Neural network modeling of heavy-quark potential from holography
Abstract Using Multi-Layer Perceptrons (MLP) and Kolmogorov–Arnold Networks (KAN), we construct a holographic model based on lattice QCD data for the heavy-quark potential in the 2+1 system. The deformation factor w(r) in the metric is obtained using the two types of neural network. First, we numeri...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-06-01
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| Series: | European Physical Journal C: Particles and Fields |
| Online Access: | https://doi.org/10.1140/epjc/s10052-025-14319-2 |
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