Package S10 tail assumptions for reusable callers#31
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Constraint: Keep theorem boundaries honest by bundling only explicit S9 conditioning and tail bridge premises. Rejected: Proving new conditioning or tail-domination facts | task requires no new hard facts. Confidence: high Scope-risk: narrow Directive: Do not treat this bundle as a full or unconditional Matrix Bernstein theorem. Tested: lake build HighDimProb.RandomMatrix.ConcentrationStatements; lake env lean HighDimProbTest/RandomMatrixConcentrationAPI.lean; lake env lean HighDimProbJudge/RandomMatrix/MatrixBernsteinUse.lean; python .github/scripts/check_text_quality.py; python scripts/judge_policy_check.py; git diff --check Not-tested: lake test
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Summary
MatrixBernsteinConditioningTraceMGFTailAssumptionsbundle for the S10 conditioning/trace-MGF-to-tail route.matrixBernsteinQuadraticFormUpperTail_of_conditioningTraceMGFTailAssumptionsas a downstream-friendly wrapper with honest assumption boundaries.Motivation
This advances the aggressive Matrix Bernstein/Lieb stack by packaging the S10 tail route behind a reusable assumption contract instead of requiring each downstream caller to thread the conditional trace-MGF assumptions manually.
Scope
HighDimProb/RandomMatrix/ConcentrationStatements.lean.HighDimProbTest/RandomMatrixConcentrationAPI.leanandHighDimProbJudge/RandomMatrix/MatrixBernsteinUse.lean.Testing
git diff --checkpython .github/scripts/check_text_quality.pypython scripts/judge_policy_check.pylake build HighDimProb.RandomMatrix.ConcentrationStatementslake env lean HighDimProbTest/RandomMatrixConcentrationAPI.leanlake env lean HighDimProbJudge/RandomMatrix/MatrixBernsteinUse.leanlake build HighDimProbJudgelake test