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Finite-channel reaction propensity systems and their generator
Definition
Fix positive integers and . A reaction propensity system consists of a state set that is finite or countable, increments for , and propensities . Here “countable” means finite or countably infinite, as in Finite, countably infinite, countable, uncountable. The total propensity is finite for every , and implies . Here and have the meanings in The natural numbers (von Neumann) and The integers as equivalence classes of pairs of naturals, and addition in is coordinatewise.
A reaction event of channel at state records the marked transition . The counting process records the number of channel- events by time . A zero increment is allowed: it records a reaction event without changing the state.
For a time-homogeneous system, the reaction generator operator on bounded functions is When is finite, set ; thus for and otherwise. If no active reaction has zero increment, the corresponding matrix has off-diagonal entries and diagonal . With zero-increment events, the operator formula remains valid and the matrix diagonal is instead minus the sum of state-changing rates; the zero-increment channels remain part of the marked event process.
For a finite horizon , a time-dependent propensity system replaces by functions whose sections are measurable for the Borel sigma-algebra of the usual topology on (The Borel sigma-algebra of a topological space). Require finite total rate . Its time-dependent generator operator is This definition specifies a stochastic model. It does not assert that a physical chemical system follows that model.
Depends on
Used by
- Critical-reaction binomial guarded tau-leaping Algorithm
- Dominating thinning for bounded time-varying propensities Algorithm
- Explicit Poisson tau-leaping with an invalid-state status Algorithm
- Gillespie direct method with horizon and budget statuses Algorithm
- Minimum-intensity coupling of reaction networks Algorithm
- Next-reaction method by internal Poisson clocks Algorithm
- Clipping an understated thinning envelope changes the waiting-time law Counterexample
- Quadratic pure-birth rates can explode Counterexample
- Density-scaled reaction jump and chemical Langevin generators Definition
- A binomial guard prevents overdraw but changes Poisson noise Example
- A Poisson leap can make a pure-death population negative Example
- A stiff reversible system exposes explicit tau-leap mean instability Example
- A zero-total-hazard state is absorbing Example
- Gillespie simulation of a finite birth-death reaction network Example
- Immigration-death chain projected onto two states Example
- Minimum-intensity coupling of two birth-death chains Example
- Conditional moments of one Poisson tau-leap increment Lemma
- Dynkin identity for a bounded-rate finite stopped reaction chain Lemma
- One-step weak defect of finite-state Poisson tau-leaping Lemma
- A proper Lyapunov bound prevents reaction-network explosion Theorem
- Compensators, brackets, and jump-integral isometry for reaction counts Theorem
- Dominating thinning has the prescribed reaction law Theorem
- Finite-state Gillespie and next-reaction methods have the specified CTMC law Theorem
- Order-one correction variance for coupled Poisson tau-leap levels Theorem
- The minimum-intensity reaction coupling preserves both marginals Theorem
- Weak order one for finite-state Poisson tau-leaping with an exit bound Theorem
Dependency tree · two levels
17 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- David F. Anderson, Introduction to Stochastic Processes with Applications to Biology, Chapters 6–7 (standard reference, not scraped)
- David F. Anderson and Thomas G. Kurtz, Continuous Time Markov Chain Models for Chemical Reaction Networks (standard reference, not scraped)