A Compressed Sensing Framework for Monte Carlo Transport Simulations Using Random Disjoint Tallies

DOI10.1080/23324309.2016.1156550OpenAlexW2465025557MaRDI QIDQ5068017

Pablo A. Vaquer, Ryan G. McClarren, Yuriy J. Ayzman

Publication date: 5 April 2022

Published in: Journal of Computational and Theoretical Transport (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/23324309.2016.1156550

zbMATH Keywords

Monte Carlo methodscompressed sensingneutronics

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Uses Software

• L1-MAGIC

Cites Work

• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Uncertainty principles and ideal atomic decomposition
• Stable signal recovery from incomplete and inaccurate measurements

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