import jax import jax.numpy as jnp from varipeps.peps import PEPS_Tensor_Triangular, PEPS_Unit_Cell from varipeps.contractions import apply_contraction_jitted from varipeps.utils.svd import gauge_fixed_svd from varipeps.utils.projector_dict import Projector_Dict_Triangular from varipeps.config import VariPEPS_Config from varipeps.global_state import VariPEPS_Global_State from .absorption import _tensor_list_from_indices, _post_process_CTM_tensors from .triangular_projectors import ( calc_corner_projectors, calc_T_30_150_270_projectors, calc_T_90_210_330_projectors, calc_split_projectors_phase_1, calc_split_projectors_phase_2, ) from typing import Sequence, Tuple, List def _get_triangular_ctmrg_2x2_structure( peps_tensors: Sequence[jnp.ndarray], view: PEPS_Unit_Cell, ) -> Tuple[List[List[jnp.ndarray]], List[List[PEPS_Tensor_Triangular]]]: x_slice = slice(0, 2, None) y_slice = slice(0, 2, None) indices = view.get_indices((x_slice, y_slice)) view_tensors = _tensor_list_from_indices(peps_tensors, indices) view_tensor_objs = view[x_slice, y_slice] return view_tensors, view_tensor_objs def decompose_new_T(new_T, chi, truncation_eps, config): new_T /= jnp.linalg.norm(new_T) new_T_matrix = new_T.reshape( new_T.shape[0] * new_T.shape[1] * new_T.shape[2], new_T.shape[3] * new_T.shape[4] * new_T.shape[5], ) new_T_U, new_T_S, new_T_Vh = gauge_fixed_svd(new_T_matrix) new_T_S = jnp.where( new_T_S / new_T_S[0] >= truncation_eps, jnp.sqrt(jnp.where(new_T_S / new_T_S[0] >= truncation_eps, new_T_S, 1)), 0, ) new_Ta = new_T_S[:, jnp.newaxis] * new_T_Vh new_Ta = new_Ta.reshape( new_Ta.shape[0], new_T.shape[3], new_T.shape[4], new_T.shape[5] ) new_Tb = new_T_U * new_T_S[jnp.newaxis, :] new_Tb = new_Tb.reshape( new_T.shape[0], new_T.shape[1], new_T.shape[2], new_Tb.shape[-1] ) new_Ta_trunc = new_T_S[:chi, jnp.newaxis] * new_T_Vh[:chi, :] new_Ta_trunc = new_Ta_trunc.reshape( new_Ta_trunc.shape[0], new_T.shape[3], new_T.shape[4], new_T.shape[5] ) new_Tb_trunc = new_T_U[:, :chi] * new_T_S[jnp.newaxis, :chi] new_Tb_trunc = new_Tb_trunc.reshape( new_T.shape[0], new_T.shape[1], new_T.shape[2], new_Tb_trunc.shape[-1] ) return ( _post_process_CTM_tensors(new_Ta, config), _post_process_CTM_tensors(new_Tb, config), _post_process_CTM_tensors(new_Ta_trunc, config), _post_process_CTM_tensors(new_Tb_trunc, config), ) def do_absorption_step_triangular( peps_tensors: Sequence[jnp.ndarray], unitcell: PEPS_Unit_Cell, config: VariPEPS_Config, state: VariPEPS_Global_State, ) -> PEPS_Unit_Cell: if config.triangular_ctmrg_use_split: return do_absorption_step_triangular_split( peps_tensors, unitcell, config, state ) max_x, max_y = unitcell.get_size() truncation_eps = ( config.ctmrg_truncation_eps if state.ctmrg_effective_truncation_eps is None else state.ctmrg_effective_truncation_eps ) corner_30_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_90_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_150_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_210_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_270_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_330_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) T_30_projectors = Projector_Dict_Triangular(view=unitcell, max_x=max_x, max_y=max_y) T_90_projectors = Projector_Dict_Triangular(view=unitcell, max_x=max_x, max_y=max_y) T_150_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) T_210_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) T_270_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) T_330_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) smallest_S_list = [] working_unitcell = unitcell.copy() for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: ( proj_30, proj_90, proj_150, proj_210, proj_270, proj_330, smallest_S_corner, ) = calc_corner_projectors( *_get_triangular_ctmrg_2x2_structure(peps_tensors, view), config, state ) corner_30_projectors[(x, y)] = proj_30 corner_90_projectors[(x, y)] = proj_90 corner_150_projectors[(x, y)] = proj_150 corner_210_projectors[(x, y)] = proj_210 corner_270_projectors[(x + 1, y)] = proj_270 corner_330_projectors[(x, y + 1)] = proj_330 smallest_S_list.append(smallest_S_corner) new_C1_list = [] new_C2_list = [] new_C3_list = [] new_C4_list = [] new_C5_list = [] new_C6_list = [] new_T1a_list = [] new_T1b_list = [] new_T2a_list = [] new_T2b_list = [] new_T3a_list = [] new_T3b_list = [] new_T4a_list = [] new_T4b_list = [] new_T5a_list = [] new_T5b_list = [] new_T6a_list = [] new_T6b_list = [] new_T1a_trunc_list = [] new_T1b_trunc_list = [] new_T2a_trunc_list = [] new_T2b_trunc_list = [] new_T3a_trunc_list = [] new_T3b_trunc_list = [] new_T4a_trunc_list = [] new_T4b_trunc_list = [] new_T5a_trunc_list = [] new_T5b_trunc_list = [] new_T6a_trunc_list = [] new_T6b_trunc_list = [] for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: working_tensor = peps_tensors[view.get_indices((0, 0))[0][0]] working_tensor_obj = view[0, 0][0][0] C1_proj_left = corner_150_projectors.get_projector(x, y, 0, 0)[0] C1_proj_right = corner_90_projectors.get_projector(x, y, 0, 0)[1] new_C1 = apply_contraction_jitted( "triangular_ctmrg_C1_absorption", [working_tensor], [working_tensor_obj], [C1_proj_left, C1_proj_right], ) new_C1_list.append(_post_process_CTM_tensors(new_C1, config)) C2_proj_left = corner_90_projectors.get_projector(x, y, 0, -1)[0] C2_proj_right = corner_30_projectors.get_projector(x, y, 0, 0)[1] new_C2 = apply_contraction_jitted( "triangular_ctmrg_C2_absorption", [working_tensor], [working_tensor_obj], [C2_proj_left, C2_proj_right], ) new_C2_list.append(_post_process_CTM_tensors(new_C2, config)) C3_proj_left = corner_30_projectors.get_projector(x, y, -1, -1)[0] C3_proj_right = corner_330_projectors.get_projector(x, y, 0, 0)[1] new_C3 = apply_contraction_jitted( "triangular_ctmrg_C3_absorption", [working_tensor], [working_tensor_obj], [C3_proj_left, C3_proj_right], ) new_C3_list.append(_post_process_CTM_tensors(new_C3, config)) C4_proj_left = corner_330_projectors.get_projector(x, y, -1, 0)[0] C4_proj_right = corner_270_projectors.get_projector(x, y, 0, -1)[1] new_C4 = apply_contraction_jitted( "triangular_ctmrg_C4_absorption", [working_tensor], [working_tensor_obj], [C4_proj_left, C4_proj_right], ) new_C4_list.append(_post_process_CTM_tensors(new_C4, config)) C5_proj_left = corner_270_projectors.get_projector(x, y, 0, 0)[0] C5_proj_right = corner_210_projectors.get_projector(x, y, -1, -1)[1] new_C5 = apply_contraction_jitted( "triangular_ctmrg_C5_absorption", [working_tensor], [working_tensor_obj], [C5_proj_left, C5_proj_right], ) new_C5_list.append(_post_process_CTM_tensors(new_C5, config)) C6_proj_left = corner_210_projectors.get_projector(x, y, 0, 0)[0] C6_proj_right = corner_150_projectors.get_projector(x, y, -1, 0)[1] new_C6 = apply_contraction_jitted( "triangular_ctmrg_C6_absorption", [working_tensor], [working_tensor_obj], [C6_proj_left, C6_proj_right], ) new_C6_list.append(_post_process_CTM_tensors(new_C6, config)) T1_proj_left = corner_90_projectors.get_projector(x, y, 0, -1)[0] T1_proj_right = corner_90_projectors.get_projector(x, y, 0, 0)[1] new_T1 = apply_contraction_jitted( "triangular_ctmrg_T1_absorption", [working_tensor], [working_tensor_obj], [T1_proj_left, T1_proj_right], ) new_T1a, new_T1b, new_T1a_trunc, new_T1b_trunc = decompose_new_T( new_T1, working_tensor_obj.chi, truncation_eps, config ) new_T1a_list.append(new_T1a) new_T1b_list.append(new_T1b) new_T1a_trunc_list.append(new_T1a_trunc) new_T1b_trunc_list.append(new_T1b_trunc) T2_proj_left = corner_30_projectors.get_projector(x, y, -1, -1)[0] T2_proj_right = corner_30_projectors.get_projector(x, y, 0, 0)[1] new_T2 = apply_contraction_jitted( "triangular_ctmrg_T2_absorption", [working_tensor], [working_tensor_obj], [T2_proj_left, T2_proj_right], ) new_T2a, new_T2b, new_T2a_trunc, new_T2b_trunc = decompose_new_T( new_T2, working_tensor_obj.chi, truncation_eps, config ) new_T2a_list.append(new_T2a) new_T2b_list.append(new_T2b) new_T2a_trunc_list.append(new_T2a_trunc) new_T2b_trunc_list.append(new_T2b_trunc) T3_proj_left = corner_330_projectors.get_projector(x, y, -1, 0)[0] T3_proj_right = corner_330_projectors.get_projector(x, y, 0, 0)[1] new_T3 = apply_contraction_jitted( "triangular_ctmrg_T3_absorption", [working_tensor], [working_tensor_obj], [T3_proj_left, T3_proj_right], ) new_T3a, new_T3b, new_T3a_trunc, new_T3b_trunc = decompose_new_T( new_T3, working_tensor_obj.chi, truncation_eps, config ) new_T3a_list.append(new_T3a) new_T3b_list.append(new_T3b) new_T3a_trunc_list.append(new_T3a_trunc) new_T3b_trunc_list.append(new_T3b_trunc) T4_proj_left = corner_270_projectors.get_projector(x, y, 0, 0)[0] T4_proj_right = corner_270_projectors.get_projector(x, y, 0, -1)[1] new_T4 = apply_contraction_jitted( "triangular_ctmrg_T4_absorption", [working_tensor], [working_tensor_obj], [T4_proj_left, T4_proj_right], ) new_T4a, new_T4b, new_T4a_trunc, new_T4b_trunc = decompose_new_T( new_T4, working_tensor_obj.chi, truncation_eps, config ) new_T4a_list.append(new_T4a) new_T4b_list.append(new_T4b) new_T4a_trunc_list.append(new_T4a_trunc) new_T4b_trunc_list.append(new_T4b_trunc) T5_proj_left = corner_210_projectors.get_projector(x, y, 0, 0)[0] T5_proj_right = corner_210_projectors.get_projector(x, y, -1, -1)[1] new_T5 = apply_contraction_jitted( "triangular_ctmrg_T5_absorption", [working_tensor], [working_tensor_obj], [T5_proj_left, T5_proj_right], ) new_T5a, new_T5b, new_T5a_trunc, new_T5b_trunc = decompose_new_T( new_T5, working_tensor_obj.chi, truncation_eps, config ) new_T5a_list.append(new_T5a) new_T5b_list.append(new_T5b) new_T5a_trunc_list.append(new_T5a_trunc) new_T5b_trunc_list.append(new_T5b_trunc) T6_proj_left = corner_150_projectors.get_projector(x, y, 0, 0)[0] T6_proj_right = corner_150_projectors.get_projector(x, y, -1, 0)[1] new_T6 = apply_contraction_jitted( "triangular_ctmrg_T6_absorption", [working_tensor], [working_tensor_obj], [T6_proj_left, T6_proj_right], ) new_T6a, new_T6b, new_T6a_trunc, new_T6b_trunc = decompose_new_T( new_T6, working_tensor_obj.chi, truncation_eps, config ) new_T6a_list.append(new_T6a) new_T6b_list.append(new_T6b) new_T6a_trunc_list.append(new_T6a_trunc) new_T6b_trunc_list.append(new_T6b_trunc) i = 0 for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: new_t = view[1, 1][0][0].copy_including_trunc() new_t.C1 = new_C1_list[i] new_t.T1a = new_T1a_list[i] new_t.T6b = new_T6b_list[i] new_t.T1a_trunc = new_T1a_trunc_list[i] new_t.T6b_trunc = new_T6b_trunc_list[i] view[1, 1] = new_t new_t = view[1, 0][0][0].copy_including_trunc() new_t.C2 = new_C2_list[i] new_t.T1b = new_T1b_list[i] new_t.T2a = new_T2a_list[i] new_t.T1b_trunc = new_T1b_trunc_list[i] new_t.T2a_trunc = new_T2a_trunc_list[i] view[1, 0] = new_t new_t = view[0, -1][0][0].copy_including_trunc() new_t.C3 = new_C3_list[i] new_t.T2b = new_T2b_list[i] new_t.T3a = new_T3a_list[i] new_t.T2b_trunc = new_T2b_trunc_list[i] new_t.T3a_trunc = new_T3a_trunc_list[i] view[0, -1] = new_t new_t = view[-1, -1][0][0].copy_including_trunc() new_t.C4 = new_C4_list[i] new_t.T3b = new_T3b_list[i] new_t.T4a = new_T4a_list[i] new_t.T3b_trunc = new_T3b_trunc_list[i] new_t.T4a_trunc = new_T4a_trunc_list[i] view[-1, -1] = new_t new_t = view[-1, 0][0][0].copy_including_trunc() new_t.C5 = new_C5_list[i] new_t.T4b = new_T4b_list[i] new_t.T5a = new_T5a_list[i] new_t.T4b_trunc = new_T4b_trunc_list[i] new_t.T5a_trunc = new_T5a_trunc_list[i] view[-1, 0] = new_t new_t = view[0, 1][0][0].copy_including_trunc() new_t.C6 = new_C6_list[i] new_t.T5b = new_T5b_list[i] new_t.T6a = new_T6a_list[i] new_t.T5b_trunc = new_T5b_trunc_list[i] new_t.T6a_trunc = new_T6a_trunc_list[i] view[0, 1] = new_t i += 1 for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: proj_90, proj_210, proj_330, smallest_S_T = calc_T_90_210_330_projectors( *_get_triangular_ctmrg_2x2_structure(peps_tensors, view), config, state ) T_90_projectors[(x, y)] = proj_90 T_210_projectors[(x, y)] = proj_210 T_330_projectors[(x, y)] = proj_330 smallest_S_list.append(smallest_S_T) for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: new_t = view[0, 0][0][0].copy() new_t.T1a = _post_process_CTM_tensors( jnp.tensordot( T_90_projectors.get_projector(x, y, 0, -1)[0], new_t.T1a, ((1,), (0,)), ), config, ) new_t.T1b = _post_process_CTM_tensors( jnp.tensordot( new_t.T1b, T_90_projectors.get_projector(x, y, 0, 0)[1], ((3,), (0,)), ), config, ) new_t.T3a = _post_process_CTM_tensors( jnp.tensordot( T_330_projectors.get_projector(x, y, -1, 0)[0], new_t.T3a, ((1,), (0,)), ), config, ) new_t.T3b = _post_process_CTM_tensors( jnp.tensordot( new_t.T3b, T_330_projectors.get_projector(x, y, 0, 0)[1], ((3,), (0,)), ), config, ) new_t.T5a = _post_process_CTM_tensors( jnp.tensordot( T_210_projectors.get_projector(x, y, 0, 0)[0], new_t.T5a, ((1,), (0,)), ), config, ) new_t.T5b = _post_process_CTM_tensors( jnp.tensordot( new_t.T5b, T_210_projectors.get_projector(x, y, -1, -1)[1], ((3,), (0,)), ), config, ) view[0, 0] = new_t for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: proj_30, proj_150, proj_270, smallest_S_T = calc_T_30_150_270_projectors( *_get_triangular_ctmrg_2x2_structure(peps_tensors, view), config, state ) T_30_projectors[(x, y)] = proj_30 T_150_projectors[(x, y)] = proj_150 T_270_projectors[(x, y)] = proj_270 smallest_S_list.append(smallest_S_T) for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: new_t = view[0, 0][0][0].copy() new_t.T2a = _post_process_CTM_tensors( jnp.tensordot( T_30_projectors.get_projector(x, y, -1, -1)[0], new_t.T2a, ((1,), (0,)), ), config, ) new_t.T2b = _post_process_CTM_tensors( jnp.tensordot( new_t.T2b, T_30_projectors.get_projector(x, y, 0, 0)[1], ((3,), (0,)), ), config, ) new_t.T4a = _post_process_CTM_tensors( jnp.tensordot( T_270_projectors.get_projector(x, y, 0, 0)[0], new_t.T4a, ((1,), (0,)), ), config, ) new_t.T4b = _post_process_CTM_tensors( jnp.tensordot( new_t.T4b, T_270_projectors.get_projector(x, y, 0, -1)[1], ((3,), (0,)), ), config, ) new_t.T6a = _post_process_CTM_tensors( jnp.tensordot( T_150_projectors.get_projector(x, y, 0, 0)[0], new_t.T6a, ((1,), (0,)), ), config, ) new_t.T6b = _post_process_CTM_tensors( jnp.tensordot( new_t.T6b, T_150_projectors.get_projector(x, y, -1, 0)[1], ((3,), (0,)), ), config, ) view[0, 0] = new_t smallest_S = jnp.linalg.norm( jnp.asarray([j for i in smallest_S_list for j in i]), ord=jnp.inf ) return working_unitcell, smallest_S def do_absorption_step_triangular_split( peps_tensors: Sequence[jnp.ndarray], unitcell: PEPS_Unit_Cell, config: VariPEPS_Config, state: VariPEPS_Global_State, ) -> PEPS_Unit_Cell: max_x, max_y = unitcell.get_size() truncation_eps = ( config.ctmrg_truncation_eps if state.ctmrg_effective_truncation_eps is None else state.ctmrg_effective_truncation_eps ) corner_30_ket_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_30_bra_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_90_ket_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_90_bra_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_150_ket_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_150_bra_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_210_ket_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_210_bra_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_270_ket_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_270_bra_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_330_ket_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) corner_330_bra_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) T_30_projectors = Projector_Dict_Triangular(view=unitcell, max_x=max_x, max_y=max_y) T_90_projectors = Projector_Dict_Triangular(view=unitcell, max_x=max_x, max_y=max_y) T_150_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) T_210_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) T_270_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) T_330_projectors = Projector_Dict_Triangular( view=unitcell, max_x=max_x, max_y=max_y ) smallest_S_list = [] working_unitcell = unitcell.copy() for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: ( proj_30_ket, proj_90_ket, proj_150_ket, proj_210_bra, proj_270_bra, proj_330_bra, smallest_S_corner, ) = calc_split_projectors_phase_1( *_get_triangular_ctmrg_2x2_structure(peps_tensors, view), config, state ) corner_30_ket_projectors[(x, y)] = proj_30_ket corner_90_ket_projectors[(x, y)] = proj_90_ket corner_150_ket_projectors[(x, y)] = proj_150_ket corner_210_bra_projectors[(x, y)] = proj_210_bra corner_270_bra_projectors[(x, y)] = proj_270_bra corner_330_bra_projectors[(x, y)] = proj_330_bra smallest_S_list.append(smallest_S_corner) for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: ( proj_30_bra, proj_90_bra, proj_150_bra, proj_210_ket, proj_270_ket, proj_330_ket, smallest_S_corner, ) = calc_split_projectors_phase_2( *_get_triangular_ctmrg_2x2_structure(peps_tensors, view), *corner_30_ket_projectors.get_projector(x, y, 0, 0), *corner_90_ket_projectors.get_projector(x, y, 0, 0), *corner_150_ket_projectors.get_projector(x, y, 0, 0), *corner_210_bra_projectors.get_projector(x, y, 0, 0), *corner_270_bra_projectors.get_projector(x, y, 1, 0), *corner_330_bra_projectors.get_projector(x, y, 0, 1), config, state, ) corner_30_bra_projectors[(x, y)] = proj_30_bra corner_90_bra_projectors[(x, y)] = proj_90_bra corner_150_bra_projectors[(x, y)] = proj_150_bra corner_210_ket_projectors[(x, y)] = proj_210_ket corner_270_ket_projectors[(x + 1, y)] = proj_270_ket corner_330_ket_projectors[(x, y + 1)] = proj_330_ket smallest_S_list.append(smallest_S_corner) new_C1_list = [] new_C2_list = [] new_C3_list = [] new_C4_list = [] new_C5_list = [] new_C6_list = [] new_T1a_list = [] new_T1b_list = [] new_T2a_list = [] new_T2b_list = [] new_T3a_list = [] new_T3b_list = [] new_T4a_list = [] new_T4b_list = [] new_T5a_list = [] new_T5b_list = [] new_T6a_list = [] new_T6b_list = [] new_T1a_trunc_list = [] new_T1b_trunc_list = [] new_T2a_trunc_list = [] new_T2b_trunc_list = [] new_T3a_trunc_list = [] new_T3b_trunc_list = [] new_T4a_trunc_list = [] new_T4b_trunc_list = [] new_T5a_trunc_list = [] new_T5b_trunc_list = [] new_T6a_trunc_list = [] new_T6b_trunc_list = [] for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: working_tensor = peps_tensors[view.get_indices((0, 0))[0][0]] working_tensor_obj = view[0, 0][0][0] C1_proj_left_bra = corner_150_bra_projectors.get_projector(x, y, 0, 0)[0] C1_proj_left_ket = corner_150_ket_projectors.get_projector(x, y, 0, 0)[0] C1_proj_right_ket = corner_90_ket_projectors.get_projector(x, y, 0, 0)[1] C1_proj_right_bra = corner_90_bra_projectors.get_projector(x, y, 0, 0)[1] new_C1 = apply_contraction_jitted( "triangular_ctmrg_split_C1_absorption", [working_tensor], [working_tensor_obj], [ C1_proj_left_bra, C1_proj_left_ket, C1_proj_right_ket, C1_proj_right_bra, ], ) new_C1_list.append(_post_process_CTM_tensors(new_C1, config)) C2_proj_left_bra = corner_90_bra_projectors.get_projector(x, y, 0, -1)[0] C2_proj_left_ket = corner_90_ket_projectors.get_projector(x, y, 0, -1)[0] C2_proj_right_ket = corner_30_ket_projectors.get_projector(x, y, 0, 0)[1] C2_proj_right_bra = corner_30_bra_projectors.get_projector(x, y, 0, 0)[1] new_C2 = apply_contraction_jitted( "triangular_ctmrg_split_C2_absorption", [working_tensor], [working_tensor_obj], [ C2_proj_left_bra, C2_proj_left_ket, C2_proj_right_ket, C2_proj_right_bra, ], ) new_C2_list.append(_post_process_CTM_tensors(new_C2, config)) C3_proj_left_bra = corner_30_bra_projectors.get_projector(x, y, -1, -1)[0] C3_proj_left_ket = corner_30_ket_projectors.get_projector(x, y, -1, -1)[0] C3_proj_right_bra = corner_330_bra_projectors.get_projector(x, y, 0, 0)[1] C3_proj_right_ket = corner_330_ket_projectors.get_projector(x, y, 0, 0)[1] new_C3 = apply_contraction_jitted( "triangular_ctmrg_split_C3_absorption", [working_tensor], [working_tensor_obj], [ C3_proj_left_bra, C3_proj_left_ket, C3_proj_right_bra, C3_proj_right_ket, ], ) new_C3_list.append(_post_process_CTM_tensors(new_C3, config)) C4_proj_left_ket = corner_330_ket_projectors.get_projector(x, y, -1, 0)[0] C4_proj_left_bra = corner_330_bra_projectors.get_projector(x, y, -1, 0)[0] C4_proj_right_bra = corner_270_bra_projectors.get_projector(x, y, 0, -1)[1] C4_proj_right_ket = corner_270_ket_projectors.get_projector(x, y, 0, -1)[1] new_C4 = apply_contraction_jitted( "triangular_ctmrg_split_C4_absorption", [working_tensor], [working_tensor_obj], [ C4_proj_left_ket, C4_proj_left_bra, C4_proj_right_bra, C4_proj_right_ket, ], ) new_C4_list.append(_post_process_CTM_tensors(new_C4, config)) C5_proj_left_ket = corner_270_ket_projectors.get_projector(x, y, 0, 0)[0] C5_proj_left_bra = corner_270_bra_projectors.get_projector(x, y, 0, 0)[0] C5_proj_right_bra = corner_210_bra_projectors.get_projector(x, y, -1, -1)[1] C5_proj_right_ket = corner_210_ket_projectors.get_projector(x, y, -1, -1)[1] new_C5 = apply_contraction_jitted( "triangular_ctmrg_split_C5_absorption", [working_tensor], [working_tensor_obj], [ C5_proj_left_ket, C5_proj_left_bra, C5_proj_right_bra, C5_proj_right_ket, ], ) new_C5_list.append(_post_process_CTM_tensors(new_C5, config)) C6_proj_left_ket = corner_210_ket_projectors.get_projector(x, y, 0, 0)[0] C6_proj_left_bra = corner_210_bra_projectors.get_projector(x, y, 0, 0)[0] C6_proj_right_ket = corner_150_ket_projectors.get_projector(x, y, -1, 0)[1] C6_proj_right_bra = corner_150_bra_projectors.get_projector(x, y, -1, 0)[1] new_C6 = apply_contraction_jitted( "triangular_ctmrg_split_C6_absorption", [working_tensor], [working_tensor_obj], [ C6_proj_left_ket, C6_proj_left_bra, C6_proj_right_ket, C6_proj_right_bra, ], ) new_C6_list.append(_post_process_CTM_tensors(new_C6, config)) T1_proj_left_bra = corner_90_bra_projectors.get_projector(x, y, 0, -1)[0] T1_proj_left_ket = corner_90_ket_projectors.get_projector(x, y, 0, -1)[0] T1_proj_right_ket = corner_90_ket_projectors.get_projector(x, y, 0, 0)[1] T1_proj_right_bra = corner_90_bra_projectors.get_projector(x, y, 0, 0)[1] new_T1 = apply_contraction_jitted( "triangular_ctmrg_split_T1_absorption", [working_tensor], [working_tensor_obj], [ T1_proj_left_bra, T1_proj_left_ket, T1_proj_right_ket, T1_proj_right_bra, ], ) new_T1a, new_T1b, new_T1a_trunc, new_T1b_trunc = decompose_new_T( new_T1, working_tensor_obj.chi, truncation_eps, config ) new_T1a_list.append(new_T1a) new_T1b_list.append(new_T1b) new_T1a_trunc_list.append(new_T1a_trunc) new_T1b_trunc_list.append(new_T1b_trunc) T2_proj_left_bra = corner_30_bra_projectors.get_projector(x, y, -1, -1)[0] T2_proj_left_ket = corner_30_ket_projectors.get_projector(x, y, -1, -1)[0] T2_proj_right_ket = corner_30_ket_projectors.get_projector(x, y, 0, 0)[1] T2_proj_right_bra = corner_30_bra_projectors.get_projector(x, y, 0, 0)[1] new_T2 = apply_contraction_jitted( "triangular_ctmrg_split_T2_absorption", [working_tensor], [working_tensor_obj], [ T2_proj_left_bra, T2_proj_left_ket, T2_proj_right_ket, T2_proj_right_bra, ], ) new_T2a, new_T2b, new_T2a_trunc, new_T2b_trunc = decompose_new_T( new_T2, working_tensor_obj.chi, truncation_eps, config ) new_T2a_list.append(new_T2a) new_T2b_list.append(new_T2b) new_T2a_trunc_list.append(new_T2a_trunc) new_T2b_trunc_list.append(new_T2b_trunc) T3_proj_left_ket = corner_330_ket_projectors.get_projector(x, y, -1, 0)[0] T3_proj_left_bra = corner_330_bra_projectors.get_projector(x, y, -1, 0)[0] T3_proj_right_bra = corner_330_bra_projectors.get_projector(x, y, 0, 0)[1] T3_proj_right_ket = corner_330_ket_projectors.get_projector(x, y, 0, 0)[1] new_T3 = apply_contraction_jitted( "triangular_ctmrg_split_T3_absorption", [working_tensor], [working_tensor_obj], [ T3_proj_left_ket, T3_proj_left_bra, T3_proj_right_bra, T3_proj_right_ket, ], ) new_T3a, new_T3b, new_T3a_trunc, new_T3b_trunc = decompose_new_T( new_T3, working_tensor_obj.chi, truncation_eps, config ) new_T3a_list.append(new_T3a) new_T3b_list.append(new_T3b) new_T3a_trunc_list.append(new_T3a_trunc) new_T3b_trunc_list.append(new_T3b_trunc) T4_proj_left_ket = corner_270_ket_projectors.get_projector(x, y, 0, 0)[0] T4_proj_left_bra = corner_270_bra_projectors.get_projector(x, y, 0, 0)[0] T4_proj_right_bra = corner_270_bra_projectors.get_projector(x, y, 0, -1)[1] T4_proj_right_ket = corner_270_ket_projectors.get_projector(x, y, 0, -1)[1] new_T4 = apply_contraction_jitted( "triangular_ctmrg_split_T4_absorption", [working_tensor], [working_tensor_obj], [ T4_proj_left_ket, T4_proj_left_bra, T4_proj_right_bra, T4_proj_right_ket, ], ) new_T4a, new_T4b, new_T4a_trunc, new_T4b_trunc = decompose_new_T( new_T4, working_tensor_obj.chi, truncation_eps, config ) new_T4a_list.append(new_T4a) new_T4b_list.append(new_T4b) new_T4a_trunc_list.append(new_T4a_trunc) new_T4b_trunc_list.append(new_T4b_trunc) T5_proj_left_ket = corner_210_ket_projectors.get_projector(x, y, 0, 0)[0] T5_proj_left_bra = corner_210_bra_projectors.get_projector(x, y, 0, 0)[0] T5_proj_right_bra = corner_210_bra_projectors.get_projector(x, y, -1, -1)[1] T5_proj_right_ket = corner_210_ket_projectors.get_projector(x, y, -1, -1)[1] new_T5 = apply_contraction_jitted( "triangular_ctmrg_split_T5_absorption", [working_tensor], [working_tensor_obj], [ T5_proj_left_ket, T5_proj_left_bra, T5_proj_right_bra, T5_proj_right_ket, ], ) new_T5a, new_T5b, new_T5a_trunc, new_T5b_trunc = decompose_new_T( new_T5, working_tensor_obj.chi, truncation_eps, config ) new_T5a_list.append(new_T5a) new_T5b_list.append(new_T5b) new_T5a_trunc_list.append(new_T5a_trunc) new_T5b_trunc_list.append(new_T5b_trunc) T6_proj_left_bra = corner_150_bra_projectors.get_projector(x, y, 0, 0)[0] T6_proj_left_ket = corner_150_ket_projectors.get_projector(x, y, 0, 0)[0] T6_proj_right_ket = corner_150_ket_projectors.get_projector(x, y, -1, 0)[1] T6_proj_right_bra = corner_150_bra_projectors.get_projector(x, y, -1, 0)[1] new_T6 = apply_contraction_jitted( "triangular_ctmrg_split_T6_absorption", [working_tensor], [working_tensor_obj], [ T6_proj_left_bra, T6_proj_left_ket, T6_proj_right_ket, T6_proj_right_bra, ], ) new_T6a, new_T6b, new_T6a_trunc, new_T6b_trunc = decompose_new_T( new_T6, working_tensor_obj.chi, truncation_eps, config ) new_T6a_list.append(new_T6a) new_T6b_list.append(new_T6b) new_T6a_trunc_list.append(new_T6a_trunc) new_T6b_trunc_list.append(new_T6b_trunc) i = 0 for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: new_t = view[1, 1][0][0].copy_including_trunc() new_t.C1 = new_C1_list[i] new_t.T1a = new_T1a_list[i] new_t.T6b = new_T6b_list[i] new_t.T1a_trunc = new_T1a_trunc_list[i] new_t.T6b_trunc = new_T6b_trunc_list[i] view[1, 1] = new_t new_t = view[1, 0][0][0].copy_including_trunc() new_t.C2 = new_C2_list[i] new_t.T1b = new_T1b_list[i] new_t.T2a = new_T2a_list[i] new_t.T1b_trunc = new_T1b_trunc_list[i] new_t.T2a_trunc = new_T2a_trunc_list[i] view[1, 0] = new_t new_t = view[0, -1][0][0].copy_including_trunc() new_t.C3 = new_C3_list[i] new_t.T2b = new_T2b_list[i] new_t.T3a = new_T3a_list[i] new_t.T2b_trunc = new_T2b_trunc_list[i] new_t.T3a_trunc = new_T3a_trunc_list[i] view[0, -1] = new_t new_t = view[-1, -1][0][0].copy_including_trunc() new_t.C4 = new_C4_list[i] new_t.T3b = new_T3b_list[i] new_t.T4a = new_T4a_list[i] new_t.T3b_trunc = new_T3b_trunc_list[i] new_t.T4a_trunc = new_T4a_trunc_list[i] view[-1, -1] = new_t new_t = view[-1, 0][0][0].copy_including_trunc() new_t.C5 = new_C5_list[i] new_t.T4b = new_T4b_list[i] new_t.T5a = new_T5a_list[i] new_t.T4b_trunc = new_T4b_trunc_list[i] new_t.T5a_trunc = new_T5a_trunc_list[i] view[-1, 0] = new_t new_t = view[0, 1][0][0].copy_including_trunc() new_t.C6 = new_C6_list[i] new_t.T5b = new_T5b_list[i] new_t.T6a = new_T6a_list[i] new_t.T5b_trunc = new_T5b_trunc_list[i] new_t.T6a_trunc = new_T6a_trunc_list[i] view[0, 1] = new_t i += 1 for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: proj_90, proj_210, proj_330, smallest_S_T = calc_T_90_210_330_projectors( *_get_triangular_ctmrg_2x2_structure(peps_tensors, view), config, state ) T_90_projectors[(x, y)] = proj_90 T_210_projectors[(x, y)] = proj_210 T_330_projectors[(x, y)] = proj_330 smallest_S_list.append(smallest_S_T) proj_30, proj_150, proj_270, smallest_S_T = calc_T_30_150_270_projectors( *_get_triangular_ctmrg_2x2_structure(peps_tensors, view), config, state ) T_30_projectors[(x, y)] = proj_30 T_150_projectors[(x, y)] = proj_150 T_270_projectors[(x, y)] = proj_270 smallest_S_list.append(smallest_S_T) for x, iter_rows in working_unitcell.iter_all_rows(only_unique=True): for y, view in iter_rows: new_t = view[0, 0][0][0].copy() new_t.T1a = _post_process_CTM_tensors( jnp.tensordot( T_90_projectors.get_projector(x, y, 0, -1)[0], new_t.T1a, ((1,), (0,)), ), config, ) new_t.T1b = _post_process_CTM_tensors( jnp.tensordot( new_t.T1b, T_90_projectors.get_projector(x, y, 0, 0)[1], ((3,), (0,)), ), config, ) new_t.T2a = _post_process_CTM_tensors( jnp.tensordot( T_30_projectors.get_projector(x, y, -1, -1)[0], new_t.T2a, ((1,), (0,)), ), config, ) new_t.T2b = _post_process_CTM_tensors( jnp.tensordot( new_t.T2b, T_30_projectors.get_projector(x, y, 0, 0)[1], ((3,), (0,)), ), config, ) new_t.T3a = _post_process_CTM_tensors( jnp.tensordot( T_330_projectors.get_projector(x, y, -1, 0)[0], new_t.T3a, ((1,), (0,)), ), config, ) new_t.T3b = _post_process_CTM_tensors( jnp.tensordot( new_t.T3b, T_330_projectors.get_projector(x, y, 0, 0)[1], ((3,), (0,)), ), config, ) new_t.T4a = _post_process_CTM_tensors( jnp.tensordot( T_270_projectors.get_projector(x, y, 0, 0)[0], new_t.T4a, ((1,), (0,)), ), config, ) new_t.T4b = _post_process_CTM_tensors( jnp.tensordot( new_t.T4b, T_270_projectors.get_projector(x, y, 0, -1)[1], ((3,), (0,)), ), config, ) new_t.T5a = _post_process_CTM_tensors( jnp.tensordot( T_210_projectors.get_projector(x, y, 0, 0)[0], new_t.T5a, ((1,), (0,)), ), config, ) new_t.T5b = _post_process_CTM_tensors( jnp.tensordot( new_t.T5b, T_210_projectors.get_projector(x, y, -1, -1)[1], ((3,), (0,)), ), config, ) new_t.T6a = _post_process_CTM_tensors( jnp.tensordot( T_150_projectors.get_projector(x, y, 0, 0)[0], new_t.T6a, ((1,), (0,)), ), config, ) new_t.T6b = _post_process_CTM_tensors( jnp.tensordot( new_t.T6b, T_150_projectors.get_projector(x, y, -1, 0)[1], ((3,), (0,)), ), config, ) view[0, 0] = new_t smallest_S = jnp.linalg.norm( jnp.asarray([j for i in smallest_S_list for j in i]), ord=jnp.inf ) return working_unitcell, smallest_S