Open Access1/ f Noise and Machine Intelligence in a Nonlinear Dopant Atom Network
Author(s) -
Chen Tao,
Bobbert Peter A.,
Wiel Wilfred G.
Publication year - 2021
Publication title -
small science
Language(s) - English
Resource type - Journals
ISSN - 2688-4046
DOI - 10.1002/smsc.202170006
Subject(s) - dopant , analogy , noise (video) , nonlinear system , atom (system on chip) , computer science , statistical physics , artificial intelligence , physics , condensed matter physics , doping , quantum mechanics , philosophy , linguistics , image (mathematics) , embedded system
1/ f Noise and Machine Intelligence Intrinsic material properties can be exploited to realise highly efficient unconventional computing. In article number 2000014 , Wilfred G. van der Wiel and co‐workers present the concomitance of 1/ f noise and machine intelligence in a dopant atom network and draw the analogy with the human brain. It is suggested that the observed conditions for optimal information processing can potentially be generalized to other complex nonlinear physical systems.