 ### Use correct bloch basis in qsymm wrapper.

`The function which finds the symmetries of kwant builders does not find all real space symmetries if the unit cell contains more than one sites, because the conversion from builder to qsymm model does not use a basis which preserves information on the real space position of sites. The tests do not catch this, because they only have one site per unit cell. This fixes the basis choice, and adds a test.`
parent 3530ee76
Pipeline #16834 passed with stages
in 42 minutes and 27 seconds
 ... ... @@ -448,7 +448,7 @@ def find_builder_symmetries(builder, momenta=None, params=None, params = dict() ham = builder_to_model(builder, momenta=momenta, real_space=False, params=params) real_space=spatial_symmetries, params=params) # Use dense or sparse computation depending on Hamiltonian size if sparse is None: ... ...
 ... ... @@ -427,6 +427,34 @@ def test_find_builder_discrete_symmetries(): assert sym_dict[class_symmetry] in builder_symmetries_dense def test_real_space_basis(): lat = kwant.lattice.honeycomb(norbs=[1, 1]) sym = kwant.TranslationalSymmetry(lat.vec((1, 0)), lat.vec((0, 1))) bulk = kwant.Builder(sym) bulk[[lat.a(0, 0), lat.b(0, 0)]] = 0 bulk[lat.neighbors()] = 1 # Including real space symmetries symmetries = find_builder_symmetries(bulk) hex_group_2D = hexagonal() hex_group_2D = set(PointGroupElement(np.array(s.R).astype(float), s.conjugate, s.antisymmetry, None) for s in hex_group_2D) assert len(symmetries) == len(hex_group_2D) assert all([s1 in symmetries and s2 in hex_group_2D for s1, s2 in zip(hex_group_2D, symmetries)]) # Only onsite discrete symmetries symmetries = find_builder_symmetries(bulk, spatial_symmetries=False) onsites = [PointGroupElement(np.eye(2), True, False, None), # T PointGroupElement(np.eye(2), True, True, None), # P PointGroupElement(np.eye(2), False, True, None), # C PointGroupElement(np.eye(2), False, False, None)] # I assert len(symmetries) == len(onsites) assert all([s1 in symmetries and s2 in onsites for s1, s2 in zip(onsites, symmetries)]) def random_onsite_hop(n, rng=0): rng = ensure_rng(rng) onsite = rng.randn(n, n) + 1j * rng.randn(n, n) ... ...
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