Roland Preuss

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Cell movement--for example, during embryogenesis or tumor metastasis--is a complex dynamical process resulting from an intricate interplay of multiple components of the cellular migration machinery. At first sight, the paths of migrating cells resemble those of thermally driven Brownian particles. However, cell migration is an active biological process(More)
The spectral properties of the 1-D Hubbard model are obtained from quantum Monte Carlo simulations using the maximum entropy method. The one-particle excitations are characterized by dispersive cosine-like bands. Velocities for spin-and charge excitations are obtained that lead to a conformal charge c = 0:98 0:05 for the largest system simulated (N = 84).(More)
The method of Maximum (relative) Entropy (ME) is used to translate the information contained in the known form of the likelihood into a prior distribution for Bayesian inference. The argument is guided by intuition gained from the successful use of ME methods in statistical mechanics. For experiments that cannot be repeated the resulting " entropic prior "(More)
Bayesian probability theory along with the maximum entropy concept is widely used for inferential problems, particularly to infer dynamic properties of strongly correlated fermion systems from Quantum-Monte-Carlo (QMC) imaginary time data. In current QMC-applications, however, the error-covariance of the QMC data is not treated consistently. Here we present(More)
On the basis of Quantum-Monte-Carlo results the evolution of the spectral weight A(k, ω) of the two-dimensional Hubbard model is studied from insulating to metallic behavior. As observed in recent photoemission experiments for cuprates, the electronic excitations display essentially doping-independent features: a quasiparticle-like dispersive narrow band of(More)
We present a method for the decomposition of the mass spectra of mixed gases using Bayesian probability theory. The method works without any calibration measurement and therefore applies also to the analysis of spectra containing unstable species. For the example of mixtures of three different hydrocarbon gases the algorithm provides concentrations and(More)
Energy connnement data of large fusion experiments have been analyzed in terms of dimensionless form free scaling functions. Several possible physical scenarios lead to diierent models with a certain number of degrees of freedom. These are used to set up the connnement function as a linear combination of di-mensionless power law terms. Then one has to solve(More)
At the heart of Bayesian model comparison lies the so-called prior-predictive value. In the important class of Quantiied-MaxEnt applications analytic approximations are routinely used which often give rise to noise-tting and ringing. We present an improved analytic expression which overcomes these shortcomings. In most interesting real-world problems,(More)