Source code for triqs_tprf.analytic_hubbard_atom

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# TRIQS: a Toolbox for Research in Interacting Quantum Systems
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# Copyright (C) 2017 by Hugo U.R. Strand
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import numpy as np

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from pytriqs.gf import *

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from triqs_tprf.ParameterCollection import ParameterCollection

from triqs_tprf.hubbard_atom import chi_ph_magnetic
from triqs_tprf.hubbard_atom import gamma_ph_magnetic
from triqs_tprf.hubbard_atom import single_particle_greens_function

from triqs_tprf.linalg import inverse_PH
from triqs_tprf.chi_from_gg2 import chi0_from_gg2_PH
from triqs_tprf.freq_conv import block_iw_AB_to_matrix_valued

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[docs]def analytic_hubbard_atom(beta, U, nw, nwf, nwf_gf): r""" Compute dynamical response functions for the Hubbard atom at half filling. This function returns an object that contains the single-particle Greens function :math:`G(\omega)`, the magnetic two-particle generalized susceptibility :math:`\chi_m(\omega, \nu, \nu')`, and the corresponding bare bubble :math:`\chi^{(0)}_m(\omega, \nu, \nu')`, and the magnetic vertex function :math:`\Gamma_m(\omega, \nu, \nu')`. This is implemented using analytical formulas from Thunstrom et al. [PRB 98, 235107 (2018)] please cite the paper if you use this function! In particular this is one exact solution to the Bethe-Salpeter equation, that is the infinite matrix inverse problem: .. math:: \Gamma_m = [\chi^{(0)}_m]^{-1} - \chi_m^{-1} Parameters ---------- beta : float Inverse temperature. U : float Hubbard U interaction parameter. nw : int Number of bosonic Matsubara frequencies in the computed two-particle response functions. nwf : int Number of fermionic Matsubara frequencies in the computed two-particle response functions. nwf_gf : int Number of fermionic Matsubara frequencies in the computed single-particle Greens function. Returns ------- p : ParameterCollection Object containing all the response functions and some other observables, `p.G_iw`, `p.chi_m`, `p.chi0_m`, `p.gamma_m`, `p.Z`, `p.m2`, `p.chi_m_static`. """ d = ParameterCollection() d.beta, d.U, d.nw, d.nwf, d.nwf_gf = beta, U, nw, nwf, nwf_gf g_iw = single_particle_greens_function(beta=beta, U=U, nw=nwf_gf) d.G_iw = g_iw # make block gf of the single gf G_iw_block = BlockGf(name_list=['up', 'dn'], block_list=[g_iw, g_iw]) g_mat = block_iw_AB_to_matrix_valued(G_iw_block) d.chi_m = chi_ph_magnetic(beta=beta, U=U, nw=nw, nwf=nwf) d.chi0_m = chi0_from_gg2_PH(g_mat, d.chi_m) # -- Numeric vertex from BSE d.gamma_m_num = inverse_PH(d.chi0_m) - inverse_PH(d.chi_m) # -- Analytic vertex d.gamma_m = gamma_ph_magnetic(beta=beta, U=U, nw=nw, nwf=nwf) # -- Analytic magnetization expecation value # -- and static susceptibility d.Z = 2. + 2*np.exp(-beta * 0.5 * U) d.m2 = 0.25 * (2 / d.Z) d.chi_m_static = 2. * beta * d.m2 d.label = r'Analytic' return d
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