Learning BPS Spectra and the Gap Conjecture
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866917757196435456 |
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| author | Gukov, Sergei Seong, Rak-Kyeong |
| author_facet | Gukov, Sergei Seong, Rak-Kyeong |
| contents | We explore statistical properties of BPS q-series for 3d N=2 strongly coupled supersymmetric theories that correspond to a particular family of 3-manifolds Y. We discover that gaps between exponents in the q-series are statistically more significant at the beginning of the q-series compared to gaps that appear in higher powers of q. Our observations are obtained by calculating saliencies of q-series features used as input data for principal component analysis, which is a standard example of an explainable machine learning technique that allows for a direct calculation and a better analysis of feature saliencies. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2405_09993 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Learning BPS Spectra and the Gap Conjecture Gukov, Sergei Seong, Rak-Kyeong High Energy Physics - Theory Machine Learning Neural and Evolutionary Computing Mathematical Physics Geometric Topology We explore statistical properties of BPS q-series for 3d N=2 strongly coupled supersymmetric theories that correspond to a particular family of 3-manifolds Y. We discover that gaps between exponents in the q-series are statistically more significant at the beginning of the q-series compared to gaps that appear in higher powers of q. Our observations are obtained by calculating saliencies of q-series features used as input data for principal component analysis, which is a standard example of an explainable machine learning technique that allows for a direct calculation and a better analysis of feature saliencies. |
| title | Learning BPS Spectra and the Gap Conjecture |
| topic | High Energy Physics - Theory Machine Learning Neural and Evolutionary Computing Mathematical Physics Geometric Topology |
| url | https://arxiv.org/abs/2405.09993 |