Modeling and simulation are critical elements of discovery science. They help us better understand our physical world, especially phenomena that cannot be fully grasped through observation or experimentation alone. These systems might be enormous, like the structure formation of our universe, or minuscule, like quantum chemistry and microelectronics design. They could also involve extremely fast processes, such as those in particle physics, or very slow ones, like climate change and stellar evolution. By shedding light on the underlying mechanisms of a system, simulations enable researchers to predict how these systems will behave in the future.
At Berkeley Lab, we develop state-of-the-art methodologies and techniques to understand and predict both continuous (measurable) and discrete (countable) aspects of physical systems—like hurricanes or traffic flow—and their dynamic behavior. We ensure that the mathematical characteristics of our models are accurate so that researchers can rely on the results. Our models and simulations can be run on computers of all scales, from laptops to modern supercomputers.
Our mathematicians, computational scientists, and data scientists collaborate with researchers from various disciplines to model complex systems, including the intricate dynamics of commercial spray painting, wind farms, transportation networks, computer hardware, fluid flows, and much more.
Our Research Pillars:
- Astrophysics & High Energy Physics
- Climate Science
- Environmental Science
- Electromagnetics
- Plasma Physics
- Multiphysics & Multiscale Fluid Dynamics
- Microelectronics
- Biological Systems
- Epidemiology
- Chemistry & Materials
