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feat: the interior of the domain of the conjugate is where tilts grow linearly - #321
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Co-Authored-By: Claude Code <noreply@github.com>
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This PR characterises the interior of the effective domain of Tau Ceti's Legendre–Fenchel conjugate, for the pairing of a real normed space$\nabla F^*$ , …"). The surjectivity half of that bijection,
Ewith its dual. A functionaluis interior to{v | f⋆ v ≠ ⊤}exactly when the tiltf - ugrows at least linearly,u x + r ‖x‖ - M ≤ f xwithr > 0. As a consequence, the tilted sublevel sets{x | f x ≤ u x + c}are bounded. It serves the Bandits roadmap's Layer 6.1, "Legendre functions", which asks for [LS, Theorem 26.6] ("the gradient is a bijection between interiors with inverse∇Fonto the interior of the domain ofF⋆, consumesisBounded_setOf_le_of_mem_interior_setOf_fenchelConjugate_ne_top. Givenuin that interior, it bounds a minimizing sequence ofF - uonD. That gives a minimizer, which steepness ([LS, Corollary 26.8]) puts in the interior, where∇F = u.Roadmap: Bandits
After this PR, Layer 6.1 still needs the surjectivity argument itself and the fact that
F⋆is Legendre. Both are stated with theIsLegendrepredicate of the open #289 and the conjugate on a set of the open #319, so they wait for those two PRs to merge. This PR depends on neither. It is stated withTauCeti.fenchelConjugate (topDualPairing ℝ E).flip, which #319'sfenchelConjugateOn_eq_fenchelConjugateidentifies withfenchelConjugateOn F D.LMLExplore/Analysis/Convex/Coercive.lean(new, 141 lines):fenchelConjugate_le_of_norm_sub_le: in any real normed space, ifu x + r ‖x‖ - M ≤ f xfor everyx, thenf⋆ v ≤ Mfor‖v - u‖ ≤ r.mem_interior_setOf_fenchelConjugate_ne_top_of_forall_le: henceuis interior to the domain off⋆whenr > 0.exists_forall_le_of_mem_interior_setOf_fenchelConjugate_ne_top: the converse, in finite dimension. Tau Ceti'sconvexOn_toRealandconvex_epigraph_fenchelConjugatemake the real representative off⋆convex on its domain. Mathlib'sConvexOn.continuousOn_interiorthen bounds it above nearu. The Fenchel–Young inequality atu + (ρ/2) φ, withφa norming functional ofx(exists_dual_vector''), gives the growth bound.mem_interior_setOf_fenchelConjugate_ne_top_iff: the two directions together, in finite dimension.isBounded_setOf_le_of_mem_interior_setOf_fenchelConjugate_ne_top: bounded tilted sublevel sets.The statements take an arbitrary
f : E → EReal, with no convexity, lower semicontinuity or properness. The casef ≡ ⊤(wheref⋆ ≡ ⊥) is covered. I searched Mathlib, Tau Ceti, LML and LMLExplore for an existing statement. Tau Ceti'stendsto_sub_atTop_of_superlinear(Analysis/Convex/Superlinear.lean) goes the other way: superlinearhmakes every tilt coercive. It says nothing about the domain of the conjugate. Nothing else relates the interior of the domain of a conjugate to growth of tilts. No Mathlib infrastructure was vendored.Sources: R. T. Rockafellar, Convex Analysis, Theorem 10.1 and Section 14; T. Lattimore and Cs. Szepesvári, Bandit Algorithms, Section 26.5, Theorem 26.6. Both are cited in the file.
🤖 Prepared with Claude Code