Alphabeta Math
DefinitionDefinition: AI-adaptedProof: Not applicablePipeline-generatedjudge pass (gpt-6-luna)
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.

Locally bounded distributional weak solutions of scalar laws

Definition

Let T>0, let f ⁣:R→R be continuous, and let u0∈L∞(R)∩Lloc1(R). A measurable function u ⁣:R×(0,T)→R is a locally bounded distributional weak solution of ut+f(u)x=0 with initial datum u0 if for every bounded interval I⊂R and every T′<T it is essentially bounded on I×(0,T′), and, for every φ∈Cc∞(R×(−∞,T)), ∫0T∫R(uφt+f(u)φx) dx dt+∫Ru0(x)φ(x,0) dx=0. The integrals are local: if a test is supported in I×[−S,T′] with I bounded and T′<T, the local essential bound makes u bounded on I×(0,T′], and continuity of f makes f(u) bounded on that bounded range. The initial integral is finite because u0 is locally integrable and φ(⋅,0) is compactly supported. This is the local integrability version of the weak identity in Distributional weak solutions of the Cauchy problem, whose published formulation assumes a global L∞ bound. This definition adds no entropy inequality or strong local L1 trace requirement.

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Used by

Dependency tree · two levels

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