root / ase / transport / greenfunction.py @ 1
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import numpy as np |
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class GreenFunction: |
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"""Equilibrium retarded Green function."""
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def __init__(self, H, S=None, selfenergies=[], eta=1e-4): |
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self.H = H
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self.S = S
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self.selfenergies = selfenergies
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self.eta = eta
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self.energy = None |
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self.Ginv = np.empty(H.shape, complex) |
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def retarded(self, energy, inverse=False): |
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"""Get retarded Green function at specified energy.
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If 'inverse' is True, the inverse Green function is returned (faster).
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"""
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if energy != self.energy: |
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self.energy = energy
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z = energy + self.eta * 1.j |
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if self.S is None: |
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self.Ginv[:] = 0.0 |
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self.Ginv.flat[:: len(self.S) + 1] = z |
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else:
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self.Ginv[:] = z
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self.Ginv *= self.S |
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self.Ginv -= self.H |
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for selfenergy in self.selfenergies: |
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self.Ginv -= selfenergy.retarded(energy)
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if inverse:
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return self.Ginv |
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else:
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return np.linalg.inv(self.Ginv) |
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def calculate(self, energy, sigma): |
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"""XXX is this really needed"""
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ginv = energy * self.S - self.H - sigma |
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return np.linalg.inv(ginv)
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def apply_retarded(self, energy, X): |
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"""Apply retarded Green function to X.
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Returns the matrix product G^r(e) . X
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"""
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return np.linalg.solve(self.retarded(energy, inverse=True), X) |
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def dos(self, energy): |
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"""Total density of states -1/pi Im(Tr(GS))"""
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if self.S is None: |
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return -self(energy).imag.trace() / np.pi |
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else:
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GS = self.apply_retarded(energy, self.S) |
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return -GS.imag.trace() / np.pi
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def pdos(self, energy): |
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"""Projected density of states -1/pi Im(SGS/S)"""
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if self.S is None: |
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return -self.retarded(energy).imag.diagonal() / np.pi |
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else:
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S = self.S
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SGS = np.dot(S, self.apply_retarded(energy, S))
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return -(SGS.diagonal() / S.diagonal()).imag / np.pi
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