Tree tensor network state approach for solving hierarchical equations of motion
Yaling Ke

TL;DR
This paper introduces a novel tree tensor network state (TTNS) approach to efficiently solve the hierarchical equations of motion (HEOM) for open quantum systems, significantly accelerating computations while maintaining accuracy.
Contribution
The work develops a TTNS-based method for HEOM, enabling faster simulations of quantum dynamics by exploiting the star-shaped entanglement structure.
Findings
HEOM+TTNS yields results consistent with traditional HEOM.
The approach speeds up calculations by several orders of magnitude.
TTNS simulation is four times faster than 1D matrix product state methods.
Abstract
The hierarchical equations of motion (HEOM) method is a numerically exact open quantum system dynamics approach. The method is rooted in an exponential expansion of the bath correlation function, which in essence strategically reshapes a continuous environment into a set of effective bath modes that allow for more efficient cutoff at finite temperatures. Based on this understanding, one can map the HEOM method into a Schr\"odinger-like equation with a non-Hermitian super Hamiltonian for an extended wavefunction being the tensor product of the central system wave function and the Fock state of these effective bath modes. Recognizing that the system and these effective bath modes form a star-shaped entanglement structure, in this work, we explore the possibility of representing the extended wave function as an efficient tree tensor network state (TTNS), the super Hamiltonian as a tree…
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Taxonomy
TopicsComputational Physics and Python Applications
