Abstract

Axions constitute a well-motivated dark matter candidate, and if PQ symmetry breaking occurred after inflation, it should be possible to make a clean prediction for the relation between the axion mass and the axion dark matter density. We show that axion (or other global) string networks in 3D have a network density that depends logarithmically on the string separation-to-core ratio. This logarithm would be about 10 times larger in axion cosmology than what we can achieve in numerical simulations. We simulate axion production in the early Universe, finding that, for the separation-to-core ratios we can achieve, the changing density of the network has little impact on the axion production efficiency.

Highlights

  • As we will soon explain, the PQ field’s evolution in the early Universe is complicated by the appearance of structures – cosmic strings – that may play a role in determining the production efficiency of axions around the QCD scale T ∼ 1 GeV

  • Axion cosmic string networks are in a family called “global string networks,” and Martins and Shellard have argued [27, 28] that such networks are sensitive to the sizes of the string cores, which cannot be properly simulated numerically

  • This implies that numerical simulations will view string networks with very different properties – in particular, a much lower string density – than the ones that would really occur for physical axion field parameter values

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Summary

String networks and string cores

We begin with a lightning review of why the strings arising from Eq (1.1) have logarithmically large string tensions. We assume some familiarity with string defects; a reader who needs some background can look in [49]. We will make the classical field approximation throughout, which is an excellent approximation for the IR axion field dynamics since the mean occupancy is ∼ fa2/H2 ∼ 1060

Cosmic strings
Scaling in 2D
Scaling in 3D
Implementation
Results for string-only networks
Scaling expectations
String-wall network evolution in 2D
Domain-wall instability
Discussion and Conclusions
A Numerical implementation
Strings and string velocities
Numerical tests
Findings
B Counting axions
Full Text
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