Physics

Monte Carlo simulations are a powerful computational technique for probabilistic and deterministic problems with applications to various fields including computer science, finance, economics, engineering, mathematics, and physics. The initial part of the course is about computer-simulated randomness and begins with pseudo-random generators and simulating one-dimensional random variables. From the moment that we can simulate one random variable, we can simulate a whole discrete process, such as Markov chains and use the simulations to extract statistical results of their equilibria. The course also explores applications in Physics via the Ising model and in Statistics via the goodness of fit tests. The course is a mixture of coding with probability theory, and students use the R software for the simulations.

This course treats the fundamental aspects of crystal growth, e.g. the thermodynamic prerequisites for crystal growth such as chemical potential, construction of binary phase diagrams, supersaturation, and nucleation. Further on, surface energies, surface diffusion, and Wulff’s theorem are studied. In the course section on epitaxial growth surface reconstructions, lattice mismatch, and dislocations, as well as characterization – both in- and ex-situ are discussed. Growth techniques and reactor models are also dealt with. During the course, the various moments are illuminated by examples from modern research, especially research on epitaxy of nanostructures. Assumed prior knowledge: FFFF11 Processing and Device Technology, a basic course in thermodynamics and materials science.

This course covers Maxwell equations, optical field-matter interaction, principles of lasers and rate equations, optical resonators, plane waves, ray-tracing, and Gaussian beams.

The course is divided in two parts. The first part of the course starts with a historical introduction to the building of the cosmological model. It is followed by the introduction of key concepts in Einstein’s theory of relativity, which then allows for the introduction of the Friedman-Lemaitre- Robertson-Walker cosmological model for an expanding universe. Several observational probes of cosmology are introduced, such as the cosmic microwave background, supernovae and the large-scale structure. From these, the presence and nature of dark energy and dark matter are examined. The course concludes the first part with a description of the earliest moments of the Universe and the building of a complete timeline for its history. The second part of the course focuses on extragalactic astrophysics. The goal is to overcome the assumption of galaxies as single points and understand the origin of their diversity. This diversity presents some structure, which is quantified in so-called “scaling relations” for different galaxy types. How they connect to the supermassive black holes at the centers of galaxies are discussed. Finally, the course looks into the stellar population composition of galaxies and some of the key evolutionary processes and understand how they lead to observed colors and estimates of galactic distances. Assumed previous knowledge includes NS-106B, NS-108B, NS-112B, NS-120B, NS-121B, NS-220B, and Python or other programming language knowledge (e.g. NS-109B). NS- 251B and NS-268B are recommended. 

In this project course, students explore the future of computation, focusing on quantum algorithms and hands-on programming on various platforms. Students collaborate on a project to apply quantum solutions to real-world problems, enhancing their skills in this cutting-edge field.

This course gives a fundamental understanding and an experimental experience of ultrasound and gain insight in an expanding research area. Topics covered include ultrasound physics, transducer technology, diagnostic equipment technology, doppler, bio-acoustics, field characterization, airborne ultrasound, diagnostic application, non-destructive testing, sonar, and research projects at the department. Assumed prior knowledge: First Course in Physics

This is a special studies course involving an internship with a corporate, public, governmental, or private organization, arranged with the Study Center Director or Liaison Officer. Specific internships vary each term and are described on a special study project form for each student. A substantial paper or series of reports is required. Units vary depending on the contact hours and method of assessment. The internship may be take taken during one or more terms but the units cannot exceed a total of 12.0 for the year.

This is an interdisciplinary, project‑based course designed to introduce the principles, methods, and communication practices of modern scientific research. Through a flipped‑classroom approach, the course actively explores how different disciplines—such as biology, informatics, mathematics, physics, chemistry, and computer science—intersect to address complex scientific questions. Throughout the course, students work in small subgroups to build and communicate a scientific project. They learn how to identify and evaluate scientific literature, analyze research methodologies across fields, and critically assess the validity, reproducibility, and interpretation of results. Students develop strong skills in teamwork, scientific reasoning, and oral communication as they prepare an interdisciplinary presentation aimed at both specialists and non‑specialists. A major component of the course is the construction of a final oral presentation based on recent scientific publications. Students progressively refine their project through guided tutorials led by instructors from multiple disciplines. They also practice writing concise research abstracts, critically reading scientific articles, and using research tools such as PubMed and AI‑assisted platforms—while assessing their benefits and limitations. By the end of the course, students gain practical experience in the entire scientific communication pipeline: exploring a topic, building a multidisciplinary understanding of its methods, and presenting their findings clearly and rigorously to a diverse scientific audience.