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

Depends on

Dependency tree · 2 levels