Will Gravitational Wave Sirens Determine the Hubble Constant?. (arXiv:1812.07775v1 [astro-ph.CO])
<a href="http://arxiv.org/find/astro-ph/1/au:+Shafieloo_A/0/1/0/all/0/1">Arman Shafieloo</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Keeley_R/0/1/0/all/0/1">Ryan E. Keeley</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Linder_E/0/1/0/all/0/1">Eric V. Linder</a>

Lack of knowledge about the background expansion history of the Universe from
independent observations makes it problematic to obtain a precise and accurate
estimation of the Hubble constant $H_0$ from gravitational wave standard
sirens, even with electromagnetic counterpart redshifts. Simply fitting
simultaneously for the matter density in a flat lcdm model can reduce the
precision on $H_0$ from 1% to 5%, while not knowing the actual background
expansion model of the universe (e.g. form of dark energy) can introduce
substantial bias in estimation of the Hubble constant. When the statistical
precision is at the level of 1% uncertainty on $H_0$, biases in non-lcdm
cosmologies that are consistent with current data could reach the 3$sigma$
level. To avoid model-dependent biases, statistical techniques that are
appropriately agnostic about model assumptions need to be employed.

Lack of knowledge about the background expansion history of the Universe from
independent observations makes it problematic to obtain a precise and accurate
estimation of the Hubble constant $H_0$ from gravitational wave standard
sirens, even with electromagnetic counterpart redshifts. Simply fitting
simultaneously for the matter density in a flat lcdm model can reduce the
precision on $H_0$ from 1% to 5%, while not knowing the actual background
expansion model of the universe (e.g. form of dark energy) can introduce
substantial bias in estimation of the Hubble constant. When the statistical
precision is at the level of 1% uncertainty on $H_0$, biases in non-lcdm
cosmologies that are consistent with current data could reach the 3$sigma$
level. To avoid model-dependent biases, statistical techniques that are
appropriately agnostic about model assumptions need to be employed.

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