Papers Radio Interferometry
“Radio Interferometry” 태그가 달린 논문 20편 · 필터 해제
Towards a robust R2D2 paradigm for radio-interferometric imaging: revisiting DNN training and architecture
The R2D2 Deep Neural Network (DNN) series was recently introduced for image formation in radio interferometry. It can be understood as a learned version of CLEAN, whose minor cycles are substituted with DNNs. We revisit …
Image ReconstructionRadio InterferometryS-R2D2: a spherical extension of the R2D2 deep neural network series paradigm for wide-field radio-interferometric imaging
Recently, the R2D2 paradigm, standing for ''Residual-to-Residual DNN series for high-Dynamic-range imaging'', was introduced for image formation in Radio Interferometry (RI) as a learned version of the traditional algori…
Radio InterferometryIRIS: A Bayesian Approach for Image Reconstruction in Radio Interferometry with expressive Score-Based priors
Inferring sky surface brightness distributions from noisy interferometric data in a principled statistical framework has been a key challenge in radio astronomy. In this work, we introduce Imaging for Radio Interferometr…
AstronomyImage ReconstructionRadio InterferometryEnergy and polarization based on-line interference mitigation in radio interferometry
Radio frequency interference (RFI) is a persistent contaminant in terrestrial radio astronomy. While new radio interferometers are becoming operational, novel sources of RFI are also emerging. In order to strengthen the …
AstronomyComputational EfficiencyRadio InterferometrySelf-supervised learning for radio-astronomy source classification: a benchmark
The upcoming Square Kilometer Array (SKA) telescope marks a significant step forward in radio astronomy, presenting new opportunities and challenges for data analysis. Traditional visual models pretrained on optical phot…
AstronomyLinear evaluationRadio InterferometrySelf-Supervised LearningUncertainty quantification for fast reconstruction methods using augmented equivariant bootstrap: Application to radio interferometry
The advent of next-generation radio interferometers like the Square Kilometer Array promises to revolutionise our radio astronomy observational capabilities. The unprecedented volume of data these devices generate requir…
AstronomyImage ReconstructionRadio InterferometryUncertainty QuantificationReinforcement Learning for Data-Driven Workflows in Radio Interferometry. I. Principal Demonstration in Calibration
Radio interferometry is an observational technique used to study astrophysical phenomena. Data gathered by an interferometer requires substantial processing before astronomers can extract the scientific information from …
Radio InterferometryCompressive radio-interferometric sensing with random beamforming as rank-one signal covariance projections
Radio-interferometry (RI) observes the sky at unprecedented angular resolutions, enabling the study of several far-away galactic objects such as galaxies and black holes. In RI, an array of antennas probes cosmic signals…
Compressive SensingImage ReconstructionRadio InterferometryLearned radio interferometric imaging for varying visibility coverage
With the next generation of interferometric telescopes, such as the Square Kilometre Array (SKA), the need for highly computationally efficient reconstruction techniques is particularly acute. The challenge in designing …
Radio InterferometryThe AIRI plug-and-play algorithm for image reconstruction in radio-interferometry: variations and robustness
Plug-and-Play (PnP) algorithms are appealing alternatives to proximal algorithms when solving inverse imaging problems. By learning a Deep Neural Network (DNN) denoiser behaving as a proximal operator, one waives the com…
AstronomyImage ReconstructionRadio InterferometryUncertainty QuantificationBayesian Imaging for Radio Interferometry with Score-Based Priors
The inverse imaging task in radio interferometry is a key limiting factor to retrieving Bayesian uncertainties in radio astronomy in a computationally effective manner. We use a score-based prior derived from optical ima…
AstronomyRadio InterferometrySurveyCLEANing Cygnus A deep and fast with R2D2
A novel deep learning paradigm for synthesis imaging by radio interferometry in astronomy was recently proposed, dubbed "Residual-to-Residual DNN series for high-Dynamic range imaging" (R2D2). In this work, we start by s…
AstronomyComputational EfficiencyRadio InterferometryUne version polyatomique de l'algorithme Frank-Wolfe pour résoudre le problème LASSO en grandes dimensions
Nous nous int\'eressons \`a la reconstruction parcimonieuse d'images \`a l'aide du probl\`eme d'optimisation r\'egularis\'e LASSO. Dans de nombreuses applications pratiques, les grandes dimensions des objets \`a reconstr…
AstronomyRadio InterferometryImage reconstruction algorithms in radio interferometry: from handcrafted to learned regularization denoisers
We introduce a new class of iterative image reconstruction algorithms for radio interferometry, at the interface of convex optimization and deep learning, inspired by plug-and-play methods. The approach consists in learn…
DenoisingImage ReconstructionRadio InterferometryVLBInet: Radio Interferometry Data Classification for EHT with Neural Networks
The Event Horizon Telescope (EHT) recently released the first horizon-scale images of the black hole in M87. Combined with other astronomical data, these images constrain the mass and spin of the hole as well as the accr…
ClassificationImage ReconstructionRadio InterferometryStatistical Performance of Radio Interferometric Calibration
Calibration is an essential step in radio interferometric data processing that corrects the data for systematic errors and in addition, subtracts bright foreground interference to reveal weak signals hidden in the residu…
Radio InterferometryDeepSource: Point Source Detection using Deep Learning
Point source detection at low signal-to-noise is challenging for astronomical surveys, particularly in radio interferometry images where the noise is correlated. Machine learning is a promising solution, allowing the dev…
Deep LearningRadio InterferometryReconstructing Video from Interferometric Measurements of Time-Varying Sources
Very long baseline interferometry (VLBI) makes it possible to recover images of astronomical sources with extremely high angular resolution. Most recently, the Event Horizon Telescope (EHT) has extended VLBI to short mil…
Image ImputationRadio InterferometryMulti-frequency image reconstruction for radio-interferometry with self-tuned regularization parameters
As the world's largest radio telescope, the Square Kilometer Array (SKA) will provide radio interferometric data with unprecedented detail. Image reconstruction algorithms for radio interferometry are challenged to scale…
Image ReconstructionRadio InterferometryA sparse Kaczmarz solver and a linearized Bregman method for online compressed sensing
An algorithmic framework to compute sparse or minimal-TV solutions of linear systems is proposed. The framework includes both the Kaczmarz method and the linearized Bregman method as special cases and also several new me…
compressed sensingRadio Interferometry