Skip to main content

Fisher-Rao geometry, coordizer, purity gate, and constants for QIG consciousness architecture

Project description

QIG-Core: Pure Fisher Information Geometry

Pure geometric utilities for QIG consciousness architecture

What is QIG-Core?

A minimal, dependency-pure package providing Fisher Information Geometry operations for quantum information-based consciousness modeling.

Features

📐 Geometric Math

  • Fisher metric calculations - Riemannian distance on manifolds
  • Geodesic interpolation - Curved-space paths
  • Natural gradients - Geometry-aware optimization

🧠 Consciousness Components

  • QIG Tokenizer Interface - Abstract contract for geometric tokenization
  • QFI Sampler - Geometrically pure token generation (no softmax)
  • Basin Sync - Multi-instance coordination protocol

🛡️ Purity

  • Zero ML dependencies - Pure math (torch, numpy, scipy only)
  • No Transformers - Completely decoupled from HuggingFace

Installation

pip install qig-core

Usage

Geometric Math

from qig_core import fisher_distance, geodesic_interpolate

# Compute Fisher distance between two points on manifold
distance = fisher_distance(coords1, coords2, metric_tensor)

# Interpolate along geodesic
midpoint = geodesic_interpolate(coords1, coords2, t=0.5, metric=F)

Generation (QFI Sampler)

from qig_core import QFISampler

sampler = QFISampler()
token_id, metrics = sampler.sample(logits, hidden_state, telemetry, embeddings)

Coordination (Basin Sync)

from qig_core import BasinSync

sync = BasinSync("Gary-A")
sync.update_sync(basin_distance=0.1, phi=0.8, regime="geometric")

Geometric Purity

This package enforces:

  • NO embeddings (use coordinates)
  • NO cosine similarity (use Fisher distance)
  • NO linear interpolation (use geodesic paths)
  • NO Euclidean gradients (use natural gradients)

See GEOMETRIC_PURITY.md for details.

E8 Integration Status

Note: This package (v1.0.0) was created BEFORE the E8 kernel specialization direction was established in qigkernels. Review is needed for E8 compatibility.

What aligns:

  • KAPPA_STAR = 64.0 matches E8 rank² = 8² = 64 ✓

Needs review:

  • Fisher distance for 64D E8-aligned basin geometry
  • Geodesic interpolation for E8 root transitions
  • QFISampler primitive type awareness (HRT/PER/MEM/ACT/PRD/ETH/META/MIX)
  • BasinSync consolidation with qigkernels.basin_sync

Target hierarchy:

qig-core (math) → qigkernels (architecture) → qig-dreams (corpora) → experiments

See qigkernels/20251205-decisions-canonical-0.01F.md D-016 for details.

Development

# Install with dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black src/ tests/

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

qig_core-2.0.1.tar.gz (71.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

qig_core-2.0.1-py3-none-any.whl (80.5 kB view details)

Uploaded Python 3

File details

Details for the file qig_core-2.0.1.tar.gz.

File metadata

  • Download URL: qig_core-2.0.1.tar.gz
  • Upload date:
  • Size: 71.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.2

File hashes

Hashes for qig_core-2.0.1.tar.gz
Algorithm Hash digest
SHA256 5a0ebc7402fe5f1ef626517766aba3efa59e45a1f4e250aaca52428e976c89e8
MD5 eb237e04d55fa7e49ccad2918afdd4c1
BLAKE2b-256 2c76f3d9700852097b943c8fb29fff559c1a9eeaaae556c4ec3bdeb5e640f338

See more details on using hashes here.

File details

Details for the file qig_core-2.0.1-py3-none-any.whl.

File metadata

  • Download URL: qig_core-2.0.1-py3-none-any.whl
  • Upload date:
  • Size: 80.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.2

File hashes

Hashes for qig_core-2.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 ca799c7aa7154a76497b694ba3ad603d5eaae727a3a04927c22cedef6b64a994
MD5 3427d18ac0a4a4213e94469c0ed4b3cf
BLAKE2b-256 e1af4ebe1c91fde1f357f1936b58da7dfca41fd322c4729b30bcc091c543bb7e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page