Siesta I - Psi-k

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Solving H (diagonalising) Nearsightedness principle Implies localisation: W. Kohn, Phys. Rev. Lett. 76, 3168 (1996) "( r r , r # r ) "( r r # r R ) ' '' % 0 r $ r #%& & && $ 0 r # R r $% Wannier-like unitary transformations of eigenvectors: ! localised basis of occupied space !
Linear-scaling solution ! ! • Search directly for localised quantities: - E BS " occ $ # n = E %( r n [ r , r &)] - by minimising E E BS = E [{ }] " ( r r ) i • Make them strictly local (finite support) (the approximation is here)
Page 1 and 2: Linear-scaling DFT and the SIESTA m
Page 3 and 4: LINEAR SCALING CPU load ~ N 3 Early
Page 5 and 6: Orbital-free linear-scaling DFT •
Page 7 and 8: HARTREE (electrostatics) • SIESTA
Page 9 and 10: SIESTA method Linear-scaling DFT ba
Page 11 and 12: Hard confining potentials A single
Page 13 and 14: Multiple-zeta E. Artacho et al. , P
Page 15 and 16: Linear-scaling matrix-element calcu
Page 17: Eggbox 50 Ry 4.4 Bohr Common to man
Page 21 and 22: Localised solutions R c
Page 23 and 24: Local minima: a way to see it Consi
Page 25 and 26: Kim, Mauri & Galli’s functional M
Page 27 and 28: Other linear-scaling solvers • Di
Page 29 and 30: http://www.uam.es/siesta
Page 31 and 32: Inhibition of cyclin-dependent kina
Page 33 and 34: Candidate material for spintronics
Page 35 and 36: Electronic structure at the LSMO/CN
Page 37 and 38: GGA: LSMO (001) surface. x = 1/3
Page 39 and 40: Acknowledgments Daniel Sanchez-Port

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