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LemmaStatement: AI-adaptedProof: AI-adaptedPipeline-generatedprecheck passjudge pass (gpt-6-luna)
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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 static fermion-mode trace and occupation identity

Statement

Let M≥0 be an integer, let E1,…,EM∈R, β>0, and μ∈R. Define the finite index set NM={0,1}M and the finite-dimensional Hilbert space HM=CNM with orthonormal basis ∣n1,…,nM⟩. Define diagonal operators H and N on this basis by H∣n⟩=(∑j=1MEjnj)∣n⟩,N∣n⟩=(∑j=1Mnj)∣n⟩. For a matrix on HM, trace means the finite sum of its diagonal entries in this basis. Then Ξ=Tr⁡e−β(H−μN)=∏j=1M(1+e−β(Ej−μ))∈(0,∞). The normalized diagonal state with weights Ξ−1e−β(∑jEjnj−μ∑jnj) has, for each 1≤j≤M, occupation mean ⟨nj⟩=1eβ(Ej−μ)+1. For M=0, the empty product and trace are 1, and there are no occupation marginals. This is a finite-dimensional algebraic identity and uses no choice principle, curved-space spectrum, or gravitational field equation.

Facts & Assumptions

Given: A finite set of modes indexed by {1,…,M}, their real energies Ej, and finite parameters β>0 and μ∈R.

[A1]

The occupation basis is indexed by bit strings n∈{0,1}M; H and N are the diagonal operators defined in the Statement. The trace is the finite diagonal sum in that basis.

Proof

1.1givenA1algebra

Put qj=e−β(Ej−μ). Each qj is a finite positive real number. Expanding the finite trace over bit strings and factoring a finite sum gives Ξ=∑(n1,…,nM)∈{0,1}M∏j=1Mqjnj=∏j=1M(1+qj). Every factor lies in (1,∞), so the product is finite and positive; for M=0 both sides equal 1.

2.1A1step 1.1algebra∎

Dividing each diagonal weight by the positive finite Ξ gives a normalized probability distribution on the finite basis. For 1≤j≤M, summing over the other bits factors their terms and yields ⟨nj⟩=qj∏k≠j(1+qk)∏k(1+qk)=qj1+qj=1eβ(Ej−μ)+1. The same calculation establishes the marginal directly and does not invoke a countable product or any axiom of choice.

Dependency tree · 0 levels

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

Sources