This reduction was carried out using image-subtraction photometry and tools developed for the HAT Surveys. The details of the process are available in Huang et al. 2015 for the general K2 data extraction pipeline, and in Soares-Furtado et al. 2017 for the image subtraction photometry pipeline. This initial data release described in Soares-Furtado et al. 2016 is restricted to Channel 81 on Module 24 of the Kepler focal plane array during Campaign 0 of the K2 observing mission. This encompasses the super-stamps generated to enclose the region containing the the M35 and NGC2158 open clusters. The density of this particular field (see the figure below for the extracted channel from the full-frame image) makes it a good test case for PSF-fitting photometry (as carried out by Libralato, et al. 2016), and image-subtraction photometry (ISM) carried out by our team. We performed time-series ISM on stitched images generated from all stamps located on this focal plane array channel. See the paper for more details.
We make available light curves for 3960 objects in and near the M 35/NGC 2158 open clusters, using 9 photometric apertures. We provide image-subtraction aperture photometry, detrended photometry, and trend-filtered (TFA) photometry for each observation. These objects are identified by 2MASS IDs for the most part, and by UCAC4 IDs for 85 objects that have no 2MASS matches. Use the search function to look for objects with specific IDs or around a specified set of sky coordinates.
The light curves are provided in a standardized column format common to all HAT reductions of the Kepler observations. There's a Python module available to read these in a convenient manner. These are just gzipped CSV files, with self-describing headers, so should be fairly straightforward to read otherwise.
For K2 Campaign 0, the light curves have an item
called kernelspec in the header that describes the
convolution kernel used for the image subtraction process that led to
the best quality light curve. This is of the
[A] is the polynomial order of the constant offset
kernel used for the background estimation. We produced light curves
using a background kernel order of 0 to 4; the best light curves
(available on this website) for each source were chosen such that they
had the lowest RMS scatter among all of these tries.
[B] is the polynomial order of the curve describing
spatial variations in the flux scale. We found that setting this to 0
produced the lowest scatter light curves, as these variations are well
modeled by a constant value.
[D] represent the half-size of the
discrete kernel and the polynomial order of its spatial varations,
respectively. These parameters by far generate the largest change in the
resulting light curve RMS catter, and are optimized when set to 2 and 0,
The light curves available from this website have been reprocessed to make them fit into the general HAT data server framework. The raw data from which these were generated are available below as tarballs (.tar.gz files). Note that the objects are identified by internal HAT IDs (one-to-one correspondence with 2MASS IDs), and UCAC4 IDs. Use the object ID search to find the HAT IDs associated with each object.
Light curves for 4 objects have doubled-up measurements. The light curves for the objects 2MASS J06090633+2415560 (HAT-264-0003844), 2MASS J06081447+2346371 (HAT-264-0345492), 2MASS J06091652+2422177 (HAT-264-0011034), and 2MASS J06102278+2418578 (HAT-264-0576773) have doubled-up observations, i.e. two measured magnitudes per cadence. This is because our pipeline relies on UCAC4 for the external catalog of point sources to extract photometry for, and these particular 2MASS sources each have two corresponding UCAC4 sources (probably because of improved deblending in UCAC4). The light curves have included x and y positions, which may be used to separate these blended sources if desired. If you're interested in these objects, we recommend that you use the raw light curves (previous section) and re-extract/merge them from scratch. In the future, we may provide separate light curves for each component of these objects.