Spiking photonic neurons based on two-section InP quantum-well lasers integrated on silicon

In this work, we experimentally investigate the self-pulsating dynamics and excitability of two-section InP quantum-well lasers heterogeneously integrated on silicon. By appropriately tuning the electrical bias conditions, we realize multiple neuronal-like self-pulsating regimes, demonstrating resonate-and-fire and integrate-and-fire-like dynamics, highlighting the potential of the device as a high-speed photonic neuron. A systematic investigation of laser design parameters, including cavity length and gain/saturable absorber (SA) ratio, elucidates their impact on self-pulsation-related properties, such as pulse repetition frequency, and traces the operational parameter space that unlocks stable spiking. Finally, we demonstrate the basic attributes of integrate-and-fire dynamics in the integrated laser-neurons, paving the way toward scalable neuromorphic photonic integrated circuits (PIC) combining low-loss silicon synapses with versatile laser neurons.