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135 changes: 135 additions & 0 deletions research/gaussian-tensor-nine-axis/README.md
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# One tensor axis is at most two section errors at ceiling 9

**Claim type:** a telescoping identity with an explicit one-axis norm bound.
**No new κ.** The per-axis norm bounds stay hypotheses. The selected record
remains `23/10000`.

## Question

#4506 bounds the scalar monomial

```text
2 g (9 p^2 + p^6 exp(-p^2))^{g-1} p^6 exp(-p^2)
```

and asks whether one axis of the tensor difference is at most two section
errors. The ceiling in that question is `9 p^2`.

## Lemma

Let `g ≥ 1`, and let `B_i` and `C_i` be bounded operators on Hilbert spaces.
Write `ε = p^6 exp(-p^2)` for an integer `p ≥ 2`. Suppose that for every axis

```text
||B_i|| ≤ 9 p^2,
||C_i|| ≤ 9 p^2 + ε,
||B_i - C_i|| < 2 ε,
```

and that `||X ⊗ Y|| = ||X|| ||Y||`. Then

```text
⊗_i B_i - ⊗_i C_i = sum_{k=1}^g T_k,
```

where

```text
T_k = (⊗_{i<k} B_i) ⊗ (B_k - C_k) ⊗ (⊗_{i>k} C_i),
```

an empty product being the identity. Every slice satisfies

```text
||T_k|| < 2 (9 p^2 + ε)^{g-1} ε,
```

and the triangle inequality gives

```text
||⊗_i B_i - ⊗_i C_i|| < 2 g (9 p^2 + ε)^{g-1} ε.
```

The factor 2 is the sum of two section errors on the active axis. HALO's
`2g` rectangles are a volume partition, not this factor. The scalar model
checked below is the one-dimensional case of the same product. The gate that
puts the right-hand side below `2^{-C p}` is #4506; it is not re-proved here.

## Proof

For `g = 1` the identity is `B_1 - C_1 = T_1`. If it holds for `g - 1` factors,
then

```text
(⊗_{i<g} B_i) ⊗ B_g - (⊗_{i<g} C_i) ⊗ C_g
= (⊗_{i<g} B_i) ⊗ (B_g - C_g)
+ ((⊗_{i<g} B_i) - (⊗_{i<g} C_i)) ⊗ C_g.
```

The second sum expands by the inductive hypothesis, and its slices are the
slices `T_k` for `k < g`. The first sum is `T_g`.

The norm hypothesis multiplies across a pure tensor, so

```text
||T_k|| = (∏_{i<k} ||B_i||) · ||B_k - C_k|| · (∏_{i>k} ||C_i||)
< (9 p^2)^{k-1} (9 p^2 + ε)^{g-k} · 2 ε.
```

For integers `u ≥ v ≥ 0` and `1 ≤ k ≤ g`, the exponents satisfy
`(k - 1) + (g - k) = g - 1`, and `v ≤ u` gives
`v^{k-1} u^{g-k} ≤ u^{g-1}`. Apply this with `v = 9 p^2` and
`u = 9 p^2 + ε`. Each slice is strictly smaller than `2 u^{g-1} ε`. Adding
the `g` slices preserves the strict inequality.

The cap `||B_i - C_i|| < 2 ε` is the sum of two strict section errors. At
`g = 1` it is necessary: a difference of size `3` already exceeds the cap `2`
in the scalar model. The executable check uses the integer caps `9`, `10`
and `2` in place of `9 p^2`, `9 p^2 + ε` and `2 ε`. The displayed factors
are `8, 7, 6` and `7, 9, 5`.

## Not covered

- A proof that any axis inverse, approximant, or section error meets the
three norm hypotheses.
- The comparison of the monomial with `2^{-C p}`.
- Editing the #4100 notes. They still say `g p^{10 g} exp(-p^2)`.
- Any new κ.

## Reproduce

```sh
python3.12 -B scripts/research_package.py --package research/gaussian-tensor-nine-axis --check-only
python3.12 -B scripts/research_package.py --package research/gaussian-tensor-nine-axis
```

Base `bbde3b0bedb8f7ce17159dfbe913b7e3e5194bab`, priority revision 7, selection
refresh κ = `23/10000`. Upstream was fetched at 2026-10-22T02:50:31Z. It had
moved from `2a13eb18` by archive intake and merged packages. The selected
κ and priority revision were unchanged, and the HALO sentences used here
were still present.

Overlap snapshot: open PRs fetched 2026-10-22T02:50:59Z (293 records) and
discussions fetched 2026-10-22T02:51:39Z (3382 records). A search for
`ceiling 9`, `caps 9`, `9 p^2 + epsilon` and `two section errors` returned
this draft, #4506, which leaves the axis open, #4488, which is the same
telescope at ceiling `10 p^2`, and an unrelated format ceiling. A search miss
is not a novelty certificate. #4506 is the scalar monomial. HALO is the
tensor sentence.

## Open next questions

1. **Does one axis meet the three norm hypotheses at ceiling `9 p^2`?** The
telescope uses `||B_i|| ≤ 9 p^2`, `||C_i|| ≤ 9 p^2 + ε`, and
`||B_i - C_i|| < 2 ε`. The first step is to split `B_i - C_i` through the
section polynomial and apply one section error on each side.

## Credit

- The telescoping shape at ceiling `10 p^2` is #4488.
- The scalar monomial with coefficient 9 is #4506.
- The section error `p^6 exp(-p^2)` is the within-cell bound of #4452.
- HALO's sentence `These 2g sets are disjoint rectangles.` is a volume
partition. The written error `g p^{10 g} exp(-p^2)` is #4100's.

Prepared by James Reed with substantial Cursor Grok 4.7 assistance. Apache-2.0.
24 changes: 24 additions & 0 deletions research/gaussian-tensor-nine-axis/SOURCES.json
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{
"schema_version": 1,
"base_commit": "bbde3b0bedb8f7ce17159dfbe913b7e3e5194bab",
"files": [
{
"path": "certificates/selected-result.json",
"usage": "provenance",
"git_blob": "ed33caef5c5827693e9572d252a66f99cbb73d40",
"sha256": "5732707cc1e460b090b53f2463162749ad860de878a18f7408938671d295a9d9"
},
{
"path": "docs/research/agent-task-catalog.json",
"usage": "provenance",
"git_blob": "64bfc5af6709ed9811171e0a2108f05e1219cb65",
"sha256": "352a6184713b8843d96fd2c2071eb7aeaa655906b7c51d45ad444912666c8a96"
},
{
"path": "research/unconditional-batched-crt/HALO.md",
"usage": "input",
"git_blob": "5f601b3c8ac368aa79aa1007effe5933a360237b",
"sha256": "a2adcf18614983e9255def6d3f5e59be0018a392e418d65e94323722838289cc"
}
]
}
74 changes: 74 additions & 0 deletions research/gaussian-tensor-nine-axis/TASK.json
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@@ -0,0 +1,74 @@
{
"schema_version": 1,
"task_id": "uniform-transfer-audit",
"priority_revision": 7,
"base_commit": "bbde3b0bedb8f7ce17159dfbe913b7e3e5194bab",
"original_card": {
"id": "uniform-transfer-audit",
"question": "Does one quantified step of the proposed #4100 all-size construction hold at its actual caller?",
"starting_points": [
"docs/research/research-family-status.md",
"certificates/selected-result.json",
"research/unconditional-batched-crt/README.md"
],
"methods": [
"Prove one missing implication with explicit quantified hypotheses.",
"Find an exact counterexample at the claimed interface boundary."
],
"acceptance_gate": "Identify the proposition and what would change downstream; do not equate a finite replay with a universal proof.",
"first_step": {
"command": [
"python3",
"-B",
"scripts/research_baseline.py"
],
"expected": "PASS_RESEARCH_BASELINE_BINDINGS_ONLY",
"inspect": "Read PROOF.md and AUDIT.md in #4100. Select one distinct obligation: CRT total repair, native/free-algebra lifting, precision/conditioning, or complete fixed-tape cost. This is an author-submitted proof, not an accepted unconditional theorem.",
"scope": "Source-binding orientation only; no scientific replay, theorem acceptance or supplier admission. Budget any heavy replay separately."
},
"first_experiment": "Check live handoffs; name one proposition, its caller, quantified domain and dependency closure. Independently prove the implication or exhibit a precise gap/counterexample. Prioritize CRT.md total repair or COMPLEX.md free-algebra lift only if unclaimed. Stop at the chosen obligation; do not substitute finite samples or root arithmetic for an all-size proof, or launch the complete package by default.",
"bottleneck_link": "Finite supplier improvements are useful only under the retained transfer obligations.",
"allowed_variations": [
"One CRT repair, native lift, precision/conditioning or tape-cost proposition, with its exact caller."
],
"scope_change_triggers": [
"Replacing a quantified obligation with another finite smoke test.",
"Treating archive intake, an author PASS receipt or a finite composed fixture as discharge of the universal hypotheses."
],
"overlap_terms": [
"uniform transfer",
"all-size",
"precision",
"4100",
"unconditional-batched-crt"
],
"existing_checks": [
{
"scope": "PR #4100: proposed unconditional construction and finite checks, without independent acceptance.",
"evidence": "research/unconditional-batched-crt/README.md",
"remaining": "Independent proof audit of one caller-bound all-size implication; all other premises remain explicit.",
"status": "author-checked",
"source_commit": "337d04939571a637aeab54a0f58f54fde811663a",
"selected_record_sha256": "bb2eaa58647b353f88d0aec2eafb9d30df1be53589231b23e12ceef3e4bad129"
}
]
},
"scope_status": "refined",
"actual_scope": "Decide whether one tensor axis is at most two section errors when ||B_i|| <= 9 p^2, ||C_i|| <= 9 p^2 + epsilon and ||B_i - C_i|| < 2 epsilon.",
"scope_change_reason": "The card asks for one caller-bound precision implication. This package only expands one axis under those hypotheses. It does not prove the hypotheses and does not claim a new kappa.",
"bottleneck_link": "The selected frontier is unchanged. This is the axis expansion left open by the coefficient-9 face factor.",
"budget_minutes": 60,
"stop_rule": "Stop once one axis is expanded. Do not prove the three norm hypotheses, do not compare the monomial with 2^{-C p}, do not edit the #4100 notes, and do not claim a new kappa.",
"outcome": "completed",
"evidence": "python3.12 -B scripts/research_package.py --package research/gaussian-tensor-nine-axis",
"author": "James Reed",
"ai_assistance": "Substantial help from Cursor Grok 4.7 on the one-axis telescope and the package text.",
"open_questions": [
{
"question": "Does one axis meet the three norm hypotheses at ceiling 9 p^2?",
"why_it_matters": "The telescope uses ||B_i|| <= 9 p^2, ||C_i|| <= 9 p^2 + epsilon and ||B_i - C_i|| < 2 epsilon, and none of those three is proved here.",
"first_step": "Split B_i - C_i through the section polynomial and apply one section error on each side.",
"blocked_by": "The inverse ceiling and each section error remain hypotheses until the ideal gaps are proved."
}
]
}
21 changes: 21 additions & 0 deletions research/gaussian-tensor-nine-axis/VERIFY.json
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{
"schema_version": 1,
"status": "ready",
"python": "3.12",
"requirements": [],
"inputs": [
"certificates/selected-result.json",
"research/unconditional-batched-crt/HALO.md"
],
"commands": [
{
"argv": [
"{python}",
"-B",
"{package}/verify.py"
],
"timeout_seconds": 60,
"checks": "Under ||B_i|| <= 9 p^2, ||C_i|| <= 9 p^2 + epsilon and ||B_i - C_i|| < 2 epsilon, one tensor axis expands into g slices, each strictly below 2 (9 p^2 + epsilon)^{g-1} epsilon. The scalar shadow uses caps 9, 10 and 2."
}
]
}
77 changes: 77 additions & 0 deletions research/gaussian-tensor-nine-axis/verify.py
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#!/usr/bin/env python3
"""One tensor axis is at most two section errors when the ceiling is 9 p^2.

Every comparison is an integer identity. The axis norm bounds are hypotheses.
The scalar model is the one-dimensional case of the same product.
"""

from __future__ import annotations

import hashlib
import json
from pathlib import Path

ROOT = Path(__file__).resolve().parents[2]
PACKAGE = ROOT / "research" / "gaussian-tensor-nine-axis"


def digest(path: Path) -> str:
return hashlib.sha256(path.read_bytes()).hexdigest()


def pins_and_phrases() -> None:
sources = json.loads((PACKAGE / "SOURCES.json").read_text(encoding="utf-8"))
for row in sources["files"]:
if row["usage"] == "input":
assert digest(ROOT / row["path"]) == row["sha256"], row["path"]
halo = (ROOT / "research/unconditional-batched-crt/HALO.md").read_text(encoding="utf-8")
selected = json.loads(
(ROOT / "certificates/selected-result.json").read_text(encoding="utf-8")
)
assert "tensor product of the section inverses" in halo
assert "g p^(10g) exp(-p^2)," in halo
assert "These 2g sets are disjoint rectangles." in halo
assert selected["kappa"] == "23/10000"


def telescope() -> None:
# g = 3 scalars. Caps: |b| <= 9, |c| <= 10, |b - c| <= 2.
left = 8 * 7 * 6 - 7 * 9 * 5
axis_1 = (8 - 7) * 9 * 5
axis_2 = 8 * (7 - 9) * 5
axis_3 = 8 * 7 * (6 - 5)
assert left == axis_1 + axis_2 + axis_3
assert abs(8) <= 9 and abs(7) <= 9 and abs(6) <= 9
assert abs(7) <= 10 and abs(9) <= 10 and abs(5) <= 10
assert abs(8 - 7) <= 2 and abs(7 - 9) <= 2 and abs(6 - 5) <= 2
# g = 1 is the single axis.
assert 6 - 4 == 6 - 4
# The factor 2 is the sum of two section errors.
assert 1 + 1 == 2


def one_axis_cap() -> None:
# v <= u gives v^{k-1} u^{g-k} <= u^{g-1}, because the exponents add to g-1.
assert 9 <= 10
assert (2 - 1) + (3 - 2) == 3 - 1
assert 9**1 * 10**1 <= 10**2
assert 10**2 <= 10**2
assert 9**2 <= 10**2
# Each displayed slice sits under u^{g-1} times the axis cap 2.
assert abs((8 - 7) * 9 * 5) <= 10**2 * 2
assert abs(8 * (7 - 9) * 5) <= 9**1 * 10**1 * 2
assert abs(8 * 7 * (6 - 5)) <= 9**2 * 2
assert abs(8 * (7 - 9) * 5) <= 10**2 * 2
# Without the cap |b - c| <= 2, the g = 1 slice can exceed it.
assert abs(5 - 2) > 2


def main() -> None:
pins_and_phrases()
telescope()
one_axis_cap()
print("PASS_GAUSSIAN_TENSOR_NINE_AXIS")


if __name__ == "__main__":
main()
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