Design and characterization of all 2D fragile topological bands

Designing topological materials with specific topological indices is a complex inverse problem, traditionally tackled through manual, intuition-driven methods that are neither scalable nor efficient for exploring the vast space of possible material configurations. In this work, we develop an algorithm that leverages the covariance matrix adaptation evolution strategy to optimize the Fourier representation of the periodic functions shaping the designer material's characteristics. This includes mass profiles or dielectric tensors for phononic and photonic crystals, respectively, as much as synthetic potentials applicable to ultra-cold atomic systems. We demonstrate our methodology with a detailed characterization of a class of topological bands known as "fragile topological," showcasing the algorithm's capability to address both topological characteristics and spectral quality, and demonstrating the experimental feasibility of realizing all of the classified fragile topological phases. This automation not only streamlines the design process but also significantly expands the potential for identifying and constructing high quality designer materials across the wide range of platforms, and is readily extendable to other setups, including higher-dimensional and nonlinear systems.

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Publication Details

Journal
PNAS Nexus
Published
2025-08-30
DOI
https://doi.org/10.1093/pnasnexus/pgaf285
Primary Topic
Topological Materials and Phenomena
Type
article
Field-Weighted Citation Impact
0.00

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article

Design and characterization of all 2D fragile topological bands

Chiara Devescovi, Valerio Peri, Sebastian D. Huber, Doruk Efe Gökmen et al.
PNAS Nexus
Topological Materials and Phenomena
article

Design and characterization of all 2D fragile topological bands

Chiara Devescovi, Valerio Peri, Sebastian D. Huber, Doruk Efe Gökmen, Agnes Valenti, Pascal Engeler, S.P. Bird, Robin Worreby
article en

Abstract

Designing topological materials with specific topological indices is a complex inverse problem, traditionally tackled through manual, intuition-driven methods that are neither scalable nor efficient for exploring the vast space of possible material configurations. In this work, we develop an algorithm that leverages the covariance matrix adaptation evolution strategy to optimize the Fourier representation of the periodic functions shaping the designer material's characteristics. This includes mass profiles or dielectric tensors for phononic and photonic crystals, respectively, as much as synthetic potentials applicable to ultra-cold atomic systems. We demonstrate our methodology with a detailed characterization of a class of topological bands known as "fragile topological," showcasing the algorithm's capability to address both topological characteristics and spectral quality, and demonstrating the experimental feasibility of realizing all of the classified fragile topological phases. This automation not only streamlines the design process but also significantly expands the potential for identifying and constructing high quality designer materials across the wide range of platforms, and is readily extendable to other setups, including higher-dimensional and nonlinear systems.

PNAS NexusVol. 4(9)
California Institute of Technology (US), ETH Zurich (CH), University of Chicago (US), Institute for Biomedical Engineering (CH), Simons Foundation (US), Instituto de Física Teórica (ES), Flatiron Health (United States) (US), Flatiron Institute (US), Donostia International Physics Center (ES)
National Science Foundation, Flatiron Health, Ministerio de Ciencia e Innovación
Openalex Percentile: Top 82%
Topological Materials and Phenomena
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