Support periodic supercell CCSD and add bisection based Aufbau #8
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This reverts commit d60e1b7.
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## master #8 +/- ##
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| @@ -120,6 +120,56 @@ def get_greens_function(self): | |||
| return self.gf.copy(chempot=self.chempot, deep=False) | |||
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| class AufbauPrincipleBisect(AufbauPrinciple): | |||
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copy the doc string for aesthetics (i know it inherits __doc__ but nicer to be able to read it in the source code). Maybe add another line saying this uses bisection
| def _kernel(self): | ||
| energies = self.gf.energies | ||
| couplings_l, couplings_r = self.gf._unpack_couplings() | ||
| weights = self.gf.weights() |
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maybe this is a stupid question, but self.gf.weight() is already O(nmo * naux), so is bisection only faster by virtue of vectorisation in calculating the weights? In the non-bisected algo you need O(nocc * naux) to calculate the weights but they're done one at a time so i can see how it would be less efficient in practice
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Yeah, it's just a prefactor improvement. However since the python loop is now log(N) it ends up being quite faster for larger problems. Performance can vary due to the ratio between MOs and couplings as well as where the Fermi level is. I implemented this for embedding where the number of auxiliaries becomes far greater than the number of MOs, particularly in solids.
| lumo = homo + 1 | ||
| chempot = 0.5 * (energies[homo] + energies[lumo]) | ||
| except: | ||
| raise ValueError("Failed to find Fermi energy.") |
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| raise ValueError("Failed to find Fermi energy.") | |
| raise ValueError("Failed to find Fermi energy.") | |
examples/03-cpgf.py
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| @@ -9,7 +9,7 @@ | |||
| from pyscf import gto, scf, agf2, lib | |||
| from dyson import CPGF, util | |||
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| ncheb = 50 # Number of Chebyshev moments | |||
| ncheb = 100 # Number of Chebyshev moments | |||
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was this a mistake? not that it really matters but which value is best for the example?
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This is a mistake. I didn't realize I committed the change.
Co-authored-by: Oliver Backhouse <[email protected]>
Co-authored-by: Oliver Backhouse <[email protected]>
Co-authored-by: Oliver Backhouse <[email protected]>
This PR adds: