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We study two operational schemes for a coherent Ising machine based on an injection-locked laser network. These schemes gradually increase the pumping rate or the mutual coupling among the slave lasers. We numerically simulate the two schemes against a data search problem implemented with the Ising model in cubic graphs without frustration. We show the machine can achieve a better success probability and effective computational time to find a target/ground state with these gradual schemes than those with the abrupt introduction of the mutual injection which has been studied previously. The computational time simulated with typical parameters is almost constant up to the problem size M = 200 and turns into a nearly linear scale holding up to M = 1000.
We show that the nonlinear stochastic dynamics of a measurement-feedback-based coherent Ising machine (MFB-CIM) in the presence of quantum noise can be exploited to sample degenerate ground and low-energy spin configurations of the Ising model. We fo
Statistical spin dynamics plays a key role to understand the working principle for novel optical Ising machines. Here we propose the gauge transformations for spatial photonic Ising machine, where a single spatial phase modulator simultaneously encod
We have recently demonstrated that optical pumping methods combined with photoassociation of ultra-cold atoms can produce ultra-cold and dense samples of molecules in their absolute rovibronic ground state. More generally, both the external and inter
Adiabatic quantum pumping in one-dimensional lattices is extended by adding a tilted potential to probe better topologically nontrivial bands. This extension leads to almost perfectly quantized pumping for an arbitrary initial state selected in a ban
Finding the ground states of the Ising Hamiltonian [1] maps to various combinatorial optimization problems in biology, medicine, wireless communications, artificial intelligence, and social network. So far no efficient classical and quantum algorithm