Spinfoams and high-performance computing
Dona P, Han M, Liu H (2024)
Publication Type: Authored book
Publication year: 2024
Publisher: Springer Nature
ISBN: 9789819976812
DOI: 10.1007/978-981-99-7681-2_100
Abstract
Numerical methods are a powerful tool for doing calculations in spinfoam theory. We review the major frameworks available, their definition, and various applications. We start from sl2cfoam-next, the state-of-the-art library to efficiently compute EPRL spinfoam amplitudes based on the booster decomposition. We also review two alternative approaches based on the integration representation of the spinfoam amplitude: Firstly, the numerical computations of the complex critical points discover the curved geometries from the spinfoam amplitude and provide important evidence of resolving the flatness problem in the spinfoam theory. Lastly, we review the numerical estimation of observable expectation values based on the Lefschetz thimble and Markov-Chain Monte Carlo method, with the EPRL spinfoam propagator as an example.
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APA:
Dona, P., Han, M., & Liu, H. (2024). Spinfoams and high-performance computing. Springer Nature.
MLA:
Dona, Pietro, Muxin Han, and Hongguang Liu. Spinfoams and high-performance computing. Springer Nature, 2024.
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