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Statements

Subject Item
dbr:KBD_algorithm
rdfs:label
KBD algorithm
rdfs:comment
The KBD algorithm is a cluster update algorithm designed for the fully frustrated Ising model in two dimensions, or more generally any two dimensional spin glass with frustrated plaquettes arranged in a checkered pattern. It is discovered in 1990 by Daniel Kandel, Radel Ben-Av, and Eytan Domany, and generalized by P. D. Coddington and L. Han in 1994. It is the inspiration for cluster algorithms used in quantum monte carlo simulations.
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dbc:Statistical_mechanics dbc:Monte_Carlo_methods
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n10:KBD_algorithm?oldid=1065072939&ns=0
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1065072939
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dbc:Monte_Carlo_methods dbr:Boltzmann_distribution dbr:Giant_component dbr:Dual_lattice dbr:Ising_model dbr:Wolff_algorithm dbr:Graph_embedding dbr:Glauber_dynamics dbr:Detailed_balance dbr:Spin_glass dbr:Homotopy dbr:Domino_tiling dbr:Ergodicity dbr:Torus dbr:Cycle_(graph_theory) dbr:Check_(pattern) dbr:Thermodynamic_limit dbr:Random_cluster_model dbr:Euler_characteristic dbr:Percolation_critical_exponents dbr:Geometrical_frustration dbr:Percolation_theory dbc:Statistical_mechanics dbr:Quantum_Monte_Carlo dbr:Swendsen–Wang_algorithm
dbo:abstract
The KBD algorithm is a cluster update algorithm designed for the fully frustrated Ising model in two dimensions, or more generally any two dimensional spin glass with frustrated plaquettes arranged in a checkered pattern. It is discovered in 1990 by Daniel Kandel, Radel Ben-Av, and Eytan Domany, and generalized by P. D. Coddington and L. Han in 1994. It is the inspiration for cluster algorithms used in quantum monte carlo simulations.
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n10:KBD_algorithm