Center for Nonlinear Studies

CNLS Research

The primary activity of the Center is conduct and support basic scientific research in nonlinear and complex systems phenomena and promote their use in applied research programs.

CNLS chooses a small number (three to four) focus topics periodically and directs a major portion of its research capabilities into these strategically important areas. The focus areas are determined by the Executive Committee, and they are chosen by taking into consideration both the Laboratory's needs for basic science relevant to mission-critical programs and the need to stay abreast of emerging and potentially important developments in complex systems research.

Current Focus Areas

Dynamics of Systems Far From Equilibrium Applied mathematics methods for plasma physics Space plasmas Structural properties of materials Fluid dynamics and turbulence Soft matter Active matter Dynamical systems	Mechanistic Studies of Human Disease Stochastic gene regulation Biomolecular simulations Disease modeling Viral dynamics
Machine Learning Enhanced Modeling Physics informed machine learning Deep learning Optimization theory Applications to grids Materials and Biology Interference and Algorithms Smart Grid applications Complex Networks Materials Informatics	Theory and Computation of Quantum Systems Quantum information Quantum many-body physics Bose-Einstein condensates Strongly correlated electron systems Molecular physics Non-adiabatic excited-state dynamics Warm dense matter

Previous Focus Areas

Mechanistic Studies of Human Disease Establish and maintain Atomistic modeling of biomolecules in aqueous and complex membrane environments. Atomistic, coarse grained, and ultra coarse grained models of multiple biomolecular complexes at large scale. Modeling Signaling Networks. Mechanistic modeling of Viral Infections.	Optimization and Physics Inspired Machine Learning Approaches The development of Machine Learning methods to study physical systems, with applications to atomistic materials models, nuclear fission, and geophysical systems. The development of novel algorithms that exploit the structural properties of the mathematics embedded in optimization problems.
The Dynamics of Systems Far From Equilibrium Turbulent and Compressible Flows Modeling of Flows in the Subsurface and the Ocean	Theory and Computation on Quantum Systems Quantum computation and quantum information theory
Multiscale Dynamics of Biological Systems Macromolecules - Dynamics at the Nano-Scale Cellular Dynamics and Function Cooperative Cellular Interactions	Correlations and Dynamics in Information Science Sensing and Processing of Information Modeling and Analysis of Complex Systems Inference and Learning