Kim, Dongok, Kimball, Derek F., Masia-Roig, Hector, Smiga, Joseph A., Wickenbrock, Arne, Budker, Dmitry, Kim, Younggeun, Shin, Yun Chang, and Semertzidis, Yannis K. A machine learning algorithm for direct detection of axion-like particle domain walls. Retrieved from https://par.nsf.gov/biblio/10437420. Physics of the Dark Universe 37.C Web. doi:10.1016/j.dark.2022.101118.
Kim, Dongok, Kimball, Derek F., Masia-Roig, Hector, Smiga, Joseph A., Wickenbrock, Arne, Budker, Dmitry, Kim, Younggeun, Shin, Yun Chang, & Semertzidis, Yannis K. A machine learning algorithm for direct detection of axion-like particle domain walls. Physics of the Dark Universe, 37 (C). Retrieved from https://par.nsf.gov/biblio/10437420. https://doi.org/10.1016/j.dark.2022.101118
Kim, Dongok, Kimball, Derek F., Masia-Roig, Hector, Smiga, Joseph A., Wickenbrock, Arne, Budker, Dmitry, Kim, Younggeun, Shin, Yun Chang, and Semertzidis, Yannis K.
"A machine learning algorithm for direct detection of axion-like particle domain walls". Physics of the Dark Universe 37 (C). Country unknown/Code not available. https://doi.org/10.1016/j.dark.2022.101118.https://par.nsf.gov/biblio/10437420.
@article{osti_10437420,
place = {Country unknown/Code not available},
title = {A machine learning algorithm for direct detection of axion-like particle domain walls},
url = {https://par.nsf.gov/biblio/10437420},
DOI = {10.1016/j.dark.2022.101118},
abstractNote = {},
journal = {Physics of the Dark Universe},
volume = {37},
number = {C},
author = {Kim, Dongok and Kimball, Derek F. and Masia-Roig, Hector and Smiga, Joseph A. and Wickenbrock, Arne and Budker, Dmitry and Kim, Younggeun and Shin, Yun Chang and Semertzidis, Yannis K.},
}
Warning: Leaving National Science Foundation Website
You are now leaving the National Science Foundation website to go to a non-government website.
Website:
NSF takes no responsibility for and exercises no control over the views expressed or the accuracy of
the information contained on this site. Also be aware that NSF's privacy policy does not apply to this site.