HK-Core: Autonomous Lattice Field Theory Engine

Autonomous lattice gauge simulation engine in Rust. Baseline: 2D U(1). Experimental: 3D SU(2) pure gauge (branch su2-3d).

Status: VALIDATED (Autonomous mass-gap-like threshold check confirmed at L=64 (2D)) License: GNU AGPLv3

Overview

HK-Core is a high-performance, autonomous simulation engine written in Rust. It implements a 2D U(1) Lattice Gauge Theory kernel as a proof-of-concept to demonstrate an industrial-grade architecture for automated scientific discovery.

Unlike traditional academic codes that output raw data for manual analysis, HK-Core acts as an autonomous scientific instrument. It incorporates an internal decision engine that performs statistical blocking, self-calibrates via Jackknife resampling, and issues binary threshold verdicts without human intervention.

Key Capabilities

1. Autonomous Decision Making: Implements an IR Dominance strategy (verdict_mode="ir_lmax"), prioritizing the infrared signal at L=64 (2D lattice) to filter out finite-volume noise.
2. Rigorous Statistics: Native implementation of APE Smearing and Jackknife Blocking to isolate signals from Monte Carlo noise.
3. Physical Integrity: Runtime diagnostics for Reflection Positivity and Translation Invariance scaling.
4. Reproducibility: Deterministic outcomes verified across independent seeds (777, 111, 1234).

Validation

For the validated configuration (beta=2.0, step_size=0.06, n_thermal_sweeps=2000, n_sweeps=60000, measure_every=10, ls=[8,16,32,64], plateau_mode="stat", verdict_mode="ir_lmax"), seeds 777, 111, 1234 reproduce:

• final_verdict.ir_lmax.per_m0["m0=0.1"] == "compatible"

Interpretation: "compatible" for m0=0.1 means mean - k_sigma*std > 0.1 with k_sigma=2.0, plateau_width>=6, and (in plateau_mode="stat") a chi2_ok=true safeguard.

See Releases for canonical JSON datasets + checksums (outputs are not committed under out/).

Tracked results

Small canonical outputs are also tracked under results/ for quick inspection:

• 2D baseline (seeds 777/111/1234): results/2d_u1/beta2_seed777_s60000_stat_ir_lmax.json
• 3D references (U(1) dim-check, SU(2) IC/IR instrumentation): results/README.md

Architecture

See ARCHITECTURE.md for the system map (pipelines, contracts, branch strategy).

Run locally

export AUTH_TOKEN=devtoken
export RUST_LOG=info
cargo run --release

IR-Lmax check (m0=0.1)

curl -sS -X POST "http://127.0.0.1:8080/mill/refine" \
  -H "Authorization: Bearer devtoken" \
  -H "Content-Type: application/json" \
  -d '{
    "ls": [8,16,32,64],
    "beta": 2.0,
    "n_thermal_sweeps": 2000,
    "n_sweeps": 60000,
    "measure_every": 10,
    "step_size": 0.06,
    "seed": 777,
    "verdict_mode": "ir_lmax",
    "plateau_mode": "stat"
  }' \
| python3 - <<'PY'
import sys, json
d=json.load(sys.stdin)
v=d["result"]["final_verdict"]
ir=v.get("ir_lmax",{})
per=ir.get("per_m0",{})
print("IR_LMAX m0=0.1:", per.get("m0=0.1"))
print("L:", ir.get("l"), "channel:", ir.get("channel"), "width:", ir.get("plateau_width"),
      "mean:", ir.get("m_eff_mean"), "std:", ir.get("m_eff_std"), "chi2_ok:", ir.get("chi2_ok"))
PY

Repo hygiene

• Build artifacts live in target/ and are ignored via .gitignore.
• Experiment outputs live in out/ and are ignored; publish “canonical” outputs as GitHub release assets instead.

License

Licensed under the GNU AGPLv3. See LICENSE.