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Department of Math, Physics, and Computer Science Colloquium

November 19 @ 3:30 pm 4:30 pm

Applications of Data Science in Neutron Star Models
A lecture by Omair Zubairi, PhD
Senior Training Engineer at MathWorks

Harold C. Smith Presentation Room, Stitzer Welcome Center at Judd Gymnasia
While we invite all who can attend in person to do so, a virtual option will be available via Zoom.

Join Zoom Meeting

Data science is an emerging field that has applications in a variety of domains ranging from finance and economics to engineering and physics. Data scientists use a combination of computer science techniques, mathematical models, and statistical methods to analyze their data. In his presentation, Omair Zubairi will discuss that by understanding your data at a deeper level, valuable insight can be gained for your applications. This is particularly true for neutron star astrophysics.

Neutron stars are compact objects formed in cataclysmic astrophysical events known as supernovae. They have masses about twice that of the sun and radii of approximately 10 to 15 kilometers resulting in densities on the nuclear scale. They have high temperatures and large magnetic fields up 15-20 orders of magnitude greater than our sun. With such extreme conditions, neutron stars make excellent laboratories for nuclear, particle, and astrophysics.

Traditional models (over the last 80 years) of non-rotating neutron stars assume that these objects are perfectly spherically symmetric; however, this may not be true if high magnetic fields are present. In this talk, Zubairi will discuss various data science and visualization techniques used to model the stellar structure of highly magnetized neutron stars and how the results give invaluable insight into a connection to gravitational waves.

Zubairi is a senior training engineer at MathWorks and also is affiliated with the Computational Science Research Center at San Diego State University as a research associate.

This event is free and open to the Springfield College community.

For more information, contact Kellie Lavoie at klavoie2@springfield.edu.

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