no problems that were previously believed to be in the complexity class P (polynomial time) have been proven to be NP-complete or QP-complete specifically because of quantum computers. The classification of problems into complexity classes like P, NP, and QP remains the same unless there have been significant advancements that I am not aware of.
However, it is worth noting that quantum computers have the potential to solve certain problems more efficiently than classical computers. For example, Shor's algorithm, a well-known quantum algorithm, can factor large numbers exponentially faster than the best-known classical algorithms. This has implications for the security of cryptographic systems based on factoring large numbers, as quantum computers could potentially break them.
Furthermore, there is ongoing research into quantum algorithms and their potential impact on solving specific problems. Some problems that are currently believed to be intractable (i.e., not solvable in polynomial time by classical computers) might have more efficient quantum algorithms. However, it is important to remember that the practical realization of large-scale, fault-tolerant quantum computers is still a significant engineering challenge.
As the field of quantum computing advances, it is possible that new problem classes or new relationships between classical and quantum complexity classes may emerge. Staying updated with the latest research in quantum computing and complexity theory will provide more insights into any potential changes or discoveries in this regard.