16 research outputs found
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 âcosmic scalesâ 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- forest power spectrum at redshift
Inhomogeneous reionization enhances the 1D Lyman- forest power
spectrum on large scales at redshifts . 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
. We use the Sherwood-Relics suite
of hybrid radiation hydrodynamical simulations to perform a first analysis of
new Lyman- forest power spectrum measurements at .
These data extend to wavenumbers , with
a relative uncertainty of -- per cent in each wavenumber bin. Our
analysis returns a preference for an enhancement in the
Lyman- 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 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 â„ 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/kmâ1âs) âČ â1.5. 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/kmâ1âs) â â3, with a relative uncertainty of 10â20 per cent in each wavenumber bin. Our analysis returns a 2.7Ï 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 âČ 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 2.5Ă 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
Depletion of follicular B cell-derived antibody secreting cells does not attenuate angiotensin II-induced hypertension or vascular compliance
IntroductionMarginal zone and follicular B cells are known to contribute to the development of angiotensin II-induced hypertension in mice, but the effector function(s) mediating this effect (e.g., antigen presentation, antibody secretion and/or cytokine production) are unknown. B cell differentiation into antibody secreting cells (ASCs) requires the transcription factor Blimp-1. Here, we studied mice with a Blimp-1 deficiency in follicular B cells to evaluate whether antibody secretion underlies the pro-hypertensive action of B cells.Methods10- to 14-week-old male follicular B cell Blimp-1 knockout (FoB-Blimp-1-KO) and floxed control mice were subcutaneously infused with angiotensin II (0.7â
mg/kg/d) or vehicle (0.1% acetic acid in saline) for 28 days. BP was measured by tail-cuff plethysmography or radiotelemetry. Pulse wave velocity was measured by ultrasound. Aortic collagen was quantified by Masson's trichrome staining. Cell types and serum antibodies were quantified by flow cytometry and a bead-based multiplex assay, respectively.ResultsIn control mice, angiotensin II modestly increased serum IgG3 levels and markedly increased BP, cardiac hypertrophy, aortic stiffening and fibrosis. FoB-Blimp-1-KO mice exhibited impaired IgG1, IgG2a and IgG3 production despite having comparable numbers of B cells and ASCs to control mice. Nevertheless, FoB-Blimp-1-KO mice still developed hypertension, cardiac hypertrophy, aortic stiffening and fibrosis following angiotensin II infusion.ConclusionsInhibition of follicular B cell differentiation into ASCs did not protect against angiotensin II-induced hypertension or vascular compliance. Follicular B cell functions independent of their differentiation into ASCs and ability to produce high-affinity antibodies, or other B cell subtypes, are likely to be involved in angiotensin II-induced hypertension
Detecting Solar system objects with convolutional neural networks
International audienc
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 27 deg. 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 610 to 1110 erg\,s, respectively. We investigate the luminosity-temperature (L-T) relation of the XC1-RM sample and find a slope equals to 3.03 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