Helen Shao

Princeton University — United States

Physics and Astronomy · Physical Sciences

9h-index311citations20works5.02yr avg
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Research Topics

Galaxies: Formation, Evolution, Phenomena(16), Computational Physics and Python Applications(9), Astronomy and Astrophysical Research(6), Cosmology and Gravitation Theories(5), Scientific Research and Discoveries(4)

Publications20 total

Cosmological limits on the neutrino mass sum for beyond-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi mathvariant="normal">Λ</mml:mi><mml:mi>CDM</mml:mi></mml:math> models
Physical review. D/Physical review. D.·2025· 9 citedOpen Access
Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects
Journal of Cosmology and Astroparticle Physics·2025· 6 citedOpen Access
Cosmological limits on the neutrino mass sum for beyond-$Λ$CDM models
arXiv (Cornell University)·2024Open Access
The CAMELS Project: Expanding the Galaxy Formation Model Space with New ASTRID and 28-parameter TNG and SIMBA Suites
The Astrophysical Journal·2023· 45 citedOpen Access
Quijote-PNG: The Information Content of the Halo Mass Function
The Astrophysical Journal·2023· 12 citedOpen Access
Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects
arXiv (Cornell University)·2023· 2 citedOpen Access
A Universal Equation to Predict Ω<sub>m</sub> from Halo and Galaxy Catalogs
The Astrophysical Journal·2023· 8 citedOpen Access
Robust Field-level Likelihood-free Inference with Galaxies
The Astrophysical Journal·2023· 39 citedOpen Access
Quijote-PNG: The Information Content of the Halo Mass Function
arXiv (Cornell University)·2023· 1 citedOpen Access
The CAMELS project: Expanding the galaxy formation model space with new ASTRID and 28-parameter TNG and SIMBA suites
arXiv (Cornell University)·2023· 9 citedOpen Access
The CAMELS Project: Public Data Release
The Astrophysical Journal Supplement Series·2023· 53 citedOpen Access
A universal equation to predict $Ω_{\rm m}$ from halo and galaxy catalogues
arXiv (Cornell University)·2023· 2 citedOpen Access
Robust Field-level Likelihood-free Inference with Galaxies
arXiv (Cornell University)·2023· 1 citedOpen Access
Robust Field-level Inference of Cosmological Parameters with Dark Matter Halos
The Astrophysical Journal·2023· 22 citedOpen Access
Robust field-level inference with dark matter halos
arXiv (Cornell University)·2022· 1 citedOpen Access
The CAMELS Multifield Data Set: Learning the Universe’s Fundamental Parameters with Artificial Intelligence
The Astrophysical Journal Supplement Series·2022· 62 citedOpen Access
Finding Universal Relations in Subhalo Properties with Artificial Intelligence
The Astrophysical Journal·2022· 31 citedOpen Access
The CAMELS project: public data release
arXiv (Cornell University)·2022· 4 citedOpen Access
Robust marginalization of baryonic effects for cosmological inference at the field level
HAL (Le Centre pour la Communication Scientifique Directe)·2021Open Access
Robust marginalization of baryonic effects for cosmological inference at\n the field level
arXiv (Cornell University)·2021· 4 citedOpen Access

Frequent Co-authors

Francisco Villaescusa-Navarro(18), Daniel Anglés‐Alcázar(14), Shy Genel(12), Yueying Ni(12), Mark Vogelsberger(11), Lars Hernquist(9), Romeel Davé(8), David N. Spergel(8), Ulrich P. Steinwandel(8), T. Castro(8), Pablo Villanueva-Domingo(7), B. D. Wandelt(7), Natalí S. M. de Santi(7), Desika Narayanan(6), Romain Teyssier(6), Christopher C. Lovell(6), Klaus Dolag(6), Leander Thiele(5), Andrina Nicola(5), Sultan Hassan(5)