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11:03
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
Published on: December 4, 2017
Large fluctuations and singular behavior of nonequilibrium systems
D Pinna1, A D Kent1, D L Stein2
1Department of Physics, New York University, New York, New York 10003, USA.
Physical Review. E
|February 13, 2016
Summary
We developed a geometrical method to study noise-driven escape from metastable states. This approach identifies when caustics affect escape paths in systems without detailed balance, like nanomagnets.
Area of Science:
- Statistical physics
- Non-equilibrium systems
- Complex systems
Background:
- Understanding escape dynamics from metastable states is crucial in various scientific fields.
- Systems lacking detailed balance present unique challenges in predicting escape behavior.
- Caustic singularities can significantly influence system trajectories.
Purpose of the Study:
- To introduce a general geometrical framework for analyzing noise-induced escape from metastable states.
- To establish a condition for identifying the influence of caustics on escape trajectories in systems without detailed balance.
- To apply this framework to specific non-equilibrium systems, such as nanomagnets.
Main Methods:
- Development of a general geometrical approach.
- Analysis of the drift field norm to detect caustic influence.
- Application to systems lacking detailed balance, including nanomagnets with spin-transfer torque.
Main Results:
- A simple condition based on the drift field norm determines caustic alteration of escape trajectories.
- The method successfully identifies regions of parameter space where caustics are present.
- Demonstrated applicability to a nanomagnet system with biaxial magnetic anisotropy and spin-transfer torque.
Conclusions:
- The proposed geometrical approach provides a powerful tool for understanding escape dynamics in complex systems.
- It offers a clear criterion for assessing the impact of caustics in non-equilibrium systems.
- This work facilitates the prediction and control of escape phenomena in experimentally relevant systems.
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