Quantum Computing: Physics, Blockchains, and Deep Learning Smart Networks Swan Melanie
Quantum Computing: Physics, Blockchains, and Deep Learning Smart Networks Swan Melanie Quantum information and contemporary smart network domains are so large and complex as to be beyond the reach of…
Specifikacia Quantum Computing: Physics, Blockchains, and Deep Learning Smart Networks Swan Melanie
Quantum Computing: Physics, Blockchains, and Deep Learning Smart Networks Swan Melanie
Quantum information and contemporary smart network domains are so large and complex as to be beyond the reach of current research approaches. Physics is implicated as smart networks are physical systems comprised of particle-many items interacting and reaching criticality and emergence across volumes of macroscopic and microscopic states. Hence, new theories are needed for their understanding and control.
Statistical neural field theory and the AdS/CFT correspondence are employed to derive a smart network field theory (SNFT) and a smart network quantum field theory (SNQFT) for the orchestration of smart network systems. Methods are integrated from statistical physics, information theory, and computer science. Specifically, a smart network field theory (conventional or quantum) is a field theory for the organization of particle-many systems from a characterization, control,