An AI-ready, Polarized Electron-Positron Collision Dataset
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911734872145920 |
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| author | Cheng, Chi Lung Corrodi, Simon Hobbs, T. J. Mete, Alaettin Serhan Nachman, Benjamin |
| author_facet | Cheng, Chi Lung Corrodi, Simon Hobbs, T. J. Mete, Alaettin Serhan Nachman, Benjamin |
| contents | We present a modernized, AI-ready release of reconstructed data from the SLD experiment at the SLAC Linear Collider (SLC). The dataset comprises approximately 660{,}000 reconstructed events collected at $\sqrt{s}\approx 91.2$~GeV with a highly polarized electron beam from 1996--1998. The data have been translated from legacy formats into modern, widely-used file formats with the help of AI agents. The release also includes a corpus of newly digitized SLD internal documentation. We describe the contents of both components and provide physics validation demonstrations along with illustrations of their utility for physics and machine learning research in particle physics. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2606_00224 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | An AI-ready, Polarized Electron-Positron Collision Dataset Cheng, Chi Lung Corrodi, Simon Hobbs, T. J. Mete, Alaettin Serhan Nachman, Benjamin High Energy Physics - Experiment High Energy Physics - Phenomenology We present a modernized, AI-ready release of reconstructed data from the SLD experiment at the SLAC Linear Collider (SLC). The dataset comprises approximately 660{,}000 reconstructed events collected at $\sqrt{s}\approx 91.2$~GeV with a highly polarized electron beam from 1996--1998. The data have been translated from legacy formats into modern, widely-used file formats with the help of AI agents. The release also includes a corpus of newly digitized SLD internal documentation. We describe the contents of both components and provide physics validation demonstrations along with illustrations of their utility for physics and machine learning research in particle physics. |
| title | An AI-ready, Polarized Electron-Positron Collision Dataset |
| topic | High Energy Physics - Experiment High Energy Physics - Phenomenology |
| url | https://arxiv.org/abs/2606.00224 |