AI Research
Do Quantum Models Scale Like LLMs?
Bridging quantum physics and deep learning through transformer scaling laws
In this work, we study the neural scaling laws of RydbergGPT, an autoregressive transformer model trained on qubit projective measurement data gathered from interacting Rydberg atom arrays. The quantum system is known to exhibit a finite-size remnant of a critical point as the la...
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ArXiv CS.LG
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ArXiv CS.LG
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Applying transformer scaling laws to quantum systems suggests a bridge between classical machine learning and high-fidelity physical simulation. This discovery implies that large-scale quantum data modeling could unlock unprecedented efficiency in predicting complex phase transitions.
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