Plasmon mass scale and quantum fluctuations of classical fields on a real time lattice
Kurkela, A., Lappi, T., & Peuron, J. (2018). Plasmon mass scale and quantum fluctuations of classical fields on a real time lattice. In M. D. Morte, P. Fritzsch, E. G. Sánchez, & C. P. Ruano (Eds.), Lattice 2017 : Proceedings of the 35th International Symposium on Lattice Field Theory (Article 11001). EDP Sciences. EPJ Web of Conferences, 175. https://doi.org/10.1051/epjconf/201817511001
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EPJ Web of ConferencesDate
2018Copyright
© The Authors, published by EDP Sciences. 2018. This is an open access article distributed under the terms of the Creative Commons License.
Classical real-time lattice simulations play an important role in understanding non-equilibrium phenomena in gauge theories and are used in particular to model the prethermal evolution of heavy-ion collisions. Above the Debye scale the classical Yang-Mills (CYM) theory can be matched smoothly to kinetic theory. First we study the limits of the quasiparticle picture of the CYM fields by determining the plasmon mass of the system using 3 different methods. Then we argue that one needs a numerical calculation of a system of classical gauge fields and small linearized fluctuations, which correspond to quantum fluctuations, in a way that keeps the separation between the two manifest. We demonstrate and test an implementation of an algorithm with the linearized fluctuation showing that the linearization indeed works and that the Gauss’s law is conserved.
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International Symposium on Lattice Field TheoryIs part of publication
Lattice 2017 : Proceedings of the 35th International Symposium on Lattice Field TheoryISSN Search the Publication Forum
2101-6275Keywords
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https://converis.jyu.fi/converis/portal/detail/Publication/27970971
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Academy of Finland; European CommissionFunding program(s)
Academy Research Fellow, AoF; Research costs of Academy Research Fellow, AoF
The content of the publication reflects only the author’s view. The funder is not responsible for any use that may be made of the information it contains.
Additional information about funding
This work has been supported by the Academy of Finland, projects 267321 and 303756, by the European Research Council, Grant ERC-2015-CoG-681707. J.P. is supported by the Jenny and Antti Wihuri Foundation. We acknowledge CSC – IT Center for Science, Finland, for computational resources.License
Except where otherwise noted, this item's license is described as © The Authors, published by EDP Sciences. 2018. This is an open access article distributed under the terms of the Creative Commons License.
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