is to adjust the values until the reduced-χ 2 of the fitted model reaches unity. Bayesian and other maximum likelihood methods have also recently been developed and applied to precision pulsar timing datasets (van Haasteren et al 2009;Lentati et al 2014). In these methods, EFAC and EQUAD are included as nuisance parameters and marginalised when calculating the posterior distributions of parameters of interest or comparing models.…”
Section: Including Jitter Noise In Timing Modelsmentioning
confidence: 99%
See 1 more Smart Citation
“…The most common method is to adjust the values until the reduced-χ 2 of the fitted model reaches unity. Bayesian and other maximum likelihood methods have also recently been developed and applied to precision pulsar timing datasets (van Haasteren et al 2009;Lentati et al 2014). In these methods, EFAC and EQUAD are included as nuisance parameters and marginalised when calculating the posterior distributions of parameters of interest or comparing models.…”
Section: Including Jitter Noise In Timing Modelsmentioning
confidence: 99%
“…In addition to providing a better model of the true TOA uncertainties, EQUAD and EFAC parameters may not need need to be modelled in timing datasets. This reduces by two the dimensionality to TOA modelling, which streamline computationally intensive Bayesian GW-search algorithms (van Haasteren et al 2009). In archival data, it may be necessary to include EFAC or EQUAD parameters to account for pulse shape distortions induced by non-linearities in instrumentation associated with low-bit digitisation.…”
Section: Including Jitter Noise In Timing Modelsmentioning
confidence: 99%
“…During his Ph.D. work at Leiden Observatory, Rutger van Haasteren developed from scratch a sophisticated mathematical algorithm that deals with this issue, and that is currently in active use within the PTA community (van Haasteren et al 2009, Chapter 2). Moving beyond purely theoretical work, van Haasteren studied the observational procedure in depth (which he learned partly during his first 2-month stay in Australia), and, together with Gemma Jansen (then a postdoctoral fellow at Jodrell Bank), led the joint effort of five teams of pulsar observers on the European continent, to combine their Europan Pulsar Timing Array (EPTA) datasets in order to search for gravitational waves.…”
Section: Supervisor's Forewordmentioning
confidence: 99%
“…van Kerkwijk & Kulkarni 1995). So far, for all three binary pulsars described in this paper, the most recently published limit on optical magnitude of the companion is R > 24 (van Kerkwijk et al 2005). …”
Section: Introductionmentioning
confidence: 99%
“…An instrument like this will use an array of MSPs as the endpoints of a Galaxy-scale gravitational wave (GW) detector. Current estimates predict that to detect a GW background, long-term high precision timing of about 20 MSPs is required (Jenet et al 2005;Van Haasteren et al 2009). Increasing the number of stable MSPs in the array will improve the detection significance.…”
Section: Introductionmentioning
confidence: 99%