Universal solution to the Schrieffer-Wolff Transformation Generator
Leander Reascos, Giovanni Francesco Diotallevi, M\'onica Benito

TL;DR
This paper introduces a universal, closed-form solution for the Schrieffer-Wolff transformation generator applicable to a wide range of quantum systems, including time-dependent cases, enhancing the method's generality and practical utility.
Contribution
The authors derive a systematic, closed-form, and universally applicable solution for the SWT generator, extending it to time-dependent systems with periodic perturbations.
Findings
Successfully applied to analyze dispersive shifts in anharmonic resonators
Provides a unified framework for static and dynamic perturbative systems
Enhances the applicability of SWT in quantum system analysis
Abstract
The Schrieffer-Wolff transformation (SWT) is an important perturbative method in quantum mechanics used to simplify Hamiltonians by decoupling low- and high-energy subspaces. Existing methods for implementing the SWT often lack general applicability to arbitrary perturbative systems or fail to provide a closed-form solution for the SWT generator. In this article, we present a systematic and unified framework for the SWT that addresses these shortcomings. Specifically, we derive a closed-form solution for the SWT generator that is universally applicable to any system that satisfies the conditions required for perturbative treatment. Furthermore, we extend this solution to time-dependent systems with periodic perturbations, covering all frequency regimes. The effectiveness of this approach is then demonstrated by applying it to analyze the dispersive shift of an anharmonic resonator…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum chaos and dynamical systems · Nonlinear Dynamics and Pattern Formation
