Source code for pyscf.pbc.dft.krkspu

#!/usr/bin/env python
# Copyright 2014-2025 The PySCF Developers. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
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# Authors: Zhi-Hao Cui <zhcui0408@gmail.com>
#

"""
Restricted DFT+U with kpoint sampling.
Based on KRHF routine.

Refs: PRB, 1998, 57, 1505.
"""

import numpy as np
import scipy.linalg as la

from pyscf import lib
from pyscf.lib import logger
from pyscf import __config__
from pyscf.pbc.dft import krks
from pyscf.data.nist import HARTREE2EV
from pyscf import lo
from pyscf.pbc import gto as pgto
from pyscf.dft.rkspu import _set_U, reference_mol

[docs] def get_veff(ks, cell=None, dm=None, dm_last=0, vhf_last=0, hermi=1, kpts=None, kpts_band=None): """ Coulomb + XC functional + Hubbard U terms. .. note:: This is a replica of pyscf.dft.rks.get_veff with kpts added. This function will change the ks object. Args: ks : an instance of :class:`RKS` XC functional are controlled by ks.xc attribute. Attribute ks.grids might be initialized. dm : ndarray or list of ndarrays A density matrix or a list of density matrices Returns: Veff : ``(nkpts, nao, nao)`` or ``(*, nkpts, nao, nao)`` ndarray Veff = J + Vxc + V_U. """ if cell is None: cell = ks.cell if dm is None: dm = ks.make_rdm1() if kpts is None: kpts = ks.kpts # J + V_xc vxc = krks.get_veff(ks, cell, dm, dm_last=dm_last, vhf_last=vhf_last, hermi=hermi, kpts=kpts, kpts_band=kpts_band) vxc = _add_Vhubbard(vxc, ks, dm, kpts) return vxc
def _add_Vhubbard(vxc, ks, dm, kpts): '''Add Hubbard U to Vxc matrix inplace. ''' cell = ks.cell pcell = reference_mol(cell, ks.minao_ref) is_ibz = hasattr(kpts, "kpts_ibz") kpts_input = kpts if is_ibz: kpts = kpts.kpts_ibz kpts = kpts.reshape(-1, 3) nkpts = len(kpts) ovlp = cell.pbc_intor('int1e_ovlp', hermi=1, kpts=kpts) U_idx, U_val, U_lab = _set_U(cell, pcell, ks.U_idx, ks.U_val) if ks.C_ao_lo is None: C_ao_lo = _make_minao_lo(cell, pcell, kpts) else: C_ao_lo = ks.C_ao_lo alphas = ks.alpha if not hasattr(alphas, '__len__'): # not a list or tuple alphas = [alphas] * len(U_idx) E_U = 0.0 weight = getattr(kpts_input, "weights_ibz", np.repeat(1.0/nkpts, nkpts)) logger.info(ks, "-" * 79) lab_string = " " with np.printoptions(precision=5, suppress=True, linewidth=1000): for idx, val, lab, alpha in zip(U_idx, U_val, U_lab, alphas): if ks.verbose >= logger.INFO: lab_string = " " for l in lab: lab_string += "%9s" %(l.split()[-1]) lab_sp = lab[0].split() logger.info(ks, "local rdm1 of atom %s: ", " ".join(lab_sp[:2]) + " " + lab_sp[2][:2]) P_loc = [] for k in range(nkpts): C_loc = C_ao_lo[k][:,idx] SC = np.dot(ovlp[k], C_loc) # ~ C^{-1} P_k = SC.conj().T.dot(dm[k]).dot(SC) E_U += weight[k] * (val * 0.5) * (P_k.trace() - np.dot(P_k, P_k).trace() * 0.5) loc_sites = P_k.shape[-1] vhub_loc = (np.eye(loc_sites) - P_k) * (val * 0.5) if alpha is not None: # The alpha perturbation is only applied to the linear term of # the local density. E_U += weight[k] * alpha * P_k.trace() vhub_loc += np.eye(loc_sites) * alpha vhub_loc = SC.dot(vhub_loc).dot(SC.conj().T) if vxc[k].dtype == np.float64: vhub_loc = vhub_loc.real vxc[k] += vhub_loc P_loc.append(P_k) if ks.verbose >= logger.INFO: if is_ibz: # FIXME: P_loc is represented in the reference AO basis. # The dm_at_ref_cell function can only transform the density # matrices for cell. # sym_kpts_obj.dm_at_ref_cell(P_loc) pass else: P_loc = sum(P_loc).real / nkpts logger.info(ks, "%s\n%s", lab_string, P_loc) logger.info(ks, "-" * 79) if E_U.real < 0.0 and all(np.asarray(U_val) > 0): logger.warn(ks, "E_U (%g) is negative...", E_U.real) vxc = lib.tag_array(vxc, E_U=E_U) return vxc
[docs] def energy_elec(ks, dm_kpts=None, h1e_kpts=None, vhf=None): """ Electronic energy for KRKSpU. """ if h1e_kpts is None: h1e_kpts = ks.get_hcore(ks.cell, ks.kpts) if dm_kpts is None: dm_kpts = ks.make_rdm1() if vhf is None or getattr(vhf, 'ecoul', None) is None: vhf = ks.get_veff(ks.cell, dm_kpts) weight = getattr(ks.kpts, "weights_ibz", np.array([1.0/len(h1e_kpts),]*len(h1e_kpts))) e1 = np.einsum('k,kij,kji', weight, h1e_kpts, dm_kpts) tot_e = e1 + vhf.ecoul + vhf.exc + vhf.E_U ks.scf_summary['e1'] = e1.real ks.scf_summary['coul'] = vhf.ecoul.real ks.scf_summary['exc'] = vhf.exc.real ks.scf_summary['E_U'] = vhf.E_U.real logger.debug(ks, 'E1 = %s Ecoul = %s Exc = %s EU = %s', e1, vhf.ecoul, vhf.exc, vhf.E_U) return tot_e.real, vhf.ecoul + vhf.exc + vhf.E_U
def _make_minao_lo(cell, minao_ref='minao', kpts=None): ''' Construct orthogonal minao local orbitals. ''' assert kpts is not None if isinstance(minao_ref, str): pcell = reference_mol(cell, minao_ref) else: pcell = minao_ref ovlp = cell.pbc_intor('int1e_ovlp', hermi=1, kpts=kpts) s12 = pgto.cell.intor_cross('int1e_ovlp', cell, pcell, kpts=kpts) C_minao = [] for k, S_k in enumerate(ovlp): s1cd = la.cho_factor(S_k) C = la.cho_solve(s1cd, s12[k]) C_minao.append(lo.vec_lowdin(C, S_k)) return C_minao
[docs] class KRKSpU(krks.KRKS): """ RKSpU class adapted for PBCs with k-point sampling. """ _keys = {"U_idx", "U_val", "C_ao_lo", "U_lab", 'minao_ref', 'alpha'} get_veff = get_veff energy_elec = energy_elec to_hf = lib.invalid_method('to_hf') def __init__(self, cell, kpts=np.zeros((1,3)), xc='LDA,VWN', exxdiv=getattr(__config__, 'pbc_scf_SCF_exxdiv', 'ewald'), U_idx=[], U_val=[], C_ao_lo=None, minao_ref='MINAO', **kwargs): """ DFT+U args: U_idx: can be list of list: each sublist is a set indices for AO orbitals (indcies corresponding to the large-basis-set mol). list of string: each string is one kind of LO orbitals, e.g. ['Ni 3d', '1 O 2pz']. or a combination of these two. U_val: a list of effective U [in eV], i.e. U-J in Dudarev's DFT+U. each U corresponds to one kind of LO orbitals, should have the same length as U_idx. C_ao_lo: LO coefficients, can be np.array, shape ((spin,), nkpts, nao, nlo), minao_ref: reference for minao orbitals, default is 'MINAO'. Attributes: U_idx: same as the input. U_val: effectiv U-J [in eV] C_ao_lo: (np.ndarray) Custom local orbitals. alpha: the perturbation [in eV] used to compute U in LR-cDFT. Refs: Cococcioni and de Gironcoli, PRB 71, 035105 (2005) """ super(self.__class__, self).__init__(cell, kpts, xc=xc, exxdiv=exxdiv, **kwargs) self.U_idx = U_idx self.U_val = U_val if isinstance(C_ao_lo, str): assert C_ao_lo.upper() == 'MINAO' C_ao_lo = None # API backward compatibility self.C_ao_lo = C_ao_lo self.minao_ref = minao_ref # The perturbation (eV) used to compute U in LR-cDFT. self.alpha = None
[docs] def dump_flags(self, verbose=None): super().dump_flags(verbose) log = logger.new_logger(self, verbose) if log.verbose >= logger.INFO: from pyscf.dft.rkspu import _print_U_info _print_U_info(self, log) return self
[docs] def Gradients(self): from pyscf.pbc.grad.krkspu import Gradients return Gradients(self)
[docs] def nuc_grad_method(self): return self.Gradients()
[docs] def linear_response_u(mf_plus_u, alphalist=(0.02, 0.05, 0.08)): ''' Refs: [1] M. Cococcioni and S. de Gironcoli, Phys. Rev. B 71, 035105 (2005) [2] H. J. Kulik, M. Cococcioni, D. A. Scherlis, and N. Marzari, Phys. Rev. Lett. 97, 103001 (2006) [3] Heather J. Kulik, J. Chem. Phys. 142, 240901 (2015) [4] https://hjkgrp.mit.edu/tutorials/2011-05-31-calculating-hubbard-u/ [5] https://hjkgrp.mit.edu/tutorials/2011-06-28-hubbard-u-multiple-sites/ Args: alphalist : alpha parameters (in eV) are the displacements for the linear response calculations. For each alpha in this list, the DFT+U with U=u0+alpha, U=u0-alpha are evaluated. u0 is the U value from the reference mf_plus_u object, which will be treated as a standard DFT functional. ''' is_ibz = hasattr(mf_plus_u.kpts, "kpts_ibz") if is_ibz: raise NotImplementedError assert isinstance(mf_plus_u, KRKSpU) assert len(mf_plus_u.U_idx) > 0 if not mf_plus_u.converged: mf_plus_u.run() assert mf_plus_u.converged # The bare density matrix without adding U bare_dm = mf_plus_u.make_rdm1() mf = mf_plus_u.copy() log = logger.new_logger(mf) alphalist = np.asarray(alphalist) alphalist = np.append(-alphalist[::-1], alphalist) kpts = mf.kpts.reshape(-1, 3) nkpts = len(kpts) cell = mf.cell ovlp = cell.pbc_intor('int1e_ovlp', hermi=1, kpts=kpts) pcell = reference_mol(cell, mf.minao_ref) U_idx, U_val, U_lab = _set_U(cell, pcell, mf.U_idx, mf.U_val) if mf.C_ao_lo is None: C_ao_lo = _make_minao_lo(cell, pcell, kpts) else: C_ao_lo = mf.C_ao_lo C_inv = [[C_k[:,local_idx].conj().T.dot(S_k) for C_k, S_k in zip(C_ao_lo, ovlp)] for local_idx in U_idx] bare_occupancies = [] final_occupancies = [] for alpha in alphalist: # All in atomic unit mf.alpha = alpha / HARTREE2EV mf.kernel(dm0=bare_dm) local_occ = 0 for c in C_inv: C_on_site = [c[k].dot(mf.mo_coeff[k]) for k in range(nkpts)] rdm1_lo = mf.make_rdm1(C_on_site, mf.mo_occ) local_occ += sum(x.trace().real for x in rdm1_lo) local_occ /= nkpts final_occupancies.append(local_occ) # The first iteration of SCF fock = mf.get_fock(dm=bare_dm) e, mo = mf.eig(fock, ovlp) local_occ = 0 for c in C_inv: C_on_site = [c[k].dot(mo[k]) for k in range(nkpts)] rdm1_lo = mf.make_rdm1(C_on_site, mf.mo_occ) local_occ += sum(x.trace().real for x in rdm1_lo) local_occ /= nkpts bare_occupancies.append(local_occ) log.info('alpha=%f bare_occ=%g final_occ=%g', alpha, bare_occupancies[-1], final_occupancies[-1]) chi0, occ0 = np.polyfit(alphalist, bare_occupancies, deg=1) chif, occf = np.polyfit(alphalist, final_occupancies, deg=1) log.info('Line fitting chi0 = %f x + %f', chi0, occ0) log.info('Line fitting chif = %f x + %f', chif, occf) Uresp = 1./chi0 - 1./chif log.note('Uresp = %f, chi0 = %f, chif = %f', Uresp, chi0, chif) return Uresp