OpenCosmo: Community Portal and Analysis Framework for Flagship Cosmological Simulations

Abstract

Cosmology is a precision observational science, and large simulations are necessary components of many analyses. These simulations are computationally expensive and produce massive, complex datasets; sharing them widely -- to enable further explorations, comparison with observations, and communication with general audiences -- is crucial to realizing their scientific value. In this paper, we introduce the OpenCosmo project, which provides flexible access to, and analysis of, flagship cosmological simulations performed with HACC. A web-based portal (https://opencosmo.science) serves custom subsets -- halo catalogs, profiles, particles, galaxy catalogs, and lightcone catalogs and maps -- from simulations including the two-trillion-particle Frontier-E gravity-only run, Last Journey, Discovery, and a 64-member hydrodynamic suite. A companion Python toolkit analyzes the returned data and scales without modification from laptop-sized subsets to full simulations on supercomputers. OpenCosmo supports multiple levels of interaction, from browser-based search and download to programmatic and AI-agent-driven workflows, by integrating with existing high-performance computing and data infrastructure. Its architecture, built on Globus services, provides a scalable and adaptable framework that can be extended to other scientific domains seeking to couple data sharing with computational capability.

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BibTeX RIS

BibTeX

@misc{wells2026opencosmo,
  title = {{OpenCosmo: Community Portal and Analysis Framework for Flagship Cosmological Simulations}},
  author = {Patrick R. Wells and Michael Buehlmann and Patricia Larsen and William M. Hicks and Manpreet Dhillon and Idunnuoluwa A. Adeniji and Katrin Heitmann and Salman Habib and Benoit Côté and Thomas Uram and Gideon McFarland and Andrew Hearin and Ezar Shinabro and Michael E. Papka},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2607.16059},
  eprint = {2607.16059},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.16059},
  note = {CC BY 4.0},
}

RIS

TY  - UNPB
TI  - OpenCosmo: Community Portal and Analysis Framework for Flagship Cosmological Simulations
AU  - Patrick R. Wells
AU  - Michael Buehlmann
AU  - Patricia Larsen
AU  - William M. Hicks
AU  - Manpreet Dhillon
AU  - Idunnuoluwa A. Adeniji
AU  - Katrin Heitmann
AU  - Salman Habib
AU  - Benoit Côté
AU  - Thomas Uram
AU  - Gideon McFarland
AU  - Andrew Hearin
AU  - Ezar Shinabro
AU  - Michael E. Papka
PY  - 2026
DA  - 2026/09/25
PB  - arXiv
DO  - 10.48550/arxiv.2607.16059
UR  - https://arxiv.org/abs/2607.16059
AB  - Cosmology is a precision observational science, and large simulations are necessary components of many analyses. These simulations are computationally expensive and produce massive, complex datasets; sharing them widely -- to enable further explorations, comparison with observations, and communication with general audiences -- is crucial to realizing their scientific value. In this paper, we introduce the OpenCosmo project, which provides flexible access to, and analysis of, flagship cosmological simulations performed with HACC. A web-based portal (https://opencosmo.science) serves custom subsets -- halo catalogs, profiles, particles, galaxy catalogs, and lightcone catalogs and maps -- from simulations including the two-trillion-particle Frontier-E gravity-only run, Last Journey, Discovery, and a 64-member hydrodynamic suite. A companion Python toolkit analyzes the returned data and scales without modification from laptop-sized subsets to full simulations on supercomputers. OpenCosmo supports multiple levels of interaction, from browser-based search and download to programmatic and AI-agent-driven workflows, by integrating with existing high-performance computing and data infrastructure. Its architecture, built on Globus services, provides a scalable and adaptable framework that can be extended to other scientific domains seeking to couple data sharing with computational capability.
ER  -

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