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DefinitionDefinition: AI-adaptedProof: Not applicablePipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-22
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Compact linear operator

Definition

Let X and Y be normed spaces over the same scalar field K, read in the real case from A norm on a real vector space, the induced metric, and the dictionary with the metric axioms and in the complex case from Real and complex scalar conventions for normed spaces. A linear map T:XY (Linear map between vector spaces over the same field) is a compact operator when the image of every bounded subset of X (Bounded subset, diameter, distance from a point to a set, and distance between two sets in a metric space) has compact closure in Y (Open cover, subcover, compact metric space, and compact subset of a metric space); explicitly, for every bounded AX the closure T(A) in Y is a compact subset of Y. The set of compact operators XY is written K(X,Y).

The closed unit ball suffices. Put BX:={xX:x1} (Open ball, closed ball and sphere in a metric space). Then T is compact if and only if T(BX) is a compact subset of Y.

Indeed, if T is compact then BX is bounded, because BXB(0,2) while B(0,2) is bounded and a subset of a bounded set is bounded, so T(BX) has compact closure. Conversely assume T(BX) compact and let AX be bounded. If A= then T(A)=, whose closure is empty and hence compact. Otherwise AB(x0,r) for some x0X and real r>0, so every xA satisfies xx0+r=:R; if R>0 then ARBX and if R=0 then A{0}, so in either case T(A)RT(BX). Scalar multiplication by R is continuous (Vector addition and scalar multiplication are continuous in a normed space), so RT(BX) is a compact subset of Y (A continuous image of a compact space is compact; a continuous real-valued map on a nonempty compact space attains a maximum and a minimum; and a continuous bijection from a compact space to a Hausdorff space is a homeomorphism), hence closed (A compact subset of a metric space is closed and bounded); therefore T(A)RT(BX) is a closed subset of a compact set, hence compact, and T is compact.

A compact operator is bounded. If T is compact then the compact set T(BX) is bounded (A compact subset of a metric space is closed and bounded), so there is a real C0 with TxC for every xBX and hence TxCx for every xX; thus T is a bounded linear operator (A bounded linear operator between normed spaces). This is a consequence of compactness, not a hypothesis of the definition.

Depends on

Used by

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Dependency tree · two levels

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Sources