  Orbital angular momentum (OAM) detection underpins almost all aspects of
vortex beams' advances such as communication and quantum analogy. Conventional
schemes are frustrated by low speed, complicated system, limited detection
range. Here, we devise an intelligent processor composed of photonic and
electronic neurons for OAM spectrum measurement in a fast, accurate and direct
manner. Specifically, optical layers extract invisible topological charge
information from incoming light and a shallow electronic layer predicts the
exact spectrum. The integration of optical-computing promises us a compact
single-shot system with high speed and energy efficiency, neither necessitating
reference wave nor repetitive steps. Importantly, our processor is endowed with
salient generalization ability and robustness against diverse structured light
and adverse effects. We further raise a universal model interpretation paradigm
to reveal the underlying physical mechanisms in the hybrid processor, as
distinct from conventional 'black-box' networks. Such interpretation algorithm
can improve the detection efficiency. We also complete the theory of
optoelectronic network enabling its efficient training. This work not only
contributes to the explorations on OAM physics and applications, and also
broadly inspires the advanced links between intelligent computing and physical
effects.
