The work demonstrates that multi-tracer field-level SBI on galaxy and HI maps yields 2-7 times better constraints on Omega_m and sigma_8 than single-tracer or summary-statistic approaches, with 3D maps performing best.
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2026 3representative citing papers
Field-level inference from weak lensing maps yields significantly tighter cosmological constraints than power-spectrum analysis when using the same forward-modeling pipeline, especially on small scales.
A field-level CNN emulator converts MG-PICOLA runs into near N-body accuracy for f(R) gravity and neutrino cosmologies, achieving sub-percent errors on power spectra and bispectra while generalizing beyond its training set.
citing papers explorer
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Field-level multi-tracers simulation-based inference of cosmological parameters from 3D maps
The work demonstrates that multi-tracer field-level SBI on galaxy and HI maps yields 2-7 times better constraints on Omega_m and sigma_8 than single-tracer or summary-statistic approaches, with 3D maps performing best.
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Towards Practical Field-Level Inference for Weak Lensing
Field-level inference from weak lensing maps yields significantly tighter cosmological constraints than power-spectrum analysis when using the same forward-modeling pipeline, especially on small scales.
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MG-NECOLA: A Field-Level Emulator for $f(R)$ Gravity and Massive Neutrino Cosmologies
A field-level CNN emulator converts MG-PICOLA runs into near N-body accuracy for f(R) gravity and neutrino cosmologies, achieving sub-percent errors on power spectra and bispectra while generalizing beyond its training set.