Year: 2026
Type: preprint
Abstract: Condensed matter stands to gain profoundly from widespread adoption of artificial intelligence (AI). However, its current means of data organization impedes this endeavor. As a premier measure of electronic structure underlying material properties, Angle-Resolved Photoemission Spectroscopy (ARPES) has accumulated over four decades of spectra, yet the community's publication-centered workflow preserves only a highly selected fraction of its experimental record. A shared data ecosystem could transform these fragmented measurements and their contexts into a persistent, collective scientific memory, creating immediate value for reproducibility and reuse while laying the foundation for AI-enabled discovery. In this Perspective, we report outcomes of a recent community workshop and propose a practical path toward such an ecosystem. Its benefits unfold along three timescales. In the near term, standardized, searchable, and citable datasets strengthen analysis pipelines independently of AI. In the intermediate future, community-validated tools operating across laboratories could enable broader reuse and increasingly closed-loop automated experiments. In the long term, a diverse corpus of measured electronic spectra could support foundation models for quantum matter. Looking forward, a diverse corpus of measured electronic spectra could support foundation models for quantum matter and new discoveries. We discuss lessons from existing scientific databases, the current state of AI in ARPES, as well as areas of community convergence on data organization, access, credit, governance, and a staged pilot program.
Source: arXiv (Cornell University)
Authors: Shen, Zhi-Xun, Wong, Jin Gene, Lei, Karen, Garcia, Leon, Baumberger, Felix, Borisenko, Sergey, Bostwick, Aaron, Cao, Ting, Chavez, Tanny, Chen, Yulin, Choudhary, Monika, Damascelli, Andrea, Dessau, Dan, Devereaux, Thomas P., Ekahana, Sandy A., Fedorov, Alexei, Fujimori, Atsushi, Guo, Yucheng, Hasan, M. Zahid, Hashimoto, Makoto, He, Yu, Hofmann, Philip, Hussain, Zahid, Hwang, Harold Y., Ji, Zhurun, Jia, Chunjing, Kim, Timur K., King, Phil D. C., Kondo, Takeshi, Lanzara, Alessandra, Lin, Chun, Lu, Donghui, Michiardi, Matteo, Mo, Sung-Kwan, Moritz, Brian, Rettig, Laurenz, Rotenberg, Eli, Sato, Takafumi, Shen, Kyle M., Sobota, Jonathan A., Vishik, Inna, Yang, Shuolong, Yi, Ming, Zaklama, Timothy
Institutions: Stanford University, University of Geneva, Paul Scherrer Institute, Swiss Light Source, Leibniz Institute for Solid State and Materials Research, Lawrence Berkeley National Laboratory, Advanced Light Source, University of Washington, University of Oxford, University of British Columbia, University of Colorado Boulder, Carnegie Mellon University, Rice University, Princeton University, SLAC National Accelerator Laboratory, Stanford Synchrotron Radiation Lightsource, Yale University, Aarhus University, Massachusetts Institute of Technology, University of Florida, Diamond Light Source, University of St Andrews, The Institute for Solid State Physics, The University of Tokyo, The University of Tokyo, University of California, Berkeley, Fritz Haber Institute of the Max Planck Society, Cornell University, University of California, Davis, University of Chicago
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7221770328