Lyman- alpha forest holography: 3D predictions from 1D measurements

arXiv:2607.27413 · astro-ph.CO · Submitted 2026-07-29 · Read on arXiv

J. Chaves-Montero, A. Font-Ribera, J. Aguilar, S. Ahlen, E. Armengaud, A. Aviles, F. Beutler, D. Bianchi, S. Blasby, D. Brooks, K. Carrion, Z. Chen, T. Claybaugh, A. Cuceu, A. de la Macorra, A. Dey, P. Doel, W. Elbers, S. Ferraro, L. Flores, J. E. Forero-Romero, E. Gaztañaga, S. Gontcho A Gontcho, D. Gonzalez, A. X. Gonzalez-Morales, R. Gsponer, G. Gutierrez, C. Hahn, M. Herbold, H. K. Herrera-Alcantar, K. Honscheid, M. Ishak, S. Juneau, N. V. Kamble, D. Kirkby, A. Kremin, A. Lambert, M. Landriau, L. Le Guillou, K. Lodha, Z. Lukić, M. Manera, P. Martini, A. Meisner, R. Miquel, P. Mukherjee, A. Muñoz-Gutiérrez, S. Nadathur, H. E. Noriega, E. Paillas, N. Palanque-Delabrouille, W. J. Percival, C. Poppett, F. Prada, H. Pulido-Hernández, I. Pérez-Ràfols, C. Ravoux, J. Rohlf, A. J. Rosado-Marín, G. Rossi, R. Ruggeri, M. F. Ruiz-Herrera Bernal, E. Sanchez, C. Saulder, D. Schlegel, M. Schubnell, F. Sinigaglia, G. Tarlé, W. Turner, B. A. Weaver, H. Zhang

astro-ph.CO

Submitted: 2026-07-29

Comments: 12 pages, 7 figures, submitted to A&A

Code: https://github.com/igmhub/ForestFlow

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Clustering — 53× in this paper · explained in 2 episodes
• Matter Power Spectrum — 7× in this paper · explained in 2 episodes
• alpha — 6× in this paper · explained in 1 episode
• Degeneracy — 4× in this paper · explained in 3 episodes
• Department of Energy — 3× in this paper
• Accuracy — 2× in this paper · explained in 1 episode
• National Science Foundation — 2× in this paper
• Anisotropy — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Markov Chain Monte Carlo — 1× in this paper
• Normalizing Flow — 1× in this paper · explained in 3 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Construction of the Damped Ly$\alpha$ Absorber Catalog for DESI DR2 Ly$\alpha$ BAO
• QuasarNET: Human-level spectral classification and redshifting with Deep Neural Networks
• Validation of the DESI DR2 Ly$\alpha$ BAO analysis using synthetic datasets
• Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest
• Cosmological analysis of the DESI DR1 Lyman alpha 1D power spectrum
• Data Release 1 of the Dark Energy Spectroscopic Instrument
• DESI DR2 Results II: Measurements of Baryon Acoustic Oscillations and Cosmological Constraints
• DESI DR2 Results I: Baryon Acoustic Oscillations from the Lyman Alpha Forest
• The DESI Experiment Part I: Science,Targeting, and Survey Design
• The DESI Experiment Part II: Instrument Design
• Optimal 1D Ly$\alpha$ Forest Power Spectrum Estimation -- III. DESI early data
• GetDist: a Python package for analysing Monte Carlo samples
• Normalizing Flows for Probabilistic Modeling and Inference
• PyTorch: An Imperative Style, High-Performance Deep Learning Library
• Learning Likelihoods with Conditional Normalizing Flows

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