Heterodyne photoacoustic gas sensing with real-time resonance tracking in high-Q resonators.

High quality-factor (High-) photoacoustic (PA) resonators are widely recognized for their superior signal enhancement in trace gas sensing; however, their practical deployment is fundamentally limited by extreme sensitivity of the resonance frequency and quality factor to variations in gas composition, gas concentration, and pressure. Existing resonance-tracking strategies typically suffer from either slow response, increased system complexity, or incompatibility with continuous-wave laser excitation, preventing simultaneous high-precision sensing and real-time resonance stabilization. Here, we report a heterodyne photoacoustic (H-PA) excitation framework that enables simultaneous gas concentration measurement and real-time tracking of intrinsic resonance parameters in high- PA resonators under rapid acquisition. By exploiting the transient acoustic response induced during fast laser wavelength scanning under off-resonant modulation, the proposed method converts resonance-encoded information into a low-frequency heterodyne signal that can be efficiently demodulated without additional modulation bandwidth or electronic locking circuits. The H-PA framework is theoretically established using a modal transient response model and experimentally validated using a high- H-type PA cell operating in the first-order radial mode. Continuous tracking of the resonance frequency and quality factor is demonstrated, with frequency deviations confined within ± 1 Hz and quality factor uncertainties below ± 50. Notably, resonance tracking and gas detection are achieved within a single acquisition cycle of 250 ms, representing a substantial improvement over conventional resonance-profiling techniques. By decoupling resonance tracking from steady-state frequency scanning and electronic locking, the proposed H-PA excitation framework provides a general, fast-response, and low-complexity solution for stabilizing high- PA sensors against resonance drift induced by variations in gas composition, gas concentration, and pressure, thereby removing a critical bottleneck for their deployment in real-time, high-precision gas sensing applications.