Dr. Ryan McClarren
Texas A&M University 

Compressed sensing reconstructs data using a small number of measurements and solving an underdetermined linear system. In this talk I will discuss some ways this technology can be applied to the nuclear engineering problems of radiation detection and computational radiation transport. The basics of compressed sensing will be discussed, including the single pixel camera, and then shown how the methods can be used in nuclear problems.  In radiation detection, I will discuss the design of a single-detector neutron imaging system. Such a system can obtain images using fast neutrons, and could be a candidate for interrogation methods.  I will also show how compressed sensing ideas can be used to improve the accuracy and speed of Monte Carlo transport calculations by defining tallies that are analogous to the single-pixel camera. Finally, I will show results of how these ideas can detect the important uncertainties in a simulation and even improve the finite element method.