AI 中文总结
研究针对不规则时间图预测，提出量子行走时间架构（QWTA），用CTQW型参数化谱传播器取代经典图传播，通过嵌入有效观察间隔及引入相位软裁剪和门控残差融合稳定传播，为相关预测提供有竞争力的图传播设计。
AI 中文摘要
基于图拉普拉斯算子构建的连续时间量子行走在演化过程中通过量子干涉产生非单调的图传播特征，这是经典扩散无法实现的。我们提出了量子行走时间架构（QWTA），用CTQW型参数化谱传播器取代经典图传播。QWTA将有效观察间隔嵌入传播核的谱相位调制中。QWTA - Base保留精确的CTQW谱演化，QWTA - GR进一步引入相位软裁剪和门控残差融合来稳定传播。结果表明，不规则时间间隔的显式相位编码与适当的稳定化相结合，为具有缺失历史观测的时间图预测提供了一种有物理动机且有竞争力的图传播设计。
英文摘要
Continuous time quantum walks built on graph Laplacians produce non monotonic graph propagation features through quantum interference during evolution, which classical diffusion cannot achieve. Such walks deliver a physically motivated propagation scheme for temporal graph signal modeling. We propose Quantum Walk Temporal Architecture (QWTA), which replaces classical graph propagation with a CTQW-type parameterized spectral propagator. QWTA embeds effective observation intervals into the spectral phase modulation of the propagation kernel. QWTA-Base preserves exact CTQW spectral evolution and serves as a physically faithful propagation reference. QWTA-GR further introduces phase soft clipping and gated residual fusion to stabilize propagation. The results show that explicit phase encoding of irregular time intervals, when combined with suitable stabilization, provides a physically motivated and competitive graph propagation design for temporal graph forecasting with missing historical observations.
