期刊
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
卷 -, 期 4, 页码 -出版社
IOP Publishing Ltd
DOI: 10.1088/1475-7516/2021/04/011
关键词
big bang nucleosynthesis; cosmology of theories beyond the SM; particle physics - cosmology connection; physics of the early universe
资金
- ERC Starting Grant 'NewAve' [638528]
- Deutsche Forschungsgemeinschaft [390833306]
- F.R.S. - FNRS under the Excellence of Science (EoS) project [30820817 -be.h]
In this study, the model-independent constraints from Big Bang Nucleosynthesis on MeV-scale particles phi decaying into photons and/or electron-positron pairs are revised and updated, with the resulting bounds significantly strengthened, especially for small masses. The release of the public code ACROPOLIS for numerical solution of reaction networks allows for evaluating the impact of photodisintegration on final light element abundances, revealing potential solutions to problems like the lithium problem through processes like the photodisintegration of beryllium.
In this work, we revise and update model-independent constraints from Big Bang Nucleosynthesis on MeV-scale particles phi which decay into photons and/or electron-positron pairs. We use the latest determinations of primordial abundances and extend the analysis in [1] by including all spin-statistical factors as well as inverse decays, significantly strengthening the resulting bounds in particular for small masses. For a very suppressed initial abundance of phi, these effects become ever more important and we find that even a pure 'freeze-in' abundance can be significantly constrained. In parallel to this article, we release the public code ACROPOLIS which numerically solves the reaction network necessary to evaluate the effect of photodisintegration on the final light element abundances. As an interesting application, we re-evaluate a possible solution of the lithium problem due to the photodisintegration of beryllium and find that e.g. an ALP produced via freeze-in can lead to a viable solution.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据