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English(EN) Reconstructing conformal field theoretical compositions with Transformers

Transformer精确重构共形场理论组成

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种使用Transformer重构二维有理共形场理论（RCFT）张量积组成的方法。这项组合上具有挑战性的任务涉及根据低能谱识别组成理论。基于Transformer的方法在从Wess-Zumino-Witten模型中恢复组成部分时达到了98%的准确率，并且通过极少的域外样本就泛化到了更大的中心荷和未见的RCFT类别。这项工作表明Transformer可以作为AdS/CFT中体态重构的宝贵工具。 AI

影响 展示了Transformer在超越传统NLP的复杂科学重构任务中的潜力。

排序理由 学术论文，详细介绍了Transformer在物理问题中的新颖应用。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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Transformer精确重构共形场理论组成

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学术论文，详细介绍了Transformer在物理问题中的新颖应用。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Haotian Cao, Garrett Merz, Kyle Cranmer, Gary Shiu ·

    使用 Transformers 重构共形场理论的组成

    arXiv:2605.01072v1 Announce Type: cross Abstract: We study the use of transformers to reconstruct the compositions of tensor products of two-dimensional rational conformal field theories (RCFTs) based on their low-energy spectra. The task is challenging due to its combinatorial n…

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