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Gauge Fixing for Heat-Transport Simulations.
Aris Marcolongo1, Loris Ercole2, Stefano Baroni2,3
1Cognitive Computing and Computational Sciences Department, IBM Research - Zürich, Säumerstrasse 4, CH-8803 Rüschlikon, Switzerland.
Journal of Chemical Theory and Computation
|April 3, 2020
Summary
Gauge invariance in transport phenomena allows optimizing statistical properties of current time series. This study introduces a variational principle using metric properties of conserved currents to improve transport coefficient evaluation.
Area of Science:
- Physics
- Physical Chemistry
- Materials Science
Background:
- Transport coefficients are often independent of microscopic details of conserved quantities.
- Gauge invariance relates to the indeterminacy of energy in interacting systems.
Purpose of the Study:
- To exploit gauge invariance for optimizing statistical properties of current time series.
- To improve the evaluation of transport coefficients.
Main Methods:
- Introduction and application of a variational principle.
- Utilizing the metric properties of conserved currents in an abstract linear space.
- Exploring different metric choices for distinct variational principles.
Main Results:
- Demonstration of how gauge invariance can optimize current time series statistics.
- Establishment of a connection between a chosen metric and specific data analysis techniques.
- Recovery of a recently proposed data-analysis technique through a suitable metric selection.
Conclusions:
- Gauge invariance offers a powerful tool for enhancing the analysis of transport phenomena.
- The proposed variational principle provides a flexible framework for optimizing transport coefficient calculations.
- The choice of metric is crucial for tailoring the analysis to specific systems and data.
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