Cosmic giants on cosmic scales

Galaxy groups and clusters are cosmic giants. They are the largest observable virialised objects that have materialised from the initial perturbations in the early Universe. These systems comprise of not only galaxies, but also hot gas and dark matter. They are ideal astrophysical laboratories to study the matter distribution of the Universe and cluster physics whilst their distribution and evolution can be used constrain cosmological parameters. Clusters are the ultimate test for the structure formation paradigm. However, for this to be achieved requires knowledge of their mass which is a particularly challenging task since there are no ‘cosmic scales’ to directly measure the masses of these objects. Groups and clusters are massive enough to gravitationally influence light emitted from background galaxies, an effect known as gravitational lensing. Its mass can be inferred from the strength of the weak lensing signal and is only dependent on the gravitational potential well depth. However, its limitations arise from systematic uncertainties of shape measurement, photometric redshift and shallow survey depth. This thesis concerns constraining accurate and precise cluster mass estimates of low mass groups and poor clusters, and testing the limits that can be achieved with current noisy, ground-based data

PSZ2LenS. Weak lensing analysis of the Planck clusters in the CFHTLenS and in the RCSLenS

The possibly unbiased selection process in surveys of the Sunyaev Zel'dovich effect can unveil new populations of galaxy clusters. We performed a weak lensing analysis of the PSZ2LenS sample, i.e. the PSZ2 galaxy clusters detected by the Planck mission in the sky portion covered by the lensing surveys CFHTLenS and RCSLenS. PSZ2LenS consists of 35 clusters and it is a statistically complete and homogeneous subsample of the PSZ2 catalogue. The Planck selected clusters appear to be unbiased tracers of the massive end of the cosmological haloes. The mass concentration relation of the sample is in excellent agreement with predictions from the Lambda cold dark matter model. The stacked lensing signal is detected at 14 sigma significance over the radial range 0.1<R<3.2 Mpc/h, and is well described by the cuspy dark halo models predicted by numerical simulations. We confirmed that Planck estimated masses are biased low by b_SZ= 27+-11(stat)+-8(sys) per cent with respect to weak lensing masses. The bias is higher for the cosmological subsample, b_SZ= 40+-14+-(stat)+-8(sys) per cent.Comment: v1: 23 pages. Comments are welcome. v2: 27 pages, in press on MNRAS. Expanded discussion on systematics and lensing average

Possible evidence for a large-scale enhancement in the Lyman-α\alpha forest power spectrum at redshift z≥4\mathbf{\textit{z}\geq 4}

Inhomogeneous reionization enhances the 1D Lyman-$\alpha$ forest power spectrum on large scales at redshifts $z\geq4$. This is due to coherent fluctuations in the ionized hydrogen fraction that arise from large-scale variations in the post-reionization gas temperature, which fade as the gas cools. It is therefore possible to use these relic fluctuations to constrain inhomogeneous reionization with the power spectrum at wavenumbers $\log_{10}(k/{\rm km^{-1}\,s})\lesssim -1.5$. We use the Sherwood-Relics suite of hybrid radiation hydrodynamical simulations to perform a first analysis of new Lyman-$\alpha$ forest power spectrum measurements at $4.0\leq z \leq 4.6$. These data extend to wavenumbers $\log_{10}(k/{\rm km^{-1}\,s})\simeq -3$, with a relative uncertainty of $10$--$20$ per cent in each wavenumber bin. Our analysis returns a $2.7\sigma$ preference for an enhancement in the Lyman-$\alpha$ forest power spectrum at large scales, in excess of that expected for a spatially uniform ultraviolet background. This large-scale enhancement could be a signature of inhomogeneous reionization, although the statistical precision of these data is not yet sufficient for obtaining a robust detection of the relic post-reionization fluctuations. We show that future power spectrum measurements with relative uncertainties of $\lesssim 2.5$ per cent should provide unambiguous evidence for an enhancement in the power spectrum on large scales.Comment: Accepted by MNRAS, 13 pages, 8 figure

Possible evidence for a large-scale enhancement in the Lyman-α forest power spectrum at redshift z ≥ 4

Inhomogeneous reionization enhances the 1D Lyα forest power spectrum on large scales at redshifts z ≥ 4. This is due to coherent fluctuations in the ionized hydrogen fraction that arise from large-scale variations in the post-reionization gas temperature, which fade as the gas cools. It is therefore possible to use these relic fluctuations to constrain inhomogeneous reionization with the power spectrum at wavenumbers log10(k/km−1 s) ≲ −1.5. We use the Sherwood-Relics suite of hybrid radiation hydrodynamical simulations to perform a first analysis of new Lyα forest power spectrum measurements at 4.0 ≤ z ≤ 4.6. These data extend to wavenumbers log10(k/km−1 s) ≃ −3, with a relative uncertainty of 10–20 per cent in each wavenumber bin. Our analysis returns a 2.7σ preference for an enhancement in the Lyα forest power spectrum at large scales, in excess of that expected for a spatially uniform ultraviolet background. This large-scale enhancement could be a signature of inhomogeneous reionization, although the statistical precision of these data is not yet sufficient for obtaining a robust detection of the relic post-reionization fluctuations. We show that future power spectrum measurements with relative uncertainties of ≲ 2.5 per cent should provide unambiguous evidence for an enhancement in the power spectrum on large scales

Deep learning-based super-resolution and de-noising for XMM-newton images

The field of artificial intelligence based image enhancement has been rapidly evolving over the last few years and is able to produce impressive results on non-astronomical images. In this work, we present the first application of Machine Learning based super-resolution (SR) and de-noising (DN) to enhance X-ray images from the European Space Agency's XMM-Newton telescope. Using XMM-Newton images in band [0.5, 2] keV from the European Photon Imaging Camera pn detector (EPIC-pn), we develop XMM-SuperRes and XMM-DeNoise - deep learning-based models that can generate enhanced SR and DN images from real observations. The models are trained on realistic XMM-Newton simulations such that XMM-SuperRes will output images with two times smaller point-spread function and with improved noise characteristics. The XMM-DeNoise model is trained to produce images with 2.5× the input exposure time from 20 to 50 ks. When tested on real images, DN improves the image quality by 8.2 per cent, as quantified by the global peak-signal-to-noise ratio. These enhanced images allow identification of features that are otherwise hard or impossible to perceive in the original or in filtered/smoothed images with traditional methods. We demonstrate the feasibility of using our deep learning models to enhance XMM-Newton X-ray images to increase their scientific value in a way that could benefit the legacy of the XMM-Newton archive

Detecting Solar system objects with convolutional neural networks

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X-ray properties of X-CLASS-redMaPPer galaxy cluster sample: The luminosity-temperature relation

International audienceThis paper presents results of a spectroscopic analysis of the X-CLASS-redMaPPer (XC1-RM) galaxy cluster sample. X-CLASS is a serendipitous search for clusters in the X-ray wavebands based on the XMM-Newton archive, whereas redMaPPer is an optical cluster catalogue derived from the Sloan Digital Sky Survey (SDSS). The present sample comprises 92 X-ray extended sources identified in optical images within 1\arcmin~separation. The area covered by the cluster sample is $\sim$ 27 deg$^{2}$. The clusters span a wide redshift range (0.05 < z < 0.6) and 88 clusters benefit from spectrosopically confirmed redshifts using data from SDSS Data Release 14. We present an automated pipeline to derive the X-ray properties of the clusters in three distinct apertures: R\textsubscript{500} (at fixed mass overdensity), R\textsubscript{fit} (at fixed signal-to-noise ratio), R\textsubscript{300kpc} (fixed physical radius). The sample extends over wide temperature and luminosity ranges: from 1 to 10 keV and from 6$\times$10$^{42}$ to 11$\times$10$^{44}$ erg\,s$^{-1}$, respectively. We investigate the luminosity-temperature (L-T) relation of the XC1-RM sample and find a slope equals to 3.03 $\pm$ 0.26. It is steeper than predicted by self-similar assumptions, in agreement with independent studies. A simplified approach is developed to estimate the amount and impact of selection biases which might be affecting our recovered L-T parameters. The result of this simulation process suggests that the measured L-T relation is biased to a steeper slope and higher normalization

XXL Survey groups and clusters in the Hyper Suprime-Cam Survey. Scaling relations between X-ray properties and weak lensing mass

International audienceScaling relations trace the formation and evolution of galaxy clusters. We exploited multi-wavelength surveys -- the XXL survey at \emph{XMM-Newton} in the X-ray band, and the Hyper Suprime-Cam Subaru Strategic Program for optical weak lensing -- to study an X-ray selected, complete sample of clusters and groups. The scalings of gas mass, temperature, and soft-band X-ray luminosity with the weak lensing mass show imprints of radiative cooling and AGN feedback in groups. From the multi-variate analysis, we found some evidence for steeper than self-similar slopes for gas mass ($\beta_{m_\text{g}|m}=1.73 \pm0.80$) and luminosity ($\beta_{l|m}=1.91\pm0.94$) and a nearly self-similar slope for the temperature ($\beta_{t|m}=0.78\pm0.43$). Intrinsic scatters of X-ray properties appear to be positively correlated at a fixed mass (median correlation factor $\rho_{X_1X_2|m}\sim0.34$) due to dynamical state and merger history of the halos. Positive correlations with the weak lensing mass (median correlation factor $\rho_{m_\text{wl}X|m}\sim0.35$) can be connected to triaxiality and orientation. Comparison of weak lensing and hydrostatic masses suggests a small role played by non-thermal pressure support ($9\pm17\%$)