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AI-Ready ARPES Database Framework Proposed for Condensed Matter Physics

By PulseAugur Editorial · [1 sources] ·

Researchers have proposed a framework for an AI-ready community database for Angle-Resolved Photoemission Spectroscopy (ARPES) data. This initiative aims to consolidate fragmented experimental records into a persistent scientific memory, enhancing reproducibility and enabling AI-driven discoveries in condensed matter physics. The proposed ecosystem will offer benefits across different timescales, from strengthening analysis pipelines in the near term to supporting foundation models for quantum matter in the long term. AI

IMPACT Could accelerate AI-driven discovery in condensed matter physics by creating a unified data ecosystem for ARPES experiments.

RANK_REASON The cluster describes a proposed framework for a scientific database, detailed in a research paper. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI-Ready ARPES Database Framework Proposed for Condensed Matter Physics

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The cluster describes a proposed framework for a scientific database, detailed in a research paper. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zhi-Xun Shen, Jin Gene Wong, Karen Lei, Leon Garcia, Felix Baumberger, Sergey Borisenko, Aaron Bostwick, Ting Cao, Tanny Chavez, Yulin Chen, Monika Choudhary, Andrea Damascelli, Dan Dessau, Thomas P. Devereaux, Sandy A. Ekahana, Alexei Fedorov, Atsushi F… ·

    Framework for an AI-Ready ARPES Community Database

    arXiv:2610.15236v1 Announce Type: cross 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 ma…

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