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Polynomial data compression for large-scale physics experiments

Numerical Analysis 2018-05-07 v1 Instrumentation and Methods for Astrophysics Computational Physics

Abstract

The new generation research experiments will introduce huge data surge to a continuously increasing data production by current experiments. This data surge necessitates efficient compression techniques. These compression techniques must guarantee an optimum tradeoff between compression rate and the corresponding compression /decompression speed ratio without affecting the data integrity. This work presents a lossless compression algorithm to compress physics data generated by Astronomy, Astrophysics and Particle Physics experiments. The developed algorithms have been tuned and tested on a real use case~: the next generation ground-based high-energy gamma ray observatory, Cherenkov Telescope Array (CTA), requiring important compression performance. Stand-alone, the proposed compression method is very fast and reasonably efficient. Alternatively, applied as pre-compression algorithm, it can accelerate common methods like LZMA, keeping close performance.

Keywords

Cite

@article{arxiv.1805.01844,
  title  = {Polynomial data compression for large-scale physics experiments},
  author = {Pierre Aubert and Thomas Vuillaume and Gilles Maurin and Jean Jacquemier and Giovanni Lamanna and Nahid Emad},
  journal= {arXiv preprint arXiv:1805.01844},
  year   = {2018}
}

Comments

12 pages

R2 v1 2026-06-23T01:45:26.463Z