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CURTAINs for your sliding window: Constructing unobserved regions by transforming adjacent intervals
We propose a new model independent technique for constructing background data templates for use in searches for new physics processes at the LHC. This method, called Curtains, uses invertible neural networks to parameterise the distribution of side band data as a function of the resonant observable....
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072325/ https://www.ncbi.nlm.nih.gov/pubmed/37025653 http://dx.doi.org/10.3389/fdata.2023.899345 |