Multi-Dimensional and Dissipative Dynamical Systems: Maximum Entropy as a Principle for Modeling Dynamics and Emergent Phenomena in Complex Systems
Abstract
The objective of this research proposal is to use the principle of maximum entropy to build a general framework to infer dynamical laws for nonequilibrium systems directly from data and then use this framework to generate mechanistic explanations for anomalous diffusion and its control. To approach the objectives the PI will further develop a statistical “trajectory ensemble theory” to infer properties of nonequilibrium systems. In particular, the PI will focus on estimating and improving upon the efficiencies of nanoscale motors that operate far-from-equilibrium (termed ‘nonergodic engines’). The PI will examine the evolution of the motors between microscates. In analogy to the microstates of traditional statistical physics, the individual stochastic paths of the nanoscale motor systems from one state to another become microtrajectories. The PI will then attempt to infer the full microtrajectory distribution using path entropy maximization and use this framework to predict properties of nonergodic engines.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 12, 2017
- Source ID
- W911NF1610056
Entities
People
- Steve Pressé
Organizations
- Army Contracting Command
- Indiana University – Purdue University Indianapolis
- United States Army