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Many NP-hard optimization problems can be mapped onto interacting spin systems, whose ground state encodes the optimal solution. Polaritonic implementations based on gain-dissipative dynamics have recently emerged as promising analog computing platforms owing to their intrinsic parallelism and ultrafast operation. However, existing approaches are hindered by two fundamental limitations: maintaining the homogeneous amplitudes required for faithful problem encoding remains challenging in realistic physical systems, and most architectures are restricted to nearest-neighbour interactions, severely limiting the variety of optimization problems that can be efficiently addressed. We introduce a feasible polaritonic XY simulator based on a reconfigurable waveguide platform that overcomes both limitations. Our approach guarantees amplitude homogeneity while enabling the implementa- tion of arbitrary symmetric coupling matrices, thereby allowing the direct encoding of a wide variety of XY Hamiltonians. These results establish a practical architecture for programmable polaritonic spin simulators and pave the way towards scalable optical hardware for analog optimisation.
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Dini et al. (2026) studied this question.
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