  We explore a case example of networks of classical electronic oscillators
evolving towards the solution of complex optimization problems. We show that
when driven into subharmonic response, a network of such nonlinear electrical
resonators can minimize the Ising Hamiltonian on non-trivial graphs such as
antiferromagnetically coupled rewired-M{\"o}bius ladders. In this context, the
spin-up and spin-down states of the Ising machine are represented by the
oscillators' response at the even or odd driving cycles. Our experimental
setting of driven nonlinear oscillators coupled via a programmable switch
matrix leads to a unique energy minimizer when one such exists, and probes
frustration where appropriate. Theoretical modeling of the electronic
oscillators and their couplings allows us to accurately reproduce the
qualitative features of the experimental results. This suggests the promise of
this setup as a prototypical one for exploring the capabilities and limitations
of such an unconventional computing platform.
