ALF merge requestshttps://git.physik.uni-wuerzburg.de/ALF/ALF/-/merge_requests2021-12-07T20:16:17Zhttps://git.physik.uni-wuerzburg.de/ALF/ALF/-/merge_requests/127Draft: Resolve "rework hop_mod and wrapgrup and wrapgrdo"2021-12-07T20:16:17ZFlorian GothDraft: Resolve "rework hop_mod and wrapgrup and wrapgrdo"Closes #208Closes #208Florian GothFlorian Gothhttps://git.physik.uni-wuerzburg.de/ALF/ALF/-/merge_requests/106Resolve "Include MSCBDECOMP + higher order checkerboard"2022-06-28T11:13:45ZFlorian GothResolve "Include MSCBDECOMP + higher order checkerboard"Closes #175 .
This now has the basic functionality that I wanted to implement:
- Automatic Decomposition
- A selection of approximations to the exact exponential.
To that end a new section in the parameter file has been added.(See Scri...Closes #175 .
This now has the basic functionality that I wanted to implement:
- Automatic Decomposition
- A selection of approximations to the exact exponential.
To that end a new section in the parameter file has been added.(See Scripts_and_parameters)
possible values for method:
- 0: Disable it
- 1: S_1 1 Euler Approximation
- 2: S_1 2 Strang splitting
- 3: SE_2 2 splitting by Blanes et al. (2014)
- 4: S_3 4 splitting by Neri(1987), Forest(1990), Yoshida(1990)
- 5: S_6 4 splitting by Blanes et al. (2002)
The Euler Approximation tends to be unstable(Hubbard, N=4 -> N=6 -> N=8), the others always worked.
unimplemented things:
- projector matrix P assumes P(i) == i -> ignored
General assumptions:
- Op_T constitutes a hermitian matrix. By this Op_T%g has to be real.Florian GothFlorian Gothhttps://git.physik.uni-wuerzburg.de/ALF/ALF/-/merge_requests/62WIP: Resolve "Cholesky vs maxent"2021-04-19T14:19:29ZFlorian GothWIP: Resolve "Cholesky vs maxent"Closes #113. Replaces the previously used eigenvalue decomposition with a cholesky decomposition in case of a dense covariance matrix. Things to note:
- made some intents on function arguments clearer.
- Testing occured on artificial i...Closes #113. Replaces the previously used eigenvalue decomposition with a cholesky decomposition in case of a dense covariance matrix. Things to note:
- made some intents on function arguments clearer.
- Testing occured on artificial input. All data that i touched in Fakher's testsuite had covariance matrices which are not positive definite.
In the attachment you'll find a small test program and compare that the resulting norms are equal, although the generated vectors are different.[test.f03](/uploads/4f59d1c5dde4c3efce8dcfb81cf10878/test.f03)