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156 changes: 156 additions & 0 deletions research/chebyshev-inverse-locality/PROOF.md
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# Chebyshev inverse locality under the retained conditioning contract

This contribution was produced by Nick Petalas. Apache-2.0.

Claim type: scoped written mathematical proof. The Chebyshev identities and
normal-equation approximation method are classical. The new contribution is
the explicit replacement of the Gaussian caller's locality parameters under
its existing conditioning hypotheses. No global literature priority is claimed.

The general approximation-based inverse-decay method also predates this
application. Credit Stephen Demko, William F. Moss and Philip W. Smith,
[Decay rates for inverses of band matrices, 1984](https://doi.org/10.1090/S0025-5718-1984-0758197-9).
The argument below gives the explicit residual and exact section-row interface
needed here; it does not claim a new general inverse-decay theorem.

## The polynomial

Let H be an invertible finite complex square matrix with

||H||_2 <= K, ||H^-1||_2 <= K, K > 1.

Write A=H*H. Its eigenvalues lie in [K^-2,K^2]. For any integer d>=1 put

c = (K^4+1)/(K^4-1),
t(x) = (K^4+1-2K^2 x)/(K^4-1),
R_d(x) = T_d(t(x))/T_d(c),
q_(d-1)(x) = (1-R_d(x))/x,
B_d(H) = q_(d-1)(H*H) H*.

Here T_d is the Chebyshev polynomial of the first kind. Since t(0)=c,
R_d(0)=1. Thus q_(d-1) is a polynomial of degree at most d-1, with no pole
at zero. In particular this definition does not require a matrix inverse.

The classical identity

T_d((z+z^-1)/2) = (z^d+z^-d)/2

and |T_d(t)|<=1 on [-1,1] follow from the recurrence T_0=1, T_1=t,
T_(j+1)=2t T_j-T_(j-1). They are also recorded in
[NIST DLMF, equation 18.5.1](https://dlmf.nist.gov/18.5.E1).
These identities are premises from classical polynomial theory, not new claims.

## Error for arbitrary nonnormal matrices

The identity x q_(d-1)(x)=1-R_d(x) gives, in the indicated order,

B_d(H)-H^-1 = -R_d(H*H) H^-1.

Indeed A^-1 H*=H^-1. The spectral theorem applies to the Hermitian A,
regardless of whether H is normal. Since t maps [K^-2,K^2] to [-1,1],

||B_d(H)-H^-1||_2 <= K/T_d(c).

Take z=(K^2+1)/(K^2-1)>1. Then c=(z+z^-1)/2, so

1/T_d(c) = 2/(z^d+z^-d) <= 2 z^-d
<= 2 exp(-2d/K^2).

For the last inequality put u=K^-2 in (0,1). Integrating
2/(1-u^2)>=2 from 0 to u gives
log((1+u)/(1-u))>=2u. Therefore log z>=2/K^2. This proves

||B_d(H)-H^-1||_2 <= 2K exp(-2d/K^2).

No row or column dominance, symmetry of H, Gaussian entry formula or
translation invariance is used in this implication.

## Exact locality and principal sections

Let the indices carry the linear or circular physical distance used by the
caller. Suppose H_ij=0 when the distance between i and j exceeds W.
The same is true of H*. A monomial (H*H)^j H* contains 2j+1 factors,
and each step moves at most W. Hence B_d(H) has physical bandwidth at most

r = (2d-1)W.

Let S be any principal index set, H_S the corresponding principal matrix,
and i in S. If the distance from i to every omitted index is greater than r,
then the row of B_d(H_S), extended by zero outside S, equals row i of B_d(H)
exactly. Every path contributing to a monomial stays in S: an exit would
reach an omitted index in at most 2d-1 steps of length at most W. The same
coefficients are used in both polynomials, including the same K and d.

This is equality of polynomial rows, not equality of exact inverse rows.
For an inverse-error assertion on H_S, that section must itself satisfy
the norm and inverse-norm hypotheses with the same K. The locality assertion
alone does not require H_S to be invertible. A separately rerounded section,
different K, or a Schur complement is not covered by this row identity.

## Substitution at the Gaussian caller

Use the precise hypotheses of Cinna Davis's
[HALO.md](../unconditional-batched-crt/HALO.md), pinned in SOURCES.json:
p is an integer at least two, W<p, and H and each section used for an inverse
have both norms at most p^10. Set

K=p^10, d=p^22.

Then

||B_d(H)-H^-1||_2 <= 2p^10 exp(-2p^2) < p^10 exp(-p^2),

because exp(p^2)>2 for p>=2. Furthermore

r <= (2p^22-1)(p-1) < 2p^23 <= p^24.

Thus a row at distance at least p^24 from every omitted index has exact
polynomial agreement. This replaces the historical Neumann degree p^42
by p^22 and permits the conservative halo p^24 in place of p^48, with a
strictly smaller error than the old p^10 exp(-p^2) majorant. Both the global
matrix and every actual inverted section retain their original assumptions.
The argument does not establish those assumptions for a new matrix.

The predecessor locality work, including Nick Petalas's #4217 and Mihir
Srivastava's #4501, supplies the distinction between polynomial locality,
section inverses and ordered nonnormal error identities. Their Neumann
polynomials and finite examples are not audited or replayed here. The new
polynomial changes the approximation method while retaining the input matrix
class and conditioning contract.

## Exact coefficient construction

For integer K>=2 put D=K^4-1 and L=(K^2+1)^2. Define integer polynomials

N_0(x)=1,
N_1(x)=K^4+1-2K^2 x,
N_(j+1)(x)=2(K^4+1-2K^2 x)N_j(x)-D^2 N_(j-1)(x).

Induction gives N_d(x)=D^d T_d(t(x)), so R_d(x)=N_d(x)/N_d(0).
N_d(0)>0. If N_d(x)=sum a_j x^j, the inverse polynomial's coefficients
are exactly -a_(j+1)/a_0. No numerical root, transcendental coefficient or
unknown inverse entry is needed to construct them.

For completeness, ||N_j||_(coefficient 1-norm) <= (3L)^j. The initial cases
hold since ||N_1||=L. Since D^2<L^2, the recurrence bounds the next norm by

2L(3L)^j + L^2(3L)^(j-1) = (7/9)(3L)^(j+1).

Thus coefficient numerator and denominator bit lengths are O(d log K).
With d=p^22 and K=p^10 this is polynomial in p. Naive exact recurrence and
local polynomial evaluation therefore give polynomial offline setup, as
required of a locality witness. This is not a practical runtime benchmark
or a charged physical coefficient-page implementation.

## Scope

This proves one conditional approximation and locality improvement. It
supplies no optimized global core geometry, complete tape/precision bill,
rounded implementation, native supplier admission, new kappa, or complete
multiplication theorem. The selected record and all five assumptions remain
unchanged. Coefficient rounding and finite-precision recurrence stability
require their own analysis before replacing a physical implementation.

The finite verifier corroborates identities on bounded rational matrices.
The universal quantifiers above rest on this written proof. Independent
human and formal proof-kernel review are unclaimed.
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# A smaller exact locality polynomial for the Gaussian inverse

This contribution was produced by Nick Petalas. Apache-2.0.

Claim type: scoped written mathematical proof with exact finite corroboration.
Under the historical Gaussian caller's unchanged assumptions
`||H||_2, ||H^-1||_2 <= p^10` and physical bandwidth `W<p`, an explicit
Chebyshev inverse polynomial replaces the Neumann locality witness:

```text
historical witness new witness
residual degree p^42 p^22
conservative halo p^48 p^24
inverse error bound p^10 exp(-p^2) 2p^10 exp(-2p^2)
```

The new error is strictly smaller than the old majorant for every integer
`p>=2`. A section polynomial row agrees exactly with its global row when
its distance to omitted indices exceeds `(2p^22-1)W`. Each section used
for an inverse estimate must retain the same conditioning assumptions.

[PROOF.md](PROOF.md) gives the polynomial, the ordered error identity for
nonnormal matrices, exact row locality and a rational coefficient recurrence
with polynomial bit lengths. Chebyshev approximation is classical, with
[DLMF equation 18.5.1](https://dlmf.nist.gov/18.5.E1) cited explicitly.
The new step is the source-compatible parameter replacement. No claim of
global literature priority is made. The general approximation-based
inverse-decay method is credited to
[Demko, Moss and Smith](https://doi.org/10.1090/S0025-5718-1984-0758197-9).

## Reproduction and evidence

From the repository root, use CPython 3.12 and its standard library:

```sh
/Users/nick/git/integer-mult-bounds/.venv/bin/python3.12 -W error -X dev -I -B research/chebyshev-inverse-locality/verify.py
/Users/nick/git/integer-mult-bounds/.venv/bin/python3.12 -W error -X dev -I -O -B research/chebyshev-inverse-locality/verify.py
/Users/nick/git/integer-mult-bounds/.venv/bin/python3.12 -B scripts/research_package.py --package research/chebyshev-inverse-locality
/Users/nick/git/integer-mult-bounds/.venv/bin/python3.12 -B scripts/check_research_commit.py --package research/chebyshev-inverse-locality --check-source-history
```

Another CPython 3.12 installation can replace the shown interpreter. Direct
replay prints `PASS_CHEBYSHEV_INVERSE_LOCALITY` in generated JSON, binding
all six package files by SHA256. It writes no files. The finite checks cover:

- 3,696 exact scalar samples for `K=2..8`, degrees `1..16`, and 33 rational
points across the complete spectral interval. Integer coefficient
construction agrees with an independent scalar Chebyshev recurrence;
normalizations agree with the closed-form identity.
- 45 nonnormal operator fixtures, checking the exact ordered inverse-error
identity and its operator-norm bound by rational LDL positivity. Moving
the residual to the wrong side or reversing its sign fails on each fixture.
- 33 full section rows on a 21-point circle, for degrees 1,2,3, with exact
global/section agreement beyond the proved radius. Six rows at the radius
reject the smaller-halo extension. All bandwidth entries are checked.
- 127 integer parameter substitutions `p=2..128`, and six rejected invalid
coefficient-constructor inputs. Checks remain active under optimized Python.

These reduced fixtures do not construct a degree-`p^22` production matrix.
The universal statement follows from the written proof, not a finite census.
No predecessor verifier, fixture or mathematical result is rechecked.

## Scope and obligations

The `uniform-transfer-audit` card is changed to an original component
construction for the `precision_tape` locality interface. This supplies a
smaller exact polynomial under explicit assumptions. It does not discharge
that entire selected assumption or provide a new supplier.

No optimized core geometry, complete physical coefficient-page cost,
finite-precision recurrence stability, native execution, rounded multiplier,
new kappa or complete multiplication theorem is supplied. No selected-source
cold replay, Lean or Docker build is run. Independent human and formal
proof-kernel review are unclaimed. The selected frontier and its five
assumptions remain unchanged.

The verifier has no recursion, subprocesses or external runtime inputs.
All loops run over fixed finite collections, with matrices at most 21 by 21
and coefficient degree at most 16. Its largest function is below 60 lines.
Python's required dynamic allocation is a Power of Ten deviation, bounded
here by those fixed domains and one active matrix fixture. Exact fractions
have bounded sizes because both dimensions and rational inputs are fixed.
The checks use explicit exceptions under normal and optimized Python, with
warnings treated as errors. No shared build settings are changed.
Ruff is unavailable in the supplied interpreter; no separate static analyzer
is claimed. Static AST inspection finds a maximum function length of 28 lines.

## Credit and overlap

Cinna Davis's PR #4100 supplies the historical Gaussian caller, its
conditioning/section contract and Neumann locality witness. Credit the
retained capped-Gaussian and multiplication-framework predecessors in its
NOTICE.md. Nick Petalas's #4217 separates polynomial locality from inverse
row equality, and Mihir Srivastava's #4501 retains the ordered nonnormal
identity and a stronger cross-cell conditioning contract. These are cited
predecessor results, not new outputs. SOURCES.json pins their retained
texts at main `19fdb086ea96af9a9f87936a2b888e10af4ed810`.

The new construction changes the approximation polynomial while retaining
the input matrix class and conditioning contract.
The exact finite verifier is new and imports no predecessor implementation.
Live open PRs, handoff claims, main README searches and
merged-PR searches were checked. Cached overlap has complete remote
pagination but incomplete sparse local-note coverage. These bounded checks
are not a novelty certificate.

Advance claim:
https://github.com/CrocSwap/integer-mult-bounds/discussions/1166#discussioncomment-19226112

## Open next questions

Can a complete coefficient-page producer realize this smaller polynomial
with a favorable rounding and physical setup bill? The first step is a
bounded, exact coefficient page at one named caller section, with every
coefficient width, recurrence intermediate and output error charged. This
matters because exact locality alone does not lower the physical invoice.
The missing rounding, coefficient-page and consumer contracts are blockers.
No further construction or search is included here.
36 changes: 36 additions & 0 deletions research/chebyshev-inverse-locality/SOURCES.json
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