Mechanism learning infers active local evolution rules via prototype-anchored descriptors to achieve more robust forecasting than direct state prediction on benchmarks like Burgers, WeatherBench2, and Lorenz96.
Response and Amplification of Terahertz Electromagnetic Waves in Intrinsic Josephson Junctions of Layered High-Tc Superconductor
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abstract
We investigate the response of a stack of intrinsic Josephson junctions (IJJs) to terahertz (THz) electromagnetic (EM) irradiation. A significant amplification of the EM wave can be achieved by the IJJs stack when the incident frequency equals to one of the cavity frequencies. The irradiation excites pi phase kinks in the junctions, which stimulate the cavity resonance when the bias voltage is tuned. A large amount of dc energy is then pumped into the Josephson plasma oscillation, and the incident wave gets amplified. From the profound current step in IV characteristics induced at the cavity resonance, the system can also be used for detection of the THz wave.
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2026 1verdicts
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Mechanism Learning: Prototype-Anchored Mechanism Inference for Scientific Forecasting
Mechanism learning infers active local evolution rules via prototype-anchored descriptors to achieve more robust forecasting than direct state prediction on benchmarks like Burgers, WeatherBench2, and Lorenz96.