def ccsd(cls, hfwavefunction, hamiltonian, maxiter=100, cutoff=1e-6):
occ = hfwavefunction.occ
Nelec = occ['alpha'] + occ['beta']
C = hfwavefunction.coefficient
dim = hamiltonian.dim * 2
#Transfer Fock integral from spatial to spin basis
fs = spinfock(hfwavefunction.eorbitals)
#Transfer electron repulsion integral from atomic basis
#to molecular basis
hamiltonian.operators['electron_repulsion'].basis_transformation(C)
#build double bar integral <ij||kl>
spinints = hamiltonian.operators['electron_repulsion'].double_bar
ts, td, Dai, Dabij = initialize(fs, spinints, Nelec, dim)
ECCSD = 0
DECC = 1.0
Iter = 0
log.hline()
log('{0:2s} {1:3s} {2:4s}'.format('Iter', 'ECC', 'Delta'))
log.hline()
while DECC > cutoff or Iter > maxiter: # arbitrary convergence criteria
Iter += 1
OLDCC = ECCSD
Fae, Fmi, Fme, Wmnij, Wabef, Wmbej = updateintermediates(
True, Nelec, dim, fs, spinints, ts, td)
ts = makeT1(True, Nelec, dim, fs, spinints, ts, td, Dai, Fae, Fmi,
Fme)
td = makeT2(True, Nelec, dim, fs, spinints, ts, td, Dabij, Fae,
Fmi, Fme, Wmnij, Wabef, Wmbej)
ECCSD = ccsdenergy(Nelec, dim, fs, spinints, ts, td)
DECC = abs(ECCSD - OLDCC)
log('{0:2d} {1:3f} {2:4f}'.format(Iter, ECCSD, DECC))
print('CC iterations converged')
print("E(corr,CCSD) = ", ECCSD)
def hf(cls,hamiltonian,occ,maxiter=100,cutoff=1e-6):
Norb = hamiltonian.dim
#Form the core Hamiltonian
Hcore = hamiltonian.operators['kinetic'].value + hamiltonian.operators['nuclear_attraction'].value
#Build the orthogonalization matrix
X = orthogonalization_matrix(hamiltonian.operators['overlap'].value)
#Initial guess of density matrix
if occ['alpha']==occ['beta']:
D = np.zeros((Norb,Norb))
else:
D = {'alpha':np.zeros((Norb,Norb)),'beta':np.zeros((Norb,Norb))}
#iteration section
Iter = 0
RMS = 1.0
log.hline()
log('{0:2s} {1:3s} {2:4s} {3:5s}'.format('Iter', 'E(elec)', 'E(tot)','RMS'))
log.hline()
while RMS > cutoff and Iter < maxiter:
Iter += 1
G = G_matrix(D,hamiltonian.operators['electron_repulsion'].value,Norb)
F = F_matrix(Hcore,G,Norb)
eorbitals,C = C_matrix(F,X,Norb)
OLDD = D
D = D_matrix(C,Norb,occ)
RMS = deltap(D,OLDD,Norb)
Eelec = energy(D,Hcore,F,Norb)
Etot = Eelec + hamiltonian.operators['nuclear_repulsion'].value
log('{0:2d} {1:3f} {2:4f} {3:5f}'.format(Iter, Eelec, Etot, RMS))
return HFWaveFunction(Norb,occ,C,D,F,eorbitals,Eelec,Etot)
def kernel(self):
"""Kernel of the solver.
Returns
-------
results : dict
CCSD calculation results.
"""
log.hline()
log('CCSD Section'.format())
log.hline()
ham = copy.deepcopy(self.ham)
wfn = copy.deepcopy(self.wfn)
hf_results = self.hf_results
occ = wfn.occ
Nelec = occ['alpha'] + occ['beta']
C = wfn.coefficients
nspin = ham.nspin
#Transfer Fock integral from spatial to spin basis
fs = spinfock(hf_results['orbital_energies'])
#Transfer electron repulsion integral from atomic basis
#to molecular basis
ham.operators['electron_repulsion'].basis_transformation(C)
#build double bar integral <ij||kl>
spinints = ham.operators['electron_repulsion'].double_bar
ts, td, Dai, Dabij = initialize(fs, spinints, Nelec, nspin)
ECCSD = 0
DECC = 1.0
Iter = 0
log.hline()
log('{0:2s} {1:3s} {2:4s}'.format('Iter', 'ECC', 'Delta'))
log.hline()
while DECC > self.E_conv or Iter > self.maxiter: # arbitrary convergence criteria
Iter += 1
OLDCC = ECCSD
Fae, Fmi, Fme, Wmnij, Wabef, Wmbej = updateintermediates(
True, Nelec, nspin, fs, spinints, ts, td)
ts = makeT1(True, Nelec, nspin, fs, spinints, ts, td, Dai, Fae,
Fmi, Fme)
td = makeT2(True, Nelec, nspin, fs, spinints, ts, td, Dabij, Fae,
Fmi, Fme, Wmnij, Wabef, Wmbej)
ECCSD = ccsdenergy(Nelec, nspin, fs, spinints, ts, td)
DECC = abs(ECCSD - OLDCC)
log('{0:2d} {1:3f} {2:4f}'.format(Iter, ECCSD, DECC))
log.hline()
log('CCSD Energy = {}'.format(ECCSD))
log('Total Energy = {}'.format(hf_results['total_energy'] + ECCSD))
log.hline()
results = {
"success": True,
"CCSD_energy": ECCSD,
"total_energy": hf_results['total_energy'] + ECCSD
}
return results
def kernel(self):
"""Kernel of the solver.
Returns
-------
results : dict
MP2 calculation results.
"""
log.hline()
log('MP2 calculation section'.format())
log.hline()
ham = copy.deepcopy(self.ham)
wfn = copy.deepcopy(self.wfn)
hf_results = self.hf_results
nspatial = ham.nspatial
occ = wfn.occ
C = wfn.coefficients
eorbitals = hf_results['orbital_energies']
Emp2 = 0.0
if isinstance(ham, RestrictedChemicalHamiltonian):
ham.operators['electron_repulsion'].basis_transformation(C)
Eri = ham.operators['electron_repulsion'].integral
for i in range(occ['alpha']):
for j in range(occ['alpha']):
for a in range(occ['alpha'], nspatial):
for b in range(occ['alpha'], nspatial):
Emp2 += Eri[i,a,j,b]*(2*Eri[i,a,j,b]-Eri[i,b,j,a])\
/(eorbitals[i] + eorbitals[j] -eorbitals[a] - eorbitals[b])
log.hline()
log('MP2 Results'.format())
log.hline()
log('{0:2s} {1:3f}'.format('Escf', hf_results['total_energy']))
log('{0:2s} {1:3f}'.format('Emp2', Emp2))
log('{0:2s} {1:3f}'.format('Etot', hf_results['total_energy'] + Emp2))
log.hline()
results = {
"success": True,
"MP2_energy": Emp2,
"total_energy": hf_results['total_energy'] + Emp2
}
return results
def mp2(cls,hfwavefunction,hamiltonian):
occ = hfwavefunction.occ
C = hfwavefunction.coefficient
eorbitals = hfwavefunction.eorbitals
Emp2 = 0.0
if occ['alpha'] == occ['beta']:
Eri = hamiltonian.operators['electron_repulsion'].basis_transformation(C)
for i in range(occ['alpha']):
for j in range(occ['alpha']):
for a in range(occ['alpha'],hamiltonian.dim):
for b in range(occ['alpha'],hamiltonian.dim):
Emp2 += Eri[i,a,j,b]*(2*Eri[i,a,j,b]-Eri[i,b,j,a])/(eorbitals[i] + eorbitals[j] -eorbitals[a] - eorbitals[b])
elif occ['alpha'] != occ['beta']:
for spin in C:
Eri = hamiltonian.operators['electron_repulsion'].basis_transformation(C[spin])
for i in range(occ[spin]):
for j in range(occ[spin]):
for a in range(occ[spin],hamiltonian.dim):
for b in range(occ[spin],hamiltonian.dim):
Emp2 += Eri[i,a,j,b]*(Eri[i,a,j,b]-0.5*Eri[i,b,j,a])/(eorbitals[spin][i] + eorbitals[spin][j] -eorbitals[spin][a] - eorbitals[spin][b])
log.hline()
log('{0:2s} {1:3f}'.format('Escf', hfwavefunction.Etot))
log('{0:2s} {1:3f}'.format('Emp2', Emp2))
log('{0:2s} {1:3f}'.format('Etot', hfwavefunction.Etot+Emp2))
log.hline()
return Emp2
def kernel(self):
"""Kernel of the solver.
Returns
-------
results : dict
CISD calculation results.
"""
log.hline()
log('CISD Section'.format())
log.hline()
ham = copy.deepcopy(self.ham)
wfn = copy.deepcopy(self.wfn)
hf_results = self.hf_results
nelec = wfn.nelec
nspatial = wfn.nspatial
ci_basis = copy.deepcopy(CIBasisSet(wfn, [0, 1, 2]))
H = RestrictedCIHamiltonian(ham, wfn, ci_basis)
ci_matrix = H.generate_matrix(ci_basis)
e_ci, vec_ci = np.linalg.eigh(ci_matrix)
E_ci_elec = e_ci[0]
E_hf_elec = hf_results['electronic_energy']
E_corr = E_ci_elec - E_hf_elec
E_ci_tot = E_ci_elec + ham.operators['nuclear_repulsion'].integral
#Build the ci wavefunction.
ci_wfn = CIWaveFunction(nelec, nspatial, {}, ci_basis, vec_ci[0])
log.hline()
log('CISD Results')
log.hline()
log('CISD Correlation energy = {}'.format(E_corr))
log('Total energy = {}'.format(E_ci_tot))
log.hline()
results = {"total_energy": E_ci_tot}
return results, ci_wfn
def kernel(self):
"""Kernel of the solver.
Returns
-------
results : dict
Full CI calculation results.
"""
log.hline()
log('Full CI Section'.format())
log.hline()
ham = copy.deepcopy(self.ham)
wfn = copy.deepcopy(self.wfn)
hf_results = self.hf_results
occ = wfn.occ['alpha'] + wfn.occ['beta']
vir = wfn.nspin - occ
excitation_level = list(range(min(occ, vir) + 1))
ci_basis = CIBasisSet(wfn, excitation_level)
H = RestrictedCIHamiltonian(ham, wfn, ci_basis)
ci_matrix = H.generate_matrix(ci_basis)
e_ci, vec_ci = np.linalg.eigh(ci_matrix)
E_ci_elec = e_ci[0]
E_hf_elec = hf_results['electronic_energy']
E_corr = E_ci_elec - E_hf_elec
E_ci_tot = E_ci_elec + ham.operators['nuclear_repulsion'].integral
log.hline()
log('Results'.format())
log.hline()
log('Full CI Correlation energy = {}'.format(E_corr))
log('Total energy = {}'.format(E_ci_tot))
log.hline()
results = {"total_energy": E_ci_tot}
return results
def kernel(self):
"""Kernel of the solver.
Returns
-------
results : dict
MP3 calculation results.
"""
log.hline()
log('MP3 Calculation Section'.format())
log.hline()
ham = copy.deepcopy(self.ham)
wfn = copy.deepcopy(self.wfn)
hf_results = self.hf_results
nspatial = ham.nspatial
occ = wfn.occ
C = wfn.coefficients
eorbitals = hf_results['orbital_energies']
Emp2 = 0.0
ham.operators['electron_repulsion'].basis_transformation(C)
Eri = ham.operators['electron_repulsion'].integral
for i in range(occ['alpha']):
for j in range(occ['alpha']):
for a in range(occ['alpha'], nspatial):
for b in range(occ['alpha'], nspatial):
Emp2 += Eri[i,a,j,b]*(2*Eri[i,a,j,b]-Eri[i,b,j,a])\
/(eorbitals[i] + eorbitals[j] -eorbitals[a] - eorbitals[b])
Emp3 = 0.0
Eri = ham.operators['electron_repulsion'].double_bar
for i in range(occ['alpha']):
for j in range(occ['alpha']):
for k in range(occ['alpha']):
for l in range(occ['alpha']):
for a in range(occ['alpha'], nspatial):
for b in range(occ['alpha'], nspatial):
Emp3 += (1/8.0)*Eri[i,j,a,b]*Eri[k,l,i,j]*Eri[a,b,k,l]\
/((eorbitals[i] + eorbitals[j] -eorbitals[a] - eorbitals[b])\
*(eorbitals[k] + eorbitals[l] -eorbitals[a] - eorbitals[b]))
for i in range(occ['alpha']):
for j in range(occ['alpha']):
for a in range(occ['alpha'], nspatial):
for b in range(occ['alpha'], nspatial):
for c in range(occ['alpha'], nspatial):
for d in range(occ['alpha'], nspatial):
Emp3 += (1/8.0)*Eri[i,j,a,b]*Eri[a,b,c,d]*Eri[c,d,i,j]\
/((eorbitals[i] + eorbitals[j] -eorbitals[a] - eorbitals[b])\
*(eorbitals[i] + eorbitals[j] -eorbitals[c] - eorbitals[d]))
for i in range(occ['alpha']):
for j in range(occ['alpha']):
for k in range(occ['alpha']):
for a in range(occ['alpha'], nspatial):
for b in range(occ['alpha'], nspatial):
for c in range(occ['alpha'], nspatial):
Emp3 += Eri[i,j,a,b]*Eri[k,b,c,j]*Eri[a,c,i,k]\
/((eorbitals[i] + eorbitals[j] -eorbitals[a] - eorbitals[b])\
*(eorbitals[i] + eorbitals[k] -eorbitals[c] - eorbitals[c]))
log.hline()
log('MP3 Results'.format())
log.hline()
log('{0:2s} {1:3f}'.format('Escf', hf_results['total_energy']))
log('{0:2s} {1:3f}'.format('Emp2', Emp2))
log('{0:2s} {1:3f}'.format('Emp3', Emp3))
log('{0:2s} {1:3f}'.format('Etot',
hf_results['total_energy'] + Emp2 + Emp3))
log.hline()
results = {
"success": True,
"MP2_energy": Emp2,
"MP3_energy": Emp3,
"total_energy": hf_results['total_energy'] + Emp2 + Emp3
}
return results
def kernel(self):
"""Kernel of the solver.
Returns
-------
results : dict
Hartree Fock calculation results.
"""
log.hline()
log('SCF Calculation Section'.format())
log.hline()
# Set defaults
ham = self.ham
occ = self.wfn.occ
Norb = ham.nspatial
maxiter = self.maxiter
E_conv = self.E_conv
D_conv = self.D_conv
#Form the core Hamiltonian
Hcore = ham.operators['kinetic'].integral + ham.operators[
'nuclear_attraction'].integral
#Build the orthogonalization matrix
X = orthogonalization_matrix(ham.operators['overlap'].integral)
#Initial guess of density matrix
D = np.zeros((Norb, Norb))
#iteration section
Enuc = ham.operators['nuclear_repulsion'].integral
RMS = 1.0
Eold = 0.0
log.hline()
log('{0:2s}\t {1:3s}\t {2:4s}\t\t {3:5s}'.format(
'Iter', 'E(elec)', 'dE', 'dRMS'))
log.hline()
for Iter in range(1, maxiter + 1):
Iter += 1
G = G_matrix(D, ham.operators['electron_repulsion'].integral, Norb)
F = F_matrix(Hcore, G, Norb)
Eorbs, C = C_matrix(F, X, Norb)
OLDD = D
D = D_matrix(C, Norb, occ)
dRMS = deltap(D, OLDD, Norb)
Eelec = energy(D, Hcore, F, Norb)
log('{0:2d}\t {1:3f}\t {2:4f}\t {3:5f}'.format(
Iter, Eelec, Eelec - Eold, dRMS))
if (abs(Eelec - Eold) < E_conv) and (dRMS < D_conv):
break
Eold = Eelec
if Iter == maxiter:
raise Exception("Maximum number of SCF cycles exceeded.")
log.hline()
log('SCF Results'.format())
log.hline()
log('Electronic Energy = {}'.format(Eelec))
log('Nuclear Energy = {}'.format(Enuc))
log('Total Energy = {}'.format(Eelec + Enuc))
log.hline()
self.wfn.assign_coefficients(C)
results = {
"success": True,
"electronic_energy": Eelec,
"nuclear_energy": Enuc,
"total_energy": Eelec + Enuc,
"orbital_energies": Eorbs
}
return results
def kernel(self):
"""Kernel of the solver.
Returns
-------
results : dict
Hartree Fock calculation results.
"""
log.hline()
log('SCF DIIS Calculation Section'.format())
log.hline()
# Set defaults
ham = self.ham
wfn = self.wfn
maxiter = self.maxiter
E_conv = self.E_conv
D_conv = self.D_conv
# Overlap Integral
S = ham.operators['overlap'].integral
# Get occ nbf and ndocc for closed shell molecules
occ = wfn.occ
nspatial = ham.nspatial
ndocc = wfn.occ['alpha']
# Compute required quantities for SCF
V = ham.operators['nuclear_attraction'].integral
T = ham.operators['kinetic'].integral
I = ham.operators['electron_repulsion'].integral
# Build H_core
H = T + V
# Orthogonalizer A = S^(-1/2)
A = np.array(ham.operators['overlap'].integral)
A = orthogonalization_matrix(A, type='symmetric')
# Calculate initial core guess: [Szabo:1996] pp. 145
Hp = A.dot(H).dot(A) # Eqn. 3.177
e, C2 = np.linalg.eigh(Hp) # Solving Eqn. 1.178
C = A.dot(C2) # Back transform, Eqn. 3.174
Cocc = C[:, :ndocc]
D = D_matrix(C, nspatial, occ)
E = 0.0
Enuc = ham.operators['nuclear_repulsion'].integral
Eold = 0.0
Fock_list = []
DIIS_error = []
log.hline()
log('{0:2s}\t {1:3s}\t {2:4s}\t\t {3:5s}'.format(
'Iter', 'E(elec)', 'dE', 'dRMS'))
log.hline()
for Iter in range(1, maxiter + 1):
# Build fock matrix
J = np.einsum('pqrs,rs->pq', I, D)
K = np.einsum('prqs,rs->pq', I, D)
F = H + J * 2 - K
# DIIS error build w/ HF analytic gradient ([Pulay:1969:197])
diis_e = np.einsum('ij,jk,kl->il', F, D, S) - np.einsum(
'ij,jk,kl->il', S, D, F)
diis_e = A.dot(diis_e).dot(A)
Fock_list.append(F)
DIIS_error.append(diis_e)
dRMS = np.mean(diis_e**2)**0.5
# SCF energy and update: [Szabo:1996], Eqn. 3.184, pp. 150
Eelec = np.einsum('pq,pq->', F + H, D)
log('{0:2d}\t {1:3f}\t {2:4f}\t {3:5f}'.format(
Iter, Eelec, Eelec - Eold, dRMS))
if (abs(Eelec - Eold) < E_conv) and (dRMS < D_conv):
break
Eold = Eelec
if Iter >= 2:
# Limit size of DIIS vector
diis_count = len(Fock_list)
if diis_count > 6:
# Remove oldest vector
del Fock_list[0]
del DIIS_error[0]
diis_count -= 1
# Build error matrix B, [Pulay:1980:393], Eqn. 6, LHS
B = np.empty((diis_count + 1, diis_count + 1))
B[-1, :] = -1
B[:, -1] = -1
B[-1, -1] = 0
for num1, e1 in enumerate(DIIS_error):
for num2, e2 in enumerate(DIIS_error):
if num2 > num1: continue
val = np.einsum('ij,ij->', e1, e2)
B[num1, num2] = val
B[num2, num1] = val
# normalize
B[:-1, :-1] /= np.abs(B[:-1, :-1]).max()
# Build residual vector, [Pulay:1980:393], Eqn. 6, RHS
resid = np.zeros(diis_count + 1)
resid[-1] = -1
# Solve Pulay equations, [Pulay:1980:393], Eqn. 6
ci = np.linalg.solve(B, resid)
# Calculate new fock matrix as linear
# combination of previous fock matrices
F = np.zeros_like(F)
for num, c in enumerate(ci[:-1]):
F += c * Fock_list[num]
# Diagonalize Fock matrix
Fp = A.dot(F).dot(A)
Eorbs, C2 = np.linalg.eigh(Fp)
C = A.dot(C2)
Cocc = C[:, :ndocc]
D = np.einsum('pi,qi->pq', Cocc, Cocc)
if Iter == maxiter:
raise Exception("Maximum number of SCF cycles exceeded.")
log.hline()
log('SCF Results'.format())
log.hline()
log('Electronic Energy = {}'.format(Eelec))
log('Nuclear Energy = {}'.format(Enuc))
log('Total Energy = {}'.format(Eelec + Enuc))
log.hline()
self.wfn.assign_coefficients(C)
results = {
"success": True,
"electronic_energy": Eelec,
"nuclear_energy": Enuc,
"total_energy": Eelec + Enuc,
"orbital_energies": Eorbs
}
return results
