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PiX · π-sequences · MDL×DCC Research Lab

PiX — a universal MDL candidate generator

Core definition: PiX is a universal MDL candidate generator. π is not a law, prophecy, or magic shortcut. It is one generator family that can propose sequences, offsets, phases, distances, masks, textures, rhythms, levels, and schedules. MDL then decides whether any proposal is actually useful.

MDL×DCCπ-indexed structure searchFalsifiable generator familyControls required

Original seed: π-sequences as a discrete partner to Fibonacci. New frame: PiX as a universal candidate layer for MDL×DCC. Latest PiT weekend test completed: 2026-06-15.

My opinion: this is bigger than trading

Core definition
Universal MDL generator

PiX does not mean “π predicts X.” PiX means a generator of candidate descriptions, parameters, and structures that MDL can accept or reject.

Main risk
Pattern trap

π is rich enough that beautiful coincidences are easy to find. The antidote is brutal controls: random, shuffled-π, e, φ, √2, uniform, and no-generator baselines.

Best first domain
8Z / compression

Your original Pi story belongs here first: can π-addressed data plus transform plus residual describe chunks shorter than raw or ordinary compression?

Trading status
First PiT seed found

The June 2026 PiT weekend test found a weak-to-moderate positive decision-slot seed, but not a live-ready trading edge.

Clean frame: PiX is not a belief that π secretly rules the world. PiX is a disciplined family of candidate generators that MDL can test across domains.

1. Definition: PiX as a universal MDL candidate generator

Definition

PiX is π-indexed structure search. Use π as a deterministic generator of sequences, bits, numbers, phases, offsets, masks, textures, rhythms, or schedules — then let MDL measure whether this description beats ordinary descriptions and controls.

The question is not: “Is π mystical?” The question is: “Does π + parameters + transform + residual sometimes describe data or decisions shorter or more usefully than the baseline?”

MDL form

A candidate can be encoded as:

candidate = constant_id + stream_mode + offset + length + transform + residual

MDL accepts the candidate only if:

L(candidate) < L(raw/baseline)
This is the important upgrade: MDL becomes stronger when we expand the candidate universe. If PiX proposes useful generators, programs, transforms, rhythms, and residual bases, MDL can discover shorter descriptions it could not even try before.

2. Applications: PiX is not a trading idea; it is a generator family

8Z / PiScout compression

Instead of storing chunks directly, test π offset + transform + residual. Exact long matches will be rare; residual/lossy matches are the interesting part for images, audio, sensors, textures, and structured noise.

Lossy image/audio

π windows can act as deterministic texture, grain, dither, or noise beds. A candidate wins only if address + transform + residual costs less than a normal representation at the chosen quality.

Search scheduling

π schedules for restarts, mutation amplitude, beam width, zoom, explore/exploit pulses, and worker desynchronization in TSP, Sudoku, chess, crossword, ARC, and AMR arenas.

ARC / program synthesis

π can propose periods, tile sizes, masks, diagonal phases, modulo rules, or offsets. MDL then selects the shortest program that explains input → output.

TSP / geometry / routing

π is natural for angles, circles, rings, radial bins, spiral paths, polar sorting, and local-search neighborhood sizes.

Time series

Markets are only one example. The same idea can test server load, traffic, weather, sports, EEG/Muse signals, sleep/HRV, network anomalies, and energy demand.

Biology / genomics

π windows, k-mer spacings, and offsets can act as hypothesis generators or null/control families against Markov-preserving controls.

Music / generative art

π can generate rhythms, phrase lengths, notes, color palettes, camera cuts, tiling, animation phases, and deterministic creative seeds.

Watermark / provenance / AI tests

π alone is not cryptography, but it can be a public carrier when the offset is chosen by a secret key or hash. It can also create reproducible AI puzzle families.

3. Universal PiX Arena design before any domain-specific script

Before building a trading arena, the better first build is a general PiX arena. It should expose π as one generator family among many and test it against strong controls.

DomainPiX candidateControlsSuccess condition
Compressionπ offset + transform + residualraw, zstd, lzma, random streamlower MDL cost with verified reconstruction or controlled loss
Image/audioπ texture/noise/grain basisrandom noise, blue noise, standard codecssmaller residual at equal PSNR/SSIM/SNR
Optimizationπ restart / mutation / beam schedulefixed, random, Fibonacci schedulesbetter solve rate, gap, stability, or runtime
Program synthesisπ period, mask, tile, offset, modulo candidatesstandard ARC primitives + random constantsbetter train fit + leave-one-out + test prediction
Trading slotπ levels / time windows / spacingFib, uniform, random, no-levellower MAE, better rescue, better profit/risk
Design rule: π is not a favorite. It is a candidate. The arena decides when π, φ, e, √2, random, domain generators, or nothing wins.

4. First overnight arena result — June 5, 2026

The first 10-worker overnight run tested the arena itself across synthetic data, small built-in real-byte samples, planted image-residual textures, and a toy optimization scheduler. This was a stability and truthfulness run, not yet a full real-corpus test on the website/project archive.

Run scale
3,341

completed jobs · 10 workers · about 8 hours · 0 failed jobs

Synthetic self-test
100%

all jobs passed planted-signal recovery; false magic on random controls stayed at 0

Real-byte compression
0

wins vs best baseline across 686,289 chunks in the default small sample set

Scheduler toy
5.18/10

π average rank by mean score; competitive, but not the winner

TestObserved resultMeaning
Fleet stability3,341 completed jobs, 0 failures, about 79.4 serial CPU-hours compressed into one overnight fleet run.The arena harness is stable enough for the next real-corpus test.
Synthetic planted π3,341 / 3,341 jobs passed the planted-signal recovery test; random false-magic count stayed at 0.The detector can recover real planted π structure without hallucinating it on random controls.
Real byte chunks0 MDL wins vs raw/zlib/best baseline across 686,289 tested chunks. Among constants only, π was often competitive, but never enough to beat the baseline.No evidence yet that exact π byte-addressing compresses ordinary real bytes. This is a useful negative result.
Image residual toyPlanted π/φ texture signals were recovered. π produced 3,341 wins in the planted image-residual channel.Residual PiX can work when the data actually contains a π-derived texture; next step is real images/audio.
Scheduler toyπ won 351 / 3,341 jobs. φ, Fibonacci, and e won more often; π was slightly better than random by aggregate mean, but not decisively.The scheduler idea stays alive, but π is not privileged. It must remain one candidate family inside DCC.
Strong win: the scientific framing survived. PiX did not magically win everywhere; the arena separated planted signal, real-byte failure, toy residual recovery, and weak scheduler hints.
Important caution: this default run used generated small sample files, not your full Web-slim/project corpus. The next run must target real folders before making any public strength claim.
Next test: keep the universal PiX corpus work separate from PiT. Universal PiX still needs real folders and media. PiT now moves to a narrow v0.4 confirmatory trading test.

5. Core seed: π as a discrete partner to Fibonacci

The original PiX insight is simple: Fibonacci/φ already guides many natural and technical search spaces, but π may provide a different family of discrete distances, rhythms, and phase cuts.

This page keeps that seed alive while placing it inside a stricter MDL×DCC frame: build candidates first, test hard second.

Good use: π proposes candidate structures that compete against controls.

Bad use: declaring every visible match meaningful after seeing the chart.

6. PiX sequence generator

Generate π-based integer sequences and compare them with Fibonacci and powers of two. This is not proof of anything; it is a candidate factory.

The chart uses a logarithmic scale so slow and fast sequences can be compared.

Useful search angles: equality/crossing points with Fibonacci, close ratios to φ, sparse integer families, and places where PiX creates different spacing than powers of two.

7. Trading as one decision slot, not the whole idea

Trading remains a useful test bed because price data is noisy and easy to fool ourselves with. If PiX survives there against controls, that is interesting. But PiX should not be defined by trading.

PiX retracement / extension levels

Recommended PiX levels for first tests

  • 31.831% = 1/π — shallow retracement.
  • 52.360% = π/6 — radian / 30° fraction.
  • 63.662% = 2/π — near Fibonacci 61.8%, but not identical.
  • 78.540% = π/4 — deep retracement / 45° fraction.
Do not judge by chart beauty. Judge by lower MAE, better rescue, lower open-tail risk, or better profit/risk against controls.

7b. PiT weekend trading result — June 15, 2026

PiT is the trading-only branch of PiX. It does not claim that π predicts price. It tests whether π-derived spacing, timing, sizing, and profit/rescue rhythms improve specific hedge-rescue decision slots against matched controls.

Wall-clock run
68h 59m

2026-06-12 12:00 → 2026-06-15 09:00 · offline replay only · 10 workers

Rows completed
774,424

out of 783,552 planned tasks · 98.84% · 15 complete cycles + 1 deadline partial

Full-gate Pi passes
126 / 2,936

Pi candidates that passed survival, profit floor, no-slot, random-p95, and matched-control gates

Best seed
+22.927

USDT final-MTM/full-close for C009 mega_rescue_timing · phi_pi_cluster · survival 100% · ruin 0

What the weekend test says

FindingObserved resultInterpretation
Arena healthSelf-test passed; final extractor wrote 16 roots with 0 warnings; the last cycle stopped because the wall-clock deadline was reached.The weekend runner, resume/state, and slim extraction are healthy enough for the next stage.
Best Pi seedmega_rescue_timing / phi_pi_cluster in C009 produced about +22.927 USDT final-MTM/full-close, with survival 100% and ruin 0.This is the first serious PiT seed worth isolating, not just a pretty pattern.
Control pressureNearest random and matched controls were close in C009; in C015 partial, a geometric matched-control candidate beat the Pi candidate.The signal is weak-to-moderate positive, not proven. Geometric and random controls remain dangerous competitors.
Coverage gapDetailed policy manifests still under-covered some surfaces, especially rescue_add_sizing.The next build must enforce balanced slot quotas before each cycle starts.
Trading statusNo live exchange, no API keys, no orders; this was offline replay research.Interesting research signal, but not live-ready and not financial advice.
Result: PiT finally produced real full-gate Pi candidates. The strongest seed is mega-rescue timing around phi_pi_cluster.
Caution: the edge is narrow and not yet validated on fresh symbols, fresh windows, fees/slippage, or stricter controls. Do not treat it as a trading system.
Next: build PiT v0.4 as a confirmatory test, not a new broad search: isolate the C009 mega-rescue seeds, compare them against geometric/fib/random/shifted/shuffled controls, enforce balanced slot coverage, add phenotype dedupe, and rank by final-MTM/full-close survival first.

8. Time zones: π as rhythm, not only price

Time generator

What to test

Time zones are not automatically a signal. They are windows of increased attention. The test asks whether reversal, acceleration, range break, or rescue probability increases after π time zones.

Minimal time test
  1. Choose objective anchors: local swing high/low, large volume spike, liquidation wick.
  2. Generate π zones and the same number of random zones.
  3. For each zone, measure MFE/MAE, direction flip, volatility, and volume change over the next N bars.
  4. Compare π against random and Fibonacci time zones.

9. Test protocol: how to stop PiX from becoming a pattern trap

Controls

Every PiX candidate must compete against Fibonacci, e, √2, √3, Champernowne, uniform, random, shuffled-π, and no-generator controls. Without this, coincidence will look like signal.

MDL score

A beautiful hit does not count. Only L(generator + params + residual) against the best baseline counts. If the residual eats the saving, PiX loses.

Decision slots

PiX should first compete in small slots: chunk predictor, residual basis, restart rhythm, tile/mask generator, TP ladder, rescue window, veto cone.

Best first experiments

DomainPiX candidateControlSuccess meaning
8Z compressionπ offset + transform + residualraw, zstd, lzma, random streamsmaller verified encoding or equal-quality lossy residual
Image/audioπ texture/noise basisrandom noise + standard codecssmaller residual at same PSNR/SSIM/SNR
TSP/Sudoku/ARCπ restart / period / tile / mask candidatesfixed + Fib + randombetter solve rate, MDL score, or test prediction
Trading slotπ retracement/time/add spacingFib + uniform + randomlower MAE, better rescue, better profit/risk

10. PiX roadmap

PiX v1 — page/tool: generate sequences, levels, time zones, CSV/JSON export. This version defines PiX as a universal MDL candidate generator.
PiX v2 — Universal Arena: Python arena for exact match, residual compression, lossy media, optimization schedules, ARC constants, and decision slots.

PiX v3 — 8Z adapter

PiX becomes one MATH/generator family in 8Z: constant_id=π, offset, transform, residual, hash verification, MDL gate.

PiX v4 — DCC selector

DCC learns when to use π, when to use φ, e, √2, random, a domain generator, or nothing. PiX must be a candidate, not a favorite.

PiX v5 — public research note

Once results exist: “PiX: π as a falsifiable MDL candidate generator across compression, search, signals, and decision slots.”

Kill condition: if PiX does not beat good controls, do not force it. It remains useful as a creative/visual generator, not as an empirical advantage.
Final sentence: “PiX tests whether π-derived sequences, ratios, phases, offsets, and streams can form a disciplined family of candidate generators that MDL can accept or reject against strong controls.”