Toward structure-preserving quantum encodings

Toward structure-preserving quantum encodings Parzygnat, Arthur J.; Bradley, Tai-Danae; Vlasic, Andrew; Pham, Anh Harnessing the potential computational advantage of quantum computers for machine learning tasks relies on the uploading of classical data onto quantum computers through what are commonly referred to as quantum encodings. The choice of such encodings may vary substantially from one task to another, and there exist only a few cases where structure has provided insight into their desig