Research-Stack/6-Documentation/docs/compression_signal_shaping_synthesis.md
2026-05-11 22:18:31 -05:00

5.7 KiB

Compression Signal-Shaping Synthesis

Date: 2026-05-08

Runner:

4-Infrastructure/shim/compression_signal_shaping_synthesis.py

Receipt:

4-Infrastructure/shim/compression_signal_shaping_synthesis_receipt.json

Receipt hash:

fc06057b20dc2281161e7380a63557171ab4d87ee7a82277fe2e8d74b1446f68

Primary Read

Across the local compression, compressed-sensing, signal-root, semantic-topology, and docmd payload notes, the new pattern is not another universal compressor.

The new pattern is:

signal-shaped route compiler

Shape the route space before coding, then pay exact residual, witness, decoder, and container bytes after coding.

Approach Classes

PAQ-style context mixing
  shapes probability context

decision-diagram route search
  shapes candidate route space

T16 candidate pipeline
  shapes weak event detection

Phi response-family selection
  shapes response curve

nonlinear compressed sensing
  shapes regular nonlinear measurement maps

generative compressed sensing
  shapes latent proposal manifold

invertible generative inverse priors
  shapes invertible / flow charts

holographic fractional recursive fold
  shapes boundary descriptor and bounded memory

signal invariant roots
  shapes signal morphology feature space

semantic topology regimes
  shapes fold / prune / tear decisions

LLM control-plane compression
  shapes prompt / logogram / metaprobe representation

docmd static payload strategy
  shapes runtime payload

What New Pops Up

N1 Signal-Shaped Route Compiler

Combine signal invariant roots with decision-diagram route search:

chunk
  -> feature vector
  -> route family
  -> codec trial
  -> exact residual

Candidate equation:

route =
  argmin_r LB(r | phi_signal(chunk), topology_regime, history_state)

First test:

wiki8 chunk sweep with:
  entropy
  XML tag density
  DCT energy
  transient edges
  autocorrelation
  cosine reuse

Promotion gate:

chosen route beats bz2 / zstd baseline after feature and witness bytes

N2 Runtime Staticization As Compression Prepass

Use the docmd lesson:

do not ship branches you can rebuild

Candidate shape:

tiddlers / articles
  -> static route pages
  -> external search index
  -> manifest

First test:

build a small TiddlyWiki / article slice as both live and static outputs
compare initial gzip payload and search-index cost

N3 Witness-Budgeted Latent Route

Generative and invertible models should only propose routes:

latent z proposes transform
exact residual repairs
uncertainty decides hold

Cost:

C =
  bytes(z)
  + bytes(model_id)
  + bytes(residual)
  + bytes(witness)
  + bytes(decoder)

Promotion gate:

C < incumbent
and decoded hash equals source hash

N4 Fractional History Route Scheduler

Use bounded memory for nonstationary corpus regions:

h_t =
  sum_{tau<t, window W}
    K_alpha(t - tau) * residual_tau

route_t =
  R(chunk_t, h_t)

Promotion gate:

history bytes counted
and total compressed size improves

N5 Topology Regime Guard

Use semantic topology before tokenbook merges:

beautiful  -> fold
ugly       -> prune
horrible   -> isolate / hold

Candidate classifier:

regime =
  classify(invariant_overlap, torsion, round_trip_loss, contradiction)

Promotion gate:

fewer bad merges without losing byte wins

N6 Physical Signal Probe Feedback

Borrow the CAD-force-probe habit for compression routes:

route hypothesis
  -> measurable perturbation
  -> negative control
  -> receipt

Promotion gate:

positive route beats baseline
and matched negative control fails or underperforms

Unifying Equations

Signal feature vector:

phi_signal(c) =
  [
    H(c),
    tag_density(c),
    DCT_energy(c),
    transient(c),
    autocorr(c),
    cosine_reuse(c)
  ]

Route selection:

r* =
  argmin_r LB(r | phi_signal(c), semantic_regime(c), history_state)

Exact cost:

C_total =
  bytes(payload)
  + bytes(sidecar)
  + bytes(residual)
  + bytes(decoder)
  + bytes(witness)
  + bytes(container)

Promotion:

promote iff
  H(decode(r*)) == H(source)
  and C_total < incumbent
  and failure_rules == none

Negative control:

valid_gain iff
  C(candidate) < C(baseline)
  and C(candidate) < C(matched_bad_route)

Immediate Experiment Ladder

E1 wiki8_signal_feature_baseline
  extract per-chunk signal features and compare feature clusters to codec outcomes

E2 route_classifier_without_new_codec
  choose among existing routes only: raw, bz2, zstd, xml_token+bz2, tokenbook+bz2

E3 topology_guard_tokenbook
  apply semantic / topology guards before tokenbook merge

E4 docmd_static_wiki_slice
  export a small tiddler / article slice to static pages plus external index

E5 bounded_history_scheduler
  route stream chunks with finite fractional residual memory

Failure Rules

feature score treated as byte gain                         -> invalid
sidecar / witness / residual / decoder bytes omitted       -> invalid receipt
latent or generative prior used as hidden source payload    -> invalid
semantic merge without round-trip / contradiction check     -> hold
history kernel unbounded or uncounted                       -> fail closed
docmd-style staticization reported as Hutter compression    -> overclaim
negative controls omitted from new route claim              -> weak claim

Claim Boundary

This synthesis proposes testable route-shaping experiments. It is not a Hutter Prize result, not proof of a new compressor, and not a guarantee that signal features will improve wiki8.