用耗散量子动力学实现连贯文本生成，揭示智能源于非守恒机制。
Path Integral Solution for Dissipative Generative Dynamics
- 基于柯普曼算子与路径积分，构建可解析的非局域上下文聚合模型
- 谱分析发现衰减、增长、中性三类模态，支撑定向信息流动
- 守恒律强制消除耗散模态，导致性能下降但模型容量不变
纯机械系统能否生成智能语言？我们证明具有解析路径积分的耗散量子动力学可实现连贯文本生成，而守恒律会导致根本性失败。通过柯普曼算子与闭式路径积分传播器，表明不可逆计算需受控信息耗散与因果上下文聚合。谱分析揭示了涌现的本征值结构，分为衰减模式（遗忘）、增长模式（放大）和中性模式（保留），构成定向信息流的基本要素。哈密顿约束迫使这些耗散模态消失，尽管模型容量不变，性能仍严重退化。这确立了语言生成为耗散量子场论，证明机械系统通过耗散与非局部性的结合获得智能，而非依赖守恒律。
原文摘要 · Abstract (English)
Can purely mechanical systems generate intelligent language? We prove that dissipative quantum dynamics with analytically tractable non-local context aggregation produce coherent text generation, while conservation laws cause fundamental failure. Employing Koopman operators with closed-form path integral propagators, we show irreversible computation fundamentally requires both controlled information dissipation and causal context aggregation. Spectral analysis reveals emergent eigenvalue structure, separating into decay modes (forgetting), growth modes (amplification), and neutral modes (preservation) -- the essential ingredients for directed information flow. Hamiltonian constraints force the elimination of these dissipative modes and degrading performance despite unchanged model capacity. This establishes language generation as dissipative quantum field theory, proving mechanical systems acquire intelligence through the combination of dissipation and non-locality, not through conservation.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。