offered to correlate proton SEE with heavy ion SEE. Such correlation can be useful for estimating proton upset sensitivity when heavy ion data is available. In addition, for present technologies, the correlation approaches can allow the estimation of heavy ion sensitivity when only proton data exist or when packaging issues preclude penetration by heavy ions to the active device regions. These estimates can be useful, but if high confidence predictions are required, these estimates should not be substituted for test results from the flight lot devices in application specific test configurations. PROFIT (for Proton Fit) is an empirical model that allows fitting of heavy ion data or heavy ion data combined with proton test data to extract parameters allowing prediction of proton upset rates [Calv-96]. The approach requires knowledge of the number of sensitive cells. It assumes that sensitive cells have the same spatial dimensions but may have differing critical charge levels. In comparisons with the two-parameter Bendel approach, the referenced paper showed very good agreement for the 18 different device types used in the study. In [O'Ne-98], another approach based on proton reaction kinematics shows how upper bounds on the heavy ion upset rates and failure probabilities can be estimated from 200 MeV proton data. This correlation requires proton data as input, and can be especially useful when heavy ion data are not available. The method does not allow estimation of proton upset sensitivity from heavy ion data. The final correlation technique we will discuss was first reported in 1983 and has been revised several times with the most recent being "The SEU Figure of Merit and Proton Upset Rate Calculations" [Pete-98 and references therein]. This approach is based on the claim that upset sensitivity for a given device can be summarized by a single parameter, the figure of merit (FOM). The referenced paper indicates how the FOM can be calculated based on either the heavy ion upset saturation cross section and threshold