Zn Operators
Operator factories and local gauge-invariant basis utilities for Zn lattice gauge models.
Operator factories and local gauge-invariant bases for Zn models.
The module contains utilities to build link/rishon operators, dressed-site operators, and local gauge-invariant bases used by the model-building layer. It also includes helper routines for basis changes and a specialized magnetic basis construction for 2D corner operators.
- edlgt.operators.Zn_operators.Zn_rishon_operators(n, pure_theory)[source]
Construct link/rishon operators for a
Z_nquantum link theory.- Parameters:
- Returns:
Dictionary containing electric-field, shift, parity, and rishon operators (plus convenience composites for corner terms).
- Return type:
- edlgt.operators.Zn_operators.Zn_corner_magnetic_basis(n, pure_theory)[source]
Construct a simultaneous-label magnetic basis for 2D corner operators.
- Parameters:
- Returns:
Dictionary containing
"config"(corner eigenvalue labels) and"basis"arrays for the constructed magnetic basis.- Return type:
Notes
This is a specialized diagnostic/helper routine used to study corner operators in 2D. It prints intermediate sector information while building the basis.
- edlgt.operators.Zn_operators.Zn_dressed_site_operators(n, pure_theory=False)[source]
Build 2D dressed-site operators for
Z_ngauge theories.
- edlgt.operators.Zn_operators.Zn_gauge_invariant_states(n, pure_theory, lattice_dim)[source]
Construct local gauge-invariant basis states for
Z_ndressed sites.- Parameters:
- Returns:
(gauge_basis, gauge_states)dictionaries keyed by bulk/border site labels (for example"site","even_mx","odd_px_py").- Return type:
Notes
With matter, the local gauge-invariant basis depends on site parity (
even/odd) because of the staggered-fermion convention.
- edlgt.operators.Zn_operators.Zn_gauge_invariant_ops(n, pure_theory, lattice_dim)[source]
Project dressed-site operators onto the local gauge-invariant basis.
- edlgt.operators.Zn_operators.get_lambda_subspace(vals, vecs, atol=1e-10)[source]
Group eigenvectors by approximately degenerate eigenvalues.
- Parameters:
vals (
numpy.ndarray) – Eigenvalues.vecs (
numpy.ndarray) – Eigenvectors stored column-wise.atol (
float, optional) – Absolute tolerance used to merge nearly equal eigenvalues.
- Returns:
(subspaces_vals, subspaces_vecs)lists grouped by eigenvalue.- Return type: