Quantum composition

Basically quantum computing and machine learning belong to different realms of science. The quantum computer is more suitable to solve tasks like factorisation and encryption. Because particular properties of algorithms are more appropriate for quantum computing than classical algorithms the quantum computer can solve specific tasks of machine learning better than a classical computer.

Techniques which resemble quantum computing techniques even affect classical forms of computing. Hybrid techniques combine the advantages of both techniques. Quantum machine learning can be based on supervised learning, unsupervised learning or reinforcement learning.

The specific
advantages of the quantum composition can be based on the capacity of the quantum computer which can search very quickly. Applying suitable algorithms the quantum composition can solve questions that will shape the future of the theory of music. Using special development tools or libraries developers can create particular applications and algorithms.


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