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Physical Review D

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Extracting cosmological information from the abundance of galaxy clusters with simulation-based inference

Íñigo Zubeldia1,2,*, Boris Bolliet3,2, Anthony Challinor1,2,4, and William Handley1,2

  • 1Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, United Kingdom
  • 2Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB3 0HA, United Kingdom
  • 3Cavendish Astrophysics, University of Cambridge, Madingley Road, Cambridge CB3 0HA, United Kingdom
  • 4DAMTP, Centre for Mathematical Sciences, Wilberforce Road, Cambridge, CB3 0WA, United Kingdom

  • *Contact author: inigo.zubeldia@ast.cam.ac.uk

Quantifying weighted morphological content of large-scale structures via simulation-based inference

M. H. Jalali Kanafi and S. M. S. Movahed

Phys. Rev. D 113 063543 (2026)

Flexible simulation-based inference for galaxy photometric fitting with synthesizer

Thomas Harvey, Christopher C Lovell, Sophie Newman, Christopher J Conselice, Duncan Austin, William J Roper, Aswin P Vijayan, Stephen M Wilkins, Patricia Iglesias-Navarro, Vadim Rusakov, Qiong Li, Nathan Adams, Kai Magdwick, Caio M Goolsby, Marc Huertas-Company, and Matthew Ho

Monthly Notices of the Royal Astronomical Society 547 stag282 (2026)

Starobinsky in stereo: SKA-CMB synergy in SBI

Benedikt Schosser, Caroline Heneka, and Björn Malte Schäfer

J. Cosmol. Astropart. Phys. 2026 086 (2026)

Galaxy cluster count cosmology with simulation-based inference

M. Regamey, D. Eckert, R. Seppi, W. Hartley, K. Umetsu, S. Tam, and D. Gerolymatou

A&A 708 A260 (2026)

How to embed any likelihood into simulation-based inference: Application to Planck and stage IV galaxy surveys and dynamical dark energy

Guillermo Franco Abellán, Noemi Anau Montel, Oleg Savchenko, and Christoph Weniger

Phys. Rev. D 112 103526 (2025)

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