28
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Machine learning phases of matter

      ,
      Nature Physics
      Springer Nature

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The success of machine learning techniques in handling big data sets proves ideal for classifying condensed-matter phases and phase transitions. The technique is even amenable to detecting non-trivial states lacking in conventional order.

          Related collections

          Most cited references11

          • Record: found
          • Abstract: found
          • Article: not found

          Learning phase transitions by confusion

          A neural-network technique can exploit the power of machine learning to mine the exponentially large data sets characterizing the state space of condensed-matter systems. Topological transitions and many-body localization are first on the list.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Big–deep–smart data in imaging for guiding materials design

            Harnessing big data, deep data, and smart data from state-of-the-art imaging might accelerate the design and realization of advanced functional materials. Here we discuss new opportunities in materials design enabled by the availability of big data in imaging and data analytics approaches, including their limitations, in material systems of practical interest. We specifically focus on how these tools might help realize new discoveries in a timely manner. Such methodologies are particularly appropriate to explore in light of continued improvements in atomistic imaging, modelling and data analytics methods.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              A structural approach to relaxation in glassy liquids

                Bookmark

                Author and article information

                Journal
                Nature Physics
                Nat Phys
                Springer Nature
                1745-2473
                1745-2481
                February 13 2017
                February 13 2017
                :
                :
                Article
                10.1038/nphys4035
                13a03365-9b97-46e4-87ab-a97eb2c320aa
                © 2017
                History

                Comments

                Comment on this article