19,171 research outputs found
Extreme Quantum Advantage for Rare-Event Sampling
We introduce a quantum algorithm for efficient biased sampling of the rare
events generated by classical memoryful stochastic processes. We show that this
quantum algorithm gives an extreme advantage over known classical biased
sampling algorithms in terms of the memory resources required. The quantum
memory advantage ranges from polynomial to exponential and when sampling the
rare equilibrium configurations of spin systems the quantum advantage diverges.Comment: 11 pages, 9 figures;
http://csc.ucdavis.edu/~cmg/compmech/pubs/eqafbs.ht
Biological evolution through mutation, selection, and drift: An introductory review
Motivated by present activities in (statistical) physics directed towards
biological evolution, we review the interplay of three evolutionary forces:
mutation, selection, and genetic drift. The review addresses itself to
physicists and intends to bridge the gap between the biological and the
physical literature. We first clarify the terminology and recapitulate the
basic models of population genetics, which describe the evolution of the
composition of a population under the joint action of the various evolutionary
forces. Building on these foundations, we specify the ingredients explicitly,
namely, the various mutation models and fitness landscapes. We then review
recent developments concerning models of mutational degradation. These predict
upper limits for the mutation rate above which mutation can no longer be
controlled by selection, the most important phenomena being error thresholds,
Muller's ratchet, and mutational meltdowns. Error thresholds are deterministic
phenomena, whereas Muller's ratchet requires the stochastic component brought
about by finite population size. Mutational meltdowns additionally rely on an
explicit model of population dynamics, and describe the extinction of
populations. Special emphasis is put on the mutual relationship between these
phenomena. Finally, a few connections with the process of molecular evolution
are established.Comment: 62 pages, 6 figures, many reference
Prospects of Transition Interface Sampling simulations for the theoretical study of zeolite synthesis
The transition interface sampling (TIS) technique allows to overcome large
free energy barriers within reasonable simulation time, which is impossible for
straightforward molecular dynamics. Still, the method does not impose an
artificial driving force, but it surmounts the timescale problem by an
importance sampling of true dynamical pathways. Recently, it was shown that the
efficiency of TIS to calculate reaction rates is less sensitive to the choice
of reaction coordinate than those of the standard free energy based techniques.
This could be an important advantage in complex systems for which a good
reaction coordinate is usually very difficult to find. We explain the
principles of this method and discuss some of the promising applications
related to zeolite formation.Comment: 9 pages, accepted for publication in Phys. Chem. Chem. Phys. for the
special issue of the CECAM workshop: Computational aspects of building
blocks, nucleation, and synthesis of porous materials Aug. 29 2006 to Aug. 31
200
An Infinite Swapping Approach to the Rare-Event Sampling Problem
We describe a new approach to the rare-event Monte Carlo sampling problem.
This technique utilizes a symmetrization strategy to create probability
distributions that are more highly connected and thus more easily sampled than
their original, potentially sparse counterparts. After discussing the formal
outline of the approach and devising techniques for its practical
implementation, we illustrate the utility of the technique with a series of
numerical applications to Lennard-Jones clusters of varying complexity and
rare-event character.Comment: 24 pages, 16 figure
Facing the LISA Data Analysis Challenge
By being the first observatory to survey the source rich low frequency region
of the gravitational wave spectrum, the Laser Interferometer Space Antenna
(LISA) will revolutionize our understanding of the Cosmos. For the first time
we will be able to detect the gravitational radiation from millions of galactic
binaries, the coalescence of two massive black holes, and the inspirals of
compact objects into massive black holes. The signals from multiple sources in
each class, and possibly others as well, will be simultaneously present in the
data. To achieve the enormous scientific return possible with LISA,
sophisticated data analysis techniques must be developed which can mine the
complex data in an effort to isolate and characterize individual signals. This
proceedings paper very briefly summarizes the challenges associated with
analyzing the LISA data, the current state of affairs, and the necessary next
steps to move forward in addressing the imminent challenges.Comment: 4 pages, no figures, Proceedings paper for the TeV Particle
Astrophysics II conference held Aug 28-31 at the Univ. of Wisconsi
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