We present an experimental and theoretical study of nonresonant detection of subterahertz radiation in GaAs/AlGaAs and GaN/AlGaN heterostructure field effect transistors. The experiments were performed in a wide range of temperatures (8–300 K) and for frequencies ranging from 100 to 600 GHz. The photoresponse measured as a function of the gate voltage exhibited a maximum near the threshold voltage. The results were interpreted using a theoretical model that shows that the maximum in photoresponse can be explained by the combined effect of exponential decrease of the electron density and the gate leakage current.

The resonant detection of subterahertz radiation by two-dimensional electron plasma confined in a submicron gate GaAs/AlGaAs field-effect transistor is demonstrated. The results show that the critical parameter that governs the sensitivity of the resonant detection is ωτ, where ω is the radiation frequency and τ is the momentum scattering time. By lowering the temperature and hence increasing τ and increasing the detection frequency ω, we reached ωτ∼1 and observed resonant detection of 600 GHz radiation in a 0.15 μm gate length GaAs field-effect transistor. The evolution of the observed photoresponse signal with temperature and frequency is reproduced well within the framework of a theoretical model.

Charles Richter's observation that 'only fools and charlatans predict earthquakes,' reflects the fact that despite more than 100 years of effort, seismologists remain unable to do so with reliable and accurate results. Meaningful prediction involves specifying the location, time, and size of an earthquake before it occurs to greater precision than expected purely by chance from the known statistics of earthquakes in an area. In this context, 'forecasting' implies a prediction with a specification of a probability of the time, location, and magnitude. Two general approaches have been used. In one, the rate of motion accumulating across faults and the amount of slip in past earthquakes is used to infer where and when future earthquakes will occur and the shaking that would be expected. Because the intervals between earthquakes are highly variable, these long-term forecasts are accurate to no better than a hundred years. They are thus valuable for earthquake hazard mitigation, given the long lives of structures, but have clear limitations. The second approach is to identify potentially observable changes in the Earth that precede earthquakes. Various precursors have been suggested, and may have been real in certain cases, but none have yet proved to be a general feature preceding all earthquakes or to stand out convincingly from the normal variability of the Earth's behavior. However, new types of data, models, and computational power may provide avenues for progress using machine learning that were not previously available. At present, it is unclear whether deterministic earthquake prediction is possible. The frustrations of this search have led to the observation that (echoing Yogi Berra) 'it is difficult to predict earthquakes, especially before