Courses by semester
Courses for Fall 2025
Complete Cornell University course descriptions and section times are in the Class Roster.
Course ID | Title | Offered |
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ASTRO 1101 |
From New Worlds to Black Holes
Explore the wonders of the universe, from black holes to newly discovered worlds. This course covers the birth and death of stars, the nature of black holes, and the search for extraterrestrial life. Engage with the latest discoveries and understand how we are made of stardust. Full details for ASTRO 1101 - From New Worlds to Black Holes |
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ASTRO 1195 |
Observational Astronomy
A hands-on introduction to observational astronomy. Learn how we gather knowledge about the universe using amateur telescopes. Includes evening labs featuring telescope observations at Fuertes Observatory and Mount Pleasant, as well as in-class experiments such as micrometeorite collection. |
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ASTRO 2202 |
A Spacecraft Tour of the Solar System: Science, Policy and Exploration
Explore planetary science through the lens of spacecraft missions. Learn how missions are selected and developed, and engage with guest speakers from NASA, ESA, and policy experts. Topics include space policy, life in the outer solar system, Mars exploration, and the search for extrasolar planets. Full details for ASTRO 2202 - A Spacecraft Tour of the Solar System: Science, Policy and Exploration |
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ASTRO 2211 |
Astronomy: Stars, Galaxies, and Cosmology
Survey the universe from the Big Bang to galaxy formation. Topics include star formation, stellar evolution, black holes, and cosmology, with discussions on quantum physics, relativity, and particle physics. More in-depth than ASTRO 1101. Full details for ASTRO 2211 - Astronomy: Stars, Galaxies, and Cosmology |
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ASTRO 3302 |
The Life of Stars: From Birth to Death
Study stellar formation, evolution, and final stages as white dwarfs, neutron stars, or black holes. Covers fundamental astrophysical concepts and observational evidence. Full details for ASTRO 3302 - The Life of Stars: From Birth to Death |
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ASTRO 3340 |
Symbolic and Numerical Computing
Introduces Mathematica and symbolic computation for applications across sciences and engineering. Includes programming concepts, data analysis, and a final project in an area of interest. Full details for ASTRO 3340 - Symbolic and Numerical Computing |
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ASTRO 4410 |
Multiwavelength Astronomical Techniques
Covers observational techniques in optical and radio astronomy. Topics include CCD imaging, spectroscopy, and interferometry. Labs use observatories on campus, emphasizing data analysis and instrumentation. Full details for ASTRO 4410 - Multiwavelength Astronomical Techniques |
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ASTRO 4431 |
Physics of Stars, Neutron Stars and Black Holes
Covers stellar structure, solar neutrinos, stellar seismology, and the physics of compact objects like white dwarfs, neutron stars, and black holes. Full details for ASTRO 4431 - Physics of Stars, Neutron Stars and Black Holes |
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ASTRO 4445 |
Introduction to General Relativity
One-semester introduction to general relativity that develops the essential structure and phenomenology of the theory without requiring prior exposure to tensor analysis. General relativity is a fundamental cornerstone of physics that underlies several of the most exciting areas of current research, including relativistic astrophysics, cosmology, and the search for a quantum theory of gravity. The course briefly reviews special relativity, introduces basic aspects of differential geometry, including metrics, geodesics, and the Riemann tensor, describes black hole spacetimes and cosmological solutions, and concludes with the Einstein equation and its linearized gravitational wave solutions. At the level of Gravity: An Introduction to Einstein's General Relativity by Hartle. Full details for ASTRO 4445 - Introduction to General Relativity |
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ASTRO 4523 |
Modeling, Mining and Machine Learning in Astronomy
This course covers probability, statistics, and signal processing to develop algorithms for detecting objects and events in astronomical data. Topics include frequentist and Bayesian model inference, time-series analysis, clustering, classification, genetic algorithms, Markov Chain Monte Carlo, and neural networks. Students will apply these methods to real and simulated data using Python and Jupiter notebooks. Full details for ASTRO 4523 - Modeling, Mining and Machine Learning in Astronomy |
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ASTRO 4940 |
Independent Study in Astronomy
Allows students to conduct independent research or study a specific area of astronomy under faculty supervision. A written report is required. Full details for ASTRO 4940 - Independent Study in Astronomy |
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ASTRO 6516 |
Galactic Structure and Stellar Dynamics
This course will focus on topics related to the structure and dynamics of collisionless and mildly collisional systems in galaxies: stars in the galactic disk, stars in globular clusters, stars in open clusters, spiral arms, and the galactic center, as well as stars in binary and triple systems. We shall also discuss the formation, structure and evolution of the galaxy and its halo. There are no specific prerequisites for this course, but knowledge of classical mechanics at the level of Physics 3318 or AEP 3330 and practical familiarity with differential equations and linear algebra at the level of Math 2940 will be assumed. Students should be aware of the existence of the objects mentioned in the course description. Full details for ASTRO 6516 - Galactic Structure and Stellar Dynamics |
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ASTRO 6523 |
Modeling, Mining and Machine Learning in Astronomy
This course covers probability, statistics, and signal processing to develop algorithms for detecting objects and events in astronomical data. Topics include frequentist and Bayesian model inference, time-series analysis, clustering, classification, genetic algorithms, Markov Chain Monte Carlo, and neural networks. Students will apply these methods to real and simulated data using Python and Jupiter notebooks. Full details for ASTRO 6523 - Modeling, Mining and Machine Learning in Astronomy |
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ASTRO 6560 |
Physics of Stars, Neutron Stars and Black Holes
Covers stellar structure, evolution, and the physics of compact objects, including neutron stars and black holes. Full details for ASTRO 6560 - Physics of Stars, Neutron Stars and Black Holes |
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ASTRO 6575 |
Planetary Atmospheres
This course will provide an overview of fundamental physical processes that govern the structure and behavior of atmospheres in the solar system and beyond. Topics covered will include the basic principles of atmospheric statics, radiative transfer, dynamics, cloud physics, and chemistry to understand the diverse range of observable atmospheres. These topics will be explored through review of relevant physical processes and research in solar system and exoplanetary science. This course is geared toward graduate students with a solid background in relevant math and physics coursework. |
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ASTRO 6940 |
Advanced Study and Research
Guided reading and seminars on topics not currently covered in regular courses. |
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ASTRO 7340 |
Symbolic and Numerical Computing
Introduces symbolic and numerical computing using Mathematica for scientific and engineering applications. Includes programming, data visualization, and a final project. Full details for ASTRO 7340 - Symbolic and Numerical Computing |
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ASTRO 7683 |
Seminar: Astronomy and Planetary Science
A reading seminar for graduate students to broaden their astronomy knowledge, practice public speaking, and analyze key findings from seminal research papers. Full details for ASTRO 7683 - Seminar: Astronomy and Planetary Science |
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ASTRO 7690 |
Computational Physics
Develops tools for using computers to model the physical world. Uses examples pulled broadly from core areas of physics: Mechanics, Electricity and Magnetism, Statistical Mechanics and Thermodynamics, and Quantum Mechanics. Focus is on algorithmic thinking, converting mathematical representations into practical algorithms, working with data, and drawing physical conclusions from numerical results. Model problems will involve numerical quadratures, ordinary and partial differential equations, numerical linear algebra, event based simulations, and Monte Carlo techniques. May include modern techniques, such as those drawn from machine learning and artificial intelligence. Instruction will largely be in Julia, with computer labs integrated into lectures. No prior experience with Julia is necessary, but students should have some experience with programming. Graduate versions, PHYS 7680 and ASTRO 7690, require an additional project which is not required in the undergraduate version, PHYS 4480. |
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