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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.08764 |
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| _version_ | 1866911627453923328 |
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| author | Borthakur, Abhimanyu Hirschman, Jack Eden Carbajo, Sergio |
| author_facet | Borthakur, Abhimanyu Hirschman, Jack Eden Carbajo, Sergio |
| contents | Ultrashort laser pulses enable attosecond-scale measurements and drive breakthroughs across science and technology, but their routine use hinges on reliable pulse characterization. Frequency-Resolved Optical Gating (FROG) is a leading solution, forming a spectrogram by scanning the delay between two pulse replicas and recording the nonlinear signal spectrum. In online settings, however, dense delay-frequency scans are costly or impractical-especially for long pulses, wavelength regimes with limited spectrometer coverage (e.g., UV), or hardware with coarse resolution, yielding severely undersampled FROG traces. Existing reconstruction methods struggle in this regime-iterative algorithms are computationally heavy, convolutional networks blur fine structure, and sequence models are unstable when inputs are discontinuous or sparse. We present a generative diffusion framework tailored to recover ultrafast pulse intensity and phase from incomplete FROG measurements. Our model infers missing spectro-temporal content with high fidelity, enabling accurate retrieval from aggressively downsampled inputs. On a simulated benchmark of FROG-pulse pairs, the diffusion approach surpasses strong CNN and Seq2Seq baselines in accuracy and stability while remaining efficient enough for near real-time deployment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_08764 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Ultrafast Pulse Retrieval from Partial FROG Traces Using Implicit Diffusion Models Borthakur, Abhimanyu Hirschman, Jack Eden Carbajo, Sergio Optics Ultrashort laser pulses enable attosecond-scale measurements and drive breakthroughs across science and technology, but their routine use hinges on reliable pulse characterization. Frequency-Resolved Optical Gating (FROG) is a leading solution, forming a spectrogram by scanning the delay between two pulse replicas and recording the nonlinear signal spectrum. In online settings, however, dense delay-frequency scans are costly or impractical-especially for long pulses, wavelength regimes with limited spectrometer coverage (e.g., UV), or hardware with coarse resolution, yielding severely undersampled FROG traces. Existing reconstruction methods struggle in this regime-iterative algorithms are computationally heavy, convolutional networks blur fine structure, and sequence models are unstable when inputs are discontinuous or sparse. We present a generative diffusion framework tailored to recover ultrafast pulse intensity and phase from incomplete FROG measurements. Our model infers missing spectro-temporal content with high fidelity, enabling accurate retrieval from aggressively downsampled inputs. On a simulated benchmark of FROG-pulse pairs, the diffusion approach surpasses strong CNN and Seq2Seq baselines in accuracy and stability while remaining efficient enough for near real-time deployment. |
| title | Ultrafast Pulse Retrieval from Partial FROG Traces Using Implicit Diffusion Models |
| topic | Optics |
| url | https://arxiv.org/abs/2511.08764 |