Institute of Cosmology and Gravitation, University of Portsmouth

About: Institute of Cosmology and Gravitation, University of Portsmouth is a based out in . It is known for research contribution in the topics: Galaxy & Redshift. The organization has 297 authors who have published 1207 publications receiving 76919 citations.

Optimizing a magnitude-limited spectroscopic training sample for photometric classification of supernovae

Abstract: In preparation for photometric classification of transients from the Legacy Survey of Space and Time (LSST) we run tests with different training data sets. Using estimates of the depth to which the 4-metre Multi-Object Spectroscopic Telescope (4MOST) Time Domain Extragalactic Survey (TiDES) can classify transients, we simulate a magnitude-limited sample reaching $r_{\textrm{AB}} \approx$ 22.5 mag. We run our simulations with the software snmachine, a photometric classification pipeline using machine learning. The machine-learning algorithms struggle to classify supernovae when the training sample is magnitude-limited, in contrast to representative training samples. Classification performance noticeably improves when we combine the magnitude-limited training sample with a simulated realistic sample of faint, high-redshift supernovae observed from larger spectroscopic facilities; the algorithms' range of average area under ROC curve (AUC) scores over 10 runs increases from 0.547-0.628 to 0.946-0.969 and purity of the classified sample reaches 95 per cent in all runs for 2 of the 4 algorithms. By creating new, artificial light curves using the augmentation software avocado, we achieve a purity in our classified sample of 95 per cent in all 10 runs performed for all machine-learning algorithms considered. We also reach a highest average AUC score of 0.986 with the artificial neural network algorithm. Having `true' faint supernovae to complement our magnitude-limited sample is a crucial requirement in optimisation of a 4MOST spectroscopic sample. However, our results are a proof of concept that augmentation is also necessary to achieve the best classification results.

AMICO galaxy clusters in KiDS-DR3: cosmological constraints from large-scale stacked weak lensing profiles

Abstract: Context. The large-scale mass distribution around dark matter haloes hosting galaxy clusters provides sensitive cosmological information. Aims. In this work, we make use of a large photometric galaxy cluster sample, constructed from the public Third Data Release of the Kilo-Degree Survey, and the corresponding shear signal, to assess cluster masses and test the concordance ${\Lambda}$-cold dark matter (${\Lambda}$CDM) model. In particular, we study the weak gravitational lensing effects on scales beyond the cluster virial radius, where the signal is dominated by correlated and uncorrelated matter density distributions along the line-of-sight. The analysed catalogue consists of 6962 galaxy clusters, in the redshift range $0.1 \leq z \leq 0.6$ and with signal-to-noise ratio larger than 3.5. Methods. We perform a full Bayesian analysis to model the stacked shear profiles of these clusters. The adopted likelihood function considers both the small-scale 1-halo term, used primarily to constrain the cluster structural properties, and the 2-halo term, that can be used to constrain cosmological parameters. Results. We find that the adopted modelling is successful to assess both the cluster masses and the total matter density parameter, ${\Omega}_M$, when fitting shear profiles up to the largest available scales of 35 Mpc/h. Moreover, our results provide a strong observational evidence of the 2-halo signal in the stacked gravitational lensing of galaxy clusters, further demonstrating the reliability of this probe for cosmological studies. The main result of this work is a robust constraint on ${\Omega}_M$, assuming a flat ${\Lambda}$CDM cosmology. We get ${\Omega}_M = 0.29 \pm 0.02$, estimated from the full posterior probability distribution, consistent with the estimates from cosmic microwave background experiments.

Fifth-force screening around extremely compact sources

Abstract: Many non-linear scalar field theories possess a screening mechanism that can suppress any associated fifth force in dense environments. As a result, these theories can evade local experimental tests of new forces. Chameleon-like screening, which occurs because of non-linearities in the scalar potential or the coupling to matter, is well understood around extended objects. However, many experimental tests of these theories involve objects with spatial extent much smaller than the scalar field's Compton wavelength, and which could therefore be considered point-like. In this work, we determine how the fifth forces are screened in the limit that the source objects become extremely compact.

Cosmological parameter forecasts by a joint 2D tomographic approach to CMB and galaxy clustering

Abstract: The cross-correlation between the cosmic microwave background (CMB) fields and matter tracers carries important cosmological information. In this paper, we forecast by a signal-to-noise ratio analysis the information contained in the cross-correlation of the CMB anisotropy fields with source counts for future cosmological observations and its impact on cosmological parameters uncertainties, using a joint tomographic analysis. We include temperature, polarization, and lensing for the CMB fields and galaxy number counts for the matter tracers. We consider Planck-like, the Simons Observatory, LiteBIRD, and CMB-S4 specifications for CMB, and Euclid-like, Vera C. Rubin Observatory, SPHEREx, EMU, and SKA1 for future galaxy surveys. We restrict ourselves to quasilinear scales in order to deliver results that are free as much as possible from the uncertainties in modeling nonlinearities. We forecast by a Fisher matrix formalism the relative importance of the cross-correlation of source counts with the CMB in the constraints on the parameters for several cosmological models. We obtain that the CMB-number counts cross-correlation can improve the dark energy figure of merit (FOM) at most up to a factor $\ensuremath{\sim}2$ for $\mathrm{LiteBIRD}+\mathrm{CMB}\text{\ensuremath{-}}\mathrm{S}4\ifmmode\times\else\texttimes\fi{}\mathrm{SKA}1$ compared to the uncorrelated combination of both probes and will enable the Euclid-like photometric survey to reach the highest FOM among those considered here. We also forecast how CMB-galaxy clustering cross-correlation could increase the FOM of the neutrino sector, also enabling a statistically significant ($\ensuremath{\gtrsim}3\ensuremath{\sigma}$ for $\mathrm{LiteBIRD}+\mathrm{CMB}\text{\ensuremath{-}}\mathrm{S}4\ifmmode\times\else\texttimes\fi{}\mathrm{SPHERE}\mathrm{x}$) detection of the minimal neutrino mass allowed in a normal hierarchy by using quasilinear scales only. Analogously, we find that the uncertainty in the local primordial non-Gaussianity could be as low as $\ensuremath{\sigma}({f}_{\mathrm{NL}})\ensuremath{\sim}1.5--2$ by using two-point statistics only with the combination of CMB and radio surveys, such as EMU and SKA1. Further, we quantify how cross-correlation will help characterizing the galaxy bias. Our results highlight the additional constraining power of the cross-correlation between CMB and galaxy clustering from future surveys, which is mainly based on quasilinear scales and therefore, sufficiently robust to nonlinear effects.

Evaluating Single Spacecraft Observations of Planetary Magnetotails With Simple Monte Carlo Simulations: 2. Magnetic Flux Rope Signature Selection Effects.

Abstract: A Monte Carlo method of investigating the effects of placing selection criteria on the magnetic signature of in situ encounters with flux ropes is presented. The technique is applied to two recent flux rope surveys of MESSENGER data within the Hermean magnetotail. It is found that the different criteria placed upon the signatures will preferentially identify slightly different subsets of the underlying population. Quantifying the selection biases first allows the distributions of flux rope parameters to be corrected, allowing a more accurate estimation of the intrinsic distributions. This is shown with regard to the distribution of flux rope radii observed. When accounting for the selection criteria, the mean radius of Hermean magnetotail quasi-force-free flux ropes is found to be 58 9 - 269 + 273 km. Second, it is possible to weight the known identifications in order to determine a rate of recurrence that accounts for the presence of the structures that will not be identified. In the case of the Hermean magnetotail, the average rate of quasi-force-free flux ropes is found to 0.12 min-1 when selection effects are accounted for (up from 0.05 min-1 previously inferred from observations).