0000000000380938

AUTHOR

Younggeun Kim

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A machine learning algorithm for direct detection of axion-like particle domain walls

2021

The Global Network of Optical Magnetometers for Exotic physics searches (GNOME) conducts an experimental search for certain forms of dark matter based on their spatiotemporal signatures imprinted on a global array of synchronized atomic magnetometers. The experiment described here looks for a gradient coupling of axion-like particles (ALPs) with proton spins as a signature of locally dense dark matter objects such as domain walls. In this work, stochastic optimization with machine learning is proposed for use in a search for ALP domain walls based on GNOME data. The validity and reliability of this method were verified using binary classification. The projected sensitivity of this new analy…

Space and Planetary SciencePhysics - Data Analysis Statistics and ProbabilityFOS: Physical sciencesddc:530Astronomy and AstrophysicsAstrophysics - Instrumentation and Methods for AstrophysicsInstrumentation and Methods for Astrophysics (astro-ph.IM)Data Analysis Statistics and Probability (physics.data-an)Physics::Geophysics
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