Quantum Learning at High Temperatures in a Dissipative Electronic System

Applications of quantum machine learning, and more generally quantum information processing, would expand enormously if dissipative quantum devices could be developed to show enhanced properties even at high temperatures. The charge density wave (CDW) is an electron condensate robust at temperatures that can exceed that of the human body – even the boiling point of water – in some systems. Several CDW systems show evidence for innate quantum learning in a highly dissipative environment. This includes a pulse-duration memory effect showing rapid learning – 1-3 training pulses vs. 100’s to 1000’s needed in classical simulations. Additional quantum behaviors include transport behavior indicating time-correlated, coherent tunneling of CDW electrons, and quantum interference in CDW rings and crystals with columnar defects. We discuss proposed concepts that exploit such phenomena, including a CDW quantum reservoir computing concept and quantum devices based on patterned ion implantation of CDW materials.