The Next Round of Hadronic Generator Tuning Heavily Based on Identified Particle Data

Event shape and charged particle inclusive distributions determined from 750 000 hadronic Z events measured with the DELPHI detector at LEP are presented. The statistical and systematic precision of this data allows for a decisive confrontation with Monte Carlo models of the hadronization process and a better understanding of the structure of the Z hadronic final state. Improved tunings of the JETSET, ARIADNE and HERWIG parton shower models and the JETSET matrix element model are obtained by fitting the models to identified particle distributions from all LEP experiments and the DELPHI data presented. The description of the data distributions by the models is critically reviewed with special importance attributed to identified particles.Comment: 73+2 pages, latex, 39 figures appended as uuencoded fil

Ground-state properties of two-dimensional dimerized Heisenberg models

The purpose of this paper is to investigate the ground-state properties of two-dimensional Heisenberg models on a square lattice with a given dimerization. Our aim is threefold: First, we want to investigate the dimensional transition from two to one dimension for three models consisting of weakly coupled chains for large dimerizations. Simple scaling arguments show that the interchain coupling is always relevant. The ground states of two of these models therefore have one-dimensional nature only at the decoupling point. The third considered model is more complicated, because it contains additional relevant intrachain couplings leading to a gap as shown by scaling arguments and numerical investigations. Second, we investigate at which point the dimerization destroys the N\'eel ordered ground state of the isotropic model. Within a mapping to a nonlinear sigma-model and linear spinwave theory (LSWT) we conclude that the stability of the N\'eel ordered state depends on the microscopic details of the model. Third, the considered models also can be regarded as effective models for a spin system with spin-phonon coupling. This leads to the question if a spin-Peierls transition, i.e. a gain of total energy due to lattice distortion, is possible. LSWT shows that such a transition is possible under certain conditions leading to a coexistence of long-range order and spin-Peierls dimerization. We also find that the gain of magnetic energy is largest for a stair-like distortion of the lattice.Comment: 13 pages, 11 figures, revte

The Scaling Behaviour of Stochastic Minimization Algorithms in a Perfect Funnel Landscape

We determined scaling laws for the numerical effort to find the optimal configurations of a simple model potential energy surface (PES) with a perfect funnel structure that reflects key characteristics of the protein interactions. Generalized Monte-Carlo methods(MCM, STUN) avoid an enumerative search of the PES and thus provide a natural resolution of the Levinthal paradox. We find that the computational effort grows with approximately the eighth power of the system size for MCM and STUN, while a genetic algorithm was found to scale exponentially. The scaling behaviour of a derived lattice model is also rationalized

BioPhysConnectoR: Connecting Sequence Information and Biophysical Models

<p>Abstract</p> <p>Background</p> <p>One of the most challenging aspects of biomolecular systems is the understanding of the coevolution in and among the molecule(s).</p> <p>A complete, theoretical picture of the selective advantage, and thus a functional annotation, of (co-)mutations is still lacking. Using sequence-based and information theoretical inspired methods we can identify coevolving residues in proteins without understanding the underlying biophysical properties giving rise to such coevolutionary dynamics. Detailed (atomistic) simulations are prohibitively expensive. At the same time reduced molecular models are an efficient way to determine the reduced dynamics around the native state. The combination of sequence based approaches with such reduced models is therefore a promising approach to annotate evolutionary sequence changes.</p> <p>Results</p> <p>With the <monospace>R</monospace> package <monospace>BioPhysConnectoR</monospace> we provide a framework to connect the information theoretical domain of biomolecular sequences to biophysical properties of the encoded molecules - derived from reduced molecular models. To this end we have integrated several fragmented ideas into one single package ready to be used in connection with additional statistical routines in <monospace>R</monospace>. Additionally, the package leverages the power of modern multi-core architectures to reduce turn-around times in evolutionary and biomolecular design studies. Our package is a first step to achieve the above mentioned annotation of coevolution by reduced dynamics around the native state of proteins.</p> <p>Conclusions</p> <p><monospace>BioPhysConnectoR</monospace> is implemented as an <monospace>R</monospace> package and distributed under GPL 2 license. It allows for efficient and perfectly parallelized functional annotation of coevolution found at the sequence level.</p