Modern digital hardware and software designs are increasingly complex but are themselves only idealizations of a real system that is instantiated in, and interacts with, an analog physical environment. Insights from physics, formal methods, and complex systems theory can aid in extending reliability and security measures from pure digital computation (itself a challenging problem) to the broader cyber-physical and out-of-nominal arena. Example applications to design and analysis of high-consequence controllers and extreme-scale scientific computing illustrate the interplay of physics and computation.
Jackson R. Mayo received a Ph.D. in physics from Princeton University in 2005. He is a Principal R&D Scientist in the Scalable Modeling & Analysis Systems Department at Sandia National Laboratories in Livermore, California, and specializes in modeling of complex, nonlinear, and statistical phenomena. Particular interests include complex systems analysis, formal methods, and the resiliency and security of computing systems.