Brett Gladman (gladman@atsro.ubc.ca) and Allison Man (aman@phas.ubc.ca)
*All are welcome to this event!
Event Information:
Abstract:
Not long after discovering the universal law of gravitation, Isaac Newton asked a troubling question. Is the solar system stable? It took over 300 years to arrive at an answer. Brute-force numerical integrations have demonstrated that it is possible that Mercury will collide with Venus or be lost into the Sun. Yet despite extensive effort on this thorny question, which led to the development of perturbation theory, the discovery of chaos, and the establishment of the field of non-linear dynamics, we still do not understand the physics driving these instabilities in a general context.
This problem has renewed relevance today, since we think such instabilities have shaped the orbital architectures of the thousands of exoplanet systems in the observed sample. I will present recent successes using machine learning techniques to make accurate predictions of long-term stability in compact exoplanetary systems, and discuss how we ultimately used our machine learning models to elucidate the underlying dynamics and arrive at an analytical understanding of the problem.
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2023-12-04T16:00:002023-12-04T17:00:00The chaotic lives of planetary systemsEvent Information:
Abstract:
Not long after discovering the universal law of gravitation, Isaac Newton asked a troubling question. Is the solar system stable? It took over 300 years to arrive at an answer. Brute-force numerical integrations have demonstrated that it is possible that Mercury will collide with Venus or be lost into the Sun. Yet despite extensive effort on this thorny question, which led to the development of perturbation theory, the discovery of chaos, and the establishment of the field of non-linear dynamics, we still do not understand the physics driving these instabilities in a general context.
This problem has renewed relevance today, since we think such instabilities have shaped the orbital architectures of the thousands of exoplanet systems in the observed sample. I will present recent successes using machine learning techniques to make accurate predictions of long-term stability in compact exoplanetary systems, and discuss how we ultimately used our machine learning models to elucidate the underlying dynamics and arrive at an analytical understanding of the problem. Event Location:
HENN 318