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SUMMARY:Computational Homology and Materials Science - Professor Kazuto Ak
 agi\, Advanced Institute for Materials Research\, Tohoku University
DTSTART:20180306T110000Z
DTEND:20180306T120000Z
UID:TALK102214@talks.cam.ac.uk
CONTACT:Georg Schusteritsch
DESCRIPTION:\nFinding relationship between structure and property is one o
 f the essential subjects in materials science. However\, it is still diffi
 cult to notice what is the structural motifs or hierarchical information c
 haracterizing complex systems. Computational homology based on “persiste
 nt homology” [1] is a powerful framework to detect and describe the "sha
 pe" in discrete data such as atomic configurations or pixel images. The ob
 tained geometrical information is contracted as a two-dimensional map call
 ed “persistence diagram (PD)”\, in which birth and death of N-dimensio
 nal holes are recorded.\n\nFrom the view point of materials science\, the 
 advantage of this mathematical method is summarized as follows:\n(1) Detec
 ting hidden order in the system.\n(2) Providing “finger prints (or descr
 iptors)” of complex systems.\n(3) Enabling us to treat “inverse proble
 ms”.\n\nIn this talk\, I will introduce the key points of computational 
 homology for materials scientists. After that\, we will see how it works i
 n the analysis of molecular dynamics simulations and experimentally observ
 ed images\, respectively.\n\n[1] Y. Hiraoka et al.\, PNAS 113\, 7035-7040 
 (2016).
LOCATION:Goldsmiths 1\, Lecture Theatre\, Department of Materials Science 
 &amp\; Metallurgy
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