7,414 research outputs found

    Comparing holographic dark energy models with statefinder

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    We apply the statefinder diagnostic to the holographic dark energy models, including the original holographic dark energy (HDE) model, the new holographic dark energy model, the new agegraphic dark energy (NADE) model, and the Ricci dark energy model. In the low-redshift region the holographic dark energy models are degenerate with each other and with the Λ\LambdaCDM model in the H(z)H(z) and q(z)q(z) evolutions. In particular, the HDE model is highly degenerate with the Λ\LambdaCDM model, and in the HDE model the cases with different parameter values are also in strong degeneracy. Since the observational data are mainly within the low-redshift region, it is very important to break this low-redshift degeneracy in the H(z)H(z) and q(z)q(z) diagnostics by using some quantities with higher order derivatives of the scale factor. It is shown that the statefinder diagnostic r(z)r(z) is very useful in breaking the low-redshift degeneracies. By employing the statefinder diagnostic the holographic dark energy models can be differentiated efficiently in the low-redshift region. The degeneracy between the holographic dark energy models and the Λ\LambdaCDM model can also be broken by this method. Especially for the HDE model, all the previous strong degeneracies appearing in the H(z)H(z) and q(z)q(z) diagnostics are broken effectively. But for the NADE model, the degeneracy between the cases with different parameter values cannot be broken, even though the statefinder diagnostic is used. A direct comparison of the holographic dark energy models in the rr--ss plane is also made, in which the separations between the models (including the Λ\LambdaCDM model) can be directly measured in the light of the current values {r0,s0}\{r_0,s_0\} of the models.Comment: 8 pages, 8 figures; accepted by European Physical Journal C; matching the publication versio

    Statefinder hierarchy exploration of the extended Ricci dark energy

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    We apply the statefinder hierarchy plus the fractional growth parameter to explore the extended Ricci dark energy (ERDE) model, in which there are two independent coefficients α\alpha and β\beta. By adjusting them, we plot evolution trajectories of some typical parameters, including Hubble expansion rate EE, deceleration parameter qq, the third and fourth order hierarchy S3(1)S_3^{(1)} and S4(1)S_4^{(1)} and fractional growth parameter ϵ\epsilon, respectively, as well as several combinations of them. For the case of variable α\alpha and constant β\beta, in the low-redshift region the evolution trajectories of EE are in high degeneracy and that of qq separate somewhat. However, the Λ\LambdaCDM model is confounded with ERDE in both of these two cases. S3(1)S_3^{(1)} and S4(1)S_4^{(1)}, especially the former, perform much better. They can differentiate well only varieties of cases within ERDE except Λ\LambdaCDM in the low-redshift region. For high-redshift region, combinations {Sn(1),ϵ}\{S_n^{(1)},\epsilon\} can break the degeneracy. Both of {S3(1),ϵ}\{S_3^{(1)},\epsilon\} and {S4(1),ϵ}\{S_4^{(1)},\epsilon\} have the ability to discriminate ERDE with α=1\alpha=1 from Λ\LambdaCDM, of which the degeneracy cannot be broken by all the before-mentioned parameters. For the case of variable β\beta and constant α\alpha, S3(1)(z)S_3^{(1)}(z) and S4(1)(z)S_4^{(1)}(z) can only discriminate ERDE from Λ\LambdaCDM. Nothing but pairs {S3(1),ϵ}\{S_3^{(1)},\epsilon\} and {S4(1),ϵ}\{S_4^{(1)},\epsilon\} can discriminate not only within ERDE but also ERDE from Λ\LambdaCDM. Finally we find that S3(1)S_3^{(1)} is surprisingly a better choice to discriminate within ERDE itself, and ERDE from Λ\LambdaCDM as well, rather than S4(1)S_4^{(1)}.Comment: 8 pages, 14 figures; published versio

    Revisiting the holographic dark energy in a non-flat universe: alternative model and cosmological parameter constraints

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    We propose an alternative model for the holographic dark energy in a non-flat universe. This new model differs from the previous one in that the IR length cutoff LL is taken to be exactly the event horizon size in a non-flat universe, which is more natural and theoretically/conceptually concordant with the model of holographic dark energy in a flat universe. We constrain the model using the recent observational data including the type Ia supernova data from SNLS3, the baryon acoustic oscillation data from 6dF, SDSS-DR7, BOSS-DR11, and WiggleZ, the cosmic microwave background data from Planck, and the Hubble constant measurement from HST. In particular, since some previous studies have shown that the color-luminosity parameter β\beta of supernovae is likely to vary during the cosmic evolution, we also consider such a case that β\beta in SNLS3 is time-varying in our data fitting. Compared to the constant β\beta case, the time-varying β\beta case reduces the value of χ2\chi^2 by about 35 and results in that β\beta deviates from a constant at about 5σ\sigma level, well consistent with the previous studies. For the parameter cc of the holographic dark energy, the constant β\beta fit gives c=0.65±0.05c=0.65\pm 0.05 and the time-varying β\beta fit yields c=0.72±0.06c=0.72\pm 0.06. In addition, an open universe is favored (at about 2σ\sigma) for the model by the current data.Comment: 8 pages, 4 figure

    Design and optimization of joint iterative detection and decoding receiver for uplink polar coded SCMA system

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    SCMA and polar coding are possible candidates for 5G systems. In this paper, we firstly propose the joint iterative detection and decoding (JIDD) receiver for the uplink polar coded sparse code multiple access (PC-SCMA) system. Then, the EXIT chart is used to investigate the performance of the JIDD receiver. Additionally, we optimize the system design and polar code construction based on the EXIT chart analysis. The proposed receiver integrates the factor graph of SCMA detector and polar soft-output decoder into a joint factor graph, which enables the exchange of messages between SCMA detector and polar decoder iteratively. Simulation results demonstrate that the JIDD receiver has better BER performance and lower complexity than the separate scheme. Specifically, when polar code length N=256 and code rate R=1/2 , JIDD outperforms the separate scheme 4.8 and 6 dB over AWGN channel and Rayleigh fading channel, respectively. It also shows that, under 150% system loading, the JIDD receiver only has 0.3 dB performance loss compared to the single user uplink PC-SCMA over AWGN channel and 0.6 dB performance loss over Rayleigh fading channel

    No evidence for the evolution of mass density power-law index γ\gamma from strong gravitational lensing observation

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    In this paper, we consider the singular isothermal sphere lensing model that has a spherically symmetric power-law mass distribution ρtot(r)rγ\rho_{tot}(r)\sim r^{-\gamma}. We investigate whether the mass density power-law index γ\gamma is cosmologically evolutionary by using the strong gravitational lensing (SGL) observation, in combination with other cosmological observations. We also check whether the constraint result of γ\gamma is affected by the cosmological model, by considering several simple dynamical dark energy models. We find that the constraint on γ\gamma is mainly decided by the SGL observation and independent of the cosmological model, and we find no evidence for the evolution of γ\gamma from the SGL observation.Comment: 7 pages, 3 figure

    Online Estimation with Rolling Validation: Adaptive Nonparametric Estimation with Stream Data

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    Online nonparametric estimators are gaining popularity due to their efficient computation and competitive generalization abilities. An important example includes variants of stochastic gradient descent. These algorithms often take one sample point at a time and instantly update the parameter estimate of interest. In this work we consider model selection and hyperparameter tuning for such online algorithms. We propose a weighted rolling-validation procedure, an online variant of leave-one-out cross-validation, that costs minimal extra computation for many typical stochastic gradient descent estimators. Similar to batch cross-validation, it can boost base estimators to achieve a better, adaptive convergence rate. Our theoretical analysis is straightforward, relying mainly on some general statistical stability assumptions. The simulation study underscores the significance of diverging weights in rolling validation in practice and demonstrates its sensitivity even when there is only a slim difference between candidate estimators
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