The Effect of Data Gaps on LISA Galactic Binary Parameter Estimation

In the last few years there has been an enormous effort in parameter estimation studies for different sources with the space based gravitational wave detector, LISA. While these studies have investigated sources of differing complexity, the one thing they all have in common is they assume continuous data streams. In reality, the LISA data stream will contain gaps from such possible events such as repointing of the satellite antennae, to discharging static charge build up on the satellites, to disruptions due to micro-meteor strikes. In this work we conduct a large scale Monte Carlo parameter estimation simulation for galactic binaries assuming data streams containing gaps. As the expected duration and frequency of the gaps are currently unknown, we have decided to focus on gaps of approximately one hour, occurring either once per day or once per week. We also study the case where, as well as the expected periodic gaps, we have a data drop-out of one continuous week. Our results show that for for galactic binaries, a gap of once per week introduces a bias of between 0.5% and 1% in the estimation of parameters, for the most important parameters such as the sky position, amplitude and frequency. This number rises to between 3% and 7% for the case of one gap a day, and to between 4% and 9% when we have one gap a day and a spurious gap of a week. A future study will investigate the effect of data gaps on supermassive black hole binaries and extreme mass ratio inspirals.