scholarly journals Searching for gravitational wave bursts via Bayesian nonparametric data analysis with pulsar timing arrays

2014 ◽  
Vol 90 (2) ◽  
Author(s):  
Xihao Deng
Keyword(s):  
Data Analysis ◽  
Gravitational Wave ◽  
Bayesian Nonparametric ◽  
Pulsar Timing ◽  
Wave Bursts

scholarly journals Coincidence and coherent data analysis methods for gravitational wave bursts in a network of interferometric detectors

2003 ◽  
Vol 68 (10) ◽  
Author(s):  
Nicolas Arnaud ◽  
Matteo Barsuglia ◽  
Marie-Anne Bizouard ◽  
Violette Brisson ◽  
Fabien Cavalier ◽  
...  
Keyword(s):  
Data Analysis ◽  
Gravitational Wave ◽  
Analysis Methods ◽  
Wave Bursts ◽  
Interferometric Detectors ◽  
Data Analysis Methods

scholarly journals Bayesian cross validation for gravitational-wave searches in pulsar-timing array data

2019 ◽  
Vol 487 (3) ◽  
pp. 3644-3649 ◽  
Author(s):  
Haochen Wang ◽  
Stephen R Taylor ◽  
Michele Vallisneri
Keyword(s):  
Data Analysis ◽  
Gravitational Wave ◽  
Bayesian Model ◽  
Model Comparison ◽  
Cross Validation ◽  
Training Data ◽  
Data Set ◽  
Bayesian Model Comparison ◽  
Pulsar Timing ◽  
Pulsar Timing Array

ABSTRACT Gravitational-wave data analysis demands sophisticated statistical noise models in a bid to extract highly obscured signals from data. In Bayesian model comparison, we choose among a landscape of models by comparing their marginal likelihoods. However, this computation is numerically fraught and can be sensitive to arbitrary choices in the specification of parameter priors. In Bayesian cross validation, we characterize the fit and predictive power of a model by computing the Bayesian posterior of its parameters in a training data set, and then use that posterior to compute the averaged likelihood of a different testing data set. The resulting cross-validation scores are straightforward to compute; they are insensitive to prior tuning; and they penalize unnecessarily complex models that overfit the training data at the expense of predictive performance. In this article, we discuss cross validation in the context of pulsar-timing-array data analysis, and we exemplify its application to simulated pulsar data (where it successfully selects the correct spectral index of a stochastic gravitational-wave background), and to a pulsar data set from the NANOGrav 11-yr release (where it convincingly favours a model that represents a transient feature in the interstellar medium). We argue that cross validation offers a promising alternative to Bayesian model comparison, and we discuss its use for gravitational-wave detection, by selecting or refuting models that include a gravitational-wave component.

scholarly journals Pulsar timing perturbations from Galactic gravitational wave bursts with memory

2017 ◽  
Vol 96 (12) ◽  
Author(s):  
Dustin R. Madison ◽  
David F. Chernoff ◽  
James M. Cordes
Keyword(s):  
Gravitational Wave ◽  
Pulsar Timing ◽  
Wave Bursts ◽  
With Memory

scholarly journals Observing gravitational wave bursts in pulsar timing measurements

2009 ◽  
Vol 402 (1) ◽  
pp. 417-423 ◽  
Author(s):  
M. S. Pshirkov ◽  
D. Baskaran ◽  
K. A. Postnov
Keyword(s):  
Gravitational Wave ◽  
Pulsar Timing ◽  
Wave Bursts
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