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Mixture Dynamics And Shells — Examples

1 · Prerequisites

2 · Summary

These leaf examples give a noncompact mixture with an unattained infimum, a finite sequence with controlled nonconcave entropy and ensemble inequivalence, a complete finite-volume Hamiltonian flow that is not ergodic, and a two-level pure state whose time-averaged density has positive entropy. Each example identifies the model and its exact mathematical conclusion; none is reported as an experiment or observation.

3 · Logical flowchart

4 · Definitions, postulates, theorems and proofs

None yet.

5 · Examples, experiments and counterexamples

CounterexampleConstruction: 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 →

Noncompact mixtures can have an unattained energy infimum

Statement refuted

For every nonempty Borel generator set K and continuous energy a:K→R bounded below, the unconstrained infimum of ∫Ka dP over Borel probability measures on K is attained whenever it is finite, without a compactness or coercivity hypothesis.

Example

Extend the objective in Compact phase-generator mixture to the noncompact Borel generator set K=(0,1) with energy a(x)=x, and impose no barycenter constraint. The infimum of ∫Kx dP(x) over Borel probability measures is 0, but no probability measure attains it. This shows that a general unconstrained attainment claim needs compactness or a substitute such as coercivity; the example makes no assertion about the barycenter-constrained theorem Attainment and finite support for compact continuous mixtures.

Facts & Assumptions

Given: The explicit noncompact set, continuous energy, and unconstrained Borel-probability objective.

[A1]

K=(0,1), a(x)=x, and P ranges over all Borel probability measures on K with objective ∫Kx dP.

[F1]

Compact phase-generator mixture defines the mean energy aˉ(P)=∫a dP; its constrained mixture energy amix is an infimum of those means at a prescribed barycenter. Here [A1] extends only the mean-energy objective to the stated noncompact set and omits the constraint. Monotonicity and nonnegative homogeneity of the nonnegative integral gives monotonicity, and The integral of a nonnegative simple function together with The nonnegative integral agrees with the simple integral on simple functions gives ∫c1E dP=cP(E) for c≥0. Since 0<x<1 and P(K)=1, these rules also give ∫Kx dP≤1<∞.

[F2]

Attainment and finite support for compact continuous mixtures: compactness of the generator space is among the hypotheses of its attained-minimum result.

Counterexample

Given: [A1] and the mixture objective [F1].

1.1A1F1algebra

For each integer n≥2, the set En=[1/n,1) is Borel, and ⋃n≥2En=(0,1). Since P((0,1))=1, at least one En has positive probability: otherwise the disjoint sets E2,E3∖E2,E4∖E3,… all have probability zero, and countable additivity would give P((0,1))=0. On En, x≥1/n, while elsewhere x≥0, so ∫(0,1)x dP≥1nP(En)>0. Therefore every admissible probability has strictly positive objective.

2.1A1F1F2step 1.1∎

The point mass δ1/n at 1/n is a Borel probability on (0,1) and has objective 1/n. These values tend to zero, while 1.1 shows all objectives are positive. Hence the infimum is zero and is not attained. The generator set is noncompact, so this conclusion does not contradict the compact result [F2]; it shows why an attainment theorem must retain its compactness/coercivity hypotheses.

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

A controlled nonconcave entropy model with ensemble inequivalence

Statement refuted

For every sequence of finite systems with admissible exact-group microcanonical energy densities tending to an interior value e, there is a fixed positive inverse temperature for which the canonical energy density concentrates at e as system size tends to infinity, without further hypotheses such as entropy concavity.

Example

Fix an energy scale ε>0. For each N≥1 and k=0,…,N, set eN,k=1+k/N, EN,k=NεeN,k, and gN,k:=⌊eNeN,k2⌋. Construct the finite state set {(k,j):0≤k≤N, 1≤j≤gN,k} with energy EN,k for each state in group k. Its dimensionless exact-group entropy density tends uniformly on the grid to s(e)=e2 on [1,2], which is nonconcave. For fixed inverse temperature β>0, put b=βε and let pN(b) be the canonical log partition sum per site. Then pN(b)⟶max⁡1≤e≤2(e2−be)=max⁡(1−b,4−2b). For every compact K⊂(1,2), the canonical probability that the energy density lies in K tends to zero, while an exact microcanonical group with eN,kN→e∈(1,2) is supported at that interior density and has entropy density tending to e2. This is an explicit constructed finite sequence demonstrating that ensemble equivalence does not follow from large N alone.

Facts & Assumptions

Given: The finite group degeneracies, energies, and canonical weighting defined in the statement.

[A1]

ε>0, N≥1, eN,k=1+k/N, and gN,k=⌊eNeN,k2⌋.

[A2]

At b=βε>0, the group weight is gN,ke−NbeN,k; an exact microcanonical group is uniform on its gN,k states.

[F1]
[F2]

The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t: log⁡ is continuous and increasing on (0,∞).

Counterexample

Given: [A1]–[A2] and [F1]–[F3].

1.1A1F1F2

Since eN,k≥1, eNeN,k2≥eN. For x≥eN, x−1≤⌊x⌋≤x, so eN,k2+1Nlog⁡(1−e−N)≤1Nlog⁡gN,k≤eN,k2. The error tends to zero uniformly in k. The grid mesh is 1/N; for a continuous function on [1,2], uniform continuity makes its grid maxima converge to its interval maximum.

2.1A1A2F1F2step 1.1algebra

Let ZN(b)=∑k=0NgN,ke−NbeN,k and mN=max⁡k[N−1log⁡gN,k−beN,k]. The largest summand is eNmN and there are N+1 summands, so mN≤N−1log⁡ZN(b)≤mN+N−1log⁡(N+1). By 1.1, mN→max⁡e∈[1,2](e2−be). If e=θ⋅1+(1−θ)⋅2 with 0<θ<1, direct expansion gives e2−be=θ(1−b)+(1−θ)(4−2b)−θ(1−θ), strictly below the weighted endpoint values. Thus the maximum is at an endpoint and equals max⁡(1−b,4−2b).

3.1A1A2F1F2F3step 1.1step 2.1

If K=∅, the probability is zero. Otherwise, for compact K⊂(1,2) strict convexity gives η:=min⁡e∈K[max⁡(1−b,4−2b)−(e2−be)]>0 by [F3]. Uniform approximation in 1.1 makes every grid exponent in K at most the maximum minus η/2 for all sufficiently large N. On the other hand, an endpoint group has exponent tending to the maximum. By [F2], log⁡(N+1)/N≤2N+1/N→0, so the polynomial factor is dominated by the exponential gap and the canonical probability of K, at most (N+1)e−Nη/2+o(N), tends to zero.

4.1A1A2step 1.1step 3.1∎

Choose integers kN with eN,kN→e∈(1,2). The microcanonical exact-group law has energy density exactly eN,kN at every state. By 1.1 its entropy density N−1log⁡gN,kN tends to e2. Thus, for example at the crossing b=3, canonical mass escapes every compact neighborhood of any interior target while the microcanonical group remains there. Finally s(3/2)=9/4<5/2=(s(1)+s(2))/2, so s(e)=e2 is not concave. The example is a constructed model, not an observation about a material.

CounterexampleConstruction: 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 finite-volume Hamiltonian map that is not ergodic

Statement refuted

Every nonzero-time map of a complete Hamiltonian flow preserving finite symplectic volume is ergodic with respect to the normalized volume measure.

Example

On the symplectic torus T2=(R/2πZ)2 with ω=dq∧dp, let H(q,p)=cos⁡q. The Hamiltonian flow is complete and preserves finite area, but every nonzero-time map is nonergodic: the invariant set A={(q,p):cos⁡q>0} has exactly half the total area. This gives a concrete reason volume preservation alone cannot identify time averages with whole-space ensemble averages.

Facts & Assumptions

Given: The symplectic torus, canonical Hamiltonian convention, and area measure.

[A1]

q,p are angular coordinates modulo 2π, ω=dq∧dp, and H(q,p)=cos⁡q.

[F1]

Symplectic form and symplectic manifold and Hamiltonian vector field and Hamiltonian function: a Hamiltonian vector field satisfies ιXHω=dH.

[F2]

Hamiltonian volume, recurrence, and ergodic scope: a complete invariant Hamiltonian flow map preserves symplectic area.

[F3]

Ergodicity relative to an invariant measure: ergodicity requires every invariant measurable set to have measure zero or full measure.

Counterexample

Given: [A1] and the canonical convention [F1].

1.1A1F1algebra

Write XH=a∂q+b∂p. Then ιXH(dq∧dp)=a dp−b dq, while dH=−sin⁡q dq. Equating coefficients gives a=0 and b=sin⁡q. The explicit solution is ϕt(q,p)=(q,p+tsin⁡q(mod2π)), which is defined for every real t and is a diffeomorphism with inverse ϕ−t.

2.1A1F2F3step 1.1algebra∎

Since H∘ϕt=H, the set A is invariant under every ϕt. The torus has total area (2π)2=4π2. The allowed q values in A have total length π, while p ranges over length 2π, so m(A)=2π2, strictly between zero and total area. The map preserves area by [F2], and the invariant set violates the criterion [F3]; hence it is not ergodic for any nonzero sampling time.

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 →

Pure-state entropy and entropy of a dephased average

Example

Use H=C2 with ⟨z,w⟩=z1w1‾+z2w2‾, linear in the first argument, and u1=(1,0), u2=(0,1). Choose real E1≠E2 and define the self-adjoint energy operator A(z1,z2)=(E1z1,E2z2). Fix ℏ>0. For t∈R set Utuj=e−iEjt/ℏuj, and define Pjz=⟨z,uj⟩uj, ρt=UtρUt∗, and for T∈(0,∞) define ρˉT=T−1∫0Tρt dt by entrywise integration. All limits below are as T→+∞. Let ψ=(u1+u2)/2, ρ=∣ψ⟩⟨ψ∣. Define the finite-dimensional entropy of a density matrix with eigenvalues pi as S(ρ)=−kB∑ipilog⁡pi, with 0log⁡0=0 and fixed kB>0. Every instantaneous unitary state ρt is pure and has entropy zero. The Cesàro states converge to ρdiag=(P1+P2)/2, whose entropy is kBlog⁡2. In fact S(ρˉT)→kBlog⁡2, whereas T−1∫0TS(ρt) dt=0 for every T>0. Entropy of the averaged state and average instantaneous entropy are distinct quantities.

Facts & Assumptions

Given: The two-level discrete-spectrum model, pure initial density, and entropy convention in the statement.

[A1]

u1,u2 are orthonormal, E1≠E2, ℏ>0, t∈R, T>0, and ρ=∣ψ⟩⟨ψ∣ for ψ=(u1+u2)/2.

[F1]

exp⁡(x+iy)=ex(cos⁡y+isin⁡y), ∣exp⁡(x+iy)∣=ex, and eiπ+1=0, The complex exponential is entire and its complex derivative is itself, and The second fundamental theorem: if G is differentiable on [a,b] with G′=f and f is integrable, then ∫abf=G(b)−G(a): imaginary exponential phases have modulus one, their derivatives give the explicit antiderivative, and the real and imaginary integrals are evaluated componentwise. The finite-dimensional Cesàro limit is computed here and does not invoke an uninstantiated infinite-dimensional Gibbs-spectrum theorem.

Verification

Given: [A1] and the entropy convention.

1.1A1F2algebra

The unitary evolution sends ψ to (e−iE1t/ℏu1+e−iE2t/ℏu2)/2, which remains a unit vector by [F2]. Its rank-one density has eigenvalues 1,0, so its entropy is −kB(1log⁡1+0log⁡0)=0 for every t.

2.1A1F1F3step 1.1

The two energy eigenspaces are one-dimensional. The matrix entry between them is an exponential with nonzero frequency; by [F1] its average has magnitude at most ℏ/(T∣E1−E2∣) and tends to zero. The diagonal entries remain 1/2, so the direct finite-dimensional average yields ρdiag=12P1+12P2. Its eigenvalues are (1/2,1/2), so S(ρdiag)=−kB(12log⁡12+12log⁡12)=kBlog⁡2. Since every S(ρt)=0, the time average of instantaneous entropy is exactly zero.

3.1A1F2F3step 2.1algebra∎

In the basis (u1,u2), ρˉT has diagonal entries 1/2 and off-diagonal entry cT=12T∫0Te−i(E1−E2)t/ℏ dt, whose magnitude is at most ℏ/(T∣E1−E2∣) by direct integration. Its eigenvalues are 1/2±∣cT∣, so both tend to 1/2. Continuity of x↦−xlog⁡x at 1/2 gives S(ρˉT)→kBlog⁡2. Thus entropy of the averaged state has a nonzero limit even though the averaged instantaneous entropy remains zero.

Sources