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States of matter

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Home » Condensed matter » States of matter » Machine learning spots topological phase transitions in experimental data

Machine learning spots topological phase transitions in experimental data

11 Nov 2020 Lavanya Taneja 
Experimental data
Experimental data: excitations in a lattice of optical waveguides. (Courtesy: Eran Lustig et al./Physical Review Letters; data from J Noh et al./Nature Physics)
A machine-learning tool called diffusion maps has been used to identify topological phase transition

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Lavanya Taneja is a former PhD student contributor to Physics World. Lavanya studied experimental quantum optics at the University of Chicago. Find out more about our student contributor networks
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