Adaptive Kink Filtration: Achieving Asymptotic Size-Independence of Path Integral Simulations Utilizing the Locality of Interactions
Amartya Bose

TL;DR
This paper introduces an adaptive kink filtration method for path integral simulations that exploits locality to achieve size-independent computational cost, enabling efficient simulation of large condensed phase systems.
Contribution
The authors develop a novel adaptive kink filtration technique that removes asymptotic size dependence in path integral simulations by leveraging interaction locality and propagator sparsity.
Findings
Cost becomes constant with system size.
Enables simulation of larger systems at reduced computational expense.
Applicable to both non-equilibrium dynamics and equilibrium correlation functions.
Abstract
Recent method developments involving path integral simulations have come a long way in making these techniques practical for studying condensed phase non-equilibrium phenomena. One of the main difficulties that still needs to be surmounted is the scaling of the algorithms with the system dimensionality. The majority of recent techniques have only changed the order of this scaling (going from exponential to possibly a very high ordered polynomial) and not eased the dependence on the system size. In this current work, we introduce an adaptive kink filtration technique for path generation approach that leverages the locality of the interactions present in the system and the consequent sparsity of the propagator matrix to remove the asymptotic size dependence of the simulations for the propagation of reduced density matrices. This enables the simulation of larger systems at a significantly…
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Taxonomy
TopicsMicrofluidic and Bio-sensing Technologies
