Quantum-inspired Chemical Rule for Discovering Topological Materials

TL;DR

This paper introduces a quantum-inspired neural network approach to efficiently discover topological materials, combining classical heuristics with quantum correlations, leading to the identification of new topological compounds.

Contribution

It develops a quantum-classical hybrid neural network that incorporates quantum correlations into topological material prediction, improving discovery efficiency and interpretability.

Findings

Identified five new topological compounds through high-throughput screening.

Validated quantum correlations with a complex-valued neural network.

Enhanced predictive power over classical heuristics.

Abstract

Topological materials exhibit unique electronic structures that underpin both fundamental quantum phenomena and next-generation technologies, yet their discovery remains constrained by the high computational cost of first-principles calculations and the slow, resource-intensive nature of experimental synthesis. Recent machine-learning approaches, such as the heuristic topogivity rule, offer data-driven alternatives by quantifying each element's intrinsic tendency toward topological behavior. Here, we develop a quantum-classical hybrid artificial neural network (QANN) that extends this rule into a quantum-inspired formulation. Within this framework, the QANN maps compositional descriptors to quantum probability amplitudes, naturally introducing pairwise inter-element correlations inaccessible to classical heuristics. The physical validity of these correlations is substantiated by constructing an equivalent complex-valued neural network (CVNN), confirming both the consistency and interpretability of the formulation. Retaining the simplicity of chemical reasoning while embedding quantum-native features, our quantum-inspired rule enables efficient and generalizable topological classification. High-throughput screening combined with first-principles (DFT) validation reveals five previously unreported topological compounds, demonstrating the enhanced predictive power and physical insight afforded by quantum-inspired heuristics.