Quantum annealers are devices that physically implement a quantum system called the Ising model to solve combinatorial optimization problems like the famous traveling salesman problem.
In the late 90s, scientists found that combinatorial optimization problems could be formulated as Ising models, which in turn could be physically implemented in quantum annealers. To obtain the solution to a combinatorial optimization problem, one simply has to observe the ground state reached in its associated quantum annealer after a short time.
However, the coefficients of the Ising model often require a large bit width, making it difficult to implement physically.
Scientists from Japan has demonstrated a method to reduce the bit width of any Ising model, increasing the applicability and versatility of quantum annealers in many fields, including cryptography, logistics, and artificial intelligence.
Their approach consists in adding auxiliary spins to the Ising model for problematic interactions or magnetic fields in such a way that the ground state (solution) of the transformed model is the same as that of the original model while also requiring a lower bit width. The technique is relatively simple and completely guaranteed to produce an equivalent Ising model with the same solution as the original. (Waseda University)
The study has been published in IEEE Transactions on Computers.