Impact of astrophysical effects on the dark matter mass constraint with 21cm intensity mapping

Abstract

We present an innovative approach to constraining the non-cold dark matter model using a convolutional neural network (CNN). We perform a suite of hydrodynamic simulations with varying dark matter particle masses and generate mock 21cm radio intensity maps to trace the dark matter distribution. Our proposed method complements the traditional power spectrum analysis. We compare our CNN classification results with those from the power spectrum of the differential brightness temperature map of 21cm radiation, and find that the CNN outperforms the latter. Moreover, we investigate the impact of baryonic physics on the dark matter model constraint, including star formation, self-shielding of HI gas, and UV background model. We find that these effects may introduce some contamination in the dark matter constraint, but they are insignificant when compared to the realistic system noise of the SKA instruments.

arXiv comment16 pages, 15 figures

References in corpus (44)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• The cosmological simulation code GADGET-2
• Cosmology at Low Frequencies: The 21 cm Transition and the High-Redshift Universe
• The Rockstar Phase-Space Temporal Halo Finder and the Velocity Offsets of Cluster Cores
• Sterile Neutrinos as Dark Matter
• The Murchison Widefield Array: the Square Kilometre Array Precursor at low radio frequencies
• Radiative transfer in a clumpy universe: IV. New synthesis models of the cosmic UV/X-ray background
• Warm Dark Matter as a solution to the small scale crisis: new constraints from high redshift Lyman-alpha forest data
• A New Calculation of the Ionizing Background Spectrum and the Effects of HeII Reionization
• Transients from Initial Conditions in Cosmological Simulations
• A Modified Magnitude System that Produces Well-Behaved Magnitudes, Colors, and Errors Even for Low Signal-to-Noise Ratio Measurements
• Cosmological Parameter Estimation Using 21 cm Radiation from the Epoch of Reionization
• Sterile Neutrino Dark Matter
• The Cosmic Linear Anisotropy Solving System (CLASS) IV: Efficient implementation of non-cold relics
• Late-time cosmology with 21cm intensity mapping experiments
• A Per-Baseline, Delay-Spectrum Technique for Accessing the 21cm Cosmic Reionization Signature
• The AGORA High-Resolution Galaxy Simulations Comparison Project
• Canadian Hydrogen Intensity Mapping Experiment (CHIME) Pathfinder
• HIRAX: A Probe of Dark Energy and Radio Transients
• The AGORA High-Resolution Galaxy Simulations Comparison Project. II: Isolated Disk Test
• Galaxy Simulation with Dust Formation and Destruction
• Weak lensing cosmology with convolutional neural networks on noisy data
• How to constrain warm dark matter with the Lyman $\alpha$ forest
• New Constraints on Warm Dark Matter from the Lyman-$\alpha$ Forest Power Spectrum
• Cosmological Reconstruction From Galaxy Light: Neural Network Based Light-Matter Connection
• The Lyman-$\alpha$ forest as a diagnostic of the nature of the dark matter
• SKAO HI Intensity Mapping: Blind Foreground Subtraction Challenge
• Distinguishing standard and modified gravity cosmologies with machine learning
• Recovery of 21 cm intensity maps with sparse component separation
• Warm dark matter signatures on the 21cm power spectrum: Intensity mapping forecasts for SKA
• Small scale aspects of warm dark matter : power spectra and acoustic oscillations
• Intensity Mapping as a Probe of Axion Dark Matter
• Determining the HI content of galaxies via intensity mapping cross-correlations
• Osaka Feedback Model: Isolated Disk Galaxy Simulations
• Polarised foreground removal at low radio frequencies using rotation measure synthesis: uncovering the signature of hydrogen reionisation
• Removing Astrophysics in 21 cm maps with Neural Networks
• Gaussian Process Regression for foreground removal in HI intensity mapping experiments
• Galaxy Formation: Warm Dark Matter, Missing Satellites, and the Angular Momentum Problem
• Probing Feedback via IGM tomography and Ly$\alpha$ forest with Subaru PFS, TMT/ELT, and JWST
• Deep learning for Sunyaev-Zel'dovich detection in Planck
• Detecting the HI Power Spectrum in the Post-Reionization Universe with SKA-Low
• The Alcock Paczynski test with 21cm intensity field
• Inferring Warm Dark Matter Masses with Deep Learning
• Reconstructing HI power spectrum with minimal parameters using the dark matter distribution beyond halos

Cited by in corpus (1)

• Differentiating Warm Dark Matter Models through 21cm Line Intensity Mapping: A Convolutional Neural Network Approach