Quantum dynamics of coupled excitons and phonons in chain-like systems: tensor train approaches and higher-order propagators
Patrick Gel{\ss}, Sebastian Matera, Rupert Klein, and Burkhard Schmidt

TL;DR
This paper explores tensor-train methods for simulating quantum dynamics of chain-like systems, demonstrating efficient approaches and comparing various propagators for accuracy and computational cost.
Contribution
It introduces tensor-train techniques for solving the Schrödinger equation in chain systems and evaluates multiple propagators for efficiency and precision.
Findings
Tensor-train methods reduce memory and computational costs.
Higher-order splitting schemes achieve near machine precision.
Explicit Euler integrators are suitable for longer chains with better scaling.
Abstract
We investigate tensor-train approaches to the solution of the time-dependent Schr\"{o}dinger equation for chain-like quantum systems with on-site and nearest-neighbor interactions only. Using efficient low-rank tensor train representations, we aim at reducing memory consumption and computational costs. As an example, coupled excitons and phonons modeled in terms of Fr\"{o}hlich-Holstein type Hamiltonians are studied here. By comparing our tensor-train based results with semi-analytical results, we demonstrate the key role of the ranks of the quantum state vectors. Typically, an excellent quality of the solutions is found only when the maximum number of ranks exceeds a certain value. One class of propagation schemes builds on splitting the Hamiltonian into two groups of interleaved nearest-neighbor interactions commutating within each of the groups. In particular, the 4-th order…
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Taxonomy
TopicsElectron Spin Resonance Studies · Advanced NMR Techniques and Applications · Tensor decomposition and applications
