hcphases 0.3.2

hcphases computes equilibrium expectations for supported homological-code models using finite-imaginary-time Monte Carlo. It provides model and observable declarations, tunable sampling plans, independent chains, resource-bounded execution, checkpoints, saved-state audits and statistical diagnostics.

Choose a reading path

The user and maintainer guides share the theory reference’s conventions for projectors, couplings, cells, imaginary time, logical shifts and observables.

Implemented scope

There are two public execution interfaces:

Interface

Models

Observables and execution

ModelSpec and plan / run

Binary periodic cubical codes with d >= 2, 1 <= p < d; uniform couplings and a finite Trotter representation.

Local Pauli operators, strings, Wilson and ‘t Hooft cycles, supported decoded cycles, products and connected correlators. Z and X families use separate source/dual ensembles.

VertexModel and run_vertex

Binary d=1, p=0 circle code with positive K,g,T, no J term and exactly zero longitudinal source.

Spacetime Wilson point products and magnetization moments. A fixed-attempt single-cluster sampler on a periodic spacetime torus.

Bounded execution currently requires Windows and one sampling worker. The package requires Python 3.12, NumPy and PyYAML. Declarations and suitable low-level calculations can be used without launching the Windows executor. General-N source declarations are available, while Monte Carlo execution is binary. See Choose and define a model for the complete support matrix.

Successful execution certifies a completed computational workflow. The caller must assess equilibration, Monte Carlo uncertainty, finite-volume effects and finite-M effects for the scientific question being studied.

Further reference