- General info: organizers, aims & scope, venue, Google group…
- Season I, fall 2009 and sping 2010.
- Season II, fall 2010 and spring 2011.

- Vladik AVETISOV (N. N. Semenov Institute for Chemical Physics)
- Serguei NECHAEV (P. N. Lebedev Physics Institute & LPTMS, Université Paris-Sud/Orsay)
- Andrei SOBOLEVSKI (Institute for Information Transmission Problems & Laboratoire J.-V. Poncelet, sobolevski@iitp.ru)
- Misha TAMM (Physics Department, M. V. Lomonosov Moscow State University)

Modern aspects of statistical physics and its applications. The
seminar welcomes **survey talks** by senior researchers
for the student audience and, more importantly, **talks by
students** of undergraduate and graduate level on their
research in progress. Note that therefore abstracts of talks are
not always available. Nevertheless we aim at keeping the seminar
interesting for senior participants (and so far seem to have been
succeeding in this!).

We mostly meet at the premises of Laboratoire Jean-Victore Poncelet at the Independent University of Moscow (access instructions in Russian are here).

The seminar has a dedicated Google group, poncelet-seminar-jeune (in Russian, in spite of its French name).

Sergei NECHAEV, P. N. Lebedev Physics Institute & LPTMS, Orsay: *Combinatorics
of locally free groups and statistical physics*

We will talk on word enumeration in a “locally free group”, which approximates the braid group and give a nontrivial estimate on the growth rate of irreducible words in the braid group. This problem will be related to the evaluation of partition function for “lattice animals.”

Olga Valba, PhysTech & LPTMS, Orsay: *From sequence
comparison algorithms to the determination of pairing energy
between two RNAs*.

Noncoding RNAs are those RNAs that do not encode proteins. However they have other important functions, such as regulation of gene expression. A non-coding RNA may pair with a matrix RNA, thus stopping translation from the latter. We present an algorithm to determine the pairing energy of two RNAs in the most general setting, where each RNA may form “cactus-like” structures. An algorithm for reconstruction of the ground state of two paired RNAs will also be described.

Olga STETIUKHINA, MSU
Math. & Mech. Dept & N. N. Semenov Institute for Chemical Physics:
*Correspondence between random walks on an ultrametric discrete
lattice and on the p-adic line*

Behaviour of complex biological systems, such as protein
structure and dynamics, can often be modeled with ultrametric random
processes. The corresponding analytical approaches employ a
*p*-adic equation of ultrametric diffusion whereas numerical
approaches emphasize a random walk on ultrametric discrete lattice.
In this talk we present discrete and contiunuos descriptions of
ultrametric random walk or diffusion. All the necessary background
from *p*-adic analysis will be introduced in the course of
exposition.

Dmitry USHAKOV, MSU Psychology
Dept: *Some [neural] network models of the human cognitive
system*.

Anna BODROVA, MSU Physics
Dept: *Size distribution of particles in the rings of
Saturn*.

The rings of Saturn are comprised with microscopic particles of ice dust as well as with boulders as big as a house. The size distribution of these objects is described with a power law for small scales, while the large scales show exponential decay. This distribution can be obtained analytically from a kinetic model for hard spheres that can coalesce or undergo fission upon collisions.

Alexander MIKHAILOV, Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin:
*Understanding protein machines*.

Misha TAMM, MSU Physics
Dept: *A queue model (continued)*.

Misha TAMM, MSU Physics
Dept: *A queue model (continued)*.

Misha TAMM, MSU Physics
Dept: *A queue model*.

We consider a one-dimensional model of a driven motion which differs from the original ASEP (asymmetric simple exclusion process) in a sense that the moving particles have two internal states - ground (unable to move) and excited (ready to move). Thus, before a particle moves it has to be excited, and after a move the excitation is relaxed. The important feature of the model, which makes it essentially different from the conventional ASEP is that in a case of failed (due to a traffic jam) movement attempt the particle's excitation does not relax.

Gregory KUCHEROV, LIFL &
Laboratoire
J.-V. Poncelet: *On the distribution of word frequencies
in genomes*.

We observe that the distribution of occurrence numbers of k-words (k-mers) in genomic sequences cannot be explained by Bernoulli ou Markov distributions, usually used in bioinformatics to model DNA sequences. I will speculate on causes and consequences of this observation and propose a probability law that fits well to the observed distribution.

Olga VALBA, PhysTech:
*Statistical comparison algorithms for RNA-like
macromolecules*.

Alexei SHKARIN, PhysTech:
*Statistical properties of random hierarchical networks*.

Last modified: Tue Mar 8 16:59:18 MSK 2011