Physicists from the Australian National University, University of Adelaide and University of New South Wales announced that they were able to develop an AI that successfully replicated the experiment that won the 2001 Nobel Prize in Physics.
In 1925, world-renowned physicist Albert Einstein predicted – based on an earlier study of Satyendra Nath Bose – that when a given number of particles move toward each other sufficiently closely and sufficiently slowly they will turn to the lowest energy state. This lowest energy state is now known as Bose-Einstein condensation (BEC).
BEC remained a theory until 1995 – the year when Eric Cornell, Wolfgang Ketterle and Carl Wieman were able to prove this lowest energy state. In 2001, the Royal Swedish Academy of Sciences awarded the Nobel Prize in Physics to Cornell, Ketterle and Wieman “for the achievement of Bose-Einstein condensation in dilute gases of alkali atoms, and for early fundamental studies of the properties of the condensates.”
In the paper entitled “Fast machine-learning online optimization of ultra-cold-atom Experiment” published by the journal Nature, the Australian physicists wrote, “Through repeated machine-controlled scientific experimentation and observations our ‘learner’ discovers an optimal evaporation ramp for BEC production.”
For the BEC experiment, the Australian physicists cooled the gas to close to one microkelvin. The team then turned over the control of three laser beams to the AI in order to cool the trapped gas down to nanokelvin.
Paul Wigley, co-lead researcher of the paper, told the Australian National University Media Team, “I didn’t expect the machine could learn to do the experiment itself, from scratch, in under an hour.”
Wigley added that the AI did things that a normal person would not have guessed such as adjusting the laser’s power up and down, and at the same time, compensating with another.
BEC applications can revolutionize nanotechnology and holography, this according to Nobelprize.org.