The Bulletin of The Korean Astronomical Society (천문학회보)
- Volume 43 Issue 1
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- Pages.41.1-41.1
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- 2018
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- 1226-2692(pISSN)
Current status and future plans of KMTNet microlensing experiments
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Chung, Sun-Ju
(Korea Astronomy and Space Science Institute) ;
- Gould, Andrew (Korea Astronomy and Space Science Institute) ;
- Jung, Youn Kil (Korea Astronomy and Space Science Institute) ;
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Hwang, Kyu-Ha
(Korea Astronomy and Space Science Institute) ;
- Ryu, Yoon-Hyun (Korea Astronomy and Space Science Institute) ;
- Shin, In-Gu (Harvard-Smithsonian Center for Astrophysics) ;
- Yee, Jennifer C. (Harvard-Smithsonian Center for Astrophysics) ;
- Zhu, Wei (Canadian Institute for Theoretical Astrophysics, University of Toronto) ;
- Han, Cheongho ;
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Cha, Sang-Mok
(Korea Astronomy and Space Science Institute) ;
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Kim, Dong-Jin
(Korea Astronomy and Space Science Institute) ;
- Kim, Hyun-Woo (Korea Astronomy and Space Science Institute) ;
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Kim, Seung-Lee
(Korea Astronomy and Space Science Institute) ;
- Lee, Chung-Uk (Korea Astronomy and Space Science Institute) ;
- Lee, Yongseok (Korea Astronomy and Space Science Institute)
- Published : 2018.05.08
Abstract
We introduce a current status and future plans of Korea Microlensing Telescope Network (KMTNet) microlensing experiments, which include an observational strategy, pipeline, event-finder, and collaborations with Spitzer. The KMTNet experiments were initiated in 2015. From 2016, KMTNet observes 27 fields including 6 main fields and 21 subfields. In 2017, we have finished the DIA photometry for all 2016 and 2017 data. Thus, it is possible to do a real-time DIA photometry from 2018. The DIA photometric data is used for finding events from the KMTNet event-finder. The KMTNet event-finder has been improved relative to the previous version, which already found 857 events in 4 main fields of 2015. We have applied the improved version to all 2016 data. As a result, we find that 2597 events are found, and out of them, 265 are found in KMTNet-K2C9 overlapping fields. For increasing the detection efficiency of event-finder, we are working on filtering false events out by machine-learning method. In 2018, we plan to measure event detection efficiency of KMTNet by injecting fake events into the pipeline near the image level. Thanks to high-cadence observations, KMTNet found fruitful interesting events including exoplanets and brown dwarfs, which were not found by other groups. Masses of such exoplanets and brown dwarfs are measured from collaborations with Spitzer and other groups. Especially, KMTNet has been closely cooperating with Spitzer from 2015. Thus, KMTNet observes Spitzer fields. As a result, we could measure the microlens parallaxes for many events. Also, the automated KMTNet PySIS pipeline was developed before the 2017 Spitzer season and it played a very important role in selecting the Spitzer target. For the 2018 Spitzer season, we will improve the PySIS pipeline to obtain better photometric results.
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