Pursuing parameters for critical-density dark matter models

被引:44
作者
Liddle, AR
Lyth, DH
Schaefer, RK
Shafi, Q
Viana, PTP
机构
[1] UNIV LANCASTER,SCH PHYS & CHEM,LANCASTER LA1 4YB,ENGLAND
[2] UNIV DELAWARE,BARTOL RES INST,NEWARK,DE 19716
关键词
cosmology; theory; dark matter;
D O I
10.1093/mnras/281.2.531
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
We present an extensive comparison of models of structure formation with observations, based on linear and quasi-linear theory. We assume a critical matter density, and study both cold dark matter models and cold plus hot dark matter models. We explore a wide range of parameters, by varying the fraction of hot dark matter Omega(v), the Hubble parameter h and the spectral index of density perturbations n, and allowing for the possibility of gravitational waves from inflation influencing large-angle microwave background anisotropies. New calculations are made of the transfer functions describing the linear power spectrum, with special emphasis on improving the accuracy on short scales where there are strong constraints. For assessing early object formation, the transfer functions are explicitly evaluated at the appropriate redshift. The observations considered are the four-year COBE observations of microwave background anisotropies, peculiar velocity flows, the galaxy correlation function, and the abundances of galaxy clusters, quasars and damped Lyman alpha systems. Each observation is interpreted in terms of the power spectrum filtered by a top-hat window function. We find that there remains a viable region of parameter space for critical-density models when all the dark matter is cold, though h must be less than 0.5 before any fit is found and n significantly below unity is preferred. Once a hot dark matter component is invoked, a wide parameter space is acceptable, including n similar or equal to 1. The allowed region is characterized by Omega(v) less than or similar to 0.35 and 0.60 less than or similar to n less than or similar to 1.25, at 95 per cent confidence on at least one piece of data. There is no useful lower bound on h, and for curious combinations of the other parameters it is possible to fit the data with h as high as 0.65.
引用
收藏
页码:531 / 551
页数:21
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