A method for hybrid quantum-classical information processing performed on a hybrid quantum-classical information processing system comprising one or more classical information processors and a quantum system, the method comprising: obtaining an initial input state for the quantum system, wherein the quantum system is represented by a graph and wherein the quantum system is associated with a corresponding energy landscape comprising multiple energy barriers and wherein a ground state of the quantum system encodes a solution to an optimization task; partitioning, within the hybrid quantum-classical information processing system, the graph into a plurality of local regions in dependence on the optimisation task; evolving the initial input state and subsequent input states within the one or more classical information processors, the evolution comprising applying one or more of (i) dynamical thermal fluctuations and/or (ii) cluster update algorithms to the initial input state and subsequent input states; determining that the (i) dynamical thermal fluctuations and/or (ii) cluster update algorithms are failing to overcome one or more energy barriers in the energy landscape at a given temperature; evolving the classically evolved initial input state and classically evolved subsequent input states within the quantum system, the evolution comprising applying dynamical quantum fluctuations to one or more local regions of the quantum system where the (i) dynamical thermal fluctuations and/or (ii) cluster update algorithms are failing to overcome one or more energy barriers in the energy landscape at a given temperature and not applying dynamical quantum fluctuations to one or more other local regions of the quantum system; and repeating the evolution and determining steps until an approximate ground state of the quantum system is obtained. obtaining an initial input state for the quantum system, wherein the quantum system is represented by a graph and wherein the quantum system is associated with a corresponding energy landscape comprising multiple energy barriers and wherein a ground state of the quantum system encodes a solution to an optimization task; partitioning, within the hybrid quantum-classical information processing system, the graph into a plurality of local regions in dependence on the optimisation task; evolving the initial input state and subsequent input states within the one or more classical information processors, the evolution comprising applying one or more of (i) dynamical thermal fluctuations and/or (ii) cluster update algorithms to the initial input state and subsequent input states; determining that the (i) dynamical thermal fluctuations and/or (ii) cluster update algorithms are failing to overcome one or more energy barriers in the energy landscape at a given temperature; evolving the classically evolved initial input state and classically evolved subsequent input states within the quantum system, the evolution comprising applying dynamical quantum fluctuations to one or more local regions of the quantum system where the (i) dynamical thermal fluctuations and/or (ii) cluster update algorithms are failing to overcome one or more energy barriers in the energy landscape at a given temperature and not applying dynamical quantum fluctuations to one or more other local regions of the quantum system; and repeating the evolution and determining steps until an approximate ground state of the quantum system is obtained. <EOS>