Fast compute engine for QIG geometry — analytical QFI, GPU contractions, observable governance
Project description
qig-compute
Fast compute engine for QIG geometry — analytical QFI, GPU contractions, observable governance.
Install
pip install qig-compute # numpy only
pip install qig-compute[tenpy] # + TeNPy for MPS-QFI
pip install qig-compute[gpu] # + CuPy for GPU acceleration
pip install qig-compute[full] # everything
Usage
from qig_compute.qfi_analytical import qfi_analytical, qfi_with_governance
# Compute QFI from a single MPS ground state (zero DMRG loops)
F = qfi_analytical(psi_mps, L=6, sites=pruned_sites)
# With governance checks (warns about blindspots, auto-fills cheap measurements)
F, report = qfi_with_governance(psi_mps, L=6, h=1.0, J=1.0)
print(report.summary())
Observable Governance
Built-in blindspot detection warns when:
- Results only tested in one regime
- Observable amplitude collapses (wrong channel)
- FFT frequency at resolution floor
- DMRG bond dimension at limit
- Energy gap not measured (auto-fills if cheap)
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