Advanced modeling and simulation of Single-Photon Avalanche Diodes

Overview & Synopsis

This thesis advances the modeling, simulation, and optimization of Single-Photon Avalanche Diodes (SPADs), which detect individual photons with high sensitivity. SPADs are essential for applications in quantum communications, imaging, and time-of-flight measurements, where precise single-photon detection is crucial. However, SPADs operate through complex, stochastic processes such as avalanche multiplication, timing jitter, and quenching, making accurate modeling a challenge. This thesis addresses these complexities by developing advanced simulation models, applying optimization techniques, and exploring methods to enhance SPAD performance. The thesis starts by reviewing SPAD technology and principles. SPADs detect photons by triggering an avalanche process in a high electric field, which amplifies the photon's signal into a measurable pulse. This thesis extends the McIntyre model, traditionally used for avalanche devices, to three dimensions, allowing for more accurate simulations of complex SPAD geometries and electric fields. A core contribution is introducing Particle Swarm Optimization (PSO) coupled with a nonlinear Poisson solver to optimize SPAD parameters like breakdown voltage, depletion width, and timing jitter. PSO navigates the design space effectively, balancing competing performance requirements and enabling customized SPADs for different applications, from low-light imaging to fast photon counting. To improve SPAD simulation accuracy, the thesis develops an Advection-Diffusion Monte Carlo (ADMC) method, which combines advection and diffusion processes for a realistic model of carrier transport, especially in high-field regions where avalanches occur. This model overcomes limitations of traditional Monte Carlo methods, achieving accurate representations of timing jitter, breakdown probability, and dark count rate. The thesis culminates in a self-consistent Monte Carlo-Poisson model for transient SPAD simulations. By combining ADMC with a 3D Poisson solver, this model captures critical SPAD behaviors like avalanche initiation, field depletion, and quenching in real time. This feedback loop is essential for understanding transient SPAD behaviors, as carriers impact the electric field as they accumulate. The model is especially useful for studying the stochastic nature of quenching, which influences SPAD reliability and timing. In summary, this thesis makes significant contributions to SPAD modeling, simulation, and optimization. By creating a self-consistent Monte Carlo-Poisson model and integrating advanced optimization techniques, this work provides a comprehensive framework for improving SPAD performance and supports further advances in high-precision applications.