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Transformer Quantum State: A Multi-Purpose Model for Quantum Many-Body Problems

Published 2 Aug 2022 in quant-ph, cond-mat.dis-nn, and physics.comp-ph | (2208.01758v4)

Abstract: Inspired by the advancements in LLMs based on transformers, we introduce the transformer quantum state (TQS): a versatile machine learning model for quantum many-body problems. In sharp contrast to Hamiltonian/task specific models, TQS can generate the entire phase diagram, predict field strengths with experimental measurements, and transfer such a knowledge to new systems it has never been trained on before, all within a single model. With specific tasks, fine-tuning the TQS produces accurate results with small computational cost. Versatile by design, TQS can be easily adapted to new tasks, thereby pointing towards a general-purpose model for various challenging quantum problems.

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