text: 472,95,1382078749802389512,791705191175360512,Niels Warburton,"Our new paper out today details the first fully relativistic EMRI template model fast enough to do parameter estimation with. As a demonstration we explore the accuracy of the semi-relativistic kludge waveform generation methods. <LINK> <LINK> For certain regions of the parameter space, using semi-relativistic amplitudes to recover an injected full relativistic waveform can lead to biases in the posterior distribution <LINK> The fully relativistic model is part of a new FastEMRIWaveform framework that provides a unified Python interface to generate EMRI waveform templates in the solar system barycenter frame. This makes it very easy for data analysts to upgrade to new models as they become available. <LINK> The fully relativistic model is fast. Using GPU acceleration you can generate a year-long EMRI waveform in less than 100ms. All the code is open source in the BHPToolkit: <LINK> The fully relativistic model, first introduced in our letter, <LINK>, is only for inspirals into non-rotating black holes. The methods we used should extend to Kerr and incorporate GSF corrections as they become available. <LINK> For the LISA Data Challenge it is useful to have waveform models that are extensive in parameter space so whilst we wait for fully relativistic Kerr waveforms we also include an updated GPU accel'd Augment Analytic Kludge model in the FEW framework.",https://arxiv.org/abs/2104.04582,"We present the FastEMRIWaveforms (FEW) package, a collection of tools to build and analyze extreme mass ratio inspiral (EMRI) waveforms. Here, we expand on the Physical Review Letter that introduced the first fast and accurate fully-relativistic EMRI waveform template model. We discuss the construction of the overall framework; constituent modules; and the general methods used to accelerate EMRI waveforms. Because the fully relativistic FEW model waveforms are for now limited to eccentric orbits in the Schwarzschild spacetime, we also introduce an improved Augmented Analytic Kludge (AAK) model that describes generic Kerr inspirals. Both waveform models can be accelerated using graphics processing unit (GPU) hardware. With the GPU-accelerated waveforms in hand, a variety of studies are performed including an analysis of EMRI mode content, template mismatch, and fully Bayesian Markov Chain Monte Carlo-based EMRI parameter estimation. We find relativistic EMRI waveform templates can be generated with fewer harmonic modes ($\sim10-100$) without biasing signal extraction. However, we show for the first time that extraction of a relativistic injection with semi-relativistic amplitudes can lead to strong bias and anomalous structure in the posterior distribution for certain regions of parameter space. ","FastEMRIWaveforms: New tools for millihertz gravitational-wave data