相关论文: Deep Learning 21cm Lightcones in 3D

Global 21cm cosmology aims to investigate the cosmic dawn and epoch of reionisation by measuring the sky averaged HI absorption signal, which requires, accurate modelling of, or correction for, the bright radio foregrounds and distortions…

Upcoming experiments will map the spatial distribution of the 21-cm signal over three-dimensional volumes of space during the Epoch of Reionization (EoR). Several methods have been proposed to mitigate the issue of astrophysical foreground…

The paper analyzes the absorption line profile at 21 cm for the hydrogen atom in the interstellar medium. The hydrogen atom is treated as a three-level system illuminated by a powerful light source at neighboring resonances corresponding to…

Modern machine learning will allow for simulation-based inference from reionization-era 21cm observations at the Square Kilometre Array. Our framework combines a convolutional summary network and a conditional invertible network through a…

Line-intensity mapping of the 21cm line is a powerful probe of large scale structure at z<6, tracing large-scale structure via neutral hydrogen content that is found within galaxies. In principle, it enables cost-efficient surveys of the…

In a previous paper we presented the results of applying machine learning to classify whether an HI 21-cm absorption spectrum arises in a source intervening the sight-line to a more distant radio source or within the host of the radio…

Motivated by the desire for wide-field images with well-defined statistical properties for 21cm cosmology, we implement an optimal mapping pipeline that computes a maximum likelihood estimator for the sky using the interferometric…

The properties of the first galaxies, expected to drive the Cosmic Dawn (CD) and the Epoch of Reionization (EoR), are encoded in the 3D structure of the cosmic 21-cm signal. Parameter inference from upcoming 21-cm observations promises to…

Lightcone observations are the natural data format of galaxy surveys, but their evolving geometry breaks the translational symmetry assumed by standard convolutional neural networks (CNNs). In particular, applying CNNs to 3D gridded…

We investigate conditional diffusion modeling for three-dimensional 21 cm lightcone emulation, focusing on cubes with a sky-plane size of $64\times64$ and a line-of-sight depth up to 1024 cells. Relative to earlier 2D studies, the 3D…

The 21-cm signal is the most important measurement for us to understand physics during cosmic dawn. It is the key for us to understand the expansion history of the Universe and the nature of dark energy. In this paper, we focused on the…

In this paper, we propose a novel method to recover the 21cm global signal from the 21cm power spectrum using artificial neural networks (ANNs). The 21cm global signal is crucial for understanding cosmic evolution from the Dark Ages through…

The hydrogen 21-cm signal is predicted to be the richest probe of the young Universe including eras known as the cosmic Dark Ages, the Cosmic Dawn when the first star and black hole formed, and the Epoch of Reionization. This signal holds…

The 21 cm signal appears to be a treasure trove to provide an insight into the period when the first generation of luminous objects formed in the Universe. Hydrogen is the predominating fraction of the total baryonic matter during cosmic…

Machine learning has been widely applied to clearly defined problems of astronomy and astrophysics. However, deep learning and its conceptual differences to classical machine learning have been largely overlooked in these fields. The broad…

We propose a lightweight deep convolutional neural network (lCNN) to estimate cosmological parameters from simulated three-dimensional dark matter (DM) halo distributions and associated statistics. The training dataset comprises 2000…

The 21-cm signal of neutral hydrogen - emitted during the Epoch of Reionization - promises to be an important source of information for the study of the infant universe. However, its detection is impossible without sufficient mitigation of…

Using the latest upper limits on the 21-cm power spectrum at $z\approx9.1$ from the Low Frequency Array (LOFAR), we explore regions of parameter space which are inconsistent with the data. We use 21CMMC, a Monte Carlo Markov Chain sampler…

We study the behavior of internal signal chain reflections and antenna cross coupling as systematics for 21 cm cosmological surveys. We outline the mathematics for how these systematics appear in interferometric visibilities and describe…

We propose a deep learning analyzing technique with convolutional neural network (CNN) to predict the evolutionary track of the Epoch of Reionization (EoR) from the 21-cm differential brightness temperature tomography images. We use…