Stochastic Resonance Spectroscopy: Characterizing Fast Dynamics with Slow Measurements
A system's internal dynamics and its interaction with the environment can be determined by tracking how external perturbations affect its transition rates between states. Quantitative measurements of these rates are crucial for optimizing quantum systems at the atomic scale but are challenging, as these dynamics are often faster than experimental observation capabilities. Here, we show that driving a stochastic system periodically enables quantitative determination of its transition rates over a wide frequency range spanning from kilohertz to gigahertz. To perform this quantitative extraction, we provide an analytical model that is applicable irrespective of the details of the studied system. We name this method stochastic resonance spectroscopy (SRS). We apply it to quantify spin switching in individual magnetic atoms, Neel state reversal in nano-antiferromagnets and quasiparticle transport through Yu-Shiba-Rusinov states. We anticipate that the ability to characterize broadband stochastic dynamics at the atomic scale will enable insights into an even wider range of systems, e.g. dynamics driven by light-matter interaction. Another exciting prospect is the investigation of systems that exhibit non-Markovian dynamics due to correlations with the environment.