Attention is all you need to solve chiral superconductivity

2025/09/03 by Li, Chun-Tse, Ong, Tzen, Geier, Max +2 · 5 citations
#FOS: Physical sciences #Superconductivity (cond-mat.supr-con)

paper · doi:10.48550/arxiv.2509.03683

Abstract

Recent advances on neural quantum states have shown that correlations between quantum particles can be efficiently captured by \it attention -- a foundation of modern neural architectures that enables neural networks to learn the relation between objects. In this work, we show that a general-purpose self-attention Fermi neural network is able to find chiral p_x ± i p_y superconductivity in an attractive Fermi gas by energy minimization, \it without prior knowledge or bias towards pairing. The superconducting state is identified from the optimized wavefunction by measuring various physical observables: the pair binding energy, the total angular momentum of the ground state, and off-diagonal long-range order in the two-body reduced density matrix. Our work paves the way for AI-driven discovery of unconventional and topological superconductivity in strongly correlated quantum materials.

Citations

• Solving the Hubbard model with Neural Quantum States
• An ab initio foundation model of wavefunctions that accurately describes chemical bond breaking
• Solving and visualizing fractional quantum Hall wavefunctions with neural network
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• EQAHMainfiguredata
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• <i>Ab initio</i> solution of the many-electron Schrödinger equation with deep neural networks
• Attention Is All You Need
• Optimizing Neural Networks with Kronecker-factored Approximate Curvature
• Natural Gradient Works Efficiently in Learning
• Multilayer feedforward networks are universal approximators
• Self-Consistent Equations Including Exchange and Correlation Effects

Cited by

• Revisiting the Broken Symmetry Phase of Solid Hydrogen: A Neural Network Variational Monte Carlo Study
• Electronic crystals and quasicrystals in semiconductor quantum wells: an AI-powered discovery
• Topological Order in Deep State
• An integrated neural wavefunction solver for spinful Fermi systems
• Visualizing the Impact of Quenched Disorder on 2D Electron Wigner Solids

Related

• Solving the Hubbard model with Neural Quantum States
• Neural-network quantum states for ultra-cold Fermi gases
• Developing a Complete AI-Accelerated Workflow for Superconductor Discovery
• Superconductivity in the two-dimensional Hubbard model revealed by neural quantum states
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