Developed by Michele Vallisneri at the Jet Propulsion Laboratory in collaboration with John Armstrong, Synthetic LISA is an open-source software package to simulate the LISA science process at the level of scientific and technical requirements.
It generates synthetic time series of the LISA fundamental noises, as filtered through all the TDI observables; it provides a streamlined module to compute the TDI responses to gravitational waves, according to a full model of TDI (including the motion of the LISA array, and the temporal and directional dependence of the armlengths).
Synthetic LISA is written as a C++/Python modular package that allows adding code for specific gravitational-wave sources, or for new noise models; time series for waves and noises can also be easily loaded from disk or memory. The package has a Python interface for easy interactive steering and scripting, and contains several documented example scripts.
Synthetic LISA is used extensively in the Mock LISA Data Challenges to generate challenge datasets. The architecture of the MLDC lisatools software suite is also heavily based on Synthetic LISA.
As of 4/15/2005, I have received ITAR clearance for the public release of Synthetic LISA (thanks to John Armstrong for following through with NASA HQ). Synthetic LISA is currently being distributed under the Caltech and MIT public-domain licenses. See also the lisatools development website.
To download the latest version of Synthetic LISA please fill in the form below. You'll get access to a tar.gz file that includes also some Python packages (such as numpy, pyRXP, PyX, and SWIG) that are required to compile Synthetic LISA.
Please note that Synthetic LISA should be considered beta software. In particular, the manual is incomplete, and some experimental features are enabled that may not be available in future versions. Still, I encourage you to experiment with it. Please e-mail me (replacing {at} with @) with any feedback, comment, or question.
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