Detector simulations are an important component of the research in High Energy Physics. However, the current Mote Carlo-based simulation tools are computationally intensive and finding a faster alternative is necessary. This talk focuses on the current development in the domain of using deep learning models for calorimeter simulations, namely the experimentation with transformer neural networks.
Studying recent empirical traffic data, we show surprising statistical anomalies in the traffic microstructure that can not be explained by current scientific approaches used in physics of traffic. We introduce the concept of Balanced Particle Systems as an effective mathematical instrument for a description of statistical properties of vehicular microstructure, quantify these anomalies...
Contemporary decision making (DM) theory stands on classical probability. However, it has been shown that there is a variety of situations when the decision theory fails to explain some psychological and cognitive effects observed in human decision making. Other aspects not covered by the classical approach are that the results of merging information depend on the order of merging, or that the...
The PDF of a positive continuous random variable $X$ can be too complex for direct evaluation e.g. when $X$ is a sum of the positive continuous random variables. But when the characteristic function $\psi(t)$ of $X$ is known, we can employ $N=2^k$ point FFT to obtain a table of PDF with equidistant spacing for the interpolation of $\mathrm{f}(x_k)$ and for $k=1,\ldots,m$. Adequate time...
We propose a multifactor asset pricing model for evaluation of excess return of ČEZ a.s. stock which is derived from the Asset pricing theory. Besides the market risk, factors, that can affect the performance of ČEZ a.s. stock, are also added. They are the price of electricity, the price of natural gas, the price of CO2 emission permits and index of industrial production. Taking into account a...
Graphs and Markov chains can be represented by matrixes. One of the most common representations is the Laplacian matrix. This presentation summarises the spectral clustering of undirected graphs. Then we consider a basic approach to spectral clustering of directed graphs by the symmetric graph. Then we show a new approach to the Laplacian matrix for directed graphs using incidence matrix M for...
Structured illumination microscopy (SIM) is a powerful imaging technique that has revolutionized the field of superresolution microscopy. This talk aims to provide an overview of SIM and highlight its numerous benefits over other superresolution methods.
SIM utilizes patterned illumination to overcome the diffraction limit posed on resolution in optical microscopy, enabling the...
