Learning Feynman Diagrams with Tensor Trains
We use tensor network techniques to obtain high-order perturbative diagrammatic expansions for the quantum many-body problem at very high precision. The approach is based on a tensor train parsimonious representation of the sum of all Feynman diagrams, obtained in a controlled and accurate way with...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2022-11-01
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| Series: | Physical Review X |
| Online Access: | http://doi.org/10.1103/PhysRevX.12.041018 |