Complex systems can exhibit emergent phenomena, wherein the interplay of simple underlying rules governing the constituent parts leads to rich and unexpected behavior of the whole. Condensed matter physics is the branch of physics devoted to understanding such emergence in physical systems. It is the largest subfield of physics, and has developed a wealth of ideas and techniques for taming complexity. The course provides an introduction to this physics of emergence.
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The course is aimed at a general audience. It assumes familiarity with algebra, and passing familiarity with basic concepts such as atoms and energy, but does not assume knowledge of advanced physics or mathematics. It is the first of a series of three courses introducing the key ideas of modern condensed matter physics. However, it can also be taken as a standalone course.
This course is part of the The Physics of Emergence: Introduction to Condensed Matter Specialization.
What you'll learn
- Define what constitutes a phase of matter.
- Interpret phases in terms of symmetries, and describe spontaneous symmetry breaking.
- Identify the competition between energy and entropy, and explain how this produces phase transitions.
Syllabus
Emergent Phenomena and Phases of Matter
Module 1
This module introduces the notion of emergent phenomena, and a central application of this notion: phases of matter. We define what constitutes a phase of matter, and explain that there are many phases beyond the familiar trio of solid, liquid, and gas.
Symmetries and Symmetry Breaking
Module 2
This module introduces the notion of symmetries, which provide a powerful tool for thinking about phases of matter. It also introduces the notion of spontaneous symmetry breaking.
Energy, Entropy and Phase Structure
Module 3
This module introduces the concepts of energy, entropy and explains how the competition between them can drive phase transitions.
Mean Field Theory
Module 4
In this module, you will learn a powerful tool for analyzing phases that are classified by symmetries, known as mean field theory. You will learn to apply this tool.
