1,720,991 research outputs found
Relationship between clustering and algorithmic phase transitions in the random k-XORSAT model and its NP-complete extensions
No full textWe study the performances of stochastic heuristic search algorithms on Uniquely Extendible Constraint Satisfaction Problems with random inputs. We show that, for any heuristic preserving the Poissonian nature of the underlying instance, the (heuristic-dependent) largest ratio a,, of constraints per variables for which a search algorithm is likely to find solutions is smaller than the critical ratio alpha(d) above which solutions are clustered and highly correlated. In addition we show that the clustering ratio can be reached when the number k of variables per constraints goes to infinity by the so-called Generalized Unit Clause heuristic
An Algorithm for Counting Circuits: Application to Real-World and Random Graphs.
No full textPreprint cond-mat/050752
Dynamical modeling of molecular constructions and setups for DNA unzipping
No full textWe present a dynamical model of DNA mechanical unzipping under the action of a force. The model includes the motion of a fork in a sequence-dependent landscape, the trap(s) acting on the bead(s) and the polymeric components of the molecular construction (unzipped single strands of DNA and linkers). Different setups are considered to test the model, and the outcome of the simulations is compared to simpler dynamical models existing in the literature where polymers are assumed to be at equilibrium
Von Neumann's expanding model on random graphs
No full textWithin the framework of Von Neumann's expanding model, we study the maximum growth rate achievable by an autocatalytic reaction network in which reactions involve a finite (fixed or fluctuating) number D of reagents. is calculated numerically using a variant of the Minover algorithm, and analytically via the cavity method for disordered systems. As the ratio between the number of reactions and that of reagents increases the system passes from a contracting () to an expanding regime (). These results extend the scenario derived in the fully connected model (D → ∞), with the important difference that, generically, larger growth rates are achievable in the expanding phase for finite D and in more diluted networks. Moreover, the range of attainable values of shrinks as the connectivity increases. © IOP Publishing Ltd
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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