Continuous and Spatial Random Processes

Continuous and spatial random processes represent sophisticated mathematical models for understanding phenomena that exhibit randomness over time and space. Continuous random processes, such as Brownian motion, provide a mathematical description of seemingly erratic movements observed in particles, stock prices, and other dynamic systems. Recent interdisciplinary research leverages these processes to construct complex models that can predict and simulate intricate behaviours in natural and engineered systems.

Examples currently being investigated within the Centre include

  1. Weather Patterns and Climate Change: Weather systems exhibit spatio-temporal randomness, with phenomena like rainfall, temperature fluctuations, and storm paths varying over time and space.
  2. Epidemiological Spread of Diseases: The spread of infectious diseases is a complex process that depends on spatial factors (like geography and population density) and temporal aspects (such as seasonal variations
  3. Ecological Systems and Biodiversity: Ecosystem dynamics, including animal migration patterns, plant growth, and species interactions, are influenced by spatial and temporal variability.
spatial process
Random fields are an important example spatio-temporal processes which are used in modelling natural phenomena.