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.

Finite tensor contractions and their variational energy and gradient

Definition

Let n,r≥1 be integers, C∈Rn×r, D∈Rr×r, H∈Rn×n, and G∈Rn×n×n×n. Define their transformed tensors by Hpq′=∑a,b=1nCapHabCbq,Gpqrs′=∑a,b,c,d=1nCapCbqCcrCdsGabcd, for 1≤p,q,r,s≤r. Define the finite variational energy functional E(C;D,H,G)=∑p,q=1rDpqHpq′+12∑p,q,r,s=1rDpqDrsGpqrs′. Its gradient ∇CE is the ordinary Euclidean gradient with respect to the nr real entries of C. The basis dimension is n, the contracted dimension is r, and for any finite matrix or tensor A, ∥A∥F=(∑∣Ai1…ik∣2)1/2, with the sum over all its entries. This is a finite algebraic functional; it assumes no Hartree–Fock, self-consistency, or minimizing-state postulate.

For perturbed integral tensors H~,G~, write E~ for the same functional with those tensors and the same fixed C,D. The word “variational” here names the finite coefficient functional only; no claim about a stationary point or physical energy is included.

Used by

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Nothing. This result depends on no other item in the library.

Sources