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Application of Compressive Sensing to Gravitational Microlensing Experiments

Published online by Cambridge University Press:  30 May 2017

Asmita Korde-Patel ,
Richard K. Barry  and
Tinoosh Mohsenin
Asmita Korde-Patel
Affiliation:
NASA Goddard Space Flight Center, Greenbelt, MD, USA University of Maryland, Baltimore County, Baltimore, MD, USA email: asmita.a.korde@nasa.gov
Richard K. Barry
Affiliation:
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Tinoosh Mohsenin
Affiliation:
University of Maryland, Baltimore County, Baltimore, MD, USA email: asmita.a.korde@nasa.gov
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Abstract

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Compressive Sensing is an emerging technology for data compression and simultaneous data acquisition. This is an enabling technique for significant reduction in data bandwidth, and transmission power and hence, can greatly benefit space-flight instruments. We apply this process to detect exoplanets via gravitational microlensing. We experiment with various impact parameters that describe microlensing curves to determine the effectiveness and uncertainty caused by Compressive Sensing. Finally, we describe implications for space-flight missions.

Keywords

Compressive SensingGravitational Microlensing
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 12 , Symposium S325: Astroinformatics , October 2016 , pp. 67 - 70
Copyright
Copyright © International Astronomical Union 2017 

References

Eldar, Y. & Kutynoik, G. 2012, Compressed Sensing, Cambridge University Press Google Scholar
O’Donoghue, B., Chu, E., Parikh, N., & Boyd, S. 2016, Conic Optimization via Operator Splitting and Homogenous Self-Dual Embedding, J. Optim Theory Appl, 169: 1042–1068 Google Scholar
Seager, S. 2010, Exoplanets, The University of Arizona Press Google Scholar
Bramich, D. 2008, A new algorithm for difference image analysis, Monthly Notices of the Royal Astronomical Society: Letters 386.1: L77–L81Google Scholar