Spiking Photonic Neurons Based on Two-Section InP Quantum-Well Lasers Integrated on Silicon

In this work we experimentally investigate the spiking dynamics of two-section InP quantum-well lasers monolithically integrated on silicon. By appropriately tuning the electrical bias conditions, we realize multiple neuronal-like operating regimes, such as integrate-and-fire and resonate-and-fire, highlighting the device's versatility as a high-speed photonic neuron. A systematic investigation of laser design parameters, including cavity length and gain/saturable absorber ratio, elucidates their impact on spiking-related properties (such as pulse repetition frequency) and traces the operational parameter space that unlocks stable spiking. Finally, these findings pave the way toward scalable neuromorphic photonic integrated circuits, where low-loss silicon synapses coexist with versatile laser neurons.