The main purpose of this work is to distinguish various holographic type dark energy （DE） models, including the AHDE, HDE, NADE, and RDE model, by using various diagnostic tools. The first diagnostic tool is the Sta...The main purpose of this work is to distinguish various holographic type dark energy （DE） models, including the AHDE, HDE, NADE, and RDE model, by using various diagnostic tools. The first diagnostic tool is the Statefinder hierarchy, in which the evolution of Statefinder hierarchy parmeter S3（1）（z） and S4（1）（z） are studied. The second is composite null diagnostic （CND）, in which the trajectories of {S（1）4, ∈} and {S4（1）, e} are investigated, where ∈ is the fractional growth parameter. The last is w-w′ analysis, where w is the equation of state for DE and the prime denotes derivative with respect to lna. In the analysis we consider two cases： varying current fractional DE density Ωde0 and varying DE model parameter C. We find that： （1） both the Statefinder S4（1） can lead to larger hierarchy and the CND have qualitative impact on AHDE, but only have quantitative impact on HDE. （2） S4（1） differences than S 4（1）, while the CND pair has a stronger ability to distinguish different models than the Statefinder hierarchy. （3） For the case of varying C, the {w, w′} pair has qualitative impact on AHDE; for the case of varying Ωde0, the {w, w′} pair only has quantitative impact; these results are different from the cases of HDE, RDE, and NADE, in which the {w, w′} pair only has quantitative impact on these models. In conclusion, compared with HDE, RDE, and NADE, the AHDE model can be easily distinguished by using these diagnostic tools.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.11405024)the Fundamental Research Funds for the Central Universities(Grant No.16lgpy50)
文摘The main purpose of this work is to distinguish various holographic type dark energy （DE） models, including the AHDE, HDE, NADE, and RDE model, by using various diagnostic tools. The first diagnostic tool is the Statefinder hierarchy, in which the evolution of Statefinder hierarchy parmeter S3（1）（z） and S4（1）（z） are studied. The second is composite null diagnostic （CND）, in which the trajectories of {S（1）4, ∈} and {S4（1）, e} are investigated, where ∈ is the fractional growth parameter. The last is w-w′ analysis, where w is the equation of state for DE and the prime denotes derivative with respect to lna. In the analysis we consider two cases： varying current fractional DE density Ωde0 and varying DE model parameter C. We find that： （1） both the Statefinder S4（1） can lead to larger hierarchy and the CND have qualitative impact on AHDE, but only have quantitative impact on HDE. （2） S4（1） differences than S 4（1）, while the CND pair has a stronger ability to distinguish different models than the Statefinder hierarchy. （3） For the case of varying C, the {w, w′} pair has qualitative impact on AHDE; for the case of varying Ωde0, the {w, w′} pair only has quantitative impact; these results are different from the cases of HDE, RDE, and NADE, in which the {w, w′} pair only has quantitative impact on these models. In conclusion, compared with HDE, RDE, and NADE, the AHDE model can be easily distinguished by using these diagnostic tools.
