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Physical Chemistry Chemical Physics

Small matrix modular path integral: iterative quantum dynamics in space and time

Nancy Makri

Published Jan 1, 2021• 20 citations
Publisher

Abstract

The modular path integral (MPI) formulation for one-dimensional extended systems, such as spin arrays or molecular aggregates, allows evaluation of spin- or exciton-vibration dynamics with effort that scales linearly with the number of units. This work presents a small matrix decomposition of the modular path integral (SMatMPI), which eliminates tensor storage and enables iterative long-time propagation.

DOI
10.1039/d1cp01483h

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The modular path integral (MPI) formulation for one-dimensional extended systems, such as spin arrays or molecular aggregates, allows evaluation of spin- or exciton-vibration dynamics with effort that scales linearly with the number of units. This work presents a small matrix decomposition of the modular path integral (SMatMPI), which eliminates tensor storage and enables iterative long-time propagation.
The modular path integral (MPI) formulation offers a numerically exact, versatile, and highly efficient approach to the quantum dynamics of extended systems characterised by a single-file arrangement of units with short-range interactions, such as hydrocarbons, molecular aggregates with exciton couplings, or spin chains. Rather than propagating the many-particle wavefunction or density matrix in time in the usual stepwise fashion, the MPI scheme proceeds by sequentially integrating over each unit after linking its quantum paths to those of its neighbour and leads to linear scaling with system length. This paper shows that the linking matrix can be further decomposed into a diagonal matrix and a product of low-dimensional matrices, which can be applied sequentially. This factorisation changes the cost scaling from L2 to Llog⁡L, where L is the number of quantum paths, leading to dramatic savings that are analogous to those attained by the fast Fourier transform algorithm and allowing application of the MPI procedure to systems with larger units and to longer propagation times. Applications to spin chains and to electron-vibration dynamics in a large molecular aggregate illustrate the efficiency of the algorithm.
The small matrix path integral (SMatPI) methodology allows fully quantum mechanical calculations on system-bath Hamiltonians under a variety of conditions with minimal array storage and is thus applicable to multistate systems. This work focuses on the SMatPI iteration algorithm, which can be computationally prohibitive in systems with many states. By transforming the SMatPI propagation matrices to the desired initial state, the cost of the iterative multiplication is reduced by a factor of n2, where n is the number of system states. This leads to dramatic savings when n≫10 and allows the simulation of large systems over very long propagation times. Applications are presented on models with up to 50 system states, including exciton transfer dynamics in one-dimensional aggregates and a square lattice.
The small matrix decomposition of the quasi-adiabatic propagator path integral (SMatPI) for a system coupled to a harmonic bath, which accounts for multitime memory correlations in the influence functional without the use of tensors, is extended to include a time-dependent term that drives the system. In the case of a periodic field, the algorithm requires the construction of SMatPI matrices initialized over a short time interval. The SMatPI algorithm circumvents the large array storage of tensor-based iterative path integral decompositions and, in the case of a periodic field, also eliminates the demanding tensor multiplication at each time step, leading to dramatic savings which allow the fully quantum mechanical treatment of multistate systems and long-memory environments.
, 101101 (2018)], it was shown that the locality of interactions in many systems of interest allows a decomposition of the path integral and its evaluation via sequential linking of the paths of relatively small "modules" (e.g., chemical groups or monomers). The present paper describes the modular path integral methodology for simulating dynamical properties by propagating the density matrix in real time. The procedure is first presented for the simple topology of a single-file arrangement of units interacting via nearest neighbor couplings and subsequently extended to the calculation of two-particle correlations in arrays that may also contain some long-range interactions, to the treatment of systems with side chains or cyclic structures, to the simulation of internal dynamics in long organic molecules, and to the modifications required for coupling of one or several units of a system to dissipative environments. Illustrative applications to the dynamics of interacting two-level-systems are presented.
The small matrix decomposition of the real-time path integral (SMatPI) allows for numerically exact and efficient propagation of the reduced density matrix (RDM) for system-bath Hamiltonians. Its high efficiency lies in the small size of the SMatPI matrices employed in the iterative algorithm, whose size is equal to that of the full RDM. By avoiding the storage and multiplication of large tensors, the SMatPI algorithm is applicable in multistate systems under a variety of conditions. The main computational effort is the evaluation of path sums within the entangled memory length to construct the SMatPI matrices. A number of methods are available for this task, each with its own favorable parameter regime, but calculations with strong system-bath coupling and long memory at low temperatures remain out of reach. The present paper evaluates the path sums by binning the paths (in forward time only) based on their amplitudes, which depend on the number and type of kinks they contain. The algorithm is very efficient, leading to a dramatic acceleration of path sums and significantly extending the accessible memory length in the most challenging regimes.