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For example, we correlate the orientation of the magnetization vector, relative to a specific crystallographic axis, to the angular coordinates of the most probable location in a probability landscape of this anisotropic system.
The probability landscape displays the evolution of the most probable angular orientation of the magnetization vector, for selected temperatures and magnetic fields.
This transition is also supported by both of the temperature dependence of the magnetic heat capacity, which develops a peak at a temperature ~114 K, and the probability landscape which shows, in zero magnetic field, a prominent peak in the basal plane at T=113.5 K.
Both probability landscape and flux vector are paramount in determining the stable oscillation.
In order to uncover the probability landscape, we begin from the chemical reaction network involved in predator-prey network.
Scores of walks were compiled into a histogram, with the 5% and 1% best-scoring walowestowest average RMSD scores) mapped onto a matrices of path-space reflecting the frequency of each position being present in a path, generating a probability landscape relating the chronologies of the LSU and SSU subunits (Figure 4).
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We highlight a correlation between magnetization curves and the associated probability landscapes.
We present a theoretical method to calculate specific magnetic properties, e.g. magnetization curves, magnetic susceptibility and probability landscapes along the [100], [110] and [111] crystallographic directions of a crystal of cubic symmetry.
Residuals of RMSD matrices generated from randomized data generally produced probability landscapes with significantly lower densities and/or stronger diagonal trends, suggesting that this path is not the result of a persistent artifact.
More specifically, this article considers certain probability landscapes, in which the probability peaks are the macrostates.
In the context of the current paper, we consider the model for its peculiar tendency to form probability landscapes with two maxima.
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