Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 189 tok/s
Gemini 2.5 Pro 46 tok/s Pro
GPT-5 Medium 35 tok/s Pro
GPT-5 High 40 tok/s Pro
GPT-4o 103 tok/s Pro
Kimi K2 207 tok/s Pro
GPT OSS 120B 451 tok/s Pro
Claude Sonnet 4.5 38 tok/s Pro
2000 character limit reached

Occurrence of Tachyonic Preheating in the Mixed Higgs-$R^2$ Model (2007.10369v2)

Published 20 Jul 2020 in hep-ph, astro-ph.CO, and gr-qc

Abstract: It has recently been suggested that at the post-inflationary stage of the mixed Higgs-$R2$ model of inflation efficient particle production can arise from the tachyonic instability of the Higgs field. It might complete the preheating of the Universe if appropriate conditions are satisfied, especially in the Higgs-like regime. In this paper, we study this behavior in more depth, including the conditions for occurrence, analytical estimates for the maximal efficiency, and the necessary degree of fine-tuning among the model parameters to complete preheating by this effect. We find that the parameter sets that cause the most efficient tachyonic instabilities obey simple laws in both the Higgs-like regime and the $R2$-like regime, respectively. We then estimate the efficiency of this instability. In particular, even in the deep $R2$-like regime with a small non-minimal coupling, this effect is strong enough to complete preheating although a severe fine-tuning is required among the model parameters. We also estimate how much fine-tuning is needed to complete preheating by this effect. It is shown that the fine-tuning of parameters for the sufficient particle production is at least $ < \mathcal{O}(0.1) $ in the deep Higgs-like regime with a large scalaron mass, while it is more severe $\sim {\cal O}(10{-4})-{\cal O}(10{-5})$ in the $R2$-like regime with a small non-minimal coupling.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.