SIMBAD references

2025MNRAS.543.1092B - Mon. Not. R. Astron. Soc., 543, 1092-1119 (2025/October-3)

Square Kilometre Array Science Data Challenge 3a: foreground removal for an EoR experiment.

BONALDI A., HARTLEY P., BRAUN R., PURSER S., ACHARYA A., AHN K., APARICIO RESCO M., BAIT O., BIANCO M., CHAKRABORTY A., CHAPMAN E., CHATTERJEE S., CHEGE K., CHEN H., CHEN X., CHEN Z., CONABOY L., CRUZ M., DARRIBA L., DE SANTIS M., DENZEL P., DIAO K., FERON J., FINLAY C., GEHLOT B., GHOSH S., GIRI S.K., GRUMITT R., HONG S.E., ITO T., JIANG M., JORDAN C., KIM S., KIM M., KIM J., KRISHNA S.P., KULKARNI A., LOPEZ-CANIEGO M., LABADIE-GARCIA I., LEE H., LEE D., LEE N., LINE J., LIU Y., MAO Y., MAZUMDER A., MERTENS F.G., MUNSHI S., NASIRUDIN A., NI S., NISTANE V., NORREGAARD C., NULL D., OFFRINGA A., OH M., OH S.-H., PARKINSON D., PRITCHARD J., RUIZ-GRANDA M., SALVADOR LOPEZ V., SHAN H., SHARMA R., TROTT C., YOSHIURA S., ZHANG L., ZHANG X., ZHENG Q., ZHU Z., ZUO S., AKAHORI T., ALBERTO P., ALLYS E., AN T., ANSTEY D., BAEK J., BASAVRAJ, BRACKENHOFF S., BROWNE P., CECCOTTI E., CHEN H., CHEN T., CHOUDHURI S., CHOUDHURY M., COLES J., COOK J., CORNU D., CUNNINGTON S., DAS S., DE LERA ACEDO ACEDO E., DELOUIS J.-M., DENG F., DING J., ELAHI K.M.A., FERNANDEZ P., FERNANDEZ C., FERNANDEZ ALCAZAR A., GALLUZZI V., GAO L.-Y., GARAIN U., GARRIDO J., GENDRON-MARSOLAIS M.-L., GESSEY-JONES T., GHORBEL H., GONG Y., GUO S., HASEGAWA K., HAYASHI T., HERRANZ D., HOLANDA V., HOLLOWAY A.J., HOTHI I., HOFER C., JELIC V., JIANG Y., JIANG X., KANG H., KIM J.-Y., KOOPMANS L.V., LACROIX R., LEE E., LEENEY S., LEVRIER F., LI Y., LIU Y., MA Q., MERIOT R., MESINGER A., MEVIUS M., MINODA T., MIVILLE-DESCHENES M.-A., MOLDON J., MONDAL R., MURMU C., MURRAY S., NIRMALA SR, NIU Q., NUNHOKEE C., O'HARA O., PAL S.K., PAL S., PARK J., PARRA M., PATRA N.N., PINDOR B., REMAZEILLES M., REY P., RUBINO-MARTIN J.A., SAHA S., SELVARAJ A., SEMELIN B., SHAH R., SHAO Y., SHAW A.K., SHI F., SHIMABUKURO H., SINGH G., SOHN B.W., STAGNI M., STARCK J.-L., SUI C., SWINBANK J.D., SANCHEZ J., SANCHEZ-EXPOSITO S., TAKAHASHI K., TAKEUCHI T., TRIPATHI A., VERDES-MONTENEGRO L., VIELVA P., VITELLO F.R., WANG G.-J., WANG Q., WANG X., WANG Y., WANG Y.-X., WIEGERT T., WILD A., WILLIAMS W.L., WOLZ L., WU X., WU P., XIA J.-Q., XU Y., YAN R., YAN Y.-P., YIN Z., YOU Z., YU X., YU K., YUE B., ZHANG L., ZHAO Z., ZHAO X. and ZHOU X.

Abstract (from CDS):

We present and analyse the results of the Science Data Challenge 3a (SDC3a, https://sdc3.skao.int/challenges/foregrounds), an epoch of reionization (EoR) foreground-removal exercise organized by the Square Kilometre Array Observatory (SKAO) on SKA simulated data. The challenge ran for 8 months, from 2023 March to October. Participants were provided with realistic simulations of SKA-Low data between 106 and 196 MHz, including foreground contamination from extragalactic and Galactic emission, instrumental, and systematic effects. They were asked to deliver cylindrical power spectra of the EoR signal, cleaned from all corruptions, and the corresponding confidence levels. Here, we describe the approaches taken by the 17 teams that completed the challenge, and we assess their performance using different metrics. The challenge results provide a positive outlook on the capabilities of current foreground-mitigation approaches to recover the faint EoR signal from SKA-Low observations. The median error committed in the EoR power spectrum recovery is below the true signal for seven teams, although in some cases, there are some significant outliers. The smallest residual overall is $4.2_{-4.2}^{+20} \times 10^{-4}\, \rm {K}^2h^{-3}$ cMpc $^{3}$ across all considered scales and frequencies. The estimation of confidence levels provided by the teams is overall less accurate, with the true error being typically underestimated, sometimes very significantly. The most accurate error bars account for $60 \pm 20$ per cent of the true errors committed. The challenge results provide a means for all teams to understand and improve their performance. This challenge indicates that the comparison between independent pipelines could be a powerful tool to assess residual biases and improve error estimation.

Abstract Copyright: © The Author(s) 2025. Published by Oxford University Press on behalf of Royal Astronomical Society.

Journal keyword(s): instrumentation: interferometers - methods: data analysis - dark ages, reionization, first stars

Simbad objects: 6

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