Table 1
Performance of AutoPhOT computing r-band light curves from Fig. 17.
| Transient | Images | Time taken (h) |  |
Mean residual (mag) | Mean error residual (mag) |
|---|---|---|---|---|---|
| AT 2018COW (HOTPANTS) | 37 | 0.5 | 45 | 0.002 | 0.003 |
| AT 2018COW (PYZOGY) | 37 | 0.5 | 46 | 0.005 | 0.005 |
| SN 2018coi | 259 | 4.69 | 65 | 0.007 | 0.021 |
| SN 2016iae | 25 | 0.53 | 34 | 0.011 | 0.040 |
Notes. Photometry for AT 2018cow was performed using template subtraction and aperture photometry (similar to the Perley et al. 2018, although a custom host subtraction pipeline was used in this case.), whereas SN 2016coi (Prentice et al. 2018a) and 2016iae (Prentice & Mazzali 2017) were reduced without subtraction and both PSF and aperture photometry were used where appropriate. Photometry performed using a 2017 MacBook Pro, using a 2.5 GHz Intel Core i7 processor with 8 Gb DDR3 RAM.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.