A simple model, derived from a Brownian-motion scheme, is capable of interpreting the results of delay-time measurements relative to frustrated total reflection experiments at the microwave scale but also in the visible region. In this framework we also obtain a plausible description of the trajectories (rays) inside the tunneling region, the air gap between two paraffin prisms.
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http://dx.doi.org/10.1103/PhysRevE.65.037601 | DOI Listing |
Theory Biosci
January 2025
Faculty of Science and Engineering, Department of Biosciences, Swansea University, Singleton Park, Swansea, SA2 8PP, UK.
Despite being a powerful tool to model ecological interactions, traditional evolutionary game theory can still be largely improved in the context of population dynamics. One of the current challenges is to devise a cohesive theoretical framework for ecological games with density-dependent (or concentration-dependent) evolution, especially one defined by individual-level events. In this work, I use the notation of reaction networks as a foundation to propose a framework and show that classic two-strategy games are a particular case of the theory.
View Article and Find Full Text PDFMultivariate Behav Res
January 2025
Psychological Methods Group, University of Amsterdam, Amsterdam, Netherlands.
Time series analysis is increasingly popular across scientific domains. A key concept in time series analysis is stationarity, the stability of statistical properties of a time series. Understanding stationarity is crucial to addressing frequent issues in time series analysis such as the consequences of failing to model non-stationarity, how to determine the mechanisms generating non-stationarity, and consequently how to model those mechanisms (i.
View Article and Find Full Text PDFNat Commun
January 2025
Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, UK.
The remarkable performance of overparameterized deep neural networks (DNNs) must arise from an interplay between network architecture, training algorithms, and structure in the data. To disentangle these three components for supervised learning, we apply a Bayesian picture based on the functions expressed by a DNN. The prior over functions is determined by the network architecture, which we vary by exploiting a transition between ordered and chaotic regimes.
View Article and Find Full Text PDFACS Nano
January 2025
Department of Physics and Astronomy, University of Manitoba, Winnipeg R3T 2N2, Canada.
Theory and simulations are used to demonstrate implementation of a variational Bayes algorithm called "active inference" in interacting arrays of nanomagnetic elements. The algorithm requires stochastic elements, and a simplified model based on a magnetic artificial spin ice geometry is used to illustrate how nanomagnets can generate the required random dynamics. Examples of tracking and PID control are demonstrated and shown to be consistent with the original stochastic differential equation formulation of active inference.
View Article and Find Full Text PDFUnlabelled: Neurophysiology studies propose that predictive coding is implemented via alpha/beta (8-30 Hz) rhythms that prepare specific pathways to process predicted inputs. This leads to a state of relative inhibition, reducing feedforward gamma (40-90 Hz) rhythms and spiking to predictable inputs. We refer to this model as predictive routing.
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