The lofar two-meter sky survey: Deep fields data release 1: II. The elais-n1 lofar deep field

J. Sabater, P. N. Best, C. Tasse, M. J. Hardcastle, T. W. Shimwell, D. Nisbet, V. Jelic, J. R. Callingham, H. J.A. Röttgering, M. Bonato, M. Bondi, B. Ciardi, R. K. Cochrane, M. J. Jarvis, R. Kondapally, L. V.E. Koopmans, S. P. O'Sullivan, I. Prandoni, D. J. Schwarz, D. J.B. SmithL. Wang, W. L. Williams, S. Zaroubi

Research output: Contribution to journalArticlepeer-review


The LOFAR Two-metre Sky Survey (LoTSS) will cover the full northern sky and, additionally, aims to observe the LoTSS deep fields to a noise level of ? 10 μJy beam-1 over several tens of square degrees in areas that have the most extensive ancillary data. This paper presents the ELAIS-N1 deep field, the deepest of the LoTSS deep fields to date. With an effective observing time of 163.7 h, it reaches a root mean square noise level of ? 20 μJy beam-1 in the central region (and below 30 μJy beam-1 over 10 square degrees). The resolution is ~6 arcsecs and 84 862 radio sources were detected in the full area (68 square degrees) with 74 127 sources in the highest quality area at less than 3 degrees from the pointing centre. The observation reaches a sky density of more than 5000 sources per square degree in the central region (~5 square degrees). We present the calibration procedure, which addresses the special configuration of some observations and the extended bandwidth covered (115-177 MHz; central frequency 146.2 MHz) compared to standard LoTSS. We also describe the methods used to calibrate the flux density scale using cross-matching with sources detected by other radio surveys in the literature. We find the flux density uncertainty related to the flux density scale to be ~6.5 per cent. By studying the variations of the flux density measurements between different epochs, we show that relative flux density calibration is reliable out to about a 3 degree radius, but that additional flux density uncertainty is present for all sources at about the 3 per cent level; this is likely to be associated with residual calibration errors, and is shown to be more significant in datasets with poorer ionosphere conditions. We also provide intra-band spectral indices, which can be useful to detect sources with unusual spectral properties. The final uncertainty in the flux densities is estimated to be ~10 per cent for ELAIS-N1.

Original languageEnglish
Article numberA2
JournalAstronomy and Astrophysics
StatePublished - 1 Apr 2021
Externally publishedYes

Bibliographical note

Funding Information:
who played a critical role in the inception of the project. We acknowledge the useful comments of the anonymous referee. We acknowledge the joint SKA and AWS Astrocompute proposal call that was used to fund all the tests and calibration in the AWS infrastructure with the projects ‘Calibration of LOFAR ELAIS-N1 data in the Amazon cloud’ and ‘Amazon Cloud Processing of LOFAR Tier-1 surveys: opening up a new window on the Universe’. Cycle 0 and 2 data are available in the Registry of Open Data on AWS in: This paper is based on data obtained with the International LOFAR Telescope (ILT) under project codes LC0_019, LC2_024 and LC4_008. LOFAR (van Haarlem et al. 2013) is the LOw Frequency ARray designed and constructed by ASTRON. It has observing, data processing, and data storage facilities in several countries, which are owned by various parties (each with their own funding sources) and are collectively operated by the ILT foundation under a joint scientific policy. The ILT resources have benefited from the following recent major funding sources: CNRS-INSU, Observatoire de Paris and Université d’Orléans, France; BMBF, MIWF-NRW, MPG, Germany; Science Foundation Ireland (SFI), Department of Business, Enterprise and Innovation (DBEI), Ireland; NWO, The Netherlands; The Science and Technology Facilities Council, UK. This work was carried out in part on the Dutch national e-infrastructure with the support of SURF Cooperative through e-infra grants 160022 & 160152. JS, PNB, RKC, and RK are grateful for support from the UK Science and Technology Facilities Council (STFC) via grant ST/M001229/1 and ST/R000972/1. MJH acknowledges support from the UK Science and Technology Facilities Council (ST/R000905/1) VJ acknowledges support by the Croatian Science Foundation for the project IP-2018-01-2889 (LowFreqCRO). HR acknowledges support from the ERC Advanced Investigator programme NewClusters 321271. MB acknowledges support from INAF under PRIN SKA/CTA FORECaST and from the Ministero degli Affari Esteri della Cooperazione Internazionale - Direzione Generale per la Promozione del Sistema Paese Progetto di Grande Rilevanza ZA18GR02. MJJ acknowledges support from the UK Science and Technology Facilities Council [ST/N000919/1] and the Oxford Hintze Centre for Astrophysical Surveys which is funded through generous support from the Hintze Family Charitable Foundation. RK acknowledges support from the Science and Technology Facilities Council (STFC) through an STFC studentship via grant ST/R504737/1. IP acknowledges support from INAF under the SKA/CTA PRIN ‘FORECaST’ and the PRIN MAIN STREAM ‘SAuROS’ projects. This research made use of ASTROPY, a community-developed core Python package for Astronomy (Astropy Collaboration, 2013, 2018); IPYTHON (Pérez & Granger 2007); MATPLOTLIB (Hunter 2007); NUMPY (Walt et al. 2011); PANDAS (McKinney 2010); SCIPY (Jones et al. 2001), TOPCAT (Taylor 2005), and KERN suite (Molenaar & Smirnov 2018).

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© ESO 2021.


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