  Brain-inspired computing concepts like artificial neural networks have become
promising alternatives to classical von Neumann computer architectures.
Photonic neural networks target the realizations of neurons, network
connections and potentially learning in photonic substrates. Here, we report
the development of a nanophotonic hardware platform of fast and
energy-efficient photonic neurons via arrays of high-quality vertical cavity
surface emitting lasers (VCSELs). The developed $5\times5$ VCSEL arrays provide
high optical injection locking efficiency through homogeneous fabrication
combined with individual control over the laser wavelengths. Injection locking
is crucial for the reliable processing of information in VCSEL-based photonic
neurons, and we demonstrate the suitability of the VCSEL arrays by injection
locking measurements and current-induced spectral fine-tuning. We find that our
investigated array can readily be tuned to the required spectral homogeneity,
and as such show that VCSEL arrays based on our technology can act as highly
energy efficient and ultra-fast photonic neurons for next generation photonic
neural networks. Combined with fully parallel photonic networks our substrates
are promising for ultra-fast operation reaching 10s of GHz bandwidths, and we
show that a nonlinear transformation based on our lasers will consume only
about 100 fJ per VCSEL, which is highly competitive, compared to other
platforms.
