41 research outputs found

    A classification of four-state spin edge Potts models

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    We classify four-state spin models with interactions along the edges according to their behavior under a specific group of symmetry transformations. This analysis uses the measure of complexity of the action of the symmetries, in the spirit of the study of discrete dynamical systems on the space of parameters of the models, and aims at uncovering solvable ones. We find that the action of these symmetries has low complexity (polynomial growth, zero entropy). We obtain natural parametrizations of various models, among which an unexpected elliptic parametrization of the four-state chiral Potts model, which we use to localize possible integrability conditions associated with high genus curves.Comment: 5 figure

    Holonomic functions of several complex variables and singularities of anisotropic Ising n-fold integrals

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    Lattice statistical mechanics, often provides a natural (holonomic) framework to perform singularity analysis with several complex variables that would, in a general mathematical framework, be too complex, or could not be defined. Considering several Picard-Fuchs systems of two-variables "above" Calabi-Yau ODEs, associated with double hypergeometric series, we show that holonomic functions are actually a good framework for actually finding the singular manifolds. We, then, analyse the singular algebraic varieties of the n-fold integrals χ(n) \chi^{(n)}, corresponding to the decomposition of the magnetic susceptibility of the anisotropic square Ising model. We revisit a set of Nickelian singularities that turns out to be a two-parameter family of elliptic curves. We then find a first set of non-Nickelian singularities for χ(3) \chi^{(3)} and χ(4) \chi^{(4)}, that also turns out to be rational or ellipic curves. We underline the fact that these singular curves depend on the anisotropy of the Ising model. We address, from a birational viewpoint, the emergence of families of elliptic curves, and of Calabi-Yau manifolds on such problems. We discuss the accumulation of these singular curves for the non-holonomic anisotropic full susceptibility.Comment: 36 page

    Random Matrix Theory and higher genus integrability: the quantum chiral Potts model

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    We perform a Random Matrix Theory (RMT) analysis of the quantum four-state chiral Potts chain for different sizes of the chain up to size L=8. Our analysis gives clear evidence of a Gaussian Orthogonal Ensemble statistics, suggesting the existence of a generalized time-reversal invariance. Furthermore a change from the (generic) GOE distribution to a Poisson distribution occurs when the integrability conditions are met. The chiral Potts model is known to correspond to a (star-triangle) integrability associated with curves of genus higher than zero or one. Therefore, the RMT analysis can also be seen as a detector of ``higher genus integrability''.Comment: 23 pages and 10 figure

    First-order transition features of the 3D bimodal random-field Ising model

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    Two numerical strategies based on the Wang-Landau and Lee entropic sampling schemes are implemented to investigate the first-order transition features of the 3D bimodal (±h\pm h) random-field Ising model at the strong disorder regime. We consider simple cubic lattices with linear sizes in the range L=4−32L=4-32 and simulate the system for two values of the disorder strength: h=2h=2 and h=2.25h=2.25. The nature of the transition is elucidated by applying the Lee-Kosterlitz free-energy barrier method. Our results indicate that, despite the strong first-order-like characteristics, the transition remains continuous, in disagreement with the early mean-field theory prediction of a tricritical point at high values of the random-field.Comment: 19 pages, 6 figures, slightly extended version as accepted for publicatio

    Critical aspects of the random-field Ising model

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    We investigate the critical behavior of the three-dimensional random-field Ising model (RFIM) with a Gaussian field distribution at zero temperature. By implementing a computational approach that maps the ground-state of the RFIM to the maximum-flow optimization problem of a network, we simulate large ensembles of disorder realizations of the model for a broad range of values of the disorder strength h and system sizes  = L3, with L ≀ 156. Our averaging procedure outcomes previous studies of the model, increasing the sampling of ground states by a factor of 103. Using well-established finite-size scaling schemes, the fourth-order’s Binder cumulant, and the sample-to-sample fluctuations of various thermodynamic quantities, we provide high-accuracy estimates for the critical field hc, as well as the critical exponents Îœ, ÎČ/Îœ, and ÎłÌ…/Îœ of the correlation length, order parameter, and disconnected susceptibility, respectively. Moreover, using properly defined noise to signal ratios, we depict the variation of the self-averaging property of the model, by crossing the phase boundary into the ordered phase. Finally, we discuss the controversial issue of the specific heat based on a scaling analysis of the bond energy, providing evidence that its critical exponent α ≈ 0−

    Exploring the ingredients required to successfully model the placement, generation, and evolution of ice streams in the British-Irish Ice Sheet

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    Ice stream evolution is a major uncertainty in projections of the future of the Greenland and Antarctic Ice sheets. Accurate simulation of ice stream evolution requires an understanding of a number of “ingredients” that control the location and behaviour of ice stream flow. Here, we test the influence of geothermal heat flux, grid resolution, and bed hydrology on simulated ice streaming. The palaeo-record provides snapshots of ice stream evolution, with a particularly well constrained ice sheet being the British-Irish Ice Sheet (BIIS). We implement a new basal sliding scheme coupled with thermo-mechanics into the BISICLES ice sheet model, to simulate the evolution of the BIIS ice streams. We find that the simulated location and spacing of ice streams matches well with the empirical reconstructions of ice stream flow in terms of position and direction when simple bed hydrology is included. We show that the new basal sliding scheme allows the accurate simulation for the majority of BIIS ice streams. The extensive empirical record of the BIIS has allowed the testing of model inputs, and has helped demonstrate the skill of the ice sheet model in simulating the evolution of the location, spacing, and migration of ice streams through millennia. Simulated ice streams also prompt new empirical mapping of features indicative of streaming in the North Channel region. Ice sheet model development has allowed accurate simulation of the palaeo record, and allows for improved modelling of future ice stream behaviour

    Global link between deformation and volcanic eruption quantified by satellite imagery

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    A key challenge for volcanological science and hazard management is that few of the world’s volcanoes are effectively monitored. Satellite imagery covers volcanoes globally throughout their eruptive cycles, independent of ground-based monitoring, providing a multidecadal archive suitable for probabilistic analysis linking deformation with eruption. Here we show that, of the 198 volcanoes systematically observed for the past 18 years, 54 deformed, of which 25 also erupted. For assessing eruption potential, this high proportion of deforming volcanoes that also erupted (46%), together with the proportion of non-deforming volcanoes that did not erupt (94%), jointly represent indicators with ‘strong’ evidential worth. Using a larger catalogue of 540 volcanoes observed for 3 years, we demonstrate how this eruption–deformation relationship is influenced by tectonic, petrological and volcanic factors. Satellite technology is rapidly evolving and routine monitoring of the deformation status of all volcanoes from space is anticipated, meaning probabilistic approaches will increasingly inform hazard decisions and strategic development
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