This module aims to give students a solid foundation in modern physics, specifically in special relativity and introductory quantum mechanics, which will serve as the basis for more specific modules later in their curriculum. The material taught in this module shows students the shortcomings of classical physical theories and the way modern physics theories were developed to overcome these limitations. At the same time, it introduces students to more advanced formalisms used in modern physics, such as the covariant formalism in relativity and the modeling of observables as linear operators in quantum mechanics. This module is then effectively a bridge between the classical physics modules that students have taken up to this point, and the following specialized modules about different topics in modern physics that constitute the remaining part of the programme.
A explain the limitations of classical physics and the solutions proposed by modern physics B describe the spacetime-based physical quantities introduced by special relativity C apply the covariant formalism in relativistic dynamics D discuss the way observers affect observables in quantum physics E solve simple quantum mechanics problems using Schrödinger’s equation
This module is delivered over 13 teaching weeks in semester 2, year 2. Students are expected to attend four hours of formal lectures and tutorials in a typical week. During the lectures, students will be introduced to the academic content and practical skills underlying the module. Tutorials will focus on solving exercises in class, aimed at teaching students how to apply the lecture concepts in practical situations. In addition, students are required to dedicate 7-8 hours per week to independent study; this time should be used for background reading, reflection, and reviewing the lecture material. Students are encouraged to utilize AI tools and to critically explore the strengths and limitations of generative AI for enhancing their learning and comprehension, including understanding when generative AI works effectively and when it does not.