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Path entropy production, fluctuation symmetry and work identities — Examples
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Areas of Elementary Plane Figures
- Binary Operations, Monoids, Groups and Subgroups
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Determinants of Matrices over a Commutative Ring
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Lebesgue Measure on Euclidean Space
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Outer Measure and the Caratheodory Extension Theorem
- Path entropy production, fluctuation symmetry and work identities
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Probability Spaces Random Variables and Expectation
- Product Measures and the Fubini Tonelli Theorems
- Properties of the Integral and the Working FTC
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Simple Field Extensions and the Construction of the Complex Numbers
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Derivative and the Mean Value Theorems
- The Exponential Function
- The Lebesgue and Riemann Integrals Compared
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Riemann Integral in Rᵐ and Jordan Content
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
3 · Logical flowchart
4 · Definitions, postulates, theorems and proofs
Entropy production on a finite biased ring
Example
Let be an integer and let the state space be the ring . From state , let the constant clockwise rate to be and the counterclockwise rate to be , with all other off-diagonal rates zero. Start the finite-state process in the uniform law . If and denote the numbers of clockwise and counterclockwise jumps on , then is stationary and, almost surely, the stationary path entropy is
Its mean is . Reversibility here means detailed balance with respect to the stationary law; it holds exactly when . For every finite , this ring also satisfies the exact measure fluctuation relation , where is the law of . If are physical rates, they have units of inverse time; and are dimensionless.
Statement references
Finite-state continuous-time Markov jump processes with bounded rates
Expected directed jump counts for a finite-state rate process
Stationary path entropy for a finite-state jump process
Finite-time fluctuation identity for stationary path entropy
Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm
Facts & Assumptions
Given: The ring size , positive rates , finite duration , and uniform initial law in the Example.
Finite-state continuous-time Markov jump processes with bounded rates: from each state , the only transitions are at rate and at rate .
Forward equation and stationary laws for finite-state rate processes: if a probability row vector satisfies for a constant rate matrix, then the process started in has law at every time.
Expected directed jump counts for a finite-state rate process: for distinct states , .
Stationary path entropy for a finite-state jump process: each jump contributes to .
Finite-time fluctuation identity for stationary path entropy: for a finite irreducible chain with positive stationary law and symmetric support, and as measures.
Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm: is strictly increasing on .
The Axiom of Countable Choice (): Countable Choice, used by the Lebesgue jump-path construction underlying [F3] and [F5].
Verification
Given: The finite ring and the suppliers [F1]–[F6].
The total rate leaving every state is . Each state also receives total stationary flow from its two neighbors, so the uniform row vector satisfies . By [F2], starting the process in makes it stationary. The condition ensures and are distinct states.
By [F1] and [F4], almost surely every jump is clockwise or counterclockwise. A clockwise jump contributes , while a counterclockwise jump contributes . Summing these almost-sure increments gives almost surely, including the no-jump case when both counts are zero.
Detailed balance on an edge requires , which under the uniform law is equivalent to . If , this equality holds on every edge; nonedges have zero rate in both directions. Hence detailed balance holds exactly in the symmetric-rate case.
By [F3] and stationarity from step 1.1, Thus step 1.2 gives . Since is strictly increasing by [F6], and have the same sign, so their product is nonnegative.
The ring is irreducible because both rates are positive and repeated clockwise jumps connect every pair of states. It has positive stationary law and symmetric support because every edge has both rates positive. Therefore [F5] applies and gives the stated exact finite-time fluctuation relation, with no assumption of a probability density for .
5 · Examples, experiments and counterexamples
None yet.