Computing time-dependent reduced models for classical and quantum dynamics

TL;DR

This paper presents a recursive, polynomial-in-time algorithm for approximating the dynamics of large systems, applicable to classical and quantum models, ensuring accuracy at short times without weak-coupling assumptions.

Contribution

A novel recursive method for constructing time-dependent generators that are polynomial in time, improving short-term accuracy and preserving physical properties in quantum and classical dynamics.

Findings

Method outperforms low-order exponential truncations

Guarantees completely positive and trace-preserving maps

Validated on spin-boson, central spin, and Ising models

Abstract

This paper introduces a novel method for approximating the dynamics of a large autonomous system projected onto a fixed subspace. The core contribution is a novel recursive algorithm to construct an effective time-dependent generator that is polynomial in the time variable, ensuring accuracy for short time scales. The derivation is based on the Taylor expansion of the exponential map and a new result for computing the time-ordered exponential of polynomial generators. This work is motivated by the challenge of deriving time-convolutionless master equations in quantum physics and the proposed method offers an alternative to typical derivations based on expansions in the coupling strength. The resulting approximation is accurate for small times, does not require a weak-coupling assumption, performs better than a truncation of the exponential map at low orders, and crucially, guarantees a completely positive and trace-preserving map at the lowest orders. The proposed method is validated against several prototypical models: a dephasing spin-boson model, a central spin model, and an Ising spin chain.