Assessing the data-analysis impact of LISA orbit approximations using a GPU-accelerated response model

The analysis of gravitational wave (GW) datasets is based on the comparisonof measured time series with theoretical templates of the detector's responseto a variety of source parameters. For LISA, the main scientific observableswill be the so-called time-delay interferometry (TDI) combinations, whichsuppress the otherwise overwhelming laser noise. Computing the TDI response toGW involves projecting the GW polarizations onto the LISA constellation arms,and then combining projections delayed by a multiple of the light propagationtime along the arms. Both computations are difficult to perform efficiently forgeneric LISA orbits and GW signals. Various approximations are currently usedin practice, e.g., assuming constant and equal armlengths, which yieldsanalytical TDI expressions. In this article, we present 'fastlisaresponse', anew efficient GPU-accelerated code that implements the generic TDI response toGWs in the time domain. We use it to characterize the parameter-estimation biasincurred by analyzing loud Galactic-binary signals using the equal-armlengthapproximation. We conclude that equal-armlength parameter-estimation codesshould be upgraded to the generic response if they are to achieve optimalaccuracy for high (but reasonable) SNR sources within the actual LISA data.