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Normalized phase volume and almost-everywhere assertions
Definition
Assume countable choice. Let be a nonempty finite set, let , and identify with by any ordering of . Put , with its quotient topology, and write for the quotient map. Put . A subset is phase-measurable exactly when is Lebesgue measurable; its normalized phase volume is . This is the complete probability measure obtained by pushing normalized Lebesgue measure on through . Write for the sigma-algebra of phase-measurable sets. Phase measurability and normalized phase volume are independent of the ordering of .
A set is phase-null when it is phase-measurable and has volume zero. A statement holds for almost every initial phase when it holds outside a phase-null set. A uniformly sampled phase configuration is a random element on a probability space, whose law is : for every , . An angular chart is the inverse of restricted to a product of open intervals, each of length less than ; its domain is the image of that product. A subset of a chart domain is phase-null exactly when its set of chart coordinates is Lebesgue-null. Every nonempty open subset of has positive phase volume. Phase volume is a measure on phase space; a separately specified probability law for a random graph is a different measure.
Definition references
The Axiom of Countable Choice (AC_ω)
Lebesgue measurable sets, the family L(ℝⁿ), and the restricted set function λₙ
Probability measures and probability spaces
Random elements and real random variables
Law or distribution of a random element
The Borel sigma-algebra of a topological space
Assuming countable choice, every Borel subset of ℝⁿ is Lebesgue measurable
Lebesgue measure on ℝⁿ is invariant under every orthogonal linear map
Facts & Assumptions
Given: Countable choice and a nonempty finite set with .
Goal: Verify the measure, ordering independence, uniform sampling, chart-nullity, positivity, and rescaling assertions in the definition.
Lebesgue measure on is complete under countable choice, and a box has measure equal to the product of its side lengths, irrespective of which faces are included (Lebesgue measurable sets, the family L(ℝⁿ), and the restricted set function λₙ, Assuming countable choice, L(ℝⁿ) is a sigma-algebra containing every elementary set and λₙ is a complete measure extending elementary volume, A box in ℝⁿ with parameters aᵢ≤ bᵢ is Lebesgue measurable of measure ∏_i<n(bᵢ-aᵢ), whichever of its faces are included, The Axiom of Countable Choice (AC_ω)).
Translation preserves Lebesgue outer measure and measurability; dilation by nonzero preserves measurability and multiplies Lebesgue measure by under countable choice (Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation, For a nonzero real c, dilation by c multiplies Lebesgue outer measure by |c|ⁿ, and reflection in the origin preserves it).
The quotient topology makes a set open exactly when its inverse image under is open; finite products of open intervals form a base for Euclidean space (The quotient topology of a surjection, quotient maps, saturated sets, and the quotient of a space by an equivalence relation with its canonical projection, The product set ∏_i ∈ I Xᵢ of functions choosing a point in each factor, the projections, the box topology, and the product topology as the initial topology of the projections; the empty product is a one-point space).
On the period-one finite torus, normalized volume of a Borel set is Lebesgue measure of its inverse image in ; the same Borel volume is obtained using any translated half-open unit cube (math:def-the-one-dimensional-torus-and-normalized-haar-integral).
The Borel sigma-algebra of a topological space is the sigma-algebra generated by its open sets. Under countable choice every Borel subset of , , is Lebesgue measurable (The Borel sigma-algebra of a topological space, Assuming countable choice, every Borel subset of ℝⁿ is Lebesgue measurable).
Under countable choice, every orthogonal linear map of preserves Lebesgue measurability and measure. Here orthogonal means a linear bijection preserving the standard inner product (Lebesgue measure on ℝⁿ is invariant under every orthogonal linear map).
A probability space is a measurable space with a measure of total mass one. A random element of a measurable space is a measurable map from a probability space; its law assigns the probability of its inverse image (Probability measures and probability spaces, Random elements and real random variables, Law or distribution of a random element).
A sigma-algebra is closed under complements relative to its ambient set and under countable unions. A measurable space is a set together with a sigma-algebra. A measure is a nonnegative extended-real-valued function on a sigma-algebra, zero on the empty set and countably additive on disjoint sequences. A measure space is complete if every subset of every measurable null set is measurable (Sigma-algebras, Measurable spaces and measurable sets, Measures on sigma-algebras, Complete measure spaces).
For any measure and sequence of measurable sets , (Finite and countable subadditivity of measures).
Justification
Proof technique: direct.
1.1 Each coordinate has a unique representative in modulo , so is a bijection. Inverse images under this bijection preserve complements and countable unions. Consequently the displayed measurable sets form a sigma-algebra, and their assigned values form a measure by countable additivity of Lebesgue measure. The box formula gives , so the total mass is one. If a phase-measurable set has zero volume, the inverse image in of any subset is a subset of a Lebesgue-null set and hence is measurable and null; thus this pushforward measure is complete. [given, F1, F8]
1.2 Let be the coordinate identifications from two orderings of , and put . This is a linear bijection permuting coordinates, with inverse given by the reverse permutation. Reindexing the finite sum gives , so is orthogonal. For every it carries to and to . Apply orthogonal invariance to and : one representative set is Lebesgue measurable exactly when the other is, and their measures agree. The factor is the same for both orderings, proving independence of phase measurability and volume. Coordinate permutations also carry open boxes to open boxes, so the product and quotient topologies used here do not depend on the ordering. [given, F3, F6]
2.1 By step 1.1, is a probability space. Its identity map is measurable because the inverse image of is itself, and its law assigns the value . It is therefore a uniformly sampled phase configuration in the stated sense, so this formulation has a realization on a probability space. [step 1.1, F7, F8]
2.2 Let be a product of intervals of length less than . Distinct points of cannot differ by a nonzero vector in , so is injective. It is an open map onto its image: the inverse image under of the image of an open subset of is the union of its lattice translates, which is open. Thus its inverse is an angular chart. For , the set is the countable union over of . Translation invariance and countable subadditivity show that if is Lebesgue-null then this inverse image is null. Conversely, is contained in the countable union of translates of ; if the latter is null, then so is . Completeness makes each null set in this argument measurable, proving the chart equivalence. [step 1.1, F1, F2, F3, F8, F9]
3.1 If is nonempty and open, its inverse image is nonempty and open. It contains a nonempty product of bounded open intervals, each shorter than . By the box formula has positive Lebesgue measure. If had zero phase volume, the chart equivalence would make null, a contradiction. Also is open, and is Borel, since it is the finite intersection of the open coordinate conditions and the closed coordinate conditions . Thus is Borel and is Lebesgue measurable under countable choice, proving that is phase-measurable. Since is a sigma-algebra containing the open sets, it contains the Borel sigma-algebra of . [step 1.1, step 2.2, F1, F3, F5]
4.1 Scaling representatives by induces a bijection from to , and becomes . Scaling and inverse scaling carry Euclidean open sets to open sets, so the induced quotient bijection is a homeomorphism. Its inverse images preserve complements and countable unions, so it and its inverse preserve Borel sets. For a Borel set, the dilation formula turns the normalized volume in the definition into the period-one volume computed on this translated half-open cube. Hence the construction has the stated normalization and agrees on Borel sets with the supplied finite-torus measure. The completed pushforward in step 1.1 supplies the phase-null and almost-everywhere conventions without imposing a law on any graph. [step 1.1, step 3.1, F2, F3, F4, F5] ∎
Depends on
- The quotient topology of a surjection, quotient maps, saturated sets, and the quotient of a space by an equivalence relation with its canonical projection
- The product set ∏_i ∈ I Xᵢ of functions choosing a point in each factor, the projections, the box topology, and the product topology as the initial topology of the projections; the empty product is a one-point space
- The Axiom of Countable Choice (AC_ω)
- Lebesgue measurable sets, the family L(ℝⁿ), and the restricted set function λₙ
- Assuming countable choice, L(ℝⁿ) is a sigma-algebra containing every elementary set and λₙ is a complete measure extending elementary volume
- A box in ℝⁿ with parameters aᵢ≤ bᵢ is Lebesgue measurable of measure ∏_i<n(bᵢ-aᵢ), whichever of its faces are included
- Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation
- For a nonzero real c, dilation by c multiplies Lebesgue outer measure by |c|ⁿ, and reflection in the origin preserves it
- The one-dimensional torus and its normalized Haar integral
- Probability measures and probability spaces
- Random elements and real random variables
- Law or distribution of a random element
- The Borel sigma-algebra of a topological space
- Assuming countable choice, every Borel subset of ℝⁿ is Lebesgue measurable
- Lebesgue measure on ℝⁿ is invariant under every orthogonal linear map
- Sigma-algebras
- Measures on sigma-algebras
- Measurable spaces and measurable sets
- Complete measure spaces
- Finite and countable subadditivity of measures
Used by · 17
- Point basins, equilibrium-set basins and aggregate volume
- A null basin for all strict saddles of a smooth compact gradient flow
- Independent inputs for the critical-density bounds
- Earlier thresholds with explicit source quantifiers and a fixed-scale deduction
- Simultaneous global synchronization from connectivity
- Globally synchronizing graph — Definition 1.1
- Spurious minima obstruct global synchrony
- Critical minimum-degree connectivity parameter
- Bounds on the critical connectivity threshold
- Families with vanishing total spurious-basin measure
- Measure-zero convergence to strict saddles
- Positive-semidefinite-equilibrium criterion for global synchrony
- Regular spectral expansion implies synchronization — Theorem 1.4
- Destroying cycle spurious minima by bounded-degree edge additions
- Connectivity is necessary but not sufficient for synchrony
- A positive transverse Hessian gives an open nonsynchronous basin
- A simple nonsynchronizing family approaching eleven sixteenths
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