Research output: Contribution to journal › Article › peer-review
Prospects for future studies using deep imaging: analysis of individual Galactic cirrus filaments. / Smirnov, Anton A.; Savchenko, Sergey; Poliakov, Denis M.; Marchuk, Alexander A.; Il'in, Vladimir B.; Román, Javier; Seguine, Jonah; Гончаров, Георгий; Мосенков, Александр Владимирович.
In: Monthly Notices of the Royal Astronomical Society, Vol. 519, No. 3, 01.03.2023, p. 4735-4752.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Prospects for future studies using deep imaging: analysis of individual Galactic cirrus filaments
AU - Smirnov, Anton A.
AU - Savchenko, Sergey
AU - Poliakov, Denis M.
AU - Marchuk, Alexander A.
AU - Il'in, Vladimir B.
AU - Román, Javier
AU - Seguine, Jonah
AU - Гончаров, Георгий
AU - Мосенков, Александр Владимирович
PY - 2023/3/1
Y1 - 2023/3/1
N2 - The presence of Galactic cirrus is an obstacle for studying both faint objects in our Galaxy and low surface brightness extragalactic structures. With the aim of studying individual cirrus filaments in Sloan Digital Sky Survey (SDSS) Stripe 82 data, we develop techniques based on machine learning and neural networks that allow one to isolate filaments from foreground and background sources in the entirety of Stripe 82 with a precision similar to that of the human expert. Our photometric study of individual filaments indicates that only those brighter than 26 mag arcsec-2 in the SDSS r band are likely to be identified in SDSS Stripe 82 data by their distinctive colours in the optical bands. We also show a significant impact of data processing (e.g. flat-fielding, masking of bright stars, and sky subtraction) on colour estimation. Analysing the distribution of filaments' colours with the help of mock simulations, we conclude that most filaments have colours in the following ranges: 0.55 ≤g - r ≤ 0.73 and 0.01 ≤ r - i ≤ 0.33. Our work provides a useful framework for an analysis of all types of low surface brightness features (cirri, tidal tails, stellar streams, etc.) in existing and future deep optical surveys. For practical purposes, we provide the catalogue of dust filaments.
AB - The presence of Galactic cirrus is an obstacle for studying both faint objects in our Galaxy and low surface brightness extragalactic structures. With the aim of studying individual cirrus filaments in Sloan Digital Sky Survey (SDSS) Stripe 82 data, we develop techniques based on machine learning and neural networks that allow one to isolate filaments from foreground and background sources in the entirety of Stripe 82 with a precision similar to that of the human expert. Our photometric study of individual filaments indicates that only those brighter than 26 mag arcsec-2 in the SDSS r band are likely to be identified in SDSS Stripe 82 data by their distinctive colours in the optical bands. We also show a significant impact of data processing (e.g. flat-fielding, masking of bright stars, and sky subtraction) on colour estimation. Analysing the distribution of filaments' colours with the help of mock simulations, we conclude that most filaments have colours in the following ranges: 0.55 ≤g - r ≤ 0.73 and 0.01 ≤ r - i ≤ 0.33. Our work provides a useful framework for an analysis of all types of low surface brightness features (cirri, tidal tails, stellar streams, etc.) in existing and future deep optical surveys. For practical purposes, we provide the catalogue of dust filaments.
KW - ISM: clouds
KW - dust
KW - extinction
KW - Astrophysics - Astrophysics of Galaxies
UR - https://www.mendeley.com/catalogue/8c112075-d27f-3f44-973a-c2d9a157bb5d/
U2 - 10.1093/mnras/stac3765
DO - 10.1093/mnras/stac3765
M3 - Article
VL - 519
SP - 4735
EP - 4752
JO - Monthly Notices of the Royal Astronomical Society
JF - Monthly Notices of the Royal Astronomical Society
SN - 0035-8711
IS - 3
ER -
ID: 105342718