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ProjectedHamiltonian.py
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import FEM
import math
import scipy as np
import sys
#
# Fem Functional : most imp function in this code
#
class ProjectedHamiltonian:
def __init__(self,
fem,
rankVeff,
rankTuckerBasis,
sigma,
tuckerDecomposedVeff,
bases):
self.fem = fem
self.rankVeff = rankVeff
self.rankTuckerBasis = rankTuckerBasis
self.sigma = sigma
self.umat = tuckerDecomposedVeff[0]
self.vmat = tuckerDecomposedVeff[1]
self.wmat = tuckerDecomposedVeff[2]
#compute quadPointValues for the basis Functions
(self.basisXQuadValues,self.basisDXQuadValues) = fem.computeFieldsAtAllQuadPoints(bases[0])
(self.basisYQuadValues,self.basisDYQuadValues) = fem.computeFieldsAtAllQuadPoints(bases[1])
(self.basisZQuadValues,self.basisDZQuadValues) = fem.computeFieldsAtAllQuadPoints(bases[2])
#
#
#
def computeOverlapKineticTuckerBasis(self):
fem = self.fem
rankTuckerBasis = self.rankTuckerBasis
#
# do some initializations
#
MatX = np.zeros((rankTuckerBasis,rankTuckerBasis))
MatY = MatX.copy()
MatZ = MatY.copy()
MatDX = MatX.copy()
MatDY = MatY.copy()
MatDZ = MatZ.copy()
#
#evaluate the requisite integrals
#
for I in range(0,rankTuckerBasis):
fieldxI = self.basisXQuadValues[I,:]
fieldDxI = self.basisDXQuadValues[I,:]
fieldyI = self.basisYQuadValues[I,:]
fieldDyI = self.basisDYQuadValues[I,:]
fieldzI = self.basisZQuadValues[I,:]
fieldDzI = self.basisDZQuadValues[I,:]
for J in range(0,rankTuckerBasis):
if(I <= J):
fieldxJ = self.basisXQuadValues[J,:]
fieldDxJ = self.basisDXQuadValues[J,:]
fieldyJ = self.basisYQuadValues[J,:]
fieldDyJ = self.basisDYQuadValues[J,:]
fieldzJ = self.basisZQuadValues[J,:]
fieldDzJ = self.basisDZQuadValues[J,:]
MatX[I,J] = fem.getIntegral1D(fieldxI*fieldxJ)
MatDX[I,J] = fem.getInvIntegral1D(fieldDxI*fieldDxJ)
MatY[I,J] = fem.getIntegral1D(fieldyI*fieldyJ)
MatDY[I,J] = fem.getInvIntegral1D(fieldDyI*fieldDyJ)
MatZ[I,J] = fem.getIntegral1D(fieldzI*fieldzJ)
MatDZ[I,J] = fem.getInvIntegral1D(fieldDzI*fieldDzJ)
else:
MatX[I,J] = MatX[J,I]
MatY[I,J] = MatY[J,I]
MatZ[I,J] = MatZ[J,I]
MatDX[I,J] = MatDX[J,I]
MatDY[I,J] = MatDY[J,I]
MatDZ[I,J] = MatDZ[J,I]
return (MatX,MatY,MatZ,MatDX,MatDY,MatDZ)
#
#
#
def computeOverlapPotentialTuckerBasis(self):
fem = self.fem
rankTuckerBasis = self.rankTuckerBasis
rankVeff = self.rankVeff
#
# do some initializations
#
MatPotX = np.zeros((rankVeff,rankTuckerBasis,rankTuckerBasis))
MatPotY = MatPotX.copy()
MatPotZ = MatPotY.copy()
#
#evaluate the requisite integrals
#
for irank in range(0,rankVeff):
potentialTuckerx = self.umat[:,irank]
potentialTuckery = self.vmat[:,irank]
potentialTuckerz = self.wmat[:,irank]
for I in range(0,rankTuckerBasis):
fieldxI = self.basisXQuadValues[I,:]
fieldyI = self.basisYQuadValues[I,:]
fieldzI = self.basisZQuadValues[I,:]
for J in range(0,rankTuckerBasis):
if(I <= J):
fieldxJ = self.basisXQuadValues[J,:]
fieldyJ = self.basisYQuadValues[J,:]
fieldzJ = self.basisZQuadValues[J,:]
MatPotX[irank,I,J] = fem.getIntegral1D(potentialTuckerx*fieldxI*fieldxJ)
MatPotY[irank,I,J] = fem.getIntegral1D(potentialTuckery*fieldyI*fieldyJ)
MatPotZ[irank,I,J]= fem.getIntegral1D(potentialTuckerz*fieldzI*fieldzJ)
else:
MatPotX[irank,I,J] = MatPotX[irank,J,I]
MatPotY[irank,I,J] = MatPotY[irank,J,I]
MatPotZ[irank,I,J] = MatPotZ[irank,J,I]
return (MatPotX,MatPotY,MatPotZ)