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Article overview
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Generative models for scalar field theories: how to deal with poor scaling? | Javad Komijani
; Marina K. Marinkovic
; | Date: |
4 Jan 2023 | Abstract: | Generative models, such as the method of normalizing flows, have been
suggested as alternatives to the standard algorithms for generating lattice
gauge field configurations. Studies with the method of normalizing flows
demonstrate the proof of principle for simple models in two dimensions.
However, further studies indicate that the training cost can be, in general,
very high for large lattices. The poor scaling traits of current models
indicate that moderate-size networks cannot efficiently handle the inherently
multi-scale aspects of the problem, especially around critical points. We
explore current models with limited acceptance rates for large lattices and
examine new architectures inspired by effective field theories to improve
scaling traits. We also discuss alternative ways of handling poor acceptance
rates for large lattices. | Source: | arXiv, 2301.01504 | Services: | Forum | Review | PDF | Favorites |
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