A high-performance code for EPRL spin foam amplitudes
arXiv:2107.13952 · doi:10.1088/1361-6382/ac2b0b
Abstract
We present , 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 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.
26 pages, many figures and code snippets
References in corpus (7)
- LQG vertex with finite Immirzi parameter
- A New Spin Foam Model for 4d Gravity
- Towards Spinfoam Cosmology
- Effective Spin Foam Models for Lorentzian Quantum Gravity
- Regularization and finiteness of the Lorentzian LQG vertices
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Cited by in corpus (16)
- Effective Spin Foam Models for Lorentzian Quantum Gravity
- Complex critical points and curved geometries in four-dimensional Lorentzian spinfoam quantum gravity
- The End of a Black Hole's Evaporation -- Part II
- How-To compute EPRL spin foam amplitudes
- Complex critical points in Lorentzian spinfoam quantum gravity: 4-simplex amplitude and effective dynamics on double- complex
- Spin-foams as semi-classical vertices: gluing constraints and a hybrid algorithm
- Numerical analysis of the self-energy in covariant Loop Quantum Gravity
- Markov Chain Monte Carlo methods for graph refinement in Spinfoam Cosmology
- Spinfoams and high performance computing
- Radiative corrections to the Lorentzian EPRL spin foam propagator
- The accidental flatness constraint does not mean a wrong classical limit
- Toward matter dynamics in spin foam quantum gravity
- Geometry from local flatness in Lorentzian spin foam theories
- Studying the EPRL spinfoam self-energy
- A spin foam framework for the black-to-white hole transition
- A saddle-point finder and its application to the spin foam model