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Computational neuroscience explores the brain at many different levels, from single cell activity, to small local network computation, to the dynamics of large neuronal populations across the brain. This course will introduce students to a...

This course will provide an in-depth understanding of what psychophysiology is and the common methods used to understand psychophysiological responses. Common psychophysiological methods will be discussed in-depth, such as sympathetic and...

This course will explore the current state of brain sensing and its application to human-computer interaction research. This course covers brain function, sensing technology, machine learning methods, and applications of brain-computer interfaces in...

Various specialized topics and/or research areas from one to two graduate students. Arranged individually with the faculty.

Lagrangian formulation Kinematics and dynamics of rigid bodies. Small oscillations. Motion in non-inertial frames, Hamiltonian mechanics. Canonical transformations. Hamilton-Jacobi theory.

Schrodinger equation, potential wells and barriers, Hilbert space formulation of quantum mechanics and applications, Central potentials, hydrogen atom, isotropic oscillator, angular momentum and spin.

Time independent perturbation theory, variational method and WKB method, time-dependent perturbation theory, partial wave theory of scattering, integral approach to scattering theory and Born approximation.

The laws of thermodynamics. Elements of kinetic theory. Ensemble theory: canonical, microcanonical, and grand canonical ensembles. Quantum statistical mechanics, Bose-Einstein and Fermi-Dirac statistics. Special topics in statistical mechanics.

Classical electrodynamics including boundary-value problems using Greens functions, Maxwell’s equations, electromagnetic properties of matter, wave propagation and radiation theory.

The emphasis of the course is on mathematical techniques needed by physicists. The course covers functions of complex variable, special functions, Fourier and Laplace transforms, linear algebra and tensor analysis.