The goal of a numerical optimization problem is to find a vector of values that minimizes some cost function. The most fundamental example is minimizing the Sphere Function f(x0, x1, .. xn) = x0^2 + ...

In the lower part of the figure, it can be seen that L2O leverages on a set of training problem instances from the target optimization problem class to gain knowledge. This knowledge can help identify ...

Researchers demonstrated a quantum algorithmic speedup with the quantum approximate optimization algorithm, laying the groundwork for advancements in telecommunications, financial modeling, materials ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

In a new paper in Science Advances, researchers at JPMorgan Chase, the U.S. Department of Energy's (DOE) Argonne National Laboratory and Quantinuum have demonstrated clear evidence of a quantum ...