Due to low numbers of qubits and their error-proneness, Noisy Intermediate-Scale Quantum
(NISQ) computers impose constraints on the size of quantum algorithms they can
successfully execute. State-of-the-art research introduces various techniques addressing
these limitations by utilizing known or inexpensively generated approximations, solutions, or
models as a starting point to approach a task instead of starting from scratch. These so-
called warm-starting techniques aim to reduce quantum resource consumption, thus …