## Physics 763: Statistical Physics Fall Semester, 2019

### Professor Henry Greenside

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Welcome to Physics 763, a graduate physics course about statistical physics, which is a branch of physics that broadly concerns trying to understand, experimentally and theoretically, three things:
• how macroscopic properties of an equilibrium physical system can be explained from the properties of the many microscopic objects that make up that system.

• how macroscopic properties of some equilibrium physical system change as some experimental thermodynamic parameter such as temperature, pressure, volume, chemical potential, or the strength of an external magnetic field is varied in slow small steps so that the system is always in equilibrium. Especially interesting to understand are phase transitions, when some macroscopic property changes abruptly as some experimental parameter is varied in slow small steps.

• statistical properties of small but still complicated objects that interact with a large equilibrium reservoir, such as the oxygen-carrying capability of the hemoglobin in your blood as a function of the chemical potential of the oxygen, and how much a long polymer like DNA in solution stretches as a constant extension force is applied between its free ends (the so-called force-extension curve of a polymer).

Some of the examples discussed in this course include electrons in a metal and in a white dwarf, neutrons in a neutron star, magnetic dipoles in a magnet, photons in blackbody radiation, neutrinos that are part of the cosmic neutrino background, phonons in a crystal, ions in a Bose-Einstein condensate, helium atoms in a superfluid, molecules in a gas, transcription factors binding to DNA, and polymers in a solution.

Statistical physics is considered one of the four fundamental areas of physics that all physics graduate students should know well, with the other three areas being classical physics, electrodynamics, and quantum mechanics. Statistical physics is arguably the broadest of the four areas since the formalism works almost without change for classical and quantum systems, and is useful for nearly all frontiers of physics. Experimental and theoretical insights from statistical physics have also proved to be valuable for fields outside of physics such as as chemistry, biology, neuroscience, engineering, machine learning, mathematics, statistics, and computer science.

Further information about Physics 763 can be found from the course syllabus. If you have any questions about the course, please contact the course instructor, Professor Greenside at hsg@phy.duke.edu.