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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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