School of Physics |

Epitaxial growth - graphene - quantum material - ab-initio simulation
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ab-initio Quantum MD Simulation; thermoelectric material
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Developing our Physics GTA Preparation course
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Exact solutions for interacting spinful 2D fermions; quantum skyrmions
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Welcome

The School of Physics offers programs of study leading to B.S., M.S. and Ph.D. degrees. The School is comprised of 44 faculty members, 225 undergraduate majors (one of the largest programs in the United States) and 130 graduate students.

The Howey Physics Building is comprised of 26,000 sq. ft. of instructional space (classrooms and laboratories), 156,000 sq. ft. of research laboratory space, and adequate office space for faculty, post-doctoral fellows, graduate students and visitors.

Undergraduate

With a degree from the Georgia Tech School of Physics, you'll have the tools you need to succeed whether you decide to go to graduate school or into the industry after graduation. The Bachelor of Science in Physics prepares students for physics graduate programs while the Bachelor of Science in Applied Physics is better suited for entry into industry or preparation for graduate study in some other discipline.

The School of Physics also offers Astrophysics Certificate and Astrophysics Concentration.

Graduate

The graduate program in the School of Physics provides the background and training needed to conduct and complete high quality, world-recognized research. Moreover, owing to the experiences we offer for supervised teaching of undergraduate laboratory courses, graduate students from diverse backgrounds develop into creative physicists who can function effectively in educational, industrial or government laboratory settings. Successful completion of the Ph.D. program in Physics requires (a) completion of course work, (b) participation in seminars and Special Problems, (c) acceptance into Ph.D. candidacy, and (d) thesis research.

Events

Oct

School of Physics Colloquium

Collapse of the Collapse: Physicists Return to Reality

Oct

Quantum Matter Seminar

Quantifying entanglement and detecting Kardar-Parisi-Zhang transport in spin chains using neutron scattering

Oct

Nonlinear Science Webinar

Speaker Mike Graham Overview: Data-driven dimension reduction, dynamic modeling, and control of complex chaotic systems

Our overall aim is to combine ideas from dynamical systems theory and machine learning to develop and apply reduced-order models of flow processes with complex chaotic dynamics. A particular aim is a minimal description of dynamics on manifolds of dimension much less than the nominal state dimension and use of these models to develop effective control strategies for reducing energy dissipation.