A Generic and Efficient E-field Parallel Imaging Correlator for Next-Generation Radio Telescopes
Nithyanandan Thyagarajan, Adam P. Beardsley, Judd D. Bowman, Miguel F., Morales

TL;DR
The paper introduces EPIC, a software correlator that significantly reduces computational costs for dense radio telescope arrays by implementing a generalized direct imaging algorithm, enabling efficient imaging of irregular and heterogeneous antenna layouts.
Contribution
It presents EPIC, a modular, parallelizable software implementation of the MOFF imaging algorithm, achieving lower complexity and supporting irregular and heterogeneous antenna arrays.
Findings
EPIC reduces computational complexity to O(N_A log N_A).
Images from EPIC match traditional methods within gridding precision.
EPIC is validated on LWA1 data and applicable to next-generation telescopes.
Abstract
Modern radio telescopes are favouring densely packed array layouts with large numbers of antennas (). Since the complexity of traditional correlators scales as , there will be a steep cost for realizing the full imaging potential of these powerful instruments. Through our generic and efficient E-field Parallel Imaging Correlator (EPIC), we present the first software demonstration of a generalized direct imaging algorithm, namely, the Modular Optimal Frequency Fourier (MOFF) imager. Not only does it bring down the cost for dense layouts to but can also image from irregular layouts and heterogeneous arrays of antennas. EPIC is highly modular, parallelizable, implemented in object-oriented Python, and publicly available. We have verified the images produced to be equivalent to those from…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
