S. Liu, Runzhang Xie, Qianlong Kang, Haonan Ge, Min Luo, Anna Liu, Hao Xie, Lu Chen, Xiwen Liu, Qing Li, Weida Hu
The mesoscopic stochasticity of single-carrier avalanche is the dominant factor governing macroscopic noise in narrow-bandgap avalanche photodiodes (APDs). In mercury cadmium telluride (HgCdTe) devices, this randomness induces local electric field fluctuations that trigger gain-limiting band-to-band tunneling (BBT) noise. Traditional macroscopic models inherently average out these statistical fluctuations, while purely microscopic simulations are often computationally prohibitive for iterative design. To bridge this gap, this work presents a micro–mesoscopic coupled Monte Carlo framework developed to analyze avalanche chain dynamics at the critical mesoscopic scale. The analysis reveals that the avalanche statistics are governed by a coupled, 2-D parameter space defined by the spatial standard deviation ($\boldsymbol {\sigma }$) and the mean free path ($\boldsymbol {\ell }$). We demonstrate that the macroscopic signal-to-noise ratio (SNR) is determined by a complex competition among multiple noise mechanisms, involving Auger, BBT, phonon, and excess noise mechanisms within this parameter space. Guided by this analysis, an acceleration meso-lattice (AML) structure is proposed to actively engineer the mesoscopic state near a precisely optimal operating point. By regulating carrier dynamics to suppress stochastic fluctuations at their origin, the AML structure suppresses the physical conditions for BBT noise and achieves significant SNR enhancement. This research shifts the design paradigm from macroscopic geometric optimization to direct mesoscopic dynamics regulation, offering a new physical pathway to transcend fundamental device limits.