Equilibrium Learning of Quantum Circuits
Equilibrium learning trains a physical system using observables of its relaxed states. We extend this principle to gate-based quantum circuits by embedding a parametrized circuit in a Feynman-Kitaev (FK) Hamiltonian and imposing the compilation target either through an output clamping term or through a target-dependent...