Papers › Galaxy Clustering Analysis with SimBIG and the Wavelet Scattering Transform

Galaxy Clustering Analysis with SimBIG and the Wavelet Scattering Transform

23 Oct 2023arXiv:2310.15250links table onlyarchive 2025-07-28

Bruno Régaldo-Saint Blancard, ChangHoon Hahn, Shirley Ho, Jiamin Hou, Pablo Lemos, Elena Massara, Chirag Modi, Azadeh Moradinezhad Dizgah, Liam Parker, Yuling Yao, Michael Eickenberg

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The non-Gaussisan spatial distribution of galaxies traces the large-scale structure of the Universe and therefore constitutes a prime observable to constrain cosmological parameters. We conduct Bayesian inference of the ΛCDM parameters Ωₘ, Ω_b, h, nₛ, and σ₈ from the BOSS CMASS galaxy sample by combining the wavelet scattering transform (WST) with a simulation-based inference approach enabled by the SIMBIG forward model. We design a set of reduced WST statistics that leverage symmetries of redshift-space data. Posterior distributions are estimated with a conditional normalizing flow trained on 20,000 simulated SIMBIG galaxy catalogs with survey realism. We assess the accuracy of the posterior estimates using simulation-based calibration and quantify generalization and robustness to the change of forward model using a suite of 2,000 test simulations. When probing scales down to kₘₐₓ=0.5 h/Mpc, we are able to derive accurate posterior estimates that are robust to the change of forward model for all parameters, except σ₈. We mitigate the robustness issues with σ₈ by removing the WST coefficients that probe scales smaller than k ∼0.3 h/Mpc. Applied to the BOSS CMASS sample, our WST analysis yields seemingly improved constraints obtained from a standard PT-based power spectrum analysis with kₘₐₓ=0.25 h/Mpc for all parameters except h. However, we still raise concerns on these results. The observational predictions significantly vary across different normalizing flow architectures, which we interpret as a form of model misspecification. This highlights a key challenge for forward modeling approaches when using summary statistics that are sensitive to detailed model-specific or observational imprints on galaxy clustering.

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check_grid bregaldo/galactic_wavelets/galactic_wavelets/wavelets.py community (archive-listed) unverified BSD-3-Clause (permissive) · 19624f3645f8da71 · report
gaussian bregaldo/galactic_wavelets/galactic_wavelets/wavelets.py community (archive-listed) unverified BSD-3-Clause (permissive) · e84bd53125474cc1 · report
lanusse_scaling_function_3d bregaldo/galactic_wavelets/galactic_wavelets/wavelets.py community (archive-listed) unverified BSD-3-Clause (permissive) · 7c2c006fb921f531 · report
mask_erosion bregaldo/galactic_wavelets/galactic_wavelets/erosion.py community (archive-listed) unverified BSD-3-Clause (permissive) · 44a9f9d6ad0c5c15 · report
mask_erosion_para bregaldo/galactic_wavelets/galactic_wavelets/erosion.py community (archive-listed) unverified BSD-3-Clause (permissive) · 3fdcc33d91777fdb · report
mask_erosion_torch bregaldo/galactic_wavelets/galactic_wavelets/erosion.py community (archive-listed) unverified BSD-3-Clause (permissive) · edcac6c23b4a1165 · report
wst_reduction bregaldo/galactic_wavelets/galactic_wavelets/reduction.py community (archive-listed) unverified BSD-3-Clause (permissive) · f4141d1d595c4d8d · report

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