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A Review of Exoplanet Detection Processes using Artificial Intelligence and Neural Networks

by Saima Khan, Md. Abidur Rahman Khan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 36
Year of Publication: 2024
Authors: Saima Khan, Md. Abidur Rahman Khan
10.5120/ijca2024923940

Saima Khan, Md. Abidur Rahman Khan . A Review of Exoplanet Detection Processes using Artificial Intelligence and Neural Networks. International Journal of Computer Applications. 186, 36 ( Aug 2024), 1-8. DOI=10.5120/ijca2024923940

@article{ 10.5120/ijca2024923940,
author = { Saima Khan, Md. Abidur Rahman Khan },
title = { A Review of Exoplanet Detection Processes using Artificial Intelligence and Neural Networks },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2024 },
volume = { 186 },
number = { 36 },
month = { Aug },
year = { 2024 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number36/a-review-of-exoplanet-detection-processes-using-artificial-intelligence-and-neural-networks/ },
doi = { 10.5120/ijca2024923940 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-08-26T20:51:51.837287+05:30
%A Saima Khan
%A Md. Abidur Rahman Khan
%T A Review of Exoplanet Detection Processes using Artificial Intelligence and Neural Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 36
%P 1-8
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Detecting exoplanets is a crucial research area because understanding exoplanets can help researchers discover new aspects of space and potentially lead to the development of new technologies that benefit humanity. There are several methods for detecting exoplanets, but achieving higher accuracy remains a significant challenge. The field of artificial intelligence (AI), particularly neural networks and convolutional neural networks (CNNs), plays a vital role in enhancing the accuracy of exoplanet detection. Various researchers have proposed and utilized numerous techniques employing artificial intelligence and neural network methods to detect exoplanets with improved precision. This paper presents a review of various exoplanet detection techniques using AI and neural networks, highlighting the approaches proposed and examined by different researchers (inclusion of the required tables and figures, accompanied by appropriate citations and references). By leveraging these advanced computational techniques, researchers can analyze vast astronomical datasets more efficiently and identify exoplanets with greater reliability. This integration of artificial intelligence and neural networks in exoplanet detection not only accelerates discoveries but also broadens our understanding of planetary systems beyond our solar system.

References
  1. Ansdell, M., Ioannou, Y., Osborn, H. P., Sasdelli, M., Smith, J. C., Caldwell, D., ... Angerhausen, D. (2018). Scientific domain knowledge improves exoplanet transit classification with deep learning. The Astrophysical journal letters, 869(1), L7.
  2. Shallue, C. J., Vanderburg, A. (2018). Identifying exoplanets with deep learning: A five-planet resonant chain around kepler- 80 and an eighth planet around kepler-90. The Astronomical Journal, 155(2), 94.
  3. Osborn, H. P., Ansdell, M., Ioannou, Y., Sasdelli, M., Angerhausen, D., Caldwell, D., ... Smith, J. C. (2020). Rapid classification of TESS planet candidates with convolutional neural networks. Astronomy Astrophysics, 633, A53.
  4. Schanche, N., Cameron, A. C., H´ebrard, G., Nielsen, L., Triaud, A. H. M. J., Almenara, J. M., ... Wheatley, P. J. (2019). Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys. Monthly Notices of the Royal Astronomical Society, 483(4), 5534-5547.
  5. Yu, L., Vanderburg, A., Huang, C., Shallue, C. J., Crossfield, I. J., Gaudi, B. S., ... Quinn, S. N. (2019). Identifying exoplanets with deep learning. III. Automated triage and vetting of TESS candidates. The Astronomical Journal, 158(1), 25.
  6. Koning, S., Greeven, C., Postma, E. (2019). Reducing artificial neural network complexity: A case study on exoplanet detection. arXiv preprint arXiv:1902.10385.
  7. Dattilo, A., Vanderburg, A., Shallue, C. J., Mayo, A. W., Berlind, P., Bieryla, A., ... Yu, L. (2019). Identifying exoplanets with deep learning. ii. two new super-earths uncovered by a neural network in k2 data. The Astronomical Journal, 157(5), 169.
  8. Malik, A., Moster, B. P., Obermeier, C. (2022). Exoplanet detection using machine learning. Monthly Notices of the Royal Astronomical Society, 513(4), 5505-5516.
  9. Pearson, K. A., Palafox, L., Griffith, C. A. (2018). Searching for exoplanets using artificial intelligence. Monthly Notices of the Royal Astronomical Society, 474(1), 478-491.
  10. Chaushev, A., Raynard, L., Goad, M. R., Eigm¨uller, P., Armstrong, D. J., Briegal, J. T., ... Vines, J. I. (2019). Classifying exoplanet candidates with convolutional neural networks: application to the Next Generation Transit Survey. Monthly Notices of the Royal Astronomical Society, 488(4), 5232-5250.
  11. Petigura, E. A., Marcy, G. W., Howard, A. W. (2013). A plateau in the planet population below twice the size of Earth. The Astrophysical Journal, 770(1), 69.
  12. Kov´acs, G., Zucker, S., Mazeh, T. (2002). A box-fitting algorithm in the search for periodic transits. Astronomy Astrophysics, 391(1), 369-377.
  13. Wolszczan, A., Frail, D. A. (1992). A planetary system around the millisecond pulsar PSR1257+ 12. Nature, 355(6356), 145-147.
  14. Mayor, M., Queloz, D. (1995). A Jupiter-mass companion to a solar-type star. nature, 378(6555), 355-359.
  15. Campbell, B., Walker, G. A., Yang, S. (1988). A search for substellar companions to solar-type stars. Astrophysical Journal, Part 1 (ISSN 0004-637X), vol. 331, Aug. 15, 1988, p. 902- 921. Research supported by the National Research Council of Canada, Canada Employment and Immigration Commission, and NSERC., 331, 902-921.
  16. Latham, D. W., Mazeh, T., Stefanik, R. P., Mayor, M., Burki, G. (1989). The unseen companion of HD114762: a probable brown dwarf. Nature, 339(6219), 38-40.
  17. Benedict, G. F., McArthur, B. E., Forveille, T., Delfosse, X., Nelan, E., Butler, R. P., ... Mayor, M. (2002). A mass for the extrasolar planet Gliese 876b determined from Hubble space telescope fine guidance sensor 3 astrometry and high-precision radial velocities. The Astrophysical Journal, 581(2), L115.
  18. Muterspaugh, M. W., Lane, B. F., Kulkarni, S. R., Konacki, M., Burke, B. F., Colavita, M. M., ... Williamson, M. (2010). The phases differential astrometry data archive. V. Candidate substellar companions to binary systems. The Astronomical Journal, 140(6), 1657.
  19. Chauvin, G., Lagrange, A. M., Dumas, C., Zuckerman, B., Mouillet, D., Song, I., ... Lowrance, P. (2004). A giant planet candidate near a young brown dwarf-direct vlt/naco observations using ir wavefront sensing. Astronomy Astrophysics, 425(2), L29-L32.
  20. Thalmann, C., Carson, J., Janson, M., Goto, M., McElwain, M., Egner, S., ... Tamura, M. (2009). Discovery of the coldest imaged companion of a sun-like star. The Astrophysical Journal, 707(2), L123.
  21. Mao, S., Paczynski, B. (1991). Gravitational microlensing by double stars and planetary systems. Astrophysical Journal, Part 2-Letters (ISSN 0004-637X), vol. 374, June 20, 1991, p. L37- L40., 374, L37-L40.
  22. Beaulieu, J. P., Bennett, D. P., Fouqu´e, P., Williams, A., Dominik, M., Jørgensen, U. G., ... Yoshioka, T. (2006). Discovery of a cool planet of 5.5 Earth masses through gravitational microlensing. Nature, 439(7075), 437-440.
  23. Charbonneau, D., Brown, T. M., Latham, D. W., Mayor, M. (1999). Detection of planetary transits across a sun-like star. The Astrophysical Journal, 529(1), L45.
  24. Naef, D., Latham, D.W., Mayor, M., Mazeh, T., Beuzit, J. L., Drukier, G. A., ... Zucker, S. (2001). HD 80606 b, a planet on an extremely elongated orbit. Astronomy Astrophysics, 375(2), L27-L30.
  25. Mayo, A. W., Vanderburg, A., Latham, D. W., Bieryla, A., Morton, T. D., Buchhave, L. A., ... Winters, J. G. (2018). 275candidates and 149 validated planets orbiting bright stars in K2 campaigns 0–10. The Astronomical Journal, 155(3), 136.
  26. Rodriguez, J. E., Becker, J. C., Eastman, J. D., Hadden, S., Vanderburg, A., Khain, T., ... Terentev, I. (2018). A compact multi-planet system with a significantly misaligned ultra short period planet. The Astronomical Journal, 156(5), 245.
  27. Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., ... Zheng, X. (2016). TensorFlow: a system for Large-Scale machine learning. In 12th USENIX symposium on operating systems design and implementation (OSDI 16) (pp. 265-283).
  28. Christ, M., Braun, N., Neuffer, J., Kempa-Liehr, A. W. (2018). Time series feature extraction on basis of scalable hypothesis tests (tsfresh–a python package). Neurocomputing, 307, 72-77.
  29. Vanderburg, A., Johnson, J. A. (2014). A technique for extracting highly precise photometry for the two-wheeled Kepler mission. Publications of the Astronomical Society of the Pacific, 126(944), 948-958.
  30. Wheatley, P. J., West, R. G., Goad, M. R., Jenkins, J. S., Pollacco, D. L., Queloz, D., ... Titz-Weider, R. (2018). The next generation transit survey (NGTS). Monthly Notices of the Royal Astronomical Society, 475(4), 4476-4493.
  31. Collier Cameron, A., Pollacco, D., Street, R. A., Lister, T. A., West, R. G.,Wilson, D. M., ... Wheatley, P. J. (2006). A fast hybrid algorithm for exoplanetary transit searches. Monthly Notices of the Royal Astronomical Society, 373(2), 799-810.
  32. Maxted, P. F. L. (2016). ellc: A fast, flexible light curve model for detached eclipsing binary stars and transiting exoplanets. Astronomy Astrophysics, 591, A111.
Index Terms

Computer Science
Information Sciences
Exoplanet
detection
classify

Keywords

Artificial Intelligence (AI) Neural Network (NN) Convolutional Neural Network (CNN) deep learning machine learning transit method K2 data

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