SRQDLCS

Quantum deep learning is in its infancy and is a potential domain where classical and quantumtechnology intersect well to speed up many classical algorithms to reduce time complexity from exponentialto polynomial. This systematic review article aims to look deeper into quantum deep learning and show thecommon architectures, building blocks, and integrating approaches. Moreover, challenges and opportunitiesin quantum deep learning for computer scientists seeking research gaps are discussed in more detail. Inaddition, this article shows that algorithms are clustered into three main categories: quantum-inspired,hybrid classical-quantum, and fully fledged quantum. For now, the limitations of quantum hardware leadto the dominance of hybrid classical-quantum over fully fledged quantum and quantum-inspired algorithms.Variational quantum algorithms that utilize parameterized quantum circuits and classical optimizationmethods are essential building blocks in modern hybrid classical-quantum and fully-fledged quantumalgorithms. These quantum circuits implementing variational quantum algorithms are also called ansatzes.An ansatz or a set of gates may be customized to a problem or be generic. The ansatz also can be considereda trial wavefunction or state that is used as an approximate starting point or guess when solving a problem.The ansatz performs its part of a quantum algorithm by applying its sequence of gates. Each gate has a fewqubits on which it can operate and may operate in parallel with other gates at each time step. The qubitshave a superposition state where they may be 0, 1, or both, and be entangled with another qubit no matterthe distance between the two. The quantum algorithm may be solved by ansatzes that are laid out on a two-dimensional grid. The integrated ansatzes with shallow quantum circuits that have constant depth or timesteps, are shown to solve problems in fewer time steps than classical algorithms and open more opportunitiesfor computer scientists interested in research in a domain historically dominated by physics.