Inferring Astrophysics and Dark Matter Properties from 21cm Tomography using Deep Learning

Abstract

21cm tomography opens a window to directly study astrophysics and fundamental physics of early epochs in our Universe's history, the Epoch of Reionisation (EoR) and Cosmic Dawn (CD). Summary statistics such as the power spectrum omit information encoded in this signal due to its highly non-Gaussian nature. Here we adopt a network-based approach for direct inference of CD and EoR astrophysics jointly with fundamental physics from 21cm tomography. We showcase a warm dark matter (WDM) universe, where dark matter density parameter ${\Omega }_{\mathrm{m}}$ and WDM mass $m_{\mathrm{WDM}}$ strongly influence both CD and EoR. Reflecting the three-dimensional nature of 21cm light-cones, we present a new, albeit simple, 3D convolutional neural network for efficient parameter recovery at moderate training cost. On simulations we observe high-fidelity parameter recovery for CD and EoR astrophysics ($R^2>0.78-0.99$), together with DM density ${\Omega }_{\mathrm{m}}$ ($R^2>0.97$) and WDM mass ($R^2>0.61$, significantly better for $m_{\mathrm{WDM}}<3-4$keV). For realistic mock observed light-cones that include noise and foreground levels expected for the Square Kilometre Array, we note that in an optimistic foreground scenario parameter recovery is unaffected, while for moderate, less optimistic foreground levels (occupying the so-called wedge) the recovery of the WDM mass deteriorates, while other parameters remain robust against increased foreground levels at $R^2>0.9$. We further test the robustness of our network-based inference against modelling uncertainties and systematics by transfer learning between bare simulations and mock observations; we find robust recovery of specific X-ray luminosity and ionising efficiency, while DM density and WDM mass come with increased bias and scatter.

arXiv comment18 pages, 9 figures, 7 tables. Accepted for publication in MNRAS. Comments are welcome

References in corpus (47)

• Adam: A Method for Stochastic Optimization
• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
• Dark Matter Substructure in Galactic Halos
• LOFAR: The LOw-Frequency ARray
• Sterile Neutrinos as Dark Matter
• Too big to fail? The puzzling darkness of massive Milky Way subhaloes
• In the Beginning: The First Sources of Light and the Reionization of the Universe
• The Murchison Widefield Array: the Square Kilometre Array Precursor at low radio frequencies
• Constraining Warm Dark Matter candidates including sterile neutrinos and light gravitinos with WMAP and the Lyman-alpha forest
• 21cmFAST: A Fast, Semi-Numerical Simulation of the High-Redshift 21-cm Signal
• Hydrogen Epoch of Reionization Array (HERA)
• Sterile Neutrino Hot, Warm, and Cold Dark Matter
• New Constraints on the free-streaming of warm dark matter from intermediate and small scale Lyman-$\alpha$ forest data
• The properties of warm dark matter haloes
• Efficient Simulations of Early Structure Formation and Reionization
• The Precision Array for Probing the Epoch of Reionization: 8 Station Results
• A White Paper on keV Sterile Neutrino Dark Matter
• What Next-Generation 21 cm Power Spectrum Measurements Can Teach Us About the Epoch of Reionization
• 21CMMC: an MCMC analysis tool enabling astrophysical parameter studies of the cosmic 21 cm signal
• Simulating Cosmic Reionization at Large Scales II: the 21-cm Emission Features and Statistical Signals
• Statistical Probes of Reionization With 21 cm Tomography
• Realistic sterile neutrino dark matter with keV mass does not contradict cosmological bounds
• The Baryon Acoustic Oscillation Broadband and Broad-beam Array: Design Overview and Sensitivity Forecasts
• HERA Phase I Limits on the Cosmic 21-cm Signal: Constraints on Astrophysics and Cosmology During the Epoch of Reionization
• 21cmFAST v3: A Python-integrated C code forgenerating 3D realizations of the cosmic 21cm signal
• Emulating Simulations of Cosmic Dawn for 21cm Power Spectrum Constraints on Cosmology, Reionization, and X-ray Heating
• The Imprint of Warm Dark Matter on the Cosmological 21-cm Signal
• Deep learning from 21-cm tomography of the Cosmic Dawn and Reionization
• 21CMMC with a 3D light-cone: the impact of the co-evolution approximation on the astrophysics of reionisation and cosmic dawn
• How to constrain warm dark matter with the Lyman $\alpha$ forest
• Analysing the 21cm signal from the Epoch of Reionization with artificial neural networks
• Emulation of reionization simulations for Bayesian inference of astrophysics parameters using neural networks
• High Mass X-ray Binaries and the Cosmic 21-cm Signal: Impact of Host Galaxy Absorption
• Unveiling the nature of dark matter with high redshift 21 cm line experiments
• Constraining the astrophysics and cosmology from 21cm tomography using deep learning with the SKA
• Warm dark matter signatures on the 21cm power spectrum: Intensity mapping forecasts for SKA
• Fuzzy Dark Matter and the 21cm Power Spectrum
• Machine learning astrophysics from 21 cm lightcones: impact of network architectures and signal contamination
• Removing Astrophysics in 21 cm maps with Neural Networks
• Constraining the reionization history using deep learning from 21cm tomography with the Square Kilometre Array
• Warm Dark Matter and Cosmic Reionization
• General Modified Gravity With 21cm Intensity Mapping: Simulations and Forecast
• Constraining the Reionization History using Bayesian Normalizing Flows
• Impact of dark matter models on the EoR 21-cm signal bispectrum
• The spin-temperature dependence of the 21cm -- LAE cross-correlation
• Simultaneously constraining the astrophysics of reionisation and the epoch of heating with 21CMMC
• Lux ex tenebris: The imprint of annihilating dark matter on the intergalactic medium during Cosmic Dawn

Cited by in corpus (15)

• Machine Learning for Observational Cosmology
• Machine Learning and Cosmology
• Optimal, fast, and robust inference of reionization-era cosmology with the 21cmPIE-INN
• SKATR: A Self-Supervised Summary Transformer for SKA
• Inferring Cosmological Parameters on SDSS via Domain-Generalized Neural Networks and Lightcone Simulations
• Deep Learning 21cm Lightcones in 3D
• The 21cm-galaxy cross-correlation: Realistic forecast for 21cm signal detection and reionisation constraints
• 3D ScatterNet: Inference from 21 cm Light-cones
• From ANN to BNN: Inferring Reionization Parameters using Uncertainty-aware Emulators of 21-cm Summaries
• Large Language Models -- the Future of Fundamental Physics?
• Direct reconstruction of the Reionization history from 21cm 2D Power Spectra
• Beyond the Power Spectrum: A New Framework for Non-Stationary Fields with Applications to Light-Cone Effects in Line Intensity Mapping
• Accelerating reionization constraints: An ANN-emulator framework for the SCRIPT Semi-numerical Model
• Exploring the Model Dependence of MCMC-Based 21 cm Power Spectrum Parameter Constraints
• CosmoUiT: A Vision Transformer-UNet Hybrid for Fast and Accurate Emulation of 21-cm Maps from the Epoch of Reionization