Big Data Meets Big Models

Scott Pratt, Department of Physics and Astronomy, NSCL/FRIB, Michigan State University, USA

Increasingly, sophisticated numerically intensive simulations are confronting large-scale heterogeneous data sets. Often, the goal is to determine model parameters from the model/data comparison, and to quantitatively, and rigorously, express the constraint. In this talk we show how model emulators were employed to analyze data from the nuclear collisions of relativistic heavy ions, with the aim of determining fundamental properties of the quark-gluon plasma.

Please direct all questions to the following contacts - Your question will be routed to get you an answer as quickly as possible.

• MSUStatSymposium2018@stt.msu.edu
• Michigan State University
  Department of Statistics and Probability
  Room C413 Wells Hall
  619 Red Cedar Road
  East Lansing, MI 48824