Deep learning-driven likelihood-free parameter inference for 21-cm forest observations
Abstract The hyperfine structure absorption lines of neutral hydrogen in high-redshift radio spectra, known as the 21-cm forest, have been demonstrated through simulations as a powerful probe of small-scale structures governed by dark matter (DM) properties and the thermal history of intergalactic m...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-025-02139-5 |
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