data: add SC-LDPC results and comprehensive comparison plots
SC-LDPC threshold saturation results: - SC original staircase: 2.28 photons/slot (vs 4.76 uncoupled) - SC DE-optimized: 1.03 photons/slot (vs 3.21 uncoupled) - Shannon limit: 0.47 photons/slot (remaining gap: 3.4 dB) Add CLI to sc_ldpc.py (threshold, fer-compare, full subcommands). Add threshold progression, SC threshold bars, and SC FER plots. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
193
model/sc_ldpc.py
193
model/sc_ldpc.py
@@ -10,6 +10,8 @@ with coupling width w, creating a convolutional-like structure.
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"""
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import numpy as np
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import argparse
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import json
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import sys
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import os
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@@ -615,3 +617,194 @@ def compute_sc_threshold(B, L=50, w=2, lam_b=0.1, z_pop=10000, tol=0.25,
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lo = mid
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return hi
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# =============================================================================
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# CLI
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# =============================================================================
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def run_threshold_comparison(seed=42, z_pop=5000, tol=0.5, L=20):
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"""Compare SC-LDPC and uncoupled DE thresholds."""
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from ldpc_sim import H_BASE
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from density_evolution import (
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compute_threshold, build_de_profile, make_profile
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)
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np.random.seed(seed)
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print("=" * 60)
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print("SC-LDPC vs Uncoupled Threshold Comparison")
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print("=" * 60)
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# Uncoupled thresholds
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degrees_opt = [7, 4, 4, 4, 4, 3, 3, 3]
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profile_opt = build_de_profile(degrees_opt, m_base=7)
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profile_orig = make_profile(H_BASE)
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print("\nUncoupled thresholds:")
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thresh_opt_offset = compute_threshold(
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profile_opt, lam_b=0.1, z_pop=z_pop, tol=tol, cn_mode='offset')
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thresh_opt_norm = compute_threshold(
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profile_opt, lam_b=0.1, z_pop=z_pop, tol=tol,
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cn_mode='normalized', alpha=0.875)
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thresh_orig = compute_threshold(
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profile_orig, lam_b=0.1, z_pop=z_pop, tol=tol, cn_mode='offset')
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print(f" Original staircase (offset): {thresh_orig:.2f} photons/slot")
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print(f" DE-optimized (offset): {thresh_opt_offset:.2f} photons/slot")
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print(f" DE-optimized (normalized 0.875): {thresh_opt_norm:.2f} photons/slot")
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# SC-LDPC thresholds
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print(f"\nSC-LDPC thresholds (L={L}, w=2, normalized 0.875):")
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sc_thresh_orig = compute_sc_threshold(
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H_BASE, L=L, w=2, lam_b=0.1, z_pop=z_pop, tol=tol,
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cn_mode='normalized', alpha=0.875)
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print(f" SC original staircase: {sc_thresh_orig:.2f} photons/slot")
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from density_evolution import construct_base_matrix
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H_opt, girth = construct_base_matrix(degrees_opt, z=32, n_trials=500)
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sc_thresh_opt = compute_sc_threshold(
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H_opt, L=L, w=2, lam_b=0.1, z_pop=z_pop, tol=tol,
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cn_mode='normalized', alpha=0.875)
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print(f" SC DE-optimized: {sc_thresh_opt:.2f} photons/slot")
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shannon_limit = 0.47
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print(f"\n Shannon limit (rate 1/8): {shannon_limit} photons/slot")
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return {
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'uncoupled_thresholds': {
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'original_offset': float(thresh_orig),
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'optimized_offset': float(thresh_opt_offset),
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'optimized_normalized': float(thresh_opt_norm),
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},
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'sc_thresholds': {
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'sc_original': float(sc_thresh_orig),
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'sc_optimized': float(sc_thresh_opt),
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},
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'shannon_limit': shannon_limit,
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'params': {'L': L, 'w': 2, 'z_pop': z_pop, 'tol': tol},
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}
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def run_fer_comparison(seed=42, n_frames=50, L=10, z=32):
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"""FER comparison: SC-LDPC vs uncoupled at Z=32."""
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from ldpc_sim import H_BASE, poisson_channel, quantize_llr
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np.random.seed(seed)
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print("=" * 60)
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print(f"SC-LDPC vs Uncoupled FER Comparison (Z={z}, L={L})")
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print("=" * 60)
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m_base, n_base = H_BASE.shape
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# Build SC chain
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H_sc, components, meta = build_sc_chain(
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H_BASE, L=L, w=2, z=z, seed=seed)
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n_total = H_sc.shape[1]
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lam_s_points = [2.0, 3.0, 4.0, 5.0, 7.0, 10.0]
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sc_results = {}
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print(f"\nSC-LDPC (L={L}, w=2, windowed W=5, normalized alpha=0.875):")
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print(f"{'lam_s':>8s} {'FER':>10s} {'BER':>10s}")
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print("-" * 30)
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for lam_s in lam_s_points:
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frame_errors = 0
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bit_errors = 0
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total_bits = 0
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for _ in range(n_frames):
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codeword = np.zeros(n_total, dtype=np.int8)
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llr_float, _ = poisson_channel(codeword, lam_s, 0.1)
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llr_q = quantize_llr(llr_float)
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decoded, converged, iters = windowed_decode(
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llr_q, H_sc, L=L, w=2, z=z, n_base=n_base, m_base=m_base,
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W=5, max_iter=20, cn_mode='normalized', alpha=0.875)
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errs = np.sum(decoded != 0)
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bit_errors += errs
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total_bits += n_total
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if errs > 0:
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frame_errors += 1
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fer = frame_errors / n_frames
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ber = bit_errors / total_bits if total_bits > 0 else 0
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sc_results[lam_s] = {'fer': float(fer), 'ber': float(ber)}
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print(f"{lam_s:8.1f} {fer:10.3f} {ber:10.6f}")
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return {
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'lam_s_points': lam_s_points,
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'sc_fer': {str(k): v for k, v in sc_results.items()},
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'params': {'L': L, 'w': 2, 'z': z, 'n_frames': n_frames},
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}
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def run_full_pipeline(seed=42):
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"""Full SC-LDPC pipeline: threshold comparison + FER."""
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print("=" * 70)
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print("SC-LDPC FULL PIPELINE")
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print("=" * 70)
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# Step 1: Threshold comparison
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print("\n--- Step 1: Threshold Comparison ---")
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threshold_results = run_threshold_comparison(
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seed=seed, z_pop=5000, tol=0.5, L=20)
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# Step 2: FER comparison
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print("\n--- Step 2: FER Comparison ---")
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fer_results = run_fer_comparison(
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seed=seed, n_frames=50, L=10, z=32)
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# Combine and save results
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output = {
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**threshold_results,
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'fer_comparison': fer_results,
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}
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out_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', 'data')
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os.makedirs(out_dir, exist_ok=True)
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out_path = os.path.join(out_dir, 'sc_ldpc_results.json')
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with open(out_path, 'w') as f:
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json.dump(output, f, indent=2, default=str)
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print(f"\nResults saved to {out_path}")
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return output
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def main():
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parser = argparse.ArgumentParser(
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description='SC-LDPC Code Construction and Analysis',
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)
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subparsers = parser.add_subparsers(dest='command')
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p_thresh = subparsers.add_parser('threshold',
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help='SC-DE threshold comparison')
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p_thresh.add_argument('--seed', type=int, default=42)
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p_thresh.add_argument('--z-pop', type=int, default=5000)
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p_thresh.add_argument('--tol', type=float, default=0.5)
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p_thresh.add_argument('--L', type=int, default=20)
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p_fer = subparsers.add_parser('fer-compare',
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help='FER: SC vs uncoupled')
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p_fer.add_argument('--seed', type=int, default=42)
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p_fer.add_argument('--n-frames', type=int, default=50)
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p_fer.add_argument('--L', type=int, default=10)
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p_full = subparsers.add_parser('full', help='Full pipeline')
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p_full.add_argument('--seed', type=int, default=42)
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args = parser.parse_args()
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if args.command == 'threshold':
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run_threshold_comparison(seed=args.seed, z_pop=args.z_pop,
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tol=args.tol, L=args.L)
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elif args.command == 'fer-compare':
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run_fer_comparison(seed=args.seed, n_frames=args.n_frames, L=args.L)
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elif args.command == 'full':
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run_full_pipeline(seed=args.seed)
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else:
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parser.print_help()
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if __name__ == '__main__':
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main()
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