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142 changes: 142 additions & 0 deletions research/bit-ambient-quotient/PROOF.md
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# Construction and proof obligations

## 1. Exact predecessor and changed object

The input is PR589's regenerated E8 word at
`research/kappa-rebuild/bit/sources/pr589-regenerated`: `WORD.json.gz` (pinned by
SHA-256 `e3e301e62bc2b41dbf1ceac0acf3d35824ebeab1848c5a2142d4577b109da52f`, which
matches `mixed_productive_bit.py`'s own `WORD_HASH`), `records/frames.json`
(636 frames stored by annihilator rows) and `records/249-records.bin` (249
records, `<6i`: `op, x, y, c, f, z`). The local record interpreter and the
declared local bill `{1:1323, 2:1342, 3:79, 4:44, 5:102, 6:11, 7:19}` are those of
`research/kappa-rebuild/bit/mixed_productive_bit.py`.

There are 661 persistent fields: `2V = 222` main fields and `R = 439` helpers, in
an eight-axis ambient. A frame's dimension is the dimension of the GF(2) nullspace
of its annihilator rows; frame 1 is the full ambient.

The changed object is the ambient. For a kernel subspace `K` of dimension `k` with
annihilator basis `r_1..r_(8-k)`,

```
phi : F2^8 -> F2^(8-k), phi(x)_i = r_i . x
```

`phi` is linear and surjective with kernel exactly `K`. `build.py` maps every
frame's vector set through `phi`, deduplicates each image basis by exact GF(2)
rank, identifies frames with equal image, and rewrites every role boundary and
every record's frame fields. Every MOVE rank is recomputed as
`dim(image(destination)) - dim(image(source))`. The record order, the ADD/COPY
structure and every helper boundary are otherwise unchanged.

The kernel is `span{150, 102, 255}`, dimension 3. It is not chosen by hand:
`scan_kernels.py` prices the dimension ladder and samples the solids. The value is
a plateau in the dimension — 445 of 455 sampled three-dimensional kernels replay
and all price at 0.032249423394893.

## 2. Frame-coordinate invariant under the quotient

A field at frame `F` carries the frame operator `C_F`; a chosen frame `E subset F`
carries `C_E`, and the paid transport between them has rank `dim F - dim E`.
Because `phi` is linear, `E subset F` implies `phi(E) subset phi(F)`, so every
nesting the records rely on survives and the transport's rank becomes
`dim phi(F) - dim phi(E)`.

The induction is unchanged: at each scalar step the participating fields are moved
into the operation's declared frame, and a scalar linear combination commutes with
a common frame operator, so the logical step is the same before and after the
quotient. The replay checks that directly — the arbitrary-column test and the
endpoint test are frame-independent value tests, and both are exact in both
directions.

No MOVE is lengthened, since `dim phi(F) <= dim F` for every `F`; a move is
shortened by the number of kernel dimensions its destination meets minus the number
its source meets.

## 2b. Re-padding the full ambient and the block

The tensor block is `ambient - 1`, and the block-7 ladder charge is correct only if
the word's ambient is eight-dimensional. The quotient leaves `k` axes unused, so
`build.py` re-pads the full-ambient image with all `k` of them: the 5-dimensional
image becomes the whole of `F2^8` again. Every role that ended at the full ambient
ends there again, so helper finals are dimension 8, helper ranks are preserved, and
the ambient is eight axes.

## 3. Complete local bill

Read off the replay:

```
emitted {1:1323, 2:1342, 3:79, 4:44, 5:102, 6:11, 7:19} mass 5,129
quotient {1:1020, 2:495, 3:75, 4:442, 5:143, 6:4, 7:12, 8:2} mass 4,842
```

The paid mass falls by 287 ranks per call and its shape shifts into ranks 4 and 5.
With the frontier's sixteen-stage controller, eighteen thick calls, fifteen thin
queries, `ports = 111` and `block = 7`:

```
targets = 63,216 (helpers) + 154,290 (ladder) = 217,506
paid = 18*paid_mass + 1,665 (thin) + 122,766 (idles)

emitted 217,506 - (18*5,129 + 1,665 + 122,766) = 753
quotient 217,506 - (18*4,842 + 1,665 + 122,766) = 5,919
```

The two-constraint screen gives

```
emitted BIT kappa = 0.003464248972 (the frontier's declared BIT value)
quotient BIT kappa = 0.032249423394893 (+830.92% over the emitted word)

Against this package's own one-dimensional quotient, the frontier base
0.012401086416, the step is +160.05%.
```

## 3b. Where the composition stands

The frontier base for this package is its own one-dimensional quotient,
0.012401086416. With the complex supplier at 0.015637149091
(`research/complex-ambient-quotient`) and the BIT supplier now at
0.032249423394893, the outer `min(complex, BIT)` is the complex side. The BIT is no
longer binding and has 2.06x of headroom over the complex.

The complex side cannot follow with the same construction yet: `synthesize` in
`research/fresh-helper-boundary/native.py:85` hardcodes the centre transport's rank
as `8`

```python
e = ['center', 0, e[2], second[3], 8]
```

and the centre frames are dim-8 hyperplanes, so a kernel of dimension >= 2 always
shrinks them and the stored rank stops matching the frame dimensions. The
one-dimensional complex quotient avoids this because its kernel direction misses
the centre frames. Deriving that rank instead of fixing it at 8 is the change the
complex side needs.

## 4. What is checked, and what is not

Checked by `verify.py` from the artifact and the pinned source word, with the
shipped record interpreter: 661 roles; ambient dimension 8; the kernel basis is
independent and the declared quotient width matches its dimension; no helper final
below dimension 8; all 439 helper starts at ground; both directions replay with
24,305 ADDs and 9 COPY episodes; all arbitrary input columns exact; all 661
endpoints exact; owned COPY cleanup exact; forward and backward paid profiles
identical; the source word reproduces the declared local bill; the emitted invoice
reproduces the frontier's BIT kappa; and the quotient strictly improves the screen.

Not claimed:

- This is not a multiplication theorem and not a Lean verification.
- **The outer kappa does not move here.** The complex supplier sets it; this
package moves the BIT supplier from the base 0.012401086416 to 0.032249423394893.
- **The frame charts are not preserved**: 636 frames become 65. The interpreter
validates the word's own frame record and `inventories` reads only the paid and
helper profiles, so no consumer in this tree reads the charts — but a contract
requiring particular charts would reject the word. This is the #4604 question.
- Kernel dimension 4 replays but prices worse (0.0175); the plateau break is
unexplained. Dimension 5 was not searched exhaustively.
- Only PR589's E8 word is exercised; 292 other `h = 8` words are untested.
- The admission parameters in `research/query-thinned-controllers/verify.py` are
declared literals, not functions of the supplier, and are not raised here.
Binary file not shown.
130 changes: 130 additions & 0 deletions research/bit-ambient-quotient/README.md
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# BIT supplier 0.032249423394893 by a three-dimensional ambient quotient

**Scoped finite construction with exact local replay evidence. Not a multiplication theorem.**

**Frontier base: 0.012401086416** — this package's own one-dimensional quotient, the
value the BIT branch carried before this change. The three-dimensional quotient moves
the BIT supplier from `0.012401086416` to **`0.032249423394893`**, a **+160.05%** step
on that base, and from the emitted word's `0.003464248972024` to that value,
**+830.92%** in total.

The BIT local word is PR589's E8 word: `h = 8`, `V = 111` roles per side, `R = 439`
helpers, 661 roles, 636 frames and 249 records. Frames are stored by annihilator
rows, so a frame is the GF(2) nullspace of its rows.

For a kernel subspace `K` of dimension `k`, the map

```
phi(x) = (r_1.x, ..., r_(8-k).x) over a basis r of the annihilator of K
```

is linear and surjective onto `F2^(8-k)` with kernel exactly `K`. It shrinks exactly
the frames meeting `K`, so a MOVE whose destination meets `K` in more dimensions than
its source loses that many ranks. Frames with equal image are identified, the
full-ambient image is re-padded with all `k` freed axes so every helper stays
physically `D_I8` and the tensor block stays 7, and every MOVE rank is recomputed.

## The kernel dimension is the lever

| kernel dim | kappa | vs base 0.012401086416 |
|---:|---:|---:|
| 1 | 0.012401086416 | — (the base) |
| 2 | 0.021785831250 | +75.68% |
| **3** | **0.032249423394893** | **+160.05%** |
| 4 | 0.017525188018 | +41.32% |

The submitted word uses `K = span{150, 102, 255}` (dimension 3, quotient width 5).
Of 455 sampled three-dimensional kernels, 445 replay and **all 445 price at
0.032249423394893** — the value is a plateau in the dimension, not a lucky triple.

| quantity | emitted | quotient |
|---|---:|---:|
| frames | 636 | **65** |
| frame dimensions | — | `{0:1, 1:13, 2:8, 3:25, 4:16, 5:1, 8:1}` |
| main widths | `{7: 222}` | `{4: 103, 7: 70, 8: 49}` |
| main rank mass | 1,554 | **1,294** |
| helper widths | `{8: 439}` | `{8: 439}` (start dim 0, final dim 8) |
| helper rank mass | 3,512 | 3,512 |
| paid profile | `{1:1323, 2:1342, 3:79, 4:44, 5:102, 6:11, 7:19}` | `{1:1020, 2:495, 3:75, 4:442, 5:143, 6:4, 7:12, 8:2}` |
| paid rank mass | 5,129 | **4,842** |
| rank surplus | 753 | **5,919** |
| **BIT kappa** | **0.003464248972024** | **0.032249423394893** |

## Why the quotient is legitimate

A frame meeting `K` in `j` dimensions loses exactly `j`, and nothing else moves, so
no MOVE is lengthened: `dim phi(F) <= dim F` for every `F`. The shipped local record
interpreter then replays the rewritten word with no change of its own:

| check | result |
|---|---:|
| forward replay | 24,305 ADDs, 9 COPY episodes, all 661 endpoints exact |
| reverse replay | 24,305 ADDs, 9 COPY episodes, all 661 endpoints exact |
| arbitrary input columns, both directions | exact |
| owned COPY cleanup | exact |
| helper finals at dim 8 | 439 of 439 |
| helper starts at ground | 439 of 439 |
| source word reproduces the declared bill | `{1:1323, 2:1342, 3:79, 4:44, 5:102, 6:11, 7:19}` |
| emitted BIT kappa reproduces the frontier | 0.003464248972024 |

The last two rows are the calibration: replaying the *pinned source word* through the
same interpreter reproduces the declared local bill exactly, and the emitted invoice's
screen reproduces the frontier's BIT kappa to fifteen digits. The quotient is that
same interpreter on the same records with recomputed ranks.

**The block stays 7.** The tensor block is `ambient - 1`, and the ambient is eight
axes for both words. The quotient would leave `k` axes unused, so the builder re-pads
the full-ambient image with all of them: every role that ended at the full ambient
ends there again, helper ranks are preserved, and the block-7 ladder charge is correct
rather than assumed. `verify.py` asserts `ambient_dim == 8`, an independent kernel
basis, a matching quotient width, and no helper final below 8.

## Reproduce

```sh
python3 -B research/bit-ambient-quotient/build.py # writes the artifact
python3 -B research/bit-ambient-quotient/verify.py # independent checks
python3 -B research/bit-ambient-quotient/scan_kernels.py # the dimension ladder
```

`verify.py` loads only the artifact and the pinned source word; it does not import the
builder. The two-constraint screen is inlined (tail offset `1/5`, cutoff `20`,
gamma `0.97`), so no file outside the base commit is required.

## What is not claimed

- **The outer kappa does not move in this package.** The outer value is
`min(complex, BIT)`; the complex supplier sets it.
- **The frame charts collapse**: 636 frames become 65. The interpreter validates the
word's own frame record and `inventories` reads only the paid and helper profiles,
so no consumer in this tree reads the charts — but a contract requiring particular
frame charts would reject the word (the #4604 question).
- Kernel dimension 4 replays but prices worse at 0.017525188018; the plateau break is
unexplained and recorded as an open question.
- This is not a multiplication theorem and not a Lean verification.
- Only PR589's E8 word is exercised; 292 other `h = 8` words are untested.

## Open next questions

1. **Why does dimension 4 fall back to 0.017525188018?** The mechanism is not
explained; it may be the helper re-padding or the frame nesting.
2. **Can the complex supplier follow?** It needs
`research/fresh-helper-boundary/native.py:85` to derive the centre transport's rank
instead of fixing it at `8`; with that one-line change a two- and three-dimensional
complex quotient replays, and the complex side moves too.
3. **Which consumer, if any, requires the frame charts?** This is the #4604 question,
and it decides whether any of these quotients is admissible.
4. **What admission parameters correspond to a 0.032249423394893 supplier?** The
declared literals in `research/query-thinned-controllers/verify.py` are far below
it.

## Attribution

Built on PR589's regenerated E8 word
(`research/kappa-rebuild/bit/sources/pr589-regenerated`) and the local record
interpreter and declared bill of
`research/kappa-rebuild/bit/mixed_productive_bit.py` (DreamingOfClouds / PR589,
eumemic / PR555 and PR543, and their cited lineage). The quotient construction follows
`research/complex-ambient-quotient`.

Apache-2.0; substantial AI assistance.
55 changes: 55 additions & 0 deletions research/bit-ambient-quotient/RESULT.json
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{
"ambient_dim": 8,
"directions_agree": true,
"emitted_kappa": 0.003464248972023964,
"emitted_paid": {
"1": 1323,
"2": 1342,
"3": 79,
"4": 44,
"5": 102,
"6": 11,
"7": 19
},
"emitted_paid_mass": 5129,
"emitted_surplus": 753,
"endpoint_failures": 0,
"frames": 65,
"gain_absolute": 0.02878517442286887,
"gain_relative": 8.309210641419726,
"helper_widths": {
"8": 439
},
"kernel_basis": [
150,
102,
255
],
"kernel_dimension": 3,
"local_checks": {
"adds": 24305,
"copies": 9
},
"main_rank_mass": 1294,
"main_widths": {
"4": 103,
"7": 70,
"8": 49
},
"package": "bit-ambient-quotient",
"quotient_kappa": 0.03224942339489283,
"quotient_paid": {
"1": 1020,
"2": 495,
"3": 75,
"4": 442,
"5": 143,
"6": 4,
"7": 12,
"8": 2
},
"quotient_paid_mass": 4842,
"quotient_surplus": 5919,
"roles": 661,
"status": "PASS_BIT_AMBIENT_QUOTIENT"
}
42 changes: 42 additions & 0 deletions research/bit-ambient-quotient/SOURCES.json
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{
"schema_version": 1,
"base_commit": "b9a13c1673e0e9697de410de16e8bbf3207a7363",
"files": [
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"usage": "provenance",
"git_blob": "ed33caef5c5827693e9572d252a66f99cbb73d40",
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},
{
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}
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