622 research outputs found

    Multi-Overlap Simulations for Transitions between Reference Configurations

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    We introduce a new procedure to construct weight factors, which flatten the probability density of the overlap with respect to some pre-defined reference configuration. This allows one to overcome free energy barriers in the overlap variable. Subsequently, we generalize the approach to deal with the overlaps with respect to two reference configurations so that transitions between them are induced. We illustrate our approach by simulations of the brainpeptide Met-enkephalin with the ECEPP/2 energy function using the global-energy-minimum and the second lowest-energy states as reference configurations. The free energy is obtained as functions of the dihedral and the root-mean-square distances from these two configurations. The latter allows one to identify the transition state and to estimate its associated free energy barrier.Comment: 12 pages, (RevTeX), 14 figures, Phys. Rev. E, submitte

    Overlap Distribution of the Three-Dimensional Ising Model

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    We study the Parisi overlap probability density P_L(q) for the three-dimensional Ising ferromagnet by means of Monte Carlo (MC) simulations. At the critical point P_L(q) is peaked around q=0 in contrast with the double peaked magnetic probability density. We give particular attention to the tails of the overlap distribution at the critical point, which we control over up to 500 orders of magnitude by using the multi-overlap MC algorithm. Below the critical temperature interface tension estimates from the overlap probability density are given and their approach to the infinite volume limit appears to be smoother than for estimates from the magnetization.Comment: 7 pages, RevTex, 9 Postscript figure

    Simulated-tempering approach to spin-glass simulations

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    After developing an appropriate iteration procedure for the determination of the parameters, the method of simulated tempering has been successfully applied to the 2D Ising spin glass. The reduction of the slowing down is comparable to that of the multicanonical algorithm. Simulated tempering has, however, the advantages to allow full vectorization of the programs and to provide the canonical ensemble directly.Comment: 12 pages (LaTeX), 4 postscript figures, uufiles encoded, submitted to Physical Review

    SU(2) potentials in quantum gravity

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    We present investigations of the potential between static charges from a simulation of quantum gravity coupled to an SU(2) gauge field on 63×46^{3}\times 4 and 83×48^{3}\times 4 simplicial lattices. In the well-defined phase of the gravity sector where geometrical expectation values are stable, we study the correlations of Polyakov loops and extract the corresponding potentials between a source and sink separated by a distance RR. In the confined phase, the potential has a linear form while in the deconfined phase, a screened Coulombic behavior is found. Our results indicate that quantum gravitational effects do not destroy confinement due to non-abelian gauge fields.Comment: 3 pages, contribution to Lattice 94 conference, uuencoded compressed postscript fil

    Spin glass overlap barriers in three and four dimensions

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    For the Edwards-Anderson Ising spin-glass model in three and four dimensions (3d and 4d) we have performed high statistics Monte Carlo calculations of those free-energy barriers FBqF^q_B which are visible in the probability density PJ(q)P_J(q) of the Parisi overlap parameter qq. The calculations rely on the recently introduced multi-overlap algorithm. In both dimensions, within the limits of lattice sizes investigated, these barriers are found to be non-self-averaging and the same is true for the autocorrelation times of our algorithm. Further, we present evidence that barriers hidden in qq dominate the canonical autocorrelation times.Comment: 20 pages, Latex, 12 Postscript figures, revised version to appear in Phys. Rev.

    About the Functional Form of the Parisi Overlap Distribution for the Three-Dimensional Edwards-Anderson Ising Spin Glass

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    Recently, it has been conjectured that the statistics of extremes is of relevance for a large class of correlated system. For certain probability densities this predicts the characteristic large xx fall-off behavior f(x)exp(aex)f(x)\sim\exp (-a e^x), a>0a>0. Using a multicanonical Monte Carlo technique, we have calculated the Parisi overlap distribution P(q)P(q) for the three-dimensional Edward-Anderson Ising spin glass at and below the critical temperature, even where P(q)P(q) is exponentially small. We find that a probability distribution related to extreme order statistics gives an excellent description of P(q)P(q) over about 80 orders of magnitude.Comment: 4 pages RevTex, 3 figure

    Phase diagram of Regge quantum gravity coupled to SU(2) gauge theory

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    We analyze Regge quantum gravity coupled to SU(2) gauge theory on 43×24^3\times 2, 63×46^{3}\times 4 and 83×48^{3}\times 4 simplicial lattices. It turns out that the window of the well-defined phase of the gravity sector where geometrical expectation values are stable extends to negative gravitational couplings as well as to gauge couplings across the deconfinement phase transition. We study the string tension from Polyakov loops, compare with the β\beta-function of pure gauge theory and conclude that a physical limit through scaling is possible.Comment: RevTeX, 14 pages, 5 figures (2 eps, 3 tex), 2 table

    Determining the density of states for classical statistical models: A random walk algorithm to produce a flat histogram

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    We describe an efficient Monte Carlo algorithm using a random walk in energy space to obtain a very accurate estimate of the density of states for classical statistical models. The density of states is modified at each step when the energy level is visited to produce a flat histogram. By carefully controlling the modification factor, we allow the density of states to converge to the true value very quickly, even for large systems. This algorithm is especially useful for complex systems with a rough landscape since all possible energy levels are visited with the same probability. In this paper, we apply our algorithm to both 1st and 2nd order phase transitions to demonstrate its efficiency and accuracy. We obtained direct simulational estimates for the density of states for two-dimensional ten-state Potts models on lattices up to 200×200200 \times 200 and Ising models on lattices up to 256×256256 \times 256. Applying this approach to a 3D ±J\pm J spin glass model we estimate the internal energy and entropy at zero temperature; and, using a two-dimensional random walk in energy and order-parameter space, we obtain the (rough) canonical distribution and energy landscape in order-parameter space. Preliminary data suggest that the glass transition temperature is about 1.2 and that better estimates can be obtained with more extensive application of the method.Comment: 22 pages (figures included

    Multicanonical Multigrid Monte Carlo

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    To further improve the performance of Monte Carlo simulations of first-order phase transitions we propose to combine the multicanonical approach with multigrid techniques. We report tests of this proposition for the dd-dimensional Φ4\Phi^4 field theory in two different situations. First, we study quantum tunneling for d=1d = 1 in the continuum limit, and second, we investigate first-order phase transitions for d=2d = 2 in the infinite volume limit. Compared with standard multicanonical simulations we obtain improvement factors of several resp. of about one order of magnitude.Comment: 12 pages LaTex, 1 PS figure appended. FU-Berlin preprint FUB-HEP 9/9

    Flat histogram simulation of lattice polymer systems

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    We demonstrate the use of a new algorithm called the Flat Histogram sampling algorithm for the simulation of lattice polymer systems. Thermodynamics properties, such as average energy or entropy and other physical quantities such as end-to-end distance or radius of gyration can be easily calculated using this method. Ground-state energy can also be determined. We also explore the accuracy and limitations of this method. Key words: Monte Carlo algorithms, flat histogram sampling, HP model, lattice polymer systemsComment: 7 RevTeX two-column page
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