Scalable Effective Models for Superconducting Nanostructures: Applications to Double, Triple, and Quadruple Quantum Dots
Daniel Bobok, Luk\'a\v{s} Frk, Vladislav Pokorn\'y, Martin \v{Z}onda

TL;DR
This paper presents a scalable and efficient framework called Chain Expansion (ChE) for modeling superconducting nanostructures with multiple quantum dots, enabling accurate simulations of complex systems and revealing new phase diagrams.
Contribution
The paper introduces the ChE method that maps superconducting leads onto finite chains, allowing for efficient and accurate modeling of multi-dot nanostructures beyond existing approximations.
Findings
ChE accurately captures phase diagrams of multi-dot systems.
Large parameter regions missed by zero-bandwidth approximation are recovered.
Complex phase behavior increases with the number of quantum dots.
Abstract
We introduce a versatile and scalable framework for constructing effective models of superconducting (SC) nanostructures described by the generalized SC Anderson impurity model with multiple quantum dots and leads. Our Chain Expansion (ChE) method maps each SC lead onto a finite tight-binding chain with parameters obtained from \emph{Pad\'e} approximants of the tunneling self-energy. We provide an explicit algorithm for the general case as well as simple analytical expressions for the chain parameters in the wide-band and infinite-chain limits. This mapping preserves low-energy physics while enabling efficient simulations: short chains are tractable using exact diagonalization, and longer ones are handled with density matrix renormalization group methods. The approach remains reliable and computationally efficient across diverse geometries, both in and out of equilibrium. We use ChE to…
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