analiza aiqbench
This research introduces a Quantum Walk Temporal Architecture (QWTA) that leverages continuous-time quantum walks on graph Laplacians to model temporal signals, offering non-monotonic propagation features unattainable by classical diffusion methods. By encoding irregular observation intervals into spectral phase modulation and applying stabilization techniques like gated residual fusion, the approach provides a physically motivated framework for forecasting with missing historical data. The study demonstrates that explicit quantum interference effects can yield competitive performance in graph signal modeling tasks where traditional algorithms struggle with non-uniform time steps.
Continuous Time Quantum Walk Propagation for Irregular Temporal Graph Forecasting
arXiv:2607.17273v1 Announce Type: new Abstract: 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.
Abstract: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.
arXiv:2607.17273 [quant-ph]
(or arXiv:2607.17273v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2607.17273 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Text integral sub licența deschisă a publicației · 220 cuvinte
Subiecte conexe

Game Design Creativity evals
LessWrong · 12 oct. 2026
Iterative quantum algorithms for the minimum vertex cover problem based on continuous-time quantum walks
arXiv · 31 iul. 2026
Continuous-Time Quantum Walks based Graph Neural Network
arXiv · 24 aug. 2026

Graph-centric agentic intelligence
Amazon Science · 1 oct. 2026