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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.

Irreversible Boundaries — Examples

1 · Prerequisites

2 · Summary

Conditional finite models distinguish entropy definitions and ensemble averages from single outcomes. The continuum examples keep local equilibrium and transport relations within explicitly chosen model inputs. The final item is an empty evidence template; it reports no observations.

3 · Logical flowchart

4 · Definitions, postulates, theorems and proofs

None yet.

5 · Examples, experiments and counterexamples

ExampleConstruction: AI-generatedVerification: AI-generatedverified 2026-10-15 (gpt-6-luna, gpt-6.1-sol, and delegated Codex review/repair agents; see completed run evidence)Open item page →

A macrocell count and a nonuniform microscopic distribution

Physical scope

A stipulated two-microstate finite model with a nonuniform probability vector; it is not an equilibrium preparation, measurement or empirical claim.

Example

Let Ω={ω1,ω2} with ω1≠ω2, and declare the finite numerical energy map ϵ:Ω→R by ϵ(ω1)=ϵ(ω2)=0, so the assigned physical energies are E(ωi)=0 J. This supplies the finite microstate pair (Ω,ϵ) required in Macroscopic and microscopic entropy quantities; no mechanical internal-energy or equilibrium-macrostate identification is assumed. Choose M={m} and the constant coarse-graining map π:Ω→M, so both states belong to the macrocell Mm=Ω, and assign p1=1, p2=0. The probability vector is deliberately nonuniform. The example shows that the macrocell-count definition and the Gibbs–Shannon definition can take different values on separately specified inputs.

Facts & Assumptions

Given: The finite model below and the entropy definitions.

[F1]

Macroscopic and microscopic entropy quantities: SB(m)=kBlog⁡Nm, while SG(p)=−kB∑ipilog⁡pi, with the zero-probability summand defined as zero.

[F2]

SI quantities and unit conventions: kB=1.380649×10−23 J K−1>0.

[L1]

Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm: log⁡ is strictly increasing on (0,∞) and log⁡1=0.

[A1]

The two states are distinct, ϵ:Ω→R is identically zero, and π:Ω→{m} is constant. Thus Mm=Ω has Nm=2, and p=(1,0) is a probability vector.

Verification

Given: [F1]–[F2], [L1], and [A1].

1.1F1A1algebra

Since Nm=2, the macrocell entropy is SB(m)=kBlog⁡2.

1.2F1L1A1algebra

The only nonzero probability term is 1log⁡1=0; the p2=0 term is zero by definition. Hence SG(p)=0.

2.1F2L1step 1.1step 1.2algebra∎

Since 2>1, [L1] gives log⁡2>log⁡1=0. With kB>0 from [F2], step 1.1 is strictly positive while step 1.2 is zero, so these two defined quantities differ in this model. This example asserts no general inequality or thermodynamic identification.

ExampleConstruction: AI-generatedVerification: AI-generatedverified 2026-10-15 (gpt-6-luna, gpt-6.1-sol, and delegated Codex review/repair agents; see completed run evidence)Open item page →

Positive ensemble mean with a negative realization

Physical scope

A two-outcome probability model for an illustrative entropy-valued random variable; it is not a specified physical fluctuation law or reported observation.

Example

Let Ω={ω+,ω−} with weights w(ω+)=3/4 and w(ω−)=1/4. Both weights are nonnegative and sum to 1, so (Ω,w) is a finite probability space as defined in Finite probability spaces, outcome weights, events, and event probabilities. For every event A⊆Ω, write P(A)=∑ω∈Aw(ω) for its event probability. Let Y:Ω→R be given by Y(ω+)=2a and Y(ω−)=−2a, where a>0 and the values are numerical values in the unit J K−1. By Real random variables on finite probability spaces and their finite distributions, Y is a finite-valued real random variable on this finite probability space, so its expectation is a finite sum. The label Y is only an illustrative entropy-valued variable; this example adopts no physical path law.

This arithmetic example illustrates the distinction in Hypotheses for microscopic fluctuation claims.

Facts & Assumptions

Given: The two-outcome model and assignments stated above.

[F1]

Expectation is the sum of each attained value times its probability: for a real random variable on a finite probability space, E[Y]=∑y∈Y(Ω)yP(Y=y).

[F2]

Finite probability spaces, outcome weights, events, and event probabilities: nonnegative weights summing to 1 define a finite probability space, and each event probability is the sum of its outcome weights.

[F3]

Real random variables on finite probability spaces and their finite distributions: every function from a finite probability space to R is a finite-valued real random variable.

[A1]

The assignments are w(ω+)=3/4, w(ω−)=1/4, Y(ω+)=2a, Y(ω−)=−2a, and a>0.

Verification

Given: [F1]–[F3] and [A1].

1.1F1F2F3A1algebra

The two values of Y are distinct because a>0. By [F2]–[F3], Y is a real random variable on the stated finite probability space, so [F1] gives E[Y]=(3/4)(2a)+(1/4)(−2a)=a>0. Its unit is J K−1.

1.2F2A1algebra

The event {ω∈Ω:Y(ω)<0} is exactly {ω−}, so by [F2] its probability is P(Y<0)=1/4>0.

2.1step 1.1step 1.2algebra∎

Steps 1.1 and 1.2 exhibit a positive mean together with a negative realization of nonzero probability. Therefore positivity of an ensemble mean alone does not imply a nonnegative value in every trial. The example is not a fluctuation theorem or a claim about measured entropy production.

ExampleConstruction: AI-generatedVerification: AI-generatedverified 2026-10-15 (gpt-6-luna, gpt-6.1-sol, and delegated Codex review/repair agents; see completed run evidence)Open item page →

A nonconstant local-equilibrium temperature field

Physical scope

A stipulated static local-equilibrium field on an open cube; no global equilibrium, transport law or observation is asserted.

Example

Use the one-coordinate convention of The Euclidean inner product ⟨x,y⟩=∑k<nxkyk on Rn explicitly: ι:R→R1 sends a to the function on {0} with value ι(a)(0)=a, and the inverse takes the coordinate at index zero. In every scalar display below, a one-coordinate parameter or field is written through this bijection. Thus Z means ι((0,∞)), the scalar formula for z denotes its ι image, C(e,y)=e means C(e,y)=ι(e), c(a)=a is the identity on Z, and q(ι(a))=(a,0); temperature and inequalities use the scalar coordinate a. This is a notation convention, not a set-theoretic identity between a real and a function.

Take O=(0,L)3 in metre coordinates and I=(0,τ) in second coordinates, with L>0 m and τ>0 s. Choose Θ0>0 K and dimensionless 0<α<1. Instantiate m=1 and the local-state parameter set Z=(0,∞)⊆R1, and define its one-coordinate field z:O×I→Z by

z(x,t)=Θ01 K(1+αx1L),T(x,t)=(1 K)z(x,t)=Θ0(1+αx1L).

For the homogeneous comparison cell, supply X=(0,∞)×R with states (e,y), physical energy (1 J)e, and numerical entropy s(e,y)=ln⁡e−y2, where ln⁡:(0,∞)→R is the natural logarithm of The natural logarithm as the inverse of the exponential function and physical entropy is (1 J K−1)s(e,y). The coordinate y is dimensionless. Set r=1, C(e,y)=e, c(a)=a, and Ba=X for every a∈Z, so the fixed-energy admissible set is Aa={(a,y):y∈R}. Its entropy-maximizing set is Ea={(a,0)}. Define Eeq=⋃a>0Ea and supply q(a)=(a,0); assign this comparison state temperature (1 K)a. Stipulate the local-equilibrium approximation with this map, so the local constitutive state at (x,t) is q(z(x,t)). The field is static and nonconstant; this stipulation is a model assumption, not an assertion that a physical sample realizes the profile.

Facts & Assumptions

Given: The local-field convention of Scope of a local-equilibrium continuum branch and the parameters just specified.

[F1]

Scope of a local-equilibrium continuum branch: the local-state field has the displayed domain and its components have continuous first spatial and time partial derivatives; a temperature component is read in kelvins.

[F2]

Scope of a local-equilibrium continuum branch: an entropy-based local-equilibrium model supplies cell states, entropy, retained constraints and conserved-value maps; Ea is the entropy-maximizing subset of Aa={e∈Ba:C(e)=c(a)}, and the supplied map must satisfy q(a)∈Ea. Its pointwise comparison state is q(z(x,t)); attainment is verified for the supplied model rather than inferred from a label.

[F3]

Scope of a local-equilibrium continuum branch: nonconstant temperature fields are permitted in this continuum model; the pointwise comparison-cell criterion alone neither establishes nor excludes equilibrium of the whole system.

[F4]

The natural logarithm as the inverse of the exponential function defines ln⁡:(0,∞)→R, so the supplied cell entropy is finite at every cell state.

[A1]

x has metre coordinates in (0,L)3, Θ0>0 K, dimensionless 0<α<1, m=1, Z=(0,∞)⊆R, and z(x,t)=(Θ0/(1 K))(1+αx1/L) with T=(1 K)z; the cell data X,s,C,c,Ba are exactly those in the Example and q(a)=(a,0); the model stipulates the resulting pointwise local-equilibrium assignment.

Verification

Given: [F1]–[F4] and [A1].

1.1A1algebra

Since 0<x1<L, 1+αx1/L>1, so z(x,t)>Θ0/(1 K)>0 and T(x,t)=(1 K)z(x,t)>Θ0>0 K. The affine formulas are C1 on O×I and meet the field regularity in [F1].

1.2A1algebra

Choose interior points with x1=L/4 and x1=3L/4, keeping the other coordinates fixed. Their temperature difference is Θ0α/2>0, so the field is not constant.

2.1F1F2F3F4A1step 1.1step 1.2algebra∎

For each a>0, [A1] gives Aa={(a,y):y∈R} and s(a,0)−s(a,y)=y2≥0, with equality exactly at y=0. Thus Ea={(a,0)} and q(a)∈Ea, meeting the constrained-maximum criterion in [F2]. The logarithm is finite since a>0. By [F1] and step 1.1, the one-coordinate field has the declared range and regularity, so its supplied comparison state is q(z(x,t)). Steps 1.1–1.2 show that its temperature component is positive and spatially nonconstant; [F3] says this need not describe global equilibrium. No dynamics or experimental outcome is inferred.

ExampleConstruction: AI-generatedVerification: AI-generatedverified 2026-10-15 (gpt-6-luna, gpt-6.1-sol, and delegated Codex review/repair agents; see completed run evidence)Open item page →

Different Fourier coefficients give different model fluxes

Physical scope

Comparison of two stipulated isotropic Fourier models on the same temperature profile; no material measurement or universal constitutive law is asserted.

Example

On O=(0,L)3 in metre coordinates and I=(0,τ) in second coordinates, with L>0 m and τ>0 s, prescribe T(x,t)=T0+ΔT x1/L, where T0>0 K and ΔT>0 K. In the chosen Cartesian coordinates, define e1:=(1,0,0)∈R3. Compare two isotropic model choices κ1,κ2>0, κ1≠κ2, each using jQ=−κi∇T. The coefficients have units W m−1 K−1.

Facts & Assumptions

Given: The Fourier-model definition and the stipulated fields and coefficients.

[F1]

Scope of transport constitutive laws: for a temperature field with continuous first spatial partial derivatives, ∇T=(∂x1T,∂x2T,∂x3T) in the physical one-based coordinate display (function indices i−1), and a Fourier model may postulate jQ=−K∇T, where K has entries in W m−1 K−1; its isotropic form is K=κI3 with κ≥0.

[A1]

T0>0 K, ΔT>0 K, L>0 m; e1=(1,0,0) in the chosen Cartesian coordinates; κ1,κ2>0 in W m−1 K−1 with κ1≠κ2; both models use the same profile T=T0+ΔT x1/L; and model i adopts jQ,i=−κi∇T.

Verification

Given: [F1] and [A1].

1.1A1constructalgebra

The common temperature gradient is ∇T=(ΔT/L)e1. The two assigned model fluxes are therefore jQ,1=−κ1(ΔT/L)e1 and jQ,2=−κ2(ΔT/L)e1.

2.1A1step 1.1algebra

Their difference is jQ,1−jQ,2=−(κ1−κ2)(ΔT/L)e1≠0. The same field profile therefore has different predicted fluxes under these two constitutive choices.

3.1F1A1step 2.1∎

The calculation uses the Fourier relation as a stated model input and does not determine either κi from equilibrium entropy data. It is a model comparison, not a measured result.

ExampleConstruction: AI-generatedVerification: Not suppliedverified 2026-10-15 (gpt-6-luna, gpt-6.1-sol, and delegated Codex review/repair agents; see completed run evidence)Open item page →

Empty source-backed evidence record template

Physical scope

Documentation template only; it contains no experiment, observation, apparatus reading or uncertainty value.

Example

The following empty record shows fields to fill from an actual source report. Bracketed text is an instruction, not a result or measurement.

The fields implement Evidence records for irreversible and transport claims.

  • Source report and exact locator: [required]
  • Material, sample geometry, apparatus and boundary conditions: [required]
  • Operational definitions and calibration: [required]
  • Preparation, controls, sampling procedure and sample size: [copy only what the source reports]
  • Observations with units and stated uncertainty: [copy only source-supported values]
  • Systematic limitations and missing information: [state explicitly]
  • Model prediction and assumptions: [keep separate from observations]
  • Statistical method and conditional conclusion: [state method, sampling assumptions and limits]

No claim of a performed experiment is made by this template.