Optimal model-free prediction from multivariate time series

Forecasting a time series from multivariate predictors constitutes a challenging problem, especially using model-free approaches. Most techniques, such as nearest-neighbor prediction, quickly suffer from the curse of dimensionality and overfitting for more than a few predictors which has limited their application mostly to the univariate case. Therefore, selection strategies are needed that harness the available information as efficiently as possible. Since often the right combination of predictors matters, ideally all subsets of possible predictors should be tested for their predictive power, but the exponentially growing number of combinations makes such an approach computationally prohibitive. Here a prediction scheme that overcomes this strong limitation is introduced utilizing a causal pre-selection step which drastically reduces the number of possible predictors to the most predictive set of causal drivers making a globally optimal search scheme tractable. The information-theoretic optimality is derived and practical selection criteria are discussed. As demonstrated for multivariate nonlinear stochastic delay processes, the optimal scheme can even be less computationally expensive than commonly used sub-optimal schemes like forward selection. The method suggests a general framework to apply the optimal model-free approach to select variables and subsequently fit a model to further improve a prediction or learn statistical dependencies. The performance of this framework is illustrated on a climatological index of El Ni\~no Southern Oscillation.Comment: 14 pages, 9 figure

Disentangling different types of El Ni\~no episodes by evolving climate network analysis

Complex network theory provides a powerful toolbox for studying the structure of statistical interrelationships between multiple time series in various scientific disciplines. In this work, we apply the recently proposed climate network approach for characterizing the evolving correlation structure of the Earth's climate system based on reanalysis data of surface air temperatures. We provide a detailed study on the temporal variability of several global climate network characteristics. Based on a simple conceptual view on red climate networks (i.e., networks with a comparably low number of edges), we give a thorough interpretation of our evolving climate network characteristics, which allows a functional discrimination between recently recognized different types of El Ni\~no episodes. Our analysis provides deep insights into the Earth's climate system, particularly its global response to strong volcanic eruptions and large-scale impacts of different phases of the El Ni\~no Southern Oscillation (ENSO).Comment: 20 pages, 12 figure

Fast energy transfer mediated by multi-quanta bound states in a nonlinear quantum lattice

By using a Generalized Hubbard model for bosons, the energy transfer in a nonlinear quantum lattice is studied, with special emphasis on the interplay between local and nonlocal nonlinearity. For a strong local nonlinearity, it is shown that the creation of v quanta on one site excites a soliton band formed by bound states involving v quanta trapped on the same site. The energy is first localized on the excited site over a significant timescale and then slowly delocalizes along the lattice. As when increasing the nonlocal nonlinearity, a faster dynamics occurs and the energy propagates more rapidly along the lattice. Nevertheless, the larger is the number of quanta, the slower is the dynamics. However, it is shown that when the nonlocal nonlinearity reaches a critical value, the lattice suddenly supports a very fast energy propagation whose dynamics is almost independent on the number of quanta. The energy is transfered by specific bound states formed by the superimposition of states involving v-p quanta trapped on one site and p quanta trapped on the nearest neighbour sites, with p=0,..,v-1. These bound states behave as independent quanta and they exhibit a dynamics which is insensitive to the nonlinearity and controlled by the single quantum hopping constant.Comment: 28 pages, 8 figure

Two-vibron bound states in alpha-helix proteins : the interplay between the intramolecular anharmonicity and the strong vibron-phonon coupling

The influence of the intramolecular anharmonicity and the strong vibron-phonon coupling on the two-vibron dynamics in an $\alpha$-helix protein is studied within a modified Davydov model. The intramolecular anharmonicity of each amide-I vibration is considered and the vibron dynamics is described according to the small polaron approach. A unitary transformation is performed to remove the intramolecular anharmonicity and a modified Lang-Firsov transformation is applied to renormalize the vibron-phonon interaction. Then, a mean field procedure is realized to obtain the dressed anharmonic vibron Hamiltonian. It is shown that the anharmonicity modifies the vibron-phonon interaction which results in an enhancement of the dressing effect. In addition, both the anharmonicity and the dressing favor the occurrence of two different bound states which the properties strongly depend on the interplay between the anharmonicity and the dressing. Such a dependence was summarized in a phase diagram which characterizes the number and the nature of the bound states as a function of the relevant parameters of the problem. For a significant anharmonicity, the low frequency bound states describe two vibrons trapped onto the same amide-I vibration whereas the high frequency bound states refer to the trapping of the two vibrons onto nearest neighbor amide-I vibrations.Comment: may 2003 submitted to Phys. Rev.

Thermal conductance of thin film YIG determined using Bayesian statistics

Thin film YIG (Y$_3$Fe$_5$O$_{12}$) is a prototypical material for experiments on thermally generated pure spin currents and the spin Seebeck effect. The 3-omega method is an established technique to measure the cross-plane thermal conductance of thin films, but can not be used in YIG/GGG (Ga$_3$Gd$_5$O$_{12}$) systems in its standard form. We use two-dimensional modeling of heat transport and introduce a technique based on Bayesian statistics to evaluate measurement data taken from the 3-omega method. Our analysis method allows us to study materials systems that have not been accessible with the conventionally used 3-omega analysis. Temperature dependent thermal conductance data of thin film YIG are of major importance for experiments in the field of spin-caloritronics. Here we show data between room temperature and 10 K for films covering a wide thickness range as well as the magnetic field effect on the thermal conductance between 10 K and 50 K

Skewed parton distributions and the scale dependence of the transverse size parameter

We discuss the scale dependence of a skewed parton distribution of the pion obtained from a generalized light-cone wave function overlap formula. Using a simple ansatz for the transverse momentum dependence of the light-cone wave function and restricting ourselves to the case of a zero skewedness parameter, the skewed parton distribution can be expressed through an ordinary parton distribution multiplied by an exponential function. Matching the generalized and ordinary DGLAP evolution equations of the skewed and ordinary parton distributions, respectively, we derive a constraint for the scale dependence of the transverse size parameter, which describes the width of the pion wave function in transverse momentum space. This constraint has implications for the Fock state probability and valence distribution. We apply our results to the pion form factor.Comment: 10 pages, 4 figures; version to appear in Phys. Rev. D; Refs. added, new discussion of results for pion form factor in view of new dat

MaGICC-WDM: the effects of warm dark matter in hydrodynamical simulations of disc galaxy formation

We study the effect of warm dark matter (WDM) on hydrodynamic simulations of galaxy formation as part of the Making Galaxies in a Cosmological Context (MaGICC) project. We simulate three different galaxies using three WDM candidates of 1, 2 and 5 keV and compare results with pure cold dark matter simulations. WDM slightly reduces star formation and produces less centrally concentrated stellar profiles. These effects are most evident for the 1 keV candidate but almost disappear for $m_{\mathrm{WDM}}>2$ keV. All simulations form similar stellar discs independent of WDM particle mass. In particular, the disc scale length does not change when WDM is considered. The reduced amount of star formation in the case of 1 keV particles is due to the effects of WDM on merging satellites which are on average less concentrated and less gas rich. The altered satellites cause a reduced starburst during mergers because they trigger weaker disc instabilities in the main galaxy. Nevertheless we show that disc galaxy evolution is much more sensitive to stellar feedback than it is to WDM candidate mass. Overall we find that WDM, especially when restricted to current observational constraints ($m_{\mathrm{WDM}}>2$ keV), has a minor impact on disc galaxy formation.Comment: 13 pages, 9 figures, 2 tables; minor clarifications added in results section, conclusions unchanged; accepted for publication in MNRA