Constructing and proving the ground state of a generalized Ising model by the cluster tree optimization algorithm

Journal Article · Thu Jun 23 04:00:00 EDT 2016 · arXiv.org Repository

OSTI ID:1605223

Huang, Wenxuan ^[1]; Kitchaev, Daniil ^[1]; Dacek, Stephen ^[1]; Rong, Ziqin ^[1]; Ding, Zhiwei ^[1]; Ceder, Gerbrand ^[2]

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1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
2. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Univ. of California, Berkeley, CA (United States). Dept. of Materials Science and Engineering; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division

Generalized Ising models, also known as cluster expansions, are an important tool in many areas of condensed-matter physics and materials science, as they are often used in the study of lattice thermodynamics, solid-solid phase transitions, magnetic and thermal properties of solids, and fluid mechanics. However, the problem of finding the global ground state of generalized Ising model has remained unresolved, with only a limited number of results for simple systems known. We propose a method to efficiently find the periodic ground state of a generalized Ising model of arbitrary complexity by a new algorithm which we term cluster tree optimization. Importantly, we are able to show that even in the case of an aperiodic ground state, our algorithm produces a sequence of states with energy converging to the true ground state energy, with a provable bound on error. Compared to the current state-of-the-art polytope method, this algorithm eliminates the necessity of introducing an exponential number of variables to counter frustration, and thus significantly improves tractability. We believe that the cluster tree algorithm offers an intuitive and efficient approach to finding and proving ground states of generalized Ising Hamiltonians of arbitrary complexity, which will help validate assumptions regarding local vs. global optimality in lattice models, as well as offer insights into the low-energy behavior of highly frustrated systems.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 1605223
• Report Number(s): arXiv:1606.07429; ark:/13030/qt96w71136
• Journal Information: arXiv.org Repository, Journal Name: arXiv.org Repository Vol. 2016; ISSN 9999-0017
• Publisher: Cornell University
• Country of Publication: United States
• Language: English

Related Subjects

75 CONDENSED MATTER PHYSICS
SUPERCONDUCTIVITY AND SUPERFLUIDITY