Application of Regularization Methods in the Sky Map Reconstruction of the Tianlai Cylinder Pathfinder Array

The Tianlai cylinder pathfinder is a radio interferometer array to test 21 cm intensity mapping techniques in the post-reionization era.It works in passive drift scan mode to survey the sky visible in the northern hemisphere.To deal with the large instantaneous field of view and the spherical sky,we decompose the drift scan data into m-modes,which are linearly related to the sky intensity.The sky map is reconstructed by solving the linear interferometer equations.Due to incomplete uv coverage of the interferometer baselines,this inverse problem is usually ill-posed,and regularization method is needed for its solution.In this paper,we use simulation to investigate two frequently used regularization methods,the Truncated Singular Value Decomposition(TSVD),and the Tikhonov regularization techniques.Choosing the regularization parameter is very important for its application.We employ the generalized cross validation method and the L-curve method to determine the optimal value.We compare the resulting maps obtained with the different regularization methods,and for the different parameters derived using the different criteria.While both methods can yield good maps for a range of regularization parameters,in the Tikhonov method the suppression of noisy modes are more gradually applied,produce more smooth maps which avoids some visual artefacts in the maps generated with the TSVD method.

Detecting HI Galaxies with Deep Neural Networks in the Presence of Radio Frequency Interference

In the neutral hydrogen(H I)galaxy survey,a significant challenge is to identify and extract the H I galaxy signal from the observational data contaminated by radio frequency interference(RFI).For a drift-scan survey,or more generally a survey of a spatially continuous region,in the time-ordered spectral data,the H I galaxies and RFI all appear as regions that extend an area in the time-frequency waterfall plot,so the extraction of the H I galaxies and RFI from such data can be regarded as an image segmentation problem,and machine-learning methods can be applied to solve such problems.In this study,we develop a method to effectively detect and extract signals of H I galaxies based on a Mask R-CNN network combined with the PointRend method.By simulating FAST-observed galaxy signals and potential RFI impact,we created a realistic data set for the training and testing of our neural network.We compared five different architectures and selected the best-performing one.This architecture successfully performs instance segmentation of H I galaxy signals in the RFI-contaminated time-ordered data,achieving a precision of 98.64%and a recall of 93.59%.

A Simulation of Calibration and Map-making Errors of the Tianlai Cylinder Pathfinder Array

The Tianlai cylinder array is a pathfinder for developing and testing 21 cm intensity mapping techniques.In this paper,we use numerical simulation to assess how its measurement is affected by thermal noise and the errors in calibration and map-making process,and the error in the sky map reconstructed from a drift scan survey.Here we consider only the single frequency,unpolarized case.The beam is modeled by fitting to the electromagnetic simulation of the antenna,and the variations of the complex gains of the array elements are modeled by Gaussian processes.Mock visibility data are generated and run through our data processing pipeline.We find that the accuracy of the current calibration is limited primarily by the absolute calibration,where the error comes mainly from the approximation of a single dominating point source.We then studied the m-mode map-making with the help of Moore-Penrose inverse.We find that discarding modes with singular values smaller than a threshold could generate visible artifacts in the map.The impacts of the residue variation of the complex gain and thermal noise are also investigated.The thermal noise in the map varies with latitude,being minimum at the latitude passing through the zenith of the telescope.The angular power spectrum of the reconstructed map show that the current Tianlai cylinder pathfinder,which has a shorter maximum baseline length in the North-South direction,can measure modes up to l■2πb_(NS)/λ~200 very well,but would lose a significant fraction of higher angular modes when noise is present.These results help us to identify the main limiting factors in our current array configuration and data analysis procedure,and suggest that the performance can be improved by reconfiguration of the array feed positions.

Map Reconstruction of Radio Observations with Conditional Invertible Neural Networks

In radio astronomy,the challenge of reconstructing a sky map from time ordered data is known as an inverse problem.Standard map-making techniques and gridding algorithms are commonly employed to address this problem,each offering its own benefits such as producing minimum-variance maps.However,these approaches also carry limitations such as computational inefficiency and numerical instability in map-making and the inability to remove beam effects in grid-based methods.To overcome these challenges,this study proposes a novel solution through the use of the conditional invertible neural network(cINN)for efficient sky map reconstruction.With the aid of forward modeling,where the simulated time-ordered data(TODs)are generated from a given sky model with a specific observation,the trained neural network can produce accurate reconstructed sky maps.Using the Five-hundred-meter Aperture Spherical radio Telescope as an example,cINN demonstrates remarkable performance in map reconstruction from simulated TODs,achieving a mean squared error of2.29±2.14×10^(-4)K^(2),a structural similarity index of 0.968±0.002,and a peak signal-to-noise ratio of26.13±5.22 at the 1σlevel.Furthermore,by sampling in the latent space of cINN,the reconstruction errors for each pixel can be accurately quantified.

The Tianlai Cylinder Pathfinder array: System functions and basic performance analysis

The Tianlai Cylinder Pathfinder is a radio interferometer array designed to test techniques for 21 cm intensity mapping in the post-reionization Universe,with the ultimate aim of mapping the large scale structure and measuring cosmological parameters such as the dark energy equation of state.Each of its three parallel cylinder reflectors is oriented in the north-south direction,and the array has a large field of view.As the Earth rotates,the northern sky is observed by drift scanning.The array is located in Hongliuxia,a radio-quiet site in Xinjiang,and saw its first light in September 2016.In this first data analysis paper for the Tianlai cylinder array,we discuss the sub-system qualification tests,and present basic system performance obtained from preliminary analysis of the commissioning observations during 2016-2018.We show typical interferometric visibility data,from which we derive the actual beam profile in the east-west direction and the frequency band-pass response.We describe also the calibration process to determine the complex gains for the array elements,either using bright astronomical point sources,or an artificial on site calibrator source,and discuss the instrument response stability,crucial for transit interferometry.Based on this analysis,we find a system temperature of about 90 K,and we also estimate the sensitivity of the array.