What in Uncertainty Quantification?

“If a man will begin with certainties, he shall end in doubts;
but if he will be content to begin with doubts, he shall end in certainties.” – F. Bacon – 1605.
The availability of powerful computational resources and general purpose numerical algorithms creates increasing opportunities to attempt simulations in complex systems. How accurate are the resulting predictions? Are the mathematical and physical models correct? Do we have sufficient information to define relevant operating conditions? In general, how can we establish error bars on the results?
Uncertainty Quantification (UQ) aims at developing rigorous methods to characterize the impact of limited knowledge on quantities of interest. At the interface between physics, mathematics, probability and optimization, and although quite mature in the experimental community, UQ efforts are in their infancy in computational science.
Proud to be part of this. Hope to continue to work with it.

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