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S. Vakulenko

Publications and source records attributed to S. Vakulenko.

3 recordsLinked to original sources

Biodiversity, extinctions and evolution of ecosystems with shared resources

We investigate the formation of stable ecological networks where many species share the same resource. We show that such stable ecosystem naturally occurs as a result of extinctions. We obtain an analytical relation for the number of coexisting species and find a relation describing how many species that may go extinct as a result of a sharp environmental change. We introduce a special parameter that is a combination of species traits and resource characteristics used in the model formulation. This parameter describes the pressure on system to converge, by extinctions. When that stress parameter is large we obtain that the species traits concentrate at some values. This stress parameter is thereby a parameter that determines the level of final biodiversity of the system. Moreover, we show that dynamics of this limit system can be described by simple differential equations.

q-bio.PE

Quantum optical device accelerating dynamic programming

In this paper we discuss analogue computers based on quantum optical systems accelerating dynamic programming for some computational problems. These computers, at least in principle, can be realized by actually existing devices. We estimate an acceleration in resolving of some NP-hard problems that can be obtained in such a way versus deterministic computers

quant-ph

Patterning by genetic networks and modular principle

We consider here the morphogenesis (pattern formation) problem for some genetic network models. First, we show that any given spatio-temporal pattern can be generated by a genetic network involving a sufficiently large number of genes. Moreover, patterning process can be performed by an effective algorithm. We also show that Turing's or Meinhardt's type reaction-diffusion models can be approximated by genetic networks. These results exploit the fundamental fact that the genes form functional units and are organised in blocks (modular principle). Due to this modular organisation, the genes always are capable to construct any new patterns and even any time sequences of new patterns from old patterns. Computer simulations illustrate analytical results.

math.DS