Sensitivity toward dark matter annihilation imprints on 21-cm signal with SKA-Low: A convolutional neural network approach
arXiv:2508.08251 · doi:10.1103/23hy-p8zq
Abstract
This study investigates the sensitivity of the radio interferometers to identify imprints of spatially inhomogeneous dark matter annihilation signatures in the 21-cm signal during the pre-reionization era. We focus on the upcoming low-mode survey of the Square Kilometre Array (SKA-Low) telescope. Using CNNs, we analyze simulated 3D 21-cm differential brightness temperature maps generated via the DM21cm code, which is based on 21cmFAST and DarkHistory, to distinguish between spatially homogeneous and inhomogeneous energy injection/deposition scenarios arising from dark matter annihilation. The inhomogeneous case accounts for local dark matter density contrasts and gas properties, such as thermal and ionization states, while the homogeneous model assumes uniform energy deposition. Our study focuses on two primary annihilation channels to electron-positron pairs () and photons (), exploring dark matter masses from 1 MeV to 100 MeV and a range of annihilation cross-sections. For channel, the distinction across dark matter models is less pronounced due to the larger mean free path of the emitted photons, resulting in a more uniform energy deposition. For channel, the results indicate that the CNNs can effectively differentiate between the inhomogeneous and homogeneous cases. Despite observational challenges, the results demonstrate that these effects remain detectable even after incorporating noise from next-generation radio interferometers, such as the SKA. We find that the inhomogeneous dark matter annihilation models can leave measurable imprints on the 21-cm signal maps distinguishable from the homogeneous scenarios for the dark matter masses MeV and the annihilation cross-sections of ( for MeV) for moderate SKA-Low noise.
arXiv comment19 pages, 7 figures. Updated to match the published version
References in corpus (54)
- LOFAR: The LOw-Frequency ARray
- Dark Matter Candidates from Particle Physics and Methods of Detection
- 21-cm cosmology
- 21cmFAST: A Fast, Semi-Numerical Simulation of the High-Redshift 21-cm Signal
- A New Calculation of the Recombination Epoch
- Indirect Dark Matter Signatures in the Cosmic Dark Ages I. Generalizing the Bound on s-wave Dark Matter Annihilation from Planck
- Reionization and Cosmology with 21 cm Fluctuations
- How exactly did the Universe become neutral?
- The intergalactic magnetic field constrained by Fermi/LAT observations of the TeV blazar 1ES 0229+200
- CMB constraints on Dark Matter models with large annihilation cross-section
- How accurately can 21 cm tomography constrain cosmology?
- Wouthuysen-Field coupling strength and application to high-redshift 21 cm radiation
- Inferring the astrophysics of reionization and cosmic dawn from galaxy luminosity functions and the 21-cm signal
- HyRec: A fast and highly accurate primordial hydrogen and helium recombination code
- Improved Constraints on the 21 cm EoR Power Spectrum and the X-Ray Heating of the IGM with HERA Phase I Observations
- Opening the 21cm EoR Window: Measurements of Foreground Isolation with PAPER
- Search for Spatial Extension in High-Latitude Sources Detected by the Fermi Large Area Telescope
- HERA Phase I Limits on the Cosmic 21-cm Signal: Constraints on Astrophysics and Cosmology During the Epoch of Reionization
- The Cosmic Dawn and Epoch of Reionization with the Square Kilometre Array
- The Darkest Hour Before Dawn: Contributions to Cosmic Reionization from Dark Matter Annihilation and Decay
- Convolutional neural networks: a magic bullet for gravitational-wave detection?
- 21cmFAST v3: A Python-integrated C code forgenerating 3D realizations of the cosmic 21cm signal
- BIGHORNS - Broadband Instrument for Global HydrOgen ReioNisation Signal
- Galaxy Morphology Classification with Deep Convolutional Neural Networks
- The Impact of the First Galaxies on Cosmic Dawn and Reionization
- Bounds on Dark Matter annihilations from 21 cm data
- Deep learning from 21-cm tomography of the Cosmic Dawn and Reionization
- Calibration of the EDGES High-Band Receiver to Observe the Global 21-cm Signature from the Epoch of Reionization
- A tale of two sites -- I: Inferring the properties of minihalo-hosted galaxies from current observations
- DarkHistory: A code package for calculating modified cosmic ionization and thermal histories with dark matter and other exotic energy injections
- LOFAR, a new low frequency radio telescope
- Galaxy Morphological Classification Catalogue of the Dark Energy Survey Year 3 data with Convolutional Neural Networks
- A Space-Based Observational Strategy for Characterizing the First Stars and Galaxies Using the Redshifted 21-cm Global Spectrum
- The impact of EDGES 21-cm data on dark matter interactions
- SARAS 3 CD/EoR Radiometer: Design and Performance of the Receiver
- Detecting Gravitational-waves from Extreme Mass Ratio Inspirals using Convolutional Neural Networks
- Gluequark Dark Matter
- Some Optimizations on Detecting Gravitational Wave Using Convolutional Neural Network
- Convolutional neural networks for the detection of the early inspiral of a gravitational-wave signal
- Prospects for clustering and lensing measurements with forthcoming intensity mapping and optical surveys
- Removing Astrophysics in 21 cm maps with Neural Networks
- Improved deep learning techniques in gravitational-wave data analysis
- Convolutional Neural Networks for Direct Detection of Dark Matter
- Analyzing γ-rays of the Galactic Center with Deep Learning
- Antenna beam characterisation for the global 21cm experiment LEDA and its impact on signal model parameter reconstruction
- Particle energy cascade in the Intergalactic Medium
- Square Kilometre Array Science Data Challenge 3a: foreground removal for an EoR experiment
- Probing Ultra-light Axion Dark Matter from 21cm Tomography using Convolutional Neural Networks
- Dark Ages Radio Explorer Mission: Probing the Cosmic Dawn
- Constraints on freeze-in dark matter from Lyman- forest and 21-cm signal : single-field models
- Exploring symbolic regression and genetic algorithms for astronomical object classification
- Non-Linearity-Free prediction of the growth-rate using Convolutional Neural Networks
- Prospects for probing dark matter particles and primordial black holes with the Square Kilometre Array using the 21 cm power spectrum at cosmic dawn
- Differentiating Warm Dark Matter Models through 21cm Line Intensity Mapping: A Convolutional Neural Network Approach