2,828 research outputs found
Opacity for Linear Constraint Markov Chains
On a partially observed system, a secret Ď• is opaque if an observer cannot ascertain that its trace belongs to Ď•. We consider specifications given as Constraint Markov Chains (CMC), which are underspec-ified Markov chains where probabilities on edges are required to belong to some set. The nondeterminism is resolved by a scheduler, and opacity on this model is defined as a worst case measure over all implementations obtained by scheduling. This measures the information obtained by a passive observer when the system is controlled by the smartest sched-uler in coalition with the observer. When restricting to the subclass of Linear CMC, we compute (or approximate) this measure and prove that refinement of a specification can only improve opacity
Haldane linearisation done right: Solving the nonlinear recombination equation the easy way
The nonlinear recombination equation from population genetics has a long
history and is notoriously difficult to solve, both in continuous and in
discrete time. This is particularly so if one aims at full generality, thus
also including degenerate parameter cases. Due to recent progress for the
continuous time case via the identification of an underlying stochastic
fragmentation process, it became clear that a direct general solution at the
level of the corresponding ODE itself should also be possible. This paper shows
how to do it, and how to extend the approach to the discrete-time case as well.Comment: 12 pages, 1 figure; some minor update
- …