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Inference of Hidden Structures in Complex Physical Systems by Multi-scale Clustering

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Information Science for Materials Discovery and Design

Part of the book series: Springer Series in Materials Science ((SSMATERIALS,volume 225))

Abstract

We survey the application of a relatively new branch of statistical physics—“community detection ”—to data mining. In particular, we focus on the diagnosis of materials and automated image segmentation. Community detection describes the quest of partitioning a complex system involving many elements into optimally decoupled subsets or communities of such elements. We review a multiresolution variant which is used to ascertain structures at different spatial and temporal scales. Significant patterns are obtained by examining the correlations between different independent solvers. Similar to other combinatorial optimization problems in the NP complexity class, community detection exhibits several phases. Typically, illuminating orders are revealed by choosing parameters that lead to extremal information theory correlations .

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Acknowledgments

We have benefited from interactions with numerous colleagues. In particular, we would like to thank S. Achilefu, S. Bloch, R. Darst, S. Fortunato, V. Gudkov, K.F. Kelton, T. Lookman, M.E.J. Newman, S. Nussinov, D.R. Reichman, and P. Sarder for numerous discussions and collaboration on some of the problems reviewed in this work and their outgrowths. We are further grateful to support by the NSF under Grants No. DMR-1106293 and DMR-1411229. ZN is indebted to the hospitality and support of the Feinberg foundation for visiting faculty program at the Weizmann Institute.

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Authors and Affiliations

  1. Washington University in St. Louis, St. Louis, MO, 63130, USA

    Z. Nussinov, Dandan Hu & Bo Sun

  2. Department of Condensed Matter Physics, Weizmann Institute of Science, 76100, Rehovot, Israel

    Z. Nussinov

  3. Findlay University, Findlay, OH, 45840, USA

    P. Ronhovde

  4. Department of Physics, Indian Institute of Science, Bangalore, 560012, India

    S. Chakrabarty

  5. North Central College, Naperville, IL, 60540, USA

    Nicholas A. Mauro

  6. School of Minerals, Metallurgical and Materials Engineering, Indian Institute of Technology, Bhubaneswar, 751007, India

    Kisor K. Sahu

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Correspondence to Z. Nussinov , P. Ronhovde or Dandan Hu .

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Editors and Affiliations

  1. Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA

    Turab Lookman

  2. Computer and Communications Service, Los Alamos National Laboratory Computer and Communications Service, LOS ALAMOS, New Mexico, USA

    Francis J. Alexander

  3. Department of Materials Design and Innovation, University at Buffalo- The State University of New York, Buffalo, New York, USA

    Krishna Rajan

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Nussinov, Z. et al. (2016). Inference of Hidden Structures in Complex Physical Systems by Multi-scale Clustering. In: Lookman, T., Alexander, F., Rajan, K. (eds) Information Science for Materials Discovery and Design. Springer Series in Materials Science, vol 225. Springer, Cham. https://doi.org/10.1007/978-3-319-23871-5_6

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