def get_udxc(voccs, weight=None, totkp=1):
"""Get up/down densities and corresponding mean field matrices"""
import correlatorsf90
ndim = voccs.shape[1] # dimension of the matrix
if weight is not None:
if len(weight) != voccs.shape[0]: raise # inconsistent dimensions
nat = ndim // 2 # one half
pdup = np.array([[2 * i, 2 * i] for i in range(nat)]) # up density
pddn = pdup + 1 # down density
pxc = np.array([[2 * i, 2 * i + 1] for i in range(nat)]) # exchange
if weight is None: # no weight
vdup = correlatorsf90.correlators(voccs, pdup) / totkp
vddn = correlatorsf90.correlators(voccs, pddn) / totkp
vxc = correlatorsf90.correlators(voccs, pxc) / totkp
else: # with weight
vdup = correlatorsf90.correlators_weighted(voccs, weight, pdup) / totkp
vddn = correlatorsf90.correlators_weighted(voccs, weight, pddn) / totkp
vxc = correlatorsf90.correlators_weighted(voccs, pxc) / totkp
ndn = csc_matrix((vdup, pddn.transpose()),
dtype=np.complex,
shape=(ndim, ndim))
nup = csc_matrix((vddn, pdup.transpose()),
dtype=np.complex,
shape=(ndim, ndim))
xc = csc_matrix((np.conjugate(vxc), pxc.transpose()),
dtype=np.complex,
shape=(ndim, ndim))
return (vdup, vddn, vxc, ndn, nup, xc) # return everything
def get_super_correlator(voccs, weight=None, totkp=1):
"""Get the different correlators for a superconducting system"""
import correlatorsf90
ndim = voccs.shape[1] # dimension of the matrix
if weight is not None:
if len(weight) != voccs.shape[0]: raise # inconsistent dimensions
nat = ndim // 4 # one fourth
corrs = [] # empty list with the different correlators
ops = [] # list with the operators
for i in nat: # loop over atoms
corrs.append([4 * i, 4 * i]) # up density
ops.append(csc_matrix(([1.], [1, 1]),
dtype=np.complex)) # down operator
corrs.append([4 * i + 1, 4 * i + 1]) # up density
ops.append(csc_matrix(([1.], [0, 0]),
dtype=np.complex)) # down operator
corrs.append([4 * i, 4 * i + 1]) # up density
ops.append(csc_matrix(([-1.], [1, 0]),
dtype=np.complex)) # down operator
corrs.append([4 * i + 1, 4 * i]) # up density
ops.append(csc_matrix(([-1.], [0, 1]),
dtype=np.complex)) # down operator
pdup = np.array([[4 * i, 4 * i] for i in range(nat)]) # up density
pddn = pdup + 1 # down density
pxc = np.array([[4 * i, 4 * i + 1] for i in range(nat)]) # exchange
deltadd = np.array([[4 * i + 1, 4 * i + 2]
for i in range(nat)]) # Delta dd
deltauu = np.array([[4 * i, 4 * i + 3] for i in range(nat)]) # Delta uu
deltaud = np.array([[4 * i, 4 * i + 2] for i in range(nat)]) # Delta ud
deltadu = np.array([[4 * i + 1, 4 * i + 3]
for i in range(nat)]) # Delta du
if weight is None: # no weight
vdup = correlatorsf90.correlators(voccs, pdup) / totkp
vddn = correlatorsf90.correlators(voccs, pddn) / totkp
vxc = correlatorsf90.correlators(voccs, pxc) / totkp
vdeltadd = correlatorsf90.correlators(voccs, deltadd) / totkp
vdeltauu = correlatorsf90.correlators(voccs, deltauu) / totkp
vdeltadu = correlatorsf90.correlators(voccs, deltadu) / totkp
vdeltaud = correlatorsf90.correlators(voccs, deltaud) / totkp
else: # with weight
raise
vdup = correlatorsf90.correlators_weighted(voccs, weight, pdup) / totkp
vddn = correlatorsf90.correlators_weighted(voccs, weight, pddn) / totkp
vxc = correlatorsf90.correlators_weighted(voccs, pxc) / totkp
ndn = csc_matrix((vdup, pddn.transpose()),
dtype=np.complex,
shape=(ndim, ndim))
nup = csc_matrix((vddn, pdup.transpose()),
dtype=np.complex,
shape=(ndim, ndim))
xc = csc_matrix((np.conjugate(vxc), pxc.transpose()),
dtype=np.complex,
shape=(ndim, ndim))
return (vdup, vddn, vxc, ndn, nup, xc) # return everything
def get_magnetization(h,nkp=20):
"""Return the magnetization of the system"""
totkp = nkp**(h.dimensionality)
nat = h.intra.shape[0]//2 # number of atoms
eigvals,eigvecs = h.eigenvectors(nkp)
voccs = [] # accupied vectors
eoccs = [] # accupied eigenvalues
occs = [] # accupied eigenvalues
for (e,v) in zip(eigvals,eigvecs): # loop over eigenvals,eigenvecs
if e<0.0000001: # if level is filled, add contribution
voccs.append(v) # store
eoccs.append(e) # store
pdup = np.array([[2*i,2*i] for i in range(nat)]) # up density
pddn = pdup + 1 # down density
pxc = np.array([[2*i,2*i+1] for i in range(nat)]) # exchange
import correlatorsf90
vdup = correlatorsf90.correlators(voccs,pdup)/totkp
vddn = correlatorsf90.correlators(voccs,pddn)/totkp
vxc = correlatorsf90.correlators(voccs,pxc)/totkp
magnetization = np.array([vxc.real,vxc.imag,vdup-vddn]).transpose().real
from scftypes import write_magnetization
write_magnetization(magnetization)
def get_udxc(voccs,weight=None,totkp=1):
"""Get up/down densities and corresponding mean field matrices"""
import correlatorsf90
ndim = voccs.shape[1] # dimension of the matrix
if weight is not None:
if len(weight)!=voccs.shape[0]: raise # inconsistent dimensions
nat = ndim//2 # one half
pdup = np.array([[2*i,2*i] for i in range(nat)]) # up density
pddn = pdup + 1 # down density
pxc = np.array([[2*i,2*i+1] for i in range(nat)]) # exchange
if weight is None: # no weight
vdup = correlatorsf90.correlators(voccs,pdup)/totkp
vddn = correlatorsf90.correlators(voccs,pddn)/totkp
vxc = correlatorsf90.correlators(voccs,pxc)/totkp
else: # with weight
vdup = correlatorsf90.correlators_weighted(voccs,weight,pdup)/totkp
vddn = correlatorsf90.correlators_weighted(voccs,weight,pddn)/totkp
vxc = correlatorsf90.correlators_weighted(voccs,pxc)/totkp
ndn = csc_matrix((vdup,pddn.transpose()),dtype=np.complex,shape=(ndim,ndim))
nup = csc_matrix((vddn,pdup.transpose()),dtype=np.complex,shape=(ndim,ndim))
xc = csc_matrix((np.conjugate(vxc),pxc.transpose()),
dtype=np.complex,shape=(ndim,ndim))
return (vdup,vddn,vxc,ndn,nup,xc) # return everything
def get_magnetization(h, nkp=20):
"""Return the magnetization of the system"""
totkp = nkp**(h.dimensionality)
nat = h.intra.shape[0] // 2 # number of atoms
eigvals, eigvecs = h.eigenvectors(nkp)
voccs = [] # accupied vectors
eoccs = [] # accupied eigenvalues
occs = [] # accupied eigenvalues
for (e, v) in zip(eigvals, eigvecs): # loop over eigenvals,eigenvecs
if e < 0.0000001: # if level is filled, add contribution
voccs.append(v) # store
eoccs.append(e) # store
pdup = np.array([[2 * i, 2 * i] for i in range(nat)]) # up density
pddn = pdup + 1 # down density
pxc = np.array([[2 * i, 2 * i + 1] for i in range(nat)]) # exchange
import correlatorsf90
vdup = correlatorsf90.correlators(voccs, pdup) / totkp
vddn = correlatorsf90.correlators(voccs, pddn) / totkp
vxc = correlatorsf90.correlators(voccs, pxc) / totkp
magnetization = np.array([vxc.real, vxc.imag,
vdup - vddn]).transpose().real
from scftypes import write_magnetization
write_magnetization(magnetization)