tokens: The two measurements are not inconsistent taking into account the large errors in both of them, however they suggest that weak CIV systems may have lower bias than strong ones, which would help explain why the individually detected CIV systems have a higher bias than the overall population. Next, we comment on the result of Blomqvist et al. ( 2018 ), who have simultaneously completed a similar analysis to ours including eBOSS data. Apart from having a larger data set (especially at low redshift), there are other differences in the two analyses. One is the different continuum-fitting methods. Blomqvist et al. ( 2018 ) apply the same continuum-fitting method used in other BOSS analyses of the Lyα forest, hence the need for a distortion matrix in their work (i.e. their Section 5.2 ). They also use an upgrade from the Baofit code we use called picca , 4 although this should not affect the results. Their fitting range extends to a larger scale than ours: from 10 to 180 , compared to our range from 5 to . We focus on comparing their result for the bias and redshift distortion factors when restricting the rest-frame wavelength range to 1420 Å Å, the same one we have used which avoids the contribution from SiIV lines. The mean result of Blomqvist et al. ( 2018 ) for their entire redshift range is β c = 0.35 ± 0.21, and b c (1 + β c ) = −0.019 ± 0.002. In comparison, we obtain a higher value of the redshift distortion factor, β c = 1.09 ± 0.56, although the large errors do not make the two values incompatible. Our value for the bias b c agrees with theirs: from our equation ( 20 ), if we use their central value β c = 0.35, we find that our measurement b c (1 + 0.44β c ) = −0.017 implies b c (1 + β c ) = −0.0199 ± 0.0015 for β c = 0.35, in full agreement with Blomqvist et al. ( 2018 ). The low central value of β c found by Blomqvist et al. ( 2018 ) is not consistent with our constraint derived from the bounds in from measurements of the incidence rate of CIV absorbers as a function of their equivalent width in Section 7.1 , implying 0.6 β c 1. Taking into account the measurement error, however, their result can be compatible with this constraint. It is worth noting that their result for β c is substantially different when dividing the data set into two redshift intervals. For low redshift ( 2.2 and a mean effective redshift eff = 1.69), they find β c = 0.05 ± 0.19, whereas for high redshift ( > 2.2 and eff = 2.41, closer to our measurement with eff = 2.29) their result is β c = 0.67 ± 0.29. Their result at high redshift is therefore fully consistent with ours, and with our derived constraint from the value of . The very low value of β c at low redshift derived by Blomqvist et al. ( 2018 ) suggests that the absorber bias factor b τ c may be increasing rapidly with decreasing redshift, perhaps because CIV is being destroyed in low-mass haloes and being formed in massive haloes. However, more data at low redshift that allow reduced error bars and
ner_tags: O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O B-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O B-Survey O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O B-Software I-Software O O O B-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O B-Formula I-Formula I-Formula O O O O O B-Formula I-Formula I-Formula O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O