We present a new photometric reduction method for precise time-series photometry of non-crowded fields that does not need to involve relatively complicated and CPU intensive techniques such as point-spread-function (PSF) fitting or difference image analysis. This method, which combines multi-aperture index photometry and a spatio-temporal de-trending algorithm, gives much superior performance in data recovery and light-curve precision. In practice, the brutal filtering that is often applied to remove outlying data points can result in the loss of vital data, with seriously negative impacts on short-term variations such as flares. Our method utilizes nearly 100% of available data and reduces the rms scatter to several times smaller than that for archived light curves for brighter stars. We outline the details of our new method, and apply it to cases of sample data from the MMT survey of the M37 field, and the HAT-South survey.
|Title of host publication||New Horizons in Time-Domain Astronomy|
|Editors||Elizabeth Griffin, Robert J. Hanisch, Robert L. Seaman|
|Number of pages||3|
|Publication status||Published - 2011 Sept|
|Name||Proceedings of the International Astronomical Union|
Bibliographical noteFunding Information:
This work is supported by the Korea Institute of Science and Technology Information under the contract of the commissioned research project, Massive Astronomical Data Applications of Cloud Computation (KISTI-P11020). We thank Joel D. Hartman and Matthew J. Holman for their suggestion to use the whole MMT data set. We also thank Daniel Bayliss and the HAT-South team for helping us access HAT-South data.
All Science Journal Classification (ASJC) codes
- Medicine (miscellaneous)
- Astronomy and Astrophysics
- Nutrition and Dietetics
- Public Health, Environmental and Occupational Health
- Space and Planetary Science