Carving out the low surface brightness universe with NoiseChisel

@article{Akhlaghi2019CarvingOT,
  title={Carving out the low surface brightness universe with NoiseChisel},
  author={M. Akhlaghi},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.11230}
}
  • M. Akhlaghi
  • Published 2019
  • Computer Science, Physics
  • ArXiv
NoiseChisel is a program to detect very low signal-to-noise ratio (S/N) features with minimal assumptions on their morphology. It was introduced in 2015 and released within a collection of data analysis programs and libraries known as GNU Astronomy Utilities (Gnuastro). Over the last ten stable releases of Gnuastro, NoiseChisel has significantly improved: detecting even fainter signal, enabling better user control over its inner workings, and many bug fixes. The most important change may be… Expand
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References

SHOWING 1-5 OF 5 REFERENCES
LSST Cadence Optimization White Paper in Support of Observations of Unresolved Tidal Stellar Streams in Galaxies beyond the Local Group
Deep observations of faint surface brightness stellar tidal streams in external galaxies with LSST are addressed in this White Paper contribution. We propose using the Wide--Fast--Deep survey thatExpand
Maximizing LSST Solar System Science: Approaches, Software Tools, and Infrastructure Needs
TLDR
The aim is for this white paper to encourage further consideration of the software development needs of the LSST solar system science community, and to be a call to action for working to meet those needs in advance of the expected start of the survey in late 2022. Expand
MNRAS , 489, 3294
  • Frigo, M. and S. G. Johnson (2005). IEEE Proc., 93, 216. Hsieh, H. H. et al. (2019). Preprint, arXiv:1906.11346. Illingworth, G. D. et al. (2013). ApJS , 209, 6. Inami, H. et al. (2017). A&A, 608, A2.
  • 2019
ApJS , 182, 543
  • Akhlaghi, M. and T. Ichikawa (2015). ApJS , 220, 1. Bacon, R. et al. (2017). A&A, 608, A1. Bertin, E. and S. Arnouts (1996). A&AS , 117, 393. Borlaff, A. et al. (2019). A&A, 621, A133.
  • 2009
ApJS , 182, 543
  • Akhlaghi, M. and T. Ichikawa (2015). ApJS , 220, 1. Bacon, R. et al. (2017). A&A, 608, A1. Bertin, E. and S. Arnouts (1996). A&AS , 117, 393. Borlaff, A. et al. (2019). A&A, 621, A133.
  • 2009