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!feat: GEVP now returns all eigenvectors instead of just the ones for
the specified state.
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commit
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2 changed files with 10 additions and 15 deletions
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@ -241,8 +241,8 @@ class Corr:
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if self.N == 1:
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raise Exception("Trying to symmetrize a correlator matrix, that already has N=1.")
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def GEVP(self, t0, ts=None, state=0, sorted_list="Eigenvalue"):
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"""Solve the general eigenvalue problem on the current correlator
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def GEVP(self, t0, ts=None, sorted_list="Eigenvalue"):
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"""Solve the generalized eigenvalue problem on the current correlator and returns the corresponding eigenvectors.
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Parameters
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----------
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@ -251,8 +251,6 @@ class Corr:
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ts : int
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fixed time G(t_s)v= lambda G(t_0)v if return_list=False
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If return_list=True and sorting=Eigenvector it gives a reference point for the sorting method.
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state : int
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The state one is interested in, ordered by energy. The lowest state is zero.
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sorted_list : string
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if this argument is set, a list of vectors (len=self.T) is returned. If it is left as None, only one vector is returned.
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"Eigenvalue" - The eigenvector is chosen according to which eigenvalue it belongs individually on every timeslice.
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@ -278,7 +276,7 @@ class Corr:
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Gt[i, j] = symmetric_corr[ts][i, j].value
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sp_vecs = _GEVP_solver(Gt, G0)
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sp_vec = sp_vecs[state]
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sp_vec = [sp_vecs[s] for s in range(self.N)]
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return sp_vec
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elif sorted_list in ["Eigenvalue", "Eigenvector"]:
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if sorted_list == "Eigenvalue" and ts is not None:
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@ -294,7 +292,7 @@ class Corr:
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sp_vecs = _GEVP_solver(Gt, G0)
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if sorted_list == "Eigenvalue":
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sp_vec = sp_vecs[state]
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sp_vec = [sp_vecs[s] for s in range(self.N)]
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all_vecs.append(sp_vec)
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else:
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all_vecs.append(sp_vecs)
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@ -304,7 +302,7 @@ class Corr:
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if (ts is None):
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raise Exception("ts is required for the Eigenvector sorting method.")
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all_vecs = _sort_vectors(all_vecs, ts)
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all_vecs = [a[state] if a is not None else None for a in all_vecs]
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all_vecs = [[a[s] if a is not None else None for a in all_vecs] for s in range(self.N)]
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else:
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raise Exception("Unkown value for 'sorted_list'.")
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@ -328,7 +326,7 @@ class Corr:
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"Eigenvector" - Use the method described in arXiv:2004.10472 [hep-lat] to find the set of v(t) belonging to the state.
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The reference state is identified by its eigenvalue at t=ts
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"""
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vec = self.GEVP(t0, ts=ts, state=state, sorted_list=sorted_list)
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vec = self.GEVP(t0, ts=ts, sorted_list=sorted_list)[state]
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return self.projected(vec)
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def Hankel(self, N, periodic=False):
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@ -1176,9 +1174,7 @@ class Corr:
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if basematrix.N != self.N:
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raise Exception('basematrix and targetmatrix have to be of the same size.')
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evecs = []
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for i in range(Ntrunc):
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evecs.append(basematrix.GEVP(t0proj, tproj, state=i, sorted_list=None))
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evecs = basematrix.GEVP(t0proj, tproj, sorted_list=None)[:Ntrunc]
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tmpmat = np.empty((Ntrunc, Ntrunc), dtype=object)
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rmat = []
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@ -231,11 +231,10 @@ def test_matrix_corr():
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corr_mat = pe.Corr(np.array([[corr_aa, corr_ab], [corr_ab, corr_aa]]))
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corr_mat.item(0, 0)
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vec_0 = corr_mat.GEVP(0, 1, sorted_list=None)
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vec_1 = corr_mat.GEVP(0, 1, state=1, sorted_list=None)
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vecs = corr_mat.GEVP(0, 1, sorted_list=None)
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corr_0 = corr_mat.projected(vec_0)
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corr_1 = corr_mat.projected(vec_1)
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corr_0 = corr_mat.projected(vecs[0])
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corr_1 = corr_mat.projected(vecs[0])
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assert np.all([o == 0 for o in corr_0 - corr_aa])
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assert np.all([o == 0 for o in corr_1 - corr_aa])
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