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Best possible strategy for finding ground states
Finding the ground state of a system with a complex energy landscape is important for many physical problems including protein folding, spin glasses, chemical clusters, and neural networks. Such problems are usually solved by heuristic search methods whose efficacy is judged by empirical performance...
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Published in: | Physical review letters 2001-06, Vol.86 (23), p.5219-5222 |
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container_title | Physical review letters |
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creator | Franz, A Hoffmann, K H Salamon, P |
description | Finding the ground state of a system with a complex energy landscape is important for many physical problems including protein folding, spin glasses, chemical clusters, and neural networks. Such problems are usually solved by heuristic search methods whose efficacy is judged by empirical performance on selected examples. We present a proof that, within the large class of algorithms that simulate a random walk on the landscape, threshold accepting is the best possible strategy. In particular, it can perform better than simulated annealing and Tsallis statistics. Our proof is the first example of a provably optimal strategy in this area. |
doi_str_mv | 10.1103/PhysRevLett.86.5219 |
format | article |
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source | American Physical Society:Jisc Collections:APS Read and Publish 2023-2025 (reading list) |
subjects | ALGORITHMS ANNEALING BASIC BIOLOGICAL SCIENCES GROUND STATES Models, Theoretical NEURAL NETWORKS PROTEINS SPIN STATISTICS |
title | Best possible strategy for finding ground states |
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