2021/06/30 by Amartya Bose · 1 citation
Physics and Astronomy · #quant-ph #physics.chem-ph
paper · pdf · doi:10.1103/physrevb.105.024309
published as Phys. Rev. B 105, 024309 (2022) · 10 pages, 13 figures
arxiv created 2021/07/06 · arxiv updated 2022/02/04
It has been recently shown how the tensorial nature of real-time path integrals involving the Feynman-Vernon influence functional can be utilized using matrix product states, taking advantage of the finite length of the non-Markovian memory. Tensor networks promise to provide a new, unified language to express the structure of path integral. Here, a generalized tensor network is derived and implemented specifically incorporating the pairwise interaction structure of the influence functional, allowing for a compact representation and efficient evaluation. This pairwise connected tensor network path integral (PCTNPI) is illustrated through applications to typical spin-boson problems and explorations of the differences caused by the exact form of the spectral density. The storage requirements and performance are compared with iterative quasi-adiabatic propagator path integral and iterative blip-summed path integral. Finally, the viability of using PCTNPI for simulating multistate problems is demonstrated taking advantage of the compressed representation.