SPMS 2024

Session

Applied Statistical Physics

23 Jun 2024, 10:50

Dobřichovice

Conveners

Applied Statistical Physics

• Tomáš Hobza (FJFI CVUT)

3. Anomalous Diffusion Coefficient via Simple Particle Hopping Analysis

Jaromír Kukal (FNSPE CTU in Prague)

23/06/2024, 10:50

One-dimensional partice hopping with constrained variance is a well known model of Brownian motion and therefore the traditional particle diffusion. Model analysis is possible using the Central Limit Theorem (CLT) which produces Einstein formula. Another strategies of heavy tile hopping with discrete Pareto distribution can be studied by the Generalized CLT (GCLT). Doing the same using only...

4. Alternatives to Monte Carlo Simulations for Fractal Diffusion Models

František Gašpar (FJFI)

23/06/2024, 11:10

A novel computational approach is introduced as a robust alternative to Monte Carlo simulations for diffusive processes over fractal sets. Unlike stochastic methods, introduced constrained convolution schema (CCS) is a deterministic numerical algorithm tailored for grid-based set models, including random sets, ensuring reproducibility and computational efficiency. CCS is designed to yield the...

10. On Board Telemetry Anomaly Detection using Machine Learning

František Voldřich (4)

23/06/2024, 11:30

Anomaly detection has numerous applications across various fields, including the space industry. A spacecraft must continuously monitor the health of its subsystems to detect non-nominal situations, but transmitting all telemetry data to the ground for analysis is not feasible due to limited transmission capacity and potential delays. Therefore, autonomous fault and anomaly detection is...

13. Heterogeneous Variants of Balanced Particle Systems

Jiří Nábělek

23/06/2024, 11:50

The research focuses on the study of special variants of heterogeneous balance particle systems and their properties. Based on the knowledge gained, we will show analytically derived descriptions and characteristics for systems described by specifically chosen probability densities, while supporting the theoretical conclusions by numerical computation on synthetic data. We also apply the...

25. Unconditional and conditional heavy-tailed distributions for returns of cryptocurrencies

Quang Van Tran (KSI, FNSPE, CTU in Prague)

23/06/2024, 12:10

We investigate which distribution is most appropriate for modeling returns of cryptocurrencies. We study distribution of both unconditional returns and conditional returns. Four well-known heavy-tailed distributions Generalized Normal, Student t-, Normal Inverse Gaussian, Alpha stable and two recently suggested distributions and four GARCH models plain GARCH, range GARCH, TGARCH and EGARCH are...