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Improved analytic extreme-mass-ratio inspiral model for scoping out eLISA data analysis

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arxiv 1510.06245 v1 pith:IN2QA6TD submitted 2015-10-21 gr-qc astro-ph.HE

Alvin J. K. Chua , Jonathan R. Gair This is my paper · ORCID
classification gr-qcastro-ph.HE
keywords dataaccuratechallengesmissionmodelwaveformswillanalysis
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The space-based gravitational-wave detector eLISA has been selected as the ESA L3 mission, and the mission design will be finalised by the end of this decade. To prepare for mission formulation over the next few years, several outstanding and urgent questions in data analysis will be addressed using mock data challenges, informed by instrument measurements from the LISA Pathfinder satellite launching at the end of 2015. These data challenges will require accurate and computationally affordable waveform models for anticipated sources such as the extreme-mass-ratio inspirals (EMRIs) of stellar-mass compact objects into massive black holes. Previous data challenges have made use of the well-known analytic EMRI waveforms of Barack and Cutler, which are extremely quick to generate but dephase relative to more accurate waveforms within hours, due to their mismatched radial, polar and azimuthal frequencies. In this paper, we describe an augmented Barack-Cutler model that uses a frequency map to the correct Kerr frequencies, along with updated evolution equations and a simple fit to a more accurate model. The augmented waveforms stay in phase for months and may be generated with virtually no additional computational cost.

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Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Searching for extreme mass ratio inspirals in LISA: from identification to parameter estimation

    gr-qc 2025-05 conditional novelty 6.0 of 10

    A staged pipeline using a new time-frequency match statistic recovers and estimates parameters of two injected EMRI signals in simulated LISA data, though with a hyperparameter tuned on those injections.

  2. Sequential simulation-based inference for extreme mass ratio inspirals

    gr-qc 2025-05 conditional novelty 6.0 of 10

    Sequential simulation-based inference with truncated marginal neural ratio estimation shrinks the 11-parameter search volume for simulated non-spinning extreme-mass-ratio inspirals by factors of 1e6 to 1e7 and recover...

  3. Shadow constraints of charged black hole with scalar hair and gravitational waves from extreme mass ratio inspirals

    gr-qc 2025-06 conditional novelty 5.0 of 10

    EHT shadow data constrain the EMCS black hole charge and scalar hair to about 0.1 and 0.01 levels, while LISA EMRI waveforms could reach 0.01 and 0.0001 levels.

  4. Constraining Lorentz symmetry breaking in bumblebee gravity with extreme mass-ratio inspirals

    gr-qc 2026-05 unverdicted novelty 4.0 of 10

    LISA can constrain the Lorentz symmetry breaking parameter ell in bumblebee gravity to O(10^{-4}) uncertainty via EMRI waveform analysis in the AAK framework.

  5. Distinguishing scale-dependent Planck stars from renormalization group improved Schwarzschild black holes by Gravitational waves

    gr-qc 2025-06 conditional novelty 4.0 of 10

    Gravitational-wave strains from analytic-kludge EMRI models can distinguish scale-dependent Planck stars from renormalization-group improved Schwarzschild black holes, at least for the chosen orbit parameters.

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