AlgoSCR: an algorithm for solar contamination removal from radio interferometric data
ABSTRACT Hydrogen intensity mapping is a new field in astronomy that promises to make three-dimensional maps of the matter distribution of the Universe using the redshifted $21\, \textrm {cm}$ line of neutral hydrogen gas (HI). Several ongoing and upcoming radio interferometers, such as Tianlai, CHI...
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| Published in | Monthly notices of the Royal Astronomical Society Vol. 512; no. 3; pp. 3520 - 3537 |
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| Main Authors | , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford University Press
04.04.2022
Oxford University Press (OUP): Policy P - Oxford Open Option A |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0035-8711 1365-2966 |
| DOI | 10.1093/mnras/stac618 |
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| Summary: | ABSTRACT
Hydrogen intensity mapping is a new field in astronomy that promises to make three-dimensional maps of the matter distribution of the Universe using the redshifted $21\, \textrm {cm}$ line of neutral hydrogen gas (HI). Several ongoing and upcoming radio interferometers, such as Tianlai, CHIME, HERA, HIRAX, etc., are using this technique. These instruments are designed to map large swaths of the sky by drift scanning over periods of many months. One of the challenges of the observations is that the daytime data are contaminated by strong radio signals from the Sun. In the case of Tianlai, this results in almost half of the measured data being unusable. We try to address this issue by developing an algorithm for solar contamination removal (AlgoSCR) from the radio data. The algorithm is based on an eigenvalue analysis of the visibility matrix and hence is applicable only to interferometers. We apply AlgoSCR to simulated visibilities, as well as real daytime data from the Tianlai dish array. The algorithm can reduce strong solar contamination by about 95 per cent without seriously affecting other weaker sky signals and thus makes the data usable for certain applications. |
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| ISSN: | 0035-8711 1365-2966 |
| DOI: | 10.1093/mnras/stac618 |