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add another comment about minmization

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jan 2022-11-22 22:21:51 -08:00
parent dfbb845bee
commit ff395277b0
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meanas/fdfd/bloch.py
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@ -582,6 +582,13 @@ def eigsolve(
d_scale = num_modes / norm(D)
D *= d_scale
# Now know the direction (D), but need to find how far to go (alpha)
# We are still minimizing E = tr((Z + alpha D)t A (Z + alpha D) U')
# = tr(ZtAZU' + alpha DtAZU' + alpha ZtADU' + alpha**2 DtADU')
# where U' = inv((Z + alpha D)t (Z + alpha D))
# = inv(ZtZ + alpha ZtD + alpha DtZ + alpha**2 DtD)
AD = scipy_op @ D
DtD = D.conj().T @ D
DtAD = D.conj().T @ AD