The electric dipole moment (EDM) challenge measures a non-zero proton EDM value and this book suggests how the challenge can be met. Any measurably large proton EDM would violate the standard model. The method to be employed uses an intense beam of 'frozen spin' protons circulating for hour-long times in a storage ring 'trap'. The smallness of EDMs allows them to test existing theories, but also makes them hard to measure. Such EDM experiments are inexpensive, at least compared to building accelerators of ever-greater energy.

Lab Manual for Biomedical Engineering: Devices and Systems examines key concepts in biomedical systems and signals in a laboratory setting. The book gives students the opportunity to complete both measurement and math modeling exercises, thus demonstrating that the experimental real-world setting directly corresponds with classroom theory. All the experiments in the lab manual have been extensively class-tested and cover concepts such as wave math, Fourier transformation, electronic and random noise, transfer functions, and systems modeling. Each experiment builds on knowledge acquired in previous experiments, allowing the level of difficulty to increase at an appropriate pace. In completing the lab work, students enhance their understanding of the lecture course. The third edition features expanded exercises, additional sample data and measurements, and lab modifications for increased ease and simple adaptation to the online teaching and learning environment. Individual activities have also been added to aid with independent learning. Lab Manual for Biomedical Engineering is ideal for undergraduate courses in biomedical engineering comprised of students who have completed introductory electrical and mechanical physics courses. A two-semester background in calculus is recommended.

Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at www.cambridge.org/9781107607590, including data files for the case studies so students can practise analysing data, and exercises to test students' understanding.