4.7 Article

Energy-momentum correlations for Abelian Higgs cosmic strings

期刊

PHYSICAL REVIEW D
卷 93, 期 8, 页码 -

出版社

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevD.93.085014

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资金

  1. Swiss National Supercomputing (CSCS) [s319, s546]
  2. STFC
  3. Large Facilities Capital Fund of BIS
  4. Eusko Jaurlaritza [IT-559-10]
  5. Ministerio de Economia y Competitividad [FPA2012-34456]
  6. Consolider-Ingenio Programme CPAN [CSD2007-00042]
  7. Consolider-Ingenio Programme EPI [CSD2010-00064]
  8. Swiss NSF
  9. Science and Technology Facilities Council [ST/L000504/1]
  10. STFC [ST/K00333X/1, ST/M00418X/1, ST/M007065/1, ST/L000636/1, ST/L000504/1, ST/J005673/1, ST/G000573/1] Funding Source: UKRI
  11. Science and Technology Facilities Council [ST/M00418X/1, ST/M007065/1, ST/K00333X/1, ST/L000504/1, ST/L000636/1, ST/J005673/1, ST/G000573/1] Funding Source: researchfish

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We report on the energy-momentum correlators obtained with recent numerical simulations of the Abelian Higgs model, essential for the computation of cosmic microwave background and matter perturbations of cosmic strings. Due to significant improvements both in raw computing power and in our parallel simulation framework, the dynamical range of the simulations has increased fourfold both in space and time, and for the first time we are able to simulate strings with a constant physical width in both the radiation and matter eras. The new simulations improve the accuracy of the measurements of the correlation functions at the horizon scale and confirm the shape around the peak. The normalization is slightly higher in the high wave-number tails, due to a small increase in the string density. We study, for the first time, the behavior of the correlators across cosmological transitions and discover that the correlation functions evolve adiabatically; i.e., the network adapts quickly to changes in the expansion rate. We propose a new method for constructing source functions for Einstein-Boltzmann integrators, comparing it with two other methods previously used. The new method is more consistent, easier to implement, and significantly more accurate.

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