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Article Dans Une Revue Class.Quant.Grav. Année : 2021

A high-performance code for EPRL spin foam amplitudes

Résumé

We present sl2cfoam-next, a high-performance software library for computing Lorentzian EPRL spin foam amplitudes. The library improves on previous codes by many orders of magnitude in single-core performance, can be parallelized on a large number of CPUs and on the GPU, and can be used interactively. We describe the techniques used in the code and provide many usage examples. As first applications, we use sl2cfoam-next to complete the numerical test of the Lorentzian single-vertex asymptotics and to confirm the presence of the ‘flatness problem’ of spin foam models in the BF and EPRL cases.

Dates et versions

hal-03320005 , version 1 (13-08-2021)

Identifiants

Citer

Francesco Gozzini. A high-performance code for EPRL spin foam amplitudes. Class.Quant.Grav., 2021, 38 (22), pp.225010. ⟨10.1088/1361-6382/ac2b0b⟩. ⟨hal-03320005⟩
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