TY - JOUR

T1 - The linear theory power spectrum from the Lyα forest in the sloan digital sky survey

AU - McDonald, Patrick

AU - Seljak, Uroš

AU - Cen, Renyue

AU - Shih, David

AU - Weinberg, David H.

AU - Burles, Scott

AU - Schneider, Donald P.

AU - Schlegel, David J.

AU - Bahcall, Neta A.

AU - Briggs, John W.

AU - Brinkmann, J.

AU - Fukugita, Masataka

AU - Ivezić, Željko

AU - Kent, Stephen

AU - Vanden Berk, Daniel E.

PY - 2005/12/20

Y1 - 2005/12/20

N2 - We analyze the SDSS Lyα forest PF(k, z) measurement to determine the linear theory power spectrum. Our analysis is based on fully hydrodynamic simulations, extended using hydro-particle-mesh simulations. We account for the effect of absorbers with damping wings, which leads to an increase in the slope of the linear power spectrum. We break the degeneracy between the mean level of absorption and the linear power spectrum without significant use of external constraints. We infer linear theory power spectrum amplitude ΔL2(kL = 0.009 s km -1, zp = 3.0) = 0.452-0.057 - 0.116+0.069 +0.141 and slope neff(kp, zp) = -2.321-0.047 - 0.102+0.055 +0.131 (possible systematic errors are included through nuisance parameters in the fit: a factor ≳5 smaller errors would be obtained on both parameters if we ignored modeling uncertainties). The errors are correlated and not perfectly Gaussian, so we provide a χ2 table to accurately describe the results. The result corresponds to σ8 = 0.85, n = 0.94 for a ΛCDM model with Ωm = 0.3, Ωb = 0.04, and h = 0.7 but is most useful in a combined fit with the CMB. The inferred curvature of the linear power spectrum and the evolution of its amplitude and slope with redshift are consistent with expectations for ΛCDM models, with the evolution of the slope, in particular, being tightly constrained. We use this information to constrain systematic contamination, e.g., fluctuations in the UV background. This paper should serve as a starting point for more work to refine the analysis, including technical improvements such as increasing the size and number of the hydrodynamic simulations and improvements in the treatment of the various forms of feedback from galaxies and quasars.

AB - We analyze the SDSS Lyα forest PF(k, z) measurement to determine the linear theory power spectrum. Our analysis is based on fully hydrodynamic simulations, extended using hydro-particle-mesh simulations. We account for the effect of absorbers with damping wings, which leads to an increase in the slope of the linear power spectrum. We break the degeneracy between the mean level of absorption and the linear power spectrum without significant use of external constraints. We infer linear theory power spectrum amplitude ΔL2(kL = 0.009 s km -1, zp = 3.0) = 0.452-0.057 - 0.116+0.069 +0.141 and slope neff(kp, zp) = -2.321-0.047 - 0.102+0.055 +0.131 (possible systematic errors are included through nuisance parameters in the fit: a factor ≳5 smaller errors would be obtained on both parameters if we ignored modeling uncertainties). The errors are correlated and not perfectly Gaussian, so we provide a χ2 table to accurately describe the results. The result corresponds to σ8 = 0.85, n = 0.94 for a ΛCDM model with Ωm = 0.3, Ωb = 0.04, and h = 0.7 but is most useful in a combined fit with the CMB. The inferred curvature of the linear power spectrum and the evolution of its amplitude and slope with redshift are consistent with expectations for ΛCDM models, with the evolution of the slope, in particular, being tightly constrained. We use this information to constrain systematic contamination, e.g., fluctuations in the UV background. This paper should serve as a starting point for more work to refine the analysis, including technical improvements such as increasing the size and number of the hydrodynamic simulations and improvements in the treatment of the various forms of feedback from galaxies and quasars.

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U2 - 10.1086/497563

DO - 10.1086/497563

M3 - Article

AN - SCOPUS:30644458315

VL - 635

SP - 761

EP - 783

JO - Astrophysical Journal

JF - Astrophysical Journal

SN - 0004-637X

IS - 2 I

ER -