Persistence-based topological descriptors from 21 cm forest spectra provide complementary constraints on X-ray heating efficiency and warm dark matter free-streaming scale.
Wavelet-Scattering Signatures of Fuzzy Dark Matter in Simulated 21 cm Brightness-Temperature Maps
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abstract
We study how fuzzy dark matter (FDM) affects the multiscale morphology of the redshifted 21 cm brightness-temperature field during Cosmic Dawn and the Epoch of Reionization. Using FDM-modified \texttt{21cmFAST} simulations, we apply the two-dimensional wavelet scattering transform (WST) to simulated 21 cm maps. The first-order coefficients $S_1(j)$ trace localized variance-like information, while the normalized second-order ratios $R(j_1,j_2)=S_2/S_1$ measure non-Gaussian cross-scale coupling. FDM shifts and reshapes both summaries, especially for scale pairs anchored on fine wavelet bands, reflecting delayed Ly$\alpha$ coupling, X-ray heating, and reionization. We compare power-spectrum-only, WST-only, and combined power-spectrum+WST Fisher forecasts using the same SKA1-Low-like mock-observation assumptions, redshift bins, nuisance parameters, thermal-noise model, and $uv$ filtering. The combined power-spectrum+WST data vector gives the tightest marginalized constraints, showing that WST carries information complementary to the power spectrum in the adopted local Fisher setup. We also include an idealized foreground-wedge avoidance test on three-dimensional light-cone chunks, demonstrating how contaminated low-$k_\parallel$ modes are removed before extracting WST summaries. A compact wedge-impact diagnostic shows that the normalized second-order ratio is less strongly reshaped by horizon-wedge filtering than the first-order amplitudes, while not constituting a foreground-aware detectability forecast. These calculations are not an end-to-end SKA foreground-subtraction pipeline, but they establish WST as an interpretable morphological summary that remains useful when compared directly with the power spectrum.
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Starlet l1-norm applied to simulated HI brightness temperature maps at z~0.4 yields almost 3x higher figure of merit for cosmological parameters than angular power spectrum by capturing non-Gaussian information and shows robustness to observational systematics.
Review chapter organizing machine learning methods for 21 cm cosmology into observation, theory, and inference domains.
citing papers explorer
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Topological Signatures of Heating and Dark Matter in the 21 cm Forest
Persistence-based topological descriptors from 21 cm forest spectra provide complementary constraints on X-ray heating efficiency and warm dark matter free-streaming scale.
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Beyond power spectrum to unveil systematics on HI intensity maps
Starlet l1-norm applied to simulated HI brightness temperature maps at z~0.4 yields almost 3x higher figure of merit for cosmological parameters than angular power spectrum by capturing non-Gaussian information and shows robustness to observational systematics.
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Application of Machine Learning to 21 cm Cosmology
Review chapter organizing machine learning methods for 21 cm cosmology into observation, theory, and inference domains.