MicroAlgo Inc. announced its research on the Quantum Information Recursive Optimization (QIRO) algorithm, which aims to address complex combinatorial optimization problems using quantum computing.

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 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 ...

Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...

Categorizing patients with cancer by their disease stage can be an important tool when conducting administrative claims-based studies. As claims databases frequently do not capture this information, ...