Armenian Genocide: Negation, Silence and Human Rights (1915-2015)
Visit from professor Ian Mackenzie for the consolidation of scientific partnership...
Exploring AC Transport Properties in the Vicinity of the Superconducting Critical ...
| Grant number: | 08/10420-9 |
| Support Opportunities: | Research Grants - Visiting Researcher Grant - International |
| Start date: | March 17, 2009 |
| End date: | June 24, 2009 |
| Field of knowledge: | Physical Sciences and Mathematics - Physics - General Physics |
| Principal Investigator: | José Fernando Fontanari |
| Grantee: | José Fernando Fontanari |
| Visiting researcher: | Davit Sahakyan |
| Visiting researcher institution: | Yerevan Physics Institute (YerPhi), Armenia |
| Host Institution: | Instituto de Física de São Carlos (IFSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil |
Abstract
We are planning interdisciplinary research at the cross of physics and biology. For the problem with few degrees of freedom mathematics is a good tool and for the many degrees statistical mechanics, perhaps, is the best in application.In evolution problems both genome and population sizes are large, giving a chance the statistical physics be applied. The models (non-linearMarkov models for infinite population case or Markov models with very large space of possible states), suggested by biologists for the important evolution problems, will be solved rigorously (sometimes exactly) using the methods of theoretical physics: statistical physics of disordered systems, quantum field theory and Hamilton-Jacobi equations (Hamilton mechanics). Exact solution are important, as the evolution phenomenon often is either non-perturbative,or has a rather subtle structure; quite reasonable mathematical approximationsin literature could overestimate the results hundreds of times. We are going to solve exactly evolution models, where fitness has both deterministic and random components, to clarify the issue: how directed is evolution? Among the tasks planned to be investigated are: 1. Exact dynamics for parallel evolution model with Random Energy Like fitness landscape. 2. The relationship of evolution with information theory. 3. Evolution in case of smooth and random fitnesses. (AU)
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