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Register a new userGaussian Process Estimation of Transition Redshift
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Added by
Jos\\'e Fernando de Jesus
Publication date
2019
fields
Physics
and research's language is
English
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This paper aims to put constraints on the transition redshift $z_t$, which determines the onset of cosmic acceleration, in cosmological-model independent frameworks. In order to do that, we use the non-parametric Gaussian Process method with $H(z)$ and SNe Ia data. The deceleration parameter reconstruction from $H(z)$ data yields $z_t=0.59^{+0.12}_{-0.11}$. The reconstruction from SNe Ia data assumes spatial flatness and yields $z_t=0.683^{+0.11}_{-0.082}$. These results were found with a Gaussian kernel and we show that they are consistent with two other kernel choices.
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Accurate photometric redshifts are a lynchpin for many future experiments to pin down the cosmological model and for studies of galaxy evolution. In this study, a novel sparse regression framework for photometric redshift estimation is presented. Simulated and real data from SDSS DR12 were used to train and test the proposed models. We show that approaches which include careful data preparation and model design offer a significant improvement in comparison with several competing machine learning algorithms. Standard implementations of most regression algorithms have as the objective the minimization of the sum of squared errors. For redshift inference, however, this induces a bias in the posterior mean of the output distribution, which can be problematic. In this paper we directly target minimizing $Delta z = (z_textrm{s} - z_textrm{p})/(1+z_textrm{s})$ and address the bias problem via a distribution-based weighting scheme, incorporated as part of the optimization objective. The results are compared with other machine learning algorithms in the field such as Artificial Neural Networks (ANN), Gaussian Processes (GPs) and sparse GPs. The proposed framework reaches a mean absolute $Delta z = 0.0026(1+z_textrm{s})$, over the redshift range of $0 le z_textrm{s} le 2$ on the simulated data, and $Delta z = 0.0178(1+z_textrm{s})$ over the entire redshift range on the SDSS DR12 survey, outperforming the standard ANNz used in the literature. We also investigate how the relative size of the training set affects the photometric redshift accuracy. We find that a training set of textgreater 30 per cent of total sample size, provides little additional constraint on the photometric redshifts, and note that our GP formalism strongly outperforms ANNz in the sparse data regime for the simulated data set.
Inflation predicts that the Universe is spatially flat. The Planck 2018 measurements of the cosmic microwave background anisotropy favour a spatially closed universe at more than 2$sigma$ confidence level. We use model independent methods to study the issue of cosmic curvature. The method reconstructs the Hubble parameter $H(z)$ from cosmic chronometers data with the Gaussian process method. The distance modulus is then calculated with the reconstructed function $H(z)$ and fitted by type Ia supernovae data. Combining the cosmic chronometers and type Ia supernovae data, we obtain $Omega_{k0}h^2=0.102pm 0.066$ which is consistent with a spatially flat universe at the 2$sigma$ confidence level. By adding the redshift space distortions data to the type Ia supernovae data with a proposed novel model independent method, we obtain $Omega_{k0}h^2=0.117^{+0.058}_{-0.045}$ and no deviation from $Lambda$CDM model is found.
Observations from Supernovae Type Ia (SNe Ia) provided strong evidence for an expanding accelerating Universe at intermediate redshifts. This means that the Universe underwent a transition from deceleration to acceleration phases at a transition redshift $z_t$ of the order unity whose value in principle depends on the cosmology as well as on the assumed gravitational theory. Since cosmological accelerating models endowed with a transition redshift are extremely degenerated, in principle, it is interesting to know whether the value of $z_t$ itself can be observationally used as a new cosmic discriminator. After a brief discussion of the potential dynamic role played by the transition redshift, it is argued that future observations combining SNe Ia, the line-of-sight (or radial) baryon acoustic oscillations, the differential age of galaxies, as well as the redshift drift of the spectral lines may tightly constrain $z_t$, thereby helping to narrow the parameter space for the most realistic models describing the accelerating Universe.
We develop an automated technique to measure quasar redshifts in the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey (SDSS). Our technique is an extension of an earlier Gaussian process method for detecting damped Lyman-alpha absorbers (DLAs) in quasar spectra with known redshifts. We apply this technique to a subsample of SDSS DR12 with BAL quasars removed and redshift larger than 2.15. We show that we are broadly competitive to existing quasar redshift estimators, disagreeing with the PCA redshift by more than 0.5 in only 0.38% of spectra. Our method produces a probabilistic density function for the quasar redshift, allowing quasar redshift uncertainty to be propagated to downstream users. We apply this method to detecting DLAs, accounting in a Bayesian fashion for redshift uncertainty. Compared to our earlier method with a known quasar redshift, we have a moderate decrease in our ability to detect DLAs, predominantly in the noisiest spectra. The area under curve drops from 0.96 to 0.91. Our code is publicly available.
We carry out a numerical calculation of the bispectrum in generalised trajectories of canonical, single--field inflation. The trajectories are generated in the Hamilton-Jacobi (HJ) formalism based on Hubble Slow Roll (HSR) parameters. The calculation allows generally shape and scale dependent bispectra, or dimensionless $f_{NL}$, in the out-of-slow-roll regime. The distributions of $f_{NL}$ for various shapes and HSR proposals are shown as an example of how this procedure can be used within the context of Monte Carlo exploration of inflationary trajectories. We also show how allowing out-of-slow-roll behaviour can lead to a bispectrum that is relatively large for equilateral shapes.
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