Determining the Neutrino Mass from Cyclotron Radiation Emission Spectroscopy (CRES)

通过回旋辐射发射光谱 (CRES) 确定中微子质量

• 批准号: 2719045
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2719045
• 关键词: Determining; Neutrino; Mass; Cyclotron; Radiation

The CRES Demonstration Apparatus (CRESDA) will be developed over the next two years. The student will become familiar with a range of topics including quantum detection & amplification, antenna theory and signal processing. CRESDA will collect a large volume of time-domain antenna waveforms, both simulated and real, and the heart of this PhD project is the development of techniques to extract complex signals that are barely visible above thermal background. The CRES signals can have a variety of shapes depending on the electron energy and motion inside the trap. Techniques to be explored include using matched-filters to compare a library of waveforms with the data, and the extraction of the most important features such as the starting frequency of the cyclotron emission (which carries information about the electron decay energy). Image analysis of spectrograms will be used to identify electron trajectories in our data. The over-arching aim of the project will be to use these machine-learning and data-analysis techniques to help inform projections for the ultimate reach of a future neutrino mass experiment employing the CRES technique.

CRES演示仪器(CRESDA)将在未来两年内开发。学生将熟悉包括量子探测与放大、天线理论和信号处理在内的一系列主题。CRESDA将收集大量的模拟和真实的时域天线波形，这个博士项目的核心是开发技术来提取在热背景上几乎看不见的复杂信号。CRES信号可以有各种形状，这取决于陷阱内的电子能量和运动。要探索的技术包括使用匹配过滤器将波形库与数据进行比较，以及提取最重要的特征，如回旋发射的起始频率(携带有关电子衰变能量的信息)。光谱图的图像分析将被用来识别我们数据中的电子轨迹。该项目的总体目标将是使用这些机器学习和数据分析技术来帮助预测未来使用CRES技术的中微子质量实验的最终范围。