Schur-complement truncations of HEOM for finite-dimensional systems converge spectrally to the full equations and are free of spectral pollution when the exact HEOM is stable.
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A machine learning model called neural quantum propagator is introduced to efficiently solve non-Markovian quantum dynamics described by HEOM and applied to simulate spectra of the FMO complex.
Tensor network scans reveal that the stationary spin entanglement entropy ridge follows population phase boundaries at small s but lacks the two-branch structure at large s in the sub-Ohmic spin-boson model.
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On truncations of hierarchical equations of motion for finite-dimensional systems
Schur-complement truncations of HEOM for finite-dimensional systems converge spectrally to the full equations and are free of spectral pollution when the exact HEOM is stable.
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Non-markovian neural quantum propagator and its application to the simulation of ultrafast nonlinear spectra
A machine learning model called neural quantum propagator is introduced to efficiently solve non-Markovian quantum dynamics described by HEOM and applied to simulate spectra of the FMO complex.
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Entanglement structure of the dynamical phases in the sub-Ohmic spin-boson model
Tensor network scans reveal that the stationary spin entanglement entropy ridge follows population phase boundaries at small s but lacks the two-branch structure at large s in the sub-Ohmic spin-boson model.