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Building effective models from sparse but precise data: Application to an alloy cluster expansion model

Cockayne, Eric and van de Walle, Axel (2010) Building effective models from sparse but precise data: Application to an alloy cluster expansion model. Physical Review B, 81 (1). Art. No. 012104 . ISSN 1098-0121.

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A common approach in computational science is to use a set of highly precise but expensive calculations to parameterize a model that allows less precise but more rapid calculations on larger-scale systems. Least-squares fitting on a model that underfits the data is generally used for this purpose. For arbitrarily precise data free from statistic noise, e.g., ab initio calculations, we argue that it is more appropriate to begin with an ensemble of models that overfit the data. Within a Bayesian framework, a most likely model can be defined that incorporates physical knowledge, provides error estimates for systems not included in the fit, and reproduces the original data exactly. We apply this approach to obtain a cluster expansion model for the CaZr_(1−x)Ti_xO_3 solid solution.

Item Type:Article
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URLURL TypeDescription DOIArticle
van de Walle, Axel0000-0002-3415-1494
Additional Information:© 2010 The American Physical Society. Received 30 December 2009; published 27 January 2010. A.v.d.W. was supported by the U.S. National Science Foundation via TeraGrid resources at NCSA and SDSC under Grant No. TG-DMR050013N. This material is based upon work supported by the Department of Energy National Nuclear Security Administration under Award No. DE-FC52-08NA28613 and National Energy Research Initiative Consortium (NERI-C) under Award No. DE-FG07-07ID14893.
Funding AgencyGrant Number
Department of Energy (DOE) National Nuclear Security AdministrationDE-FC52-08NA28613
Department of Energy (DOE)DE-FG07-07ID14893
Issue or Number:1
Classification Code:PACS: 71.15.Nc, 02.50.Tt, 61.50.Lt, 71.15.Mb
Record Number:CaltechAUTHORS:20100218-095946294
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:17513
Deposited By: Tony Diaz
Deposited On:19 Feb 2010 17:47
Last Modified:09 Mar 2020 13:19

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