LOFAR Sparse Image Reconstruction

Abstract

Context. The LOw Frequency ARray (LOFAR) radio telescope is a giant digital phased array interferometer with multiple antennas distributed in Europe. It provides discrete sets of Fourier components of the sky brightness. Recovering the original brightness distribution with aperture synthesis forms an inverse problem that can be solved by various deconvolution and minimization methods Aims. Recent papers have established a clear link between the discrete nature of radio interferometry measurement and the "compressed sensing" (CS) theory, which supports sparse reconstruction methods to form an image from the measured visibilities. Empowered by proximal theory, CS offers a sound framework for efficient global minimization and sparse data representation using fast algorithms. Combined with instrumental direction-dependent effects (DDE) in the scope of a real instrument, we developed and validated a new method based on this framework Methods. We implemented a sparse reconstruction method in the standard LOFAR imaging tool and compared the photometric and resolution performance of this new imager with that of CLEAN-based methods (CLEAN and MS-CLEAN) with simulated and real LOFAR data Results. We show that i) sparse reconstruction performs as well as CLEAN in recovering the flux of point sources; ii) performs much better on extended objects (the root mean square error is reduced by a factor of up to 10); and iii) provides a solution with an effective angular resolution 2-3 times better than the CLEAN images. Conclusions. Sparse recovery gives a correct photometry on high dynamic and wide-field images and improved realistic structures of extended sources (of simulated and real LOFAR datasets). This sparse reconstruction method is compatible with modern interferometric imagers that handle DDE corrections (A- and W-projections) required for current and future instruments such as LOFAR and SKA

Published in A&A, 19 pages, 9 figures

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• Cygnus A super-resolved via convex optimisation from VLA data
• Non-convex optimization for self-calibration of direction-dependent effects in radio interferometric imaging
• Sparse representations and convex optimization as tools for LOFAR radio interferometric imaging
• An improved method for polarimetric image restoration in interferometry
• Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA): I. Algorithm and simulations
• LOFAR 150-MHz observations of SS 433 and W 50
• Wideband Super-resolution Imaging in Radio Interferometry via Low Rankness and Joint Average Sparsity Models (HyperSARA)
• Photometric Properties of Ceres from Telescopic Observations using Dawn Framing Camera Color Filters
• Sparse interferometric Stokes imaging under polarization constraint (Polarized SARA)
• NOIRE Study Report: Towards a Low Frequency Radio Interferometer in Space
• InfraRed Astronomy Satellite Swarm Interferometry (IRASSI): Overview and Study Results
• Sparse Lens Inversion Technique (SLIT): lens and source separability from linear inversion of the source reconstruction problem
• Solar hard X-ray imaging by means of Compressed Sensing and Finite Isotropic Wavelet Transform
• A Fourier dimensionality reduction model for big data interferometric imaging
• Polca SARA - Full polarization, direction-dependent calibration and sparse imaging for radio interferometry
• Multi-scale and Multi-directional VLBI Imaging with CLEAN
• 21cm Signal Recovery via the Robust Principle Component Analysis
• Space variant deconvolution of galaxy survey images
• Deep Learning-based galaxy image deconvolution
• Cygnus A jointly calibrated and imaged via non-convex optimisation from VLA data
• Scalable precision wide-field imaging in radio interferometry: I. uSARA validated on ASKAP data
• Dynamic and polarimetric VLBI imaging with a multiscalar approach
• The w-effect in interferometric imaging: from a fast sparse measurement operator to super-resolution
• High resolution VLBI polarisation imaging of AGN with the Maximum Entropy Method
• A parallel & automatically tuned algorithm for multispectral image deconvolution
• Wide-band Rotation Measure Synthesis
• Multi-frequency image reconstruction for radio interferometry. A regularized inverse problem approach
• Deep learning-based deconvolution for interferometric radio transient reconstruction
• PolyCLEAN: Atomic Optimization for Super-Resolution Imaging and Uncertainty Estimation in Radio Interferometry
• Parallel Calibration for Sensor Array Radio Interferometers
• A novel radio imaging method for physical spectral index modelling
• Simulating images of radio galaxies with diffusion models
• Multi-Step Reconstruction of Radio-Interferometric Images
• Distributed and parallel sparse convex optimization for radio interferometry with PURIFY
• A Decentralized Framework for Radio-interferometric Image Reconstruction
• Accelerating the CLEAN algorithm of radio interferometry with convex optimization
• Multi-frequency image reconstruction for radio-interferometry with self-tuned regularization parameters
• An Unsupervised Learning Method for Radio Interferometry Deconvolution
• ShapeNet: Shape Constraint for Galaxy Image Deconvolution
• DoG-HiT: A novel VLBI Multiscale Imaging Approach
• High-Performance Gridding For Radio Interferometric Image Synthesis