Condensed matter physics is the branch of physics that studies systems of very large numbers of particles in a condensed state, like solids or liquids. Condensed matter physics wants to answer questions like: why is a material magnetic? Or why is it insulating or conducting? Or new, exciting questions like: what materials are good to make a reliable quantum computer? Can we describe gravity as the behavior of a material? The behavior of a system with many particles is very different from that of its individual particles. We say that the laws of many body physics are emergent or collective. Emergence explains the beauty of physics laws.
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Physics of Quantum Information II
The dialogue between quantum information and quantum matter has fostered notable progress in both fields. Quantum information science has revolutionized our understanding of the structure of quantum many-body systems and novel forms of out-of-equilibrium quantum dynamics. The advances of quantum -
Quantum Matter (Elective), PHYS 777, March 30 - May 1 2026
This course introduces key concepts in modern quantum matter, including spontaneous symmetry breaking, topological phases, and quantum criticality, illustrated through simple and instructive examples. -
Scientific Machine Learning (Elective), PHYS 777, February 23 - March 27, 2026
This course introduces Scientific Machine Learning, beginning with an overview of traditional and modern machine learning methods illustrated with examples from physics. It then transitions to physics-informed approaches, where physical laws, symmetries, and mechanistic models are embedded into -
Statistical Physics (Core), PHYS 602, October 8 - November 7, 2025
The aim of this course is to explore the main ideas of the statistical physics approach to critical phenomena. We will discuss phase transitions, using the ferromagnetic phase transition and the Ising model as our primary example. The renormalisation group approach will be an important part of this -
Beautiful Papers, PHYS 773, September 12 - December 1, 2025
-15 talks C25046 Courses Condensed Matter Mathematical physics Quantum Fields and Strings Quantum InformationScroll down to Registration and Enrollment to participate. Structure: We will discuss 8 papers which had huge impact in physics. One week Instructor Pedro Vieira will discuss a paper; students should read it beforehand. One week later students discuss recent papers referring to that paper (20 min -
Quantum Matter (Elective), PHYS 777, March 31 - May 2, 2025
This course will cover quantum phases of matter, with a focus on long-range entangled states, topological states, and quantum criticality. Instructor: Chong Wang/Subhayan Sahu Students who are not part of the PSI MSc program should review enrollment and course format information here: https:/ -
Machine Learning (Elective), PHYS 777, February 24 - March 28, 2025
Machine learning has become a very valuable toolbox for scientists including physicists. In this course, we will learn the basics of machine learning with an emphasis on applications for many-body physics. At the end of this course, you will be equipped with the necessary and preliminary tools for -
Quantum Field Theory II (Core), PHYS 603, November 12 - December 11, 2024
This course introduces the functional integral formalism, the renormalization group, and non-abelian gauge theory. Additional topics may be covered as time allows. Instructor: Francois David / Gang Xu Students who are not part of the PSI MSc program should review enrollment and course format -
Quantum Field Theory I (Core), PHYS 601, October 7 - November 6, 2024
The first half of the course explains why fields are desirable when quantum mechanics meets special relativity. The second half introduces different kinds of spinor fields and their interactions. Instructor: Gang Xu Students who are not part of the PSI MSc program should review enrollment and course -
Statistical Physics (Core), PHYS 602, October 7 - November 6, 2024
The aim of this course is to explore the main ideas of the statistical physics approach to critical phenomena. We will discuss phase transitions, using the ferromagnetic phase transition and the Ising model as our primary example, with particular emphasis on the renormalisation group approach -
Machine Learning 2023/24
Machine learning has become a very valuable toolbox for scientists including physicists. In this course, we will learn the basics of machine learning with an emphasis on applications for many-body physics. At the end of this course, you will be equipped with the necessary and preliminary tools for -
Higher Categorical Tools for Quantum Phases of Matter
Quantum phases have become a staple of modern physics, thanks to their appearance in fields as diverse as condensed matter physics, quantum field theory, quantum information processing, and topology. The description of quantum phases of matter requires novel mathematical tools that lie beyond the