• Corpus ID: 119411494

Distributed and parallel sparse convex optimization for radio interferometry with PURIFY

@article{Pratley2019DistributedAP,
  title={Distributed and parallel sparse convex optimization for radio interferometry with PURIFY},
  author={Luke Pratley and Jason D. McEwen and Mayeul d'Avezac and Xiaohao Cai and David P{\'e}rez-Su{\'a}rez and Ilektra A. Christidi and Roland Guichard},
  journal={arXiv: Instrumentation and Methods for Astrophysics},
  year={2019}
}
Next generation radio interferometric telescopes are entering an era of big data with extremely large data sets. While these telescopes can observe the sky in higher sensitivity and resolution than before, computational challenges in image reconstruction need to be overcome to realize the potential of forthcoming telescopes. New methods in sparse image reconstruction and convex optimisation techniques (cf. compressive sensing) have shown to produce higher fidelity reconstructions of simulations… 

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