Introduction
pySYD was initially established as a one-to-one translation of the IDL-based SYD pipeline
from Huber et al. (2009). In the
Kepler days, SYD was extensively used to measure global asteroseismic parameters
for many stars (e.g., [H2011]; [C2014]; [S2017a]; [Y2018]).
In order to process and analyze the enormous amounts of data from Kepler in real time, there were a a handful of other closed-source pipelines developed around the same time that perform roughly similar types of analyses. In fact, there were several papers that compared results from each of these pipelines in order to ensure the reproducibility of science results from the Kepler legacy sample ([L2017]; [S2017b]).
pySYD adapts the well-tested methodology from SYD while simultaneously improving these
existing analyses and expanding upon numerous new features. Some improvements include:
automated background model comparison and selection
parallel processing and other easy compatabilities for running many stars
easily customizable with command-line friendly interface
modular and adaptable across different applications
saves reproducible samples for future analyses (i.e. seeds)
Benchmarking to the Kepler legacy sample
We ran pySYD on ~100 Kepler legacy stars (defined here)
observed in short-cadence and compared the output to SYD results from [S2017a].
The same time series and power spectra were used for both analyses, which are publicly available
and hosted online c/o KASOC 1. The resulting values are compared for the two methods below for
numax (\(\rm \nu_{max}\), left) and dnu (\(\Delta\nu\), right).
The residuals show no strong systematics to within <0.5% in Dnu and <~1% in numax, which
is smaller than the typical random uncertainties. This confirms that the open-source Python
package pySYD provides consistent results with the legacy IDL version that has been
used extensively in the literature.