| Reference Type | Journal (article/letter/editorial) |
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| Title | LHC signals of a heavy doublet Higgs as dark matter portal: cut-based approach and improvement with gradient boosting and neural networks |
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| Journal | Journal of High Energy Physics |
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| Authors | Dey, Atri | Author |
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| Lahiri, Jayita | Author |
| Mukhopadhyaya, Biswarup | Author |
| Year | 2019 (September) | Volume | 2019 |
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| Publisher | Springer Science and Business Media LLC |
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| DOI | doi:10.1007/jhep09(2019)004Search in ResearchGate |
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| Generate Citation Formats |
| Mindat Ref. ID | 12372686 | Long-form Identifier | mindat:1:5:12372686:7 |
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|
| GUID | 0 |
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| Full Reference | Dey, Atri, Lahiri, Jayita, Mukhopadhyaya, Biswarup (2019) LHC signals of a heavy doublet Higgs as dark matter portal: cut-based approach and improvement with gradient boosting and neural networks. Journal of High Energy Physics, 2019. doi:10.1007/jhep09(2019)004 |
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| Plain Text | Dey, Atri, Lahiri, Jayita, Mukhopadhyaya, Biswarup (2019) LHC signals of a heavy doublet Higgs as dark matter portal: cut-based approach and improvement with gradient boosting and neural networks. Journal of High Energy Physics, 2019. doi:10.1007/jhep09(2019)004 |
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| In | (n.d.) Journal of High Energy Physics Vol. 2019. Springer Science and Business Media LLC |
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