6,195 research outputs found
Are there laws of genome evolution?
Research in quantitative evolutionary genomics and systems biology led to the
discovery of several universal regularities connecting genomic and molecular
phenomic variables. These universals include the log-normal distribution of the
evolutionary rates of orthologous genes; the power law-like distributions of
paralogous family size and node degree in various biological networks; the
negative correlation between a gene's sequence evolution rate and expression
level; and differential scaling of functional classes of genes with genome
size. The universals of genome evolution can be accounted for by simple
mathematical models similar to those used in statistical physics, such as the
birth-death-innovation model. These models do not explicitly incorporate
selection, therefore the observed universal regularities do not appear to be
shaped by selection but rather are emergent properties of gene ensembles.
Although a complete physical theory of evolutionary biology is inconceivable,
the universals of genome evolution might qualify as 'laws of evolutionary
genomics' in the same sense 'law' is understood in modern physics.Comment: 17 pages, 2 figure
Calculation of exciton densities in SMMC
We develop a shell-model Monte Carlo (SMMC) method to calculate densities of
states with varying exciton (particle-hole) number. We then apply this method
to the doubly closed-shell nucleus 40Ca in a full 0s-1d-0f-1p shell-model space
and compare our results to those found using approximate analytic expressions
for the partial densities. We find that the effective one-body level density is
reduced by approximately 22% when a residual two-body interaction is included
in the shell model calculation.Comment: 10 pages, 4 figure
Monte Carlo Simulation of Quantum Computation
The many-body dynamics of a quantum computer can be reduced to the time
evolution of non-interacting quantum bits in auxiliary fields by use of the
Hubbard-Stratonovich representation of two-bit quantum gates in terms of
one-bit gates. This makes it possible to perform the stochastic simulation of a
quantum algorithm, based on the Monte Carlo evaluation of an integral of
dimension polynomial in the number of quantum bits. As an example, the
simulation of the quantum circuit for the Fast Fourier Transform is discussed.Comment: 12 pages Latex, 2 Postscript figures, to appear in Proceedings of the
IMACS (International Association for Mathematics and Computers in Simulation)
Conference on Monte Carlo Methods, Brussels, April 9
- …