A novel scenario in the semi-constrained NMSSM
Abstract In this work, we develop a novel efficient scan method, combining the Heuristically Search (HS) and the Generative Adversarial Network (GAN), where the HS can shift marginal samples to perfect samples, and the GAN can generate a huge amount of recommended samples from noise in a short time....
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2020-06-01
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Series: | Journal of High Energy Physics |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1007/JHEP06(2020)078 |