Testing Theories Of Dark Energy Using Atom Interferometry

使用原子干涉测量法测试暗能量理论

• 批准号: ST/W00626X/1
• 负责人: Edmund Copeland
• 金额: $ 1.81万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FW00626X%2F1
• 关键词: Testing; Theories; Dark; Energy; Using

Cosmological observations provide compelling evidence that the standard models of particle physics and cosmology are incomplete. Key observations are the presence and structure of the cosmic microwave background and the expansion history of the universe seen using Type 1a supernovae. These observations show that the expansion of the universe began to accelerate at the time of the formation of the solar system. The as-yet unknown cause of this expansion has been dubbed 'dark energy'. Dark energy is not explained in any current theory of physics or cosmology. Current observations are a poor guide to the structure and energy scales of the new physics needed. We propose to address these fundamental cosmological mysteries by making an improved search for dark energy using atom interferometry. In an atom interferometer a tiny sample of atoms in vacuum is cooled to nearly absolute zero. At such low temperatures an atom's quantum interaction with laser light makes it exquisitely sensitive to tiny forces such as one which might have its origin from dark energy. The improvements we will make will advance not only the search for dark energy but also the sensitivity of atom interferometers for detecting other new physics.

宇宙学观测提供了令人信服的证据，证明粒子物理和宇宙学的标准模型是不完整的。主要的观测是宇宙微波背景的存在和结构，以及利用1a型超新星观测到的宇宙膨胀历史。这些观测表明，宇宙的膨胀在太阳系形成时就开始加速。到目前为止，这种膨胀的原因还不为人所知，它被称为“暗能量”。目前的任何物理学或宇宙学理论都没有解释暗能量。对于所需的新物理的结构和能量尺度，目前的观测并不能提供很好的指导。我们建议通过使用原子干涉计量学改进暗能量的搜索来解决这些基本的宇宙学谜团。在原子干涉仪中，真空中的微小原子样本被冷却到接近绝对零度。在如此低的温度下，原子与激光的量子相互作用使其对微小的力非常敏感，例如可能来自暗能量的力。我们将作出的改进不仅将促进暗能量的探索，而且还将提高原子干涉仪探测其他新物理的灵敏度。

项目成果

FeynMG: A FeynRules extension for scalar-tensor theories of gravity

• DOI: 10.1016/j.cpc.2023.109035
• 发表时间: 2022-11
• 期刊: Comput. Phys. Commun.
• 作者: Sergio Sevillano Muñoz;E. Copeland;P. Millington;M. Spannowsky

Using machine learning to optimise chameleon fifth force experiments

使用机器学习优化变色龙第五力实验

• DOI: 10.1088/1475-7516/2024/02/011
• 发表时间: 2024
• 期刊: Journal of Cosmology and Astroparticle Physics
• 影响因子: 6.4
• 作者: Briddon C