def setLehmannTermsDynamicFermionic(self, dynamicObservable):
for statePair, operatorPair in dynamicObservable.operatorPairs.items():
operator1 = operatorPair[0]
operator2 = operatorPair[1]
if type(operator1) != ndarray:
operator1 = operator1.toarray()
operator2 = operator2.toarray()
e = self.getEnergyEigenvalues()
ve = self.getEnergyEigenstates().toarray()
fockstates = range(self.fockspaceSize)
n_inds_p = array(scatter_list(fockstates))
nominators_p = []
denominators_p = []
for n in n_inds_p:
n_op1 = ve[:,n].dot(operator1)
op2_n = operator2.dot(ve[:,n])
expn = exp(-self.beta*e[n])
for m in fockstates:
if dynamicObservable.species == 'bosonic':
if equals(e[n], e[m]):
continue
el1 = n_op1.dot(ve[:,m])
if not equals(el1, 0):
el2 = ve[:,m].dot(op2_n)
if not equals(el2, 0):
expm = exp(-self.beta*e[m])
el = el1*el2
nominators_p.append([])
nominators_p[-1].append(expn*el)
nominators_p[-1].append(expm*el)
denominators_p.append(e[n]-e[m])
dynamicObservable.lehmannNominators.update({statePair: allgather_list(nominators_p)})
dynamicObservable.lehmannDenominators.update({statePair: allgather_list(denominators_p)})
dynamicObservable.partitionFunction = self.getPartitionFunction()
def setZeroFrequencyTerms(self, dynamicObservable):
for statePair, operatorPair in dynamicObservable.operatorPairs.items():
operator1 = operatorPair[0]
operator2 = operatorPair[1]
if type(operator1) != ndarray:
operator1 = operator1.toarray()
operator2 = operator2.toarray()
e = self.getEnergyEigenvalues()
ve = self.getEnergyEigenstates().toarray()
fockstates = range(self.fockspaceSize)
n_inds_p = array(scatter_list(fockstates))
zeroFrequencyTerms_p = []
for n in n_inds_p:
n_op1 = ve[:,n].dot(operator1)
op2_n = operator2.dot(ve[:,n])
expn = exp(-self.beta*e[n])
for m in fockstates:
if equals(e[n], e[m]):
el1 = n_op1.dot(ve[:,m])
if not equals(el1, 0):
el2 = ve[:,m].dot(op2_n)
if not equals(el2, 0):
el = el1*el2
zeroFrequencyTerms_p.append(-self.beta*expn*el)
dynamicObservable.zeroFrequencyTerms.update({statePair: allgather_list(zeroFrequencyTerms_p)})
def lehmannSumDynamic(elementProducts, energyDifferences, partitionFunction, mesh, zeroFrequencyTerms, imaginaryOffset, nominatorCoefficients):
if type(imaginaryOffset) != list:
imaginaryOffset = [imaginaryOffset]*2
result = dict()
for statePair, nominators, denominators in zip(elementProducts.keys(), elementProducts.values(), energyDifferences.values()):
data_p = list()
for w in scatter_list(mesh):
terms = [coeff * nom/(w + denom + complex(0, offset)) for noms, denom in zip(nominators, denominators) for nom, coeff, offset in zip(noms, nominatorCoefficients, imaginaryOffset)]
if len(zeroFrequencyTerms.values()) > 0 and w == 0:
terms += zeroFrequencyTerms[statePair]
data_p.append(nsum(terms/partitionFunction))
result.update({statePair: array(allgather_list(data_p))})
return result
def setLehmannSumStatic(self, staticObservable):
assert type(staticObservable) == StaticObservable, 'StaticObservable expected.'
e = self.getEnergyEigenvalues()
ve = self.getEnergyEigenstates().toarray()
z = self.getPartitionFunction()
fockstates = range(self.fockspaceSize)
for index, matrix in staticObservable.operators.items():
if type(matrix) != ndarray:
m = matrix.toarray()
else:
m = matrix
n_inds_p = array(scatter_list(fockstates))
terms_p = list()
for n in n_inds_p:
el = ve[:,n].dot(m.dot(ve[:,n]))
expn = exp(-self.beta*e[n])
if not equals(el, 0) and not equals(expn, 0):
terms_p.append(expn * el)
staticObservable.expectationValue.update({index: sumScatteredLists(terms_p)/z})
def solve(self):
report('Solving the Hamiltonian...', self.verbose)
t0 = time()
self.eigenEnergies = list()
self.eigenStates = list()
self.gatherPermutations()
self.matrix = self.transformation.dot(self.matrix).dot(self.transformation.H)
hBlocks = BlockMatrix(self.blocksizes, self.all_real)
rows, cols = self.matrix.nonzero()
for val, i, j in izip(self.matrix.data, rows, cols):
hBlocks[i, j] = val
hBlocks_scat = scatter_list(hBlocks.datablocks)
e_scat = list()
v_scat = list()
for block in hBlocks_scat:
e, v = eigh(block)
e_scat += list(e)
v_scat += list(v)
self.eigenEnergies, self.energyShift = shiftEnergies(diag(self.transformation.H.dot(self.transformation.transpose().dot(diag(allgather_list(e_scat)).transpose()).transpose())).copy()) # scipy hack for A = U^.D.U
#self.eigenEnergies = diag(self.transformation.H.dot(self.transformation.transpose().dot(diag(allgather_list(e_scat)).transpose()).transpose())).copy() # scipy hack for A = U^.D.U
v = allgather_list(v_scat)
self.eigenStates = self.transformation.H.dot(embedV(v, self.blocksizes)).dot(self.transformation)
self.matrix = self.transformation.H.dot(self.matrix).dot(self.transformation)
report('took '+str(time()-t0)[:4]+' seconds', self.verbose)
