Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Parameter estimation for inspiraling eccentric compact binaries
  including pericenter precession   Inspiraling supermassive black hole binary systems with high orbital
eccentricity are important sources for space-based gravitational wave (GW)
observatories like the Laser Interferometer Space Antenna (LISA). Eccentricity
adds orbital harmonics to the Fourier transform of the GW signal and
relativistic pericenter precession leads to a three-way splitting of each
harmonic peak. We study the parameter estimation accuracy for such waveforms
with different initial eccentricity using the Fisher matrix method and a Monte
Carlo sampling of the initial binary orientation. The eccentricity improves the
parameter estimation by breaking degeneracies between different parameters. In
particular, we find that the source localization precision improves
significantly for higher-mass binaries due to eccentricity. The typical sky
position errors are $\sim1 $deg for a nonspinning, $10^7\,M_{\odot}$ equal-mass
binary at redshift $z=1$, if the initial eccentricity 1 yr before merger is
$e_0\sim 0.6$. Pericenter precession does not affect the source localization
accuracy significantly, but it does further improve the mass and eccentricity
estimation accuracy systematically by a factor of 3--10 for masses between
$10^6$ and $10^7\,M_{\odot}$ for $e_0 \sim 0.3$.

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The categories of this paper are: hep-ph
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The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci
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The categories of this paper are: nlin
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The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
1
The categories of this paper are: cs
28
The categories of this paper are: alg-geom
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The categories of this paper are: funct-an
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The categories of this paper are: q-fin
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The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: econ
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The categories of this paper are: bayes-an
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The categories of this paper are: eess
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The categories of this paper are: chao-dyn