An improved particle swarm optimization algorithm and its application to search for new magnetic ground states in the Hubbard model

Abstract

An improved particle swarm optimization algorithm is proposed and its superiority over standard particle swarm optimization algorithm is tested on two typical benchmark functions. By employing this algorithm to search for the magnetic ground states of the Hubbard model on the real-space square lattice with finite size based on the mean-field approximation, two new magnetic states, namely the double striped-type antiferromagnetic state and the triple antiferromagnetic state, are found. We further perform mean-field calculations in the thermodynamical limit to confirm that these two new magnetic states are not a result of a finite-size effect, where the properties of the double striped-type antiferromagnetic state are also presented.

8 pages, 7 figures

References in corpus (12)

• Magnetic Order versus superconductivity in the Iron-based layered La(O1-xFx)FeAs systems
• Magnetic order in BaFe2As2, the parent compound of the FeAs based superconductors in a new structural family
• First-order magnetic and structural phase transitions in Fe${}_{1+y}$Se${}_x$Te${}_{1-x}$
• Bi-collinear antiferromagnetic order in the tetragonal $\alpha$-FeTe
• Unified Picture for Magnetic Correlations in Iron-Based Superconductors
• Role of backflow correlations for the non-magnetic phase of the t-t' Hubbard model
• Gapless quantum spin liquid, stripe and antiferromagnetic phases in frustrated Hubbard models in two dimensions
• Antiferromagnetic ground state with pair-checkboard order in FeSe
• Magnetism and d-wave superconductivity on the half-filled square lattice with frustration
• Spin-wave excitations and superconducting resonant mode in Cs(x)Fe(2-y)Se2
• Collinear antiferromagnetic state in a two-dimensional Hubbard model at half filling
• Uncovering double-stripe and plaquette antiferromagnetic states in the one-band Hubbard model on a frustrated square lattice