Fundamentals of the physics of the solid earth, including thermodynamics, rheology, geomagnetism, gravity, and plate tectonics. Graduate-level requirements include a term paper in publication format on some aspect of a major course topic. Identical to: GEOS 519; GEOS is home department. May be convened with: PTYS 419. Usually offered: Spring.
Fall 2016 Graduate Courses
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Dynamic Meteorology (3)
Thermodynamics and its application to planetary atmospheres, hydrostatics, fundamental concepts and laws of dynamic meteorology. Identical to ATMO 541A. ATMO is home department.
Special Topics in Planetary Science (1-4)
Course will emphasize emerging and current topical research in Planetary Science; course will be offered as needed or required. Sample course topics might include an active spacecraft mission, an emerging research area, or new discoveries. Course may be co-convened with PTYS 495B. Graduate-level requirements may include an additional project for graduate credit and extra questions on exams, depending on the course/topic taught. Course may be repeated for credit 4x (or up to 12 units). Regular grades assigned (ABC).
Scientific Instrumentation for Spacecraft: Instrumentation for remote sensing and in situ measurements from the remote perspective of planetary probes, orbiting observatories, and landers have very specific requirements that affect their design and operation. In this course we will introduce several different technologies that are used to obtain spectroscopic, optical, and direct sampling measurements throughout the solar system. We will then discuss the limitation and trades associated with their use in the various environments encountered and platforms available in modern space exploration. Part 1 of a two-course series where a mission concept will be developed. 3 units. Course may be co-convened with PTYS 495B. Graduate-level requirements may include an additional project for graduate credit and extra questions on exams, depending on the course/topic taught.
Machine Learning for Planetary Science: Study of Machine Learning techniques, and their applications in different fields. The emphasis of the class is on geological, planetary and astronomical applications. The course will cover basic and state of the art Machine Learning techniques: Support Vector Machines, K-Means, Linear Regression, Neural Networks. Student will be able to code and test different Machine Learning Algorithms in a scripting language like Python or Matlab. 2 units. Course may be co-convened with PTYS 495B. Graduate-level requirements may include an additional project for graduate credit and extra questions on exams, depending on the course/topic taught.
Methods in Computational Astrophysics (3)
The course is a "hands-on" introduction to computer use for research by scientists in astrophysics and related areas. The course begins with a survey of and introduction to tools available on Linux systems, web-based tools, and open-source software widely used in astrophysics. Standard methods for integration, iteration, differential and difference equations, and Monte Carlo simulations, are discussed, in one to four dimensions. Historically important methods of radiative transfer, reaction networks, and hydrodynamics are presented, and contrasted with presently-used methods. Parallel programming is introduced, and discussed in terms of new and future computer systems. Special topics are added to reflect new developments. The course is task-oriented, with individual and team work projects, and class participation determining grades. Most of the work is done on the student's own personal computer (Linux or Mac operating systems are preferred). Identical to ASTR/PHYS 596B. ASTR is home department. Equivalent to ASTR 596B and PHYS 596B; ASTR is home department. Typically Offered Spring. Regular or Alternative Grades: ABCDE or SPF.
Atmospheric Radiation and Remote Sensing (3)
Theory of atmospheric radiative transfer processes; specific methods for solving the relevant equations; applications to problems in radiative transfer; theoretical basis for remote sensing from the ground and from space; solutions to the "inverse" problem. Identical to ATMO 656A; ATMO is home department. Prerequisite(s): MATH 254.