{"ID":2844713,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.06126","arxiv_id":"2511.06126","title":"Video-rate gigapixel ptychography via space-time neural field representations","abstract":"Achieving gigapixel space-bandwidth products (SBP) at video rates represents a fundamental challenge in imaging science. Here we demonstrate video-rate ptychography that overcomes this barrier by exploiting spatiotemporal correlations through neural field representations. Our approach factorizes the space-time volume into low-rank spatial and temporal features, transforming SBP scaling from sequential measurements to efficient correlation extraction. The architecture employs dual networks for decoding real and imaginary field components, avoiding phase-wrapping discontinuities plagued in amplitude-phase representations. A gradient-domain loss on spatial derivatives ensures robust convergence. We demonstrate video-rate gigapixel imaging with centimeter-scale coverage while resolving 308-nm linewidths. Validations span from monitoring sample dynamics of crystals, bacteria, stem cells, microneedle to characterizing time-varying probes in extreme ultraviolet experiments, demonstrating versatility across wavelengths. By transforming temporal variations from a constraint into exploitable correlations, we establish that gigapixel video is tractable with single-sensor measurements, making ptychography a high-throughput sensing tool for monitoring mesoscale dynamics without lenses.","short_abstract":"Achieving gigapixel space-bandwidth products (SBP) at video rates represents a fundamental challenge in imaging science. Here we demonstrate video-rate ptychography that overcomes this barrier by exploiting spatiotemporal correlations through neural field representations. Our approach factorizes the space-time volume i...","url_abs":"https://arxiv.org/abs/2511.06126","url_pdf":"https://arxiv.org/pdf/2511.06126v1","authors":"[\"Ruihai Wang\",\"Qianhao Zhao\",\"Zhixuan Hong\",\"Qiong Ma\",\"Tianbo Wang\",\"Lingzhi Jiang\",\"Liming Yang\",\"Shaowei Jiang\",\"Feifei Huang\",\"Thanh D. Nguyen\",\"Leslie Shor\",\"Daniel Gage\",\"Mary Lipton\",\"Christopher Anderton\",\"Arunima Bhattacharjee\",\"David Brady\",\"Guoan Zheng\"]","published":"2025-11-08T20:35:04Z","proceeding":"physics.optics","tasks":"[\"physics.optics\",\"eess.IV\"]","methods":"[]","has_code":false}