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M. Lieu

Publications and source records attributed to M. Lieu.

14 recordsLinked to original sources

A New Emulated Monte Carlo Radiative Transfer Disk-Wind Model: X-Ray Accretion Disk-wind Emulator -- XRADE

We present a new X-Ray Accretion Disk-wind Emulator (\textsc{xrade}) based on the 2.5D Monte Carlo radiative transfer code which provides a physically-motivated, self-consistent treatment of both absorption and emission from a disk-wind by computing the local ionization state and velocity field within the flow. \textsc{xrade} is then implemented through a process that combines X-ray tracing with supervised machine learning. We develop a novel emulation method consisting in training, validating, and testing the simulated disk-wind spectra into a purposely built artificial neural network. The trained emulator can generate a single synthetic spectrum for a particular parameter set in a fraction of a second, in contrast to the few hours required by a standard Monte Carlo radiative transfer pipeline. The emulator does not suffer from interpolation issues with multi-dimensional spaces that are typically faced by traditional X-ray fitting packages such as \textsc{xspec}. \textsc{xrade} will be suitable to a wide number of sources across the black-hole mass, ionizing luminosity, and accretion rate scales. As an example, we demonstrate the applicability of \textsc{xrade} to the physical interpretation of the X-ray spectra of the bright quasar PDS 456, which hosts the best-established accretion-disk wind observed to date. We anticipate that our emulation method will be an indispensable tool for the development of high-resolution theoretical models, with the necessary flexibility to be optimized for the next generation micro-calorimeters on board future missions, like \textit{XRISM/resolve} and \textit{Athena/X-IFU}. This tool can also be implemented across a wide variety of X-ray spectral models and beyond.

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AGN X-ray Spectroscopy with Neural Networks

We explore the possibility of using machine learning to estimate physical parameters directly from AGN X-ray spectra without needing computationally expensive spectral fitting. Specifically, we consider survey quality data, rather than long pointed observations, to ensure that this approach works in the regime where it is most likely to be applied. We simulate Athena WFI spectra of AGN with warm absorbers, and train simple neural networks to estimate the ionisation and column density of the absorbers. We find that this approach can give comparable accuracy to spectral fitting, without the risk of outliers caused by the fit sticking in a false minimum, and with an improvement of around three orders of magnitude in speed. We also demonstrate that using principal component analysis to reduce the dimensionality of the data prior to inputting it into the neural net can significantly increase the accuracy of the parameter estimation for negligible computational cost, while also allowing a simpler network architecture to be used.

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The X-CLASS survey: A catalogue of 1646 X-ray-selected galaxy clusters up to z$\sim$1.5

Cosmological probes based on galaxy clusters rely on cluster number counts and large-scale structure information. X-ray cluster surveys are well suited for this purpose, since they are far less affected than optical surveys by projection effects, and cluster properties can be predicted with good accuracy. The XMM Cluster Archive Super Survey, X-CLASS, is a serendipitous search of X-ray-detected galaxy clusters in 4176 XMM-Newton archival observations until August 2015. All observations are clipped to exposure times of 10 and 20 ks to obtain uniformity and they span ~269 deg$^2$ across the high-Galactic latitude sky ($|b|> 20^o$). The main goal of the survey is the compilation of a well-selected cluster sample suitable for cosmological analyses. We describe the detection algorithm, the visual inspection, the verification process and the redshift validation of the cluster sample, as well as the cluster selection function computed by simulations. We also present the various metadata that are released with the catalogue, along with the redshifts of 124 clusters obtained with a dedicated multi-object spectroscopic follow-up programme. With this publication we release the new X-CLASS catalogue of 1646 well-selected X-ray-detected clusters over a wide sky area, along with their selection function. The sample spans a wide redshift range, from the local Universe up to z~1.5, with 982 spectroscopically confirmed clusters, and over 70 clusters above z=0.8. Because of its homogeneous selection and thorough verification, the cluster sample can be used for cosmological analyses, but also as a test-bed for the upcoming eROSITA observations and other current and future large-area cluster surveys. It is the first time that such a catalogue is made available to the community via an interactive database which gives access to a wealth of supplementary information, images, and data.

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Understanding X-ray and optical selection of galaxy clusters: A comparison of the XXL and CAMIRA cluster catalogues obtained in the common XXL-HSC SSP area

Large samples of galaxy clusters provide knowledge of both astrophysics in the most massive virialised environments and the properties of the cosmological model that defines our Universe. However, an important issue that affects the interpretation of galaxy cluster samples is the role played by the selection waveband and the potential for this to introduce a bias in the physical properties of clusters thus selected. We aim to investigate waveband-dependent selection effects in the identification of galaxy clusters by comparing the X-ray Multi-Mirror (XMM) Ultimate Extra-galactic Survey (XXL) and Subaru Hyper Suprime-Cam (HSC) CAMIRA cluster samples identified from a common 22.6 deg2 sky area. We compare 150 XXL and 270 CAMIRA clusters in a common parameter space defined by X-ray aperture brightness and optical richness. We find that 71/150 XXL clusters are matched to the location of a CAMIRA cluster, the majority of which (67/71) display richness values N>15 that exceed the CAMIRA catalogue richness threshold. We find that 67/270 CAMIRA clusters are matched to the location of an XXL cluster (defined within XXL as an extended X-ray source). Of the unmatched CAMIRA clusters, the majority display low X-ray fluxes consistent with the lack of an XXL counterpart. However, a significant fraction (64/107) CAMIRA clusters that display high X-ray fluxes are not asociated with an extended source in the XXL catalogue. We demonstrate that this disparity arises from a variety of effects including the morphological criteria employed to identify X-ray clusters and the properties of the XMM PSF.

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The XXL Survey XXV. Cosmological analysis of the C1 cluster number counts

Context. We present an estimation of cosmological parameters with clusters of galaxies. Aims. We constrain the $\Omega_m$, $\sigma_8$, and $w$ parameters from a stand-alone sample of X-ray clusters detected in the 50 deg$^2$ XMM-XXL survey with a well-defined selection function. Methods. We analyse the redshift distribution of a sample comprising 178 high S/N clusters out to a redshift of unity. The cluster sample scaling relations are determined in a self-consistent manner. Results. In a lambda cold dark matter ($\Lambda$CDM) model, the cosmology favoured by the XXL clusters compares well with results derived from the Planck S-Z clusters for a totally different sample (mass/redshift range, selection biases, and scaling relations). However, with this preliminary sample and current mass calibration uncertainty, we find no inconsistency with the Planck CMB cosmology. If we relax the $w$ parameter, the Planck CMB uncertainties increase by a factor of $\sim$10 and become comparable with those from XXL clusters. Combining the two probes allows us to put constraints on $\Omega_m$=0.316$\pm$0.060, $\sigma_8$=0.814$\pm$0.054, and $w$=-1.02$\pm$0.20. Conclusions. This first self-consistent cosmological analysis of a sample of serendipitous XMM clusters already provides interesting insights into the constraining power of the XXL survey. Subsequent analysis will use a larger sample extending to lower confidence detections and include additional observable information, potentially improving posterior uncertainties by roughly a factor of 3.

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The XXL survey: first results and future

The XXL survey currently covers two 25 sq. deg. patches with XMM observations of ~10ks. We summarise the scientific results associated with the first release of the XXL data set, that occurred mid 2016. We review several arguments for increasing the survey depth to 40 ks during the next decade of XMM operations. X-ray (z<2) cluster, (z<4) AGN and cosmic background survey science will then benefit from an extraordinary data reservoir. This, combined with deep multi-$λ$ observations, will lead to solid standalone cosmological constraints and provide a wealth of information on the formation and evolution of AGN, clusters and the X-ray background. In particular, it will offer a unique opportunity to pinpoint the z>1 cluster density. It will eventually constitute a reference study and an ideal calibration field for the upcoming eROSITA and Euclid missions.

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The XXL survey XV: Evidence for dry merger driven BCG growth in XXL-100-GC X-ray clusters

The growth of brightest cluster galaxies is closely related to the properties of their host cluster. We present evidence for dry mergers as the dominant source of BCG mass growth at $z\lesssim1$ in the XXL 100 brightest cluster sample. We use the global red sequence, H$α$ emission and mean star formation history to show that BCGs in the sample possess star formation levels comparable to field ellipticals of similar stellar mass and redshift. XXL 100 brightest clusters are less massive on average than those in other X-ray selected samples such as LoCuSS or HIFLUGCS. Few clusters in the sample display high central gas concentration, rendering inefficient the growth of BCGs via star formation resulting from the accretion of cool gas. Using measures of the relaxation state of their host clusters, we show that BCGs grow as relaxation proceeds. We find that the BCG stellar mass corresponds to a relatively constant fraction 1\%\ of the total cluster mass in relaxed systems. We also show that, following a cluster scale merger event, the BCG stellar mass lags behind the expected value from the M$_{cluster}$ - M$_{BCG}$ relation but subsequently accretes stellar mass via dry mergers as the BCG and cluster evolve towards a relaxed state.

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The XXL Survey X: K-band luminosity - weak-lensing mass relation for groups and clusters of galaxies

We present the K-band luminosity-halo mass relation, $L_{K,500}-M_{500,WL}$, for a subsample of 20 of the 100 brightest clusters in the XXL Survey observed with WIRCam at the Canada-France-Hawaii Telescope (CFHT). For the first time, we have measured this relation via weak-lensing analysis down to $M_{500,WL} =3.5 \times 10^{13}\,M_\odot$. This allows us to investigate whether the slope of the $L_K-M$ relation is different for groups and clusters, as seen in other works. The clusters in our sample span a wide range in mass, $M_{500,WL} =0.35-12.10 \times 10^{14}\,M_\odot$, at $0<z<0.6$. The K-band luminosity scales as $\log_{10}(L_{K,500}/10^{12}L_\odot) \propto βlog_{10}(M_{500,WL}/10^{14}M_\odot)$ with $β= 0.85^{+0.35}_{-0.27}$ and an intrinsic scatter of $σ_{lnL_K|M} =0.37^{+0.19}_{-0.17}$. Combining our sample with some clusters in the Local Cluster Substructure Survey (LoCuSS) present in the literature, we obtain a slope of $1.05^{+0.16}_{-0.14}$ and an intrinsic scatter of $0.14^{+0.09}_{-0.07}$. The flattening in the $L_K-M$ seen in previous works is not seen here and might be a result of a bias in the mass measurement due to assumptions on the dynamical state of the systems. We also study the richness-mass relation and find that group-sized halos have more galaxies per unit halo mass than massive clusters. However, the brightest cluster galaxy (BCG) in low-mass systems contributes a greater fraction to the total cluster light than BCGs do in massive clusters; the luminosity gap between the two brightest galaxies is more prominent for group-sized halos. This result is a natural outcome of the hierarchical growth of structures, where massive galaxies form and gain mass within low-mass groups and are ultimately accreted into more massive clusters to become either part of the BCG or one of the brighter galaxies. [Abridged]

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The XXL Survey: I. Scientific motivations - XMM-Newton observing plan - Follow-up observations and simulation programme

We present the XXL Survey, the largest XMM programme totaling some 6.9 Ms to date and involving an international consortium of roughly 100 members. The XXL Survey covers two extragalactic areas of 25 deg2 each at a point-source sensitivity of ~ 5E-15 erg/sec/cm2 in the [0.5-2] keV band (completeness limit). The survey's main goals are to provide constraints on the dark energy equation of state from the space-time distribution of clusters of galaxies and to serve as a pathfinder for future, wide-area X-ray missions. We review science objectives, including cluster studies, AGN evolution, and large-scale structure, that are being conducted with the support of approximately 30 follow-up programmes. We describe the 542 XMM observations along with the associated multi-lambda and numerical simulation programmes. We give a detailed account of the X-ray processing steps and describe innovative tools being developed for the cosmological analysis. The paper provides a thorough evaluation of the X-ray data, including quality controls, photon statistics, exposure and background maps, and sky coverage. Source catalogue construction and multi-lambda associations are briefly described. This material will be the basis for the calculation of the cluster and AGN selection functions, critical elements of the cosmological and science analyses. The XXL multi-lambda data set will have a unique lasting legacy value for cosmological and extragalactic studies and will serve as a calibration resource for future dark energy studies with clusters and other X-ray selected sources. With the present article, we release the XMM XXL photon and smoothed images along with the corresponding exposure maps. The XMM XXL observation list (Table B.1) is available in electronic form at the CDS. The present paper is the first in a series reporting results of the XXL-XMM survey.

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The XXL Survey. II. The bright cluster sample: catalogue and luminosity function

Context. The XXL Survey is the largest survey carried out by the XMM-Newton satellite and covers a total area of 50 square degrees distributed over two fields. It primarily aims at investigating the large-scale structures of the Universe using the distribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. Aims. This article presents the XXL bright cluster sample, a subsample of 100 galaxy clusters selected from the full XXL catalogue by setting a lower limit of $3\times 10^{-14}\,\mathrm{erg \,s^{-1}cm^{-2}}$ on the source flux within a 1$^{\prime}$ aperture. Methods. The selection function was estimated using a mixture of Monte Carlo simulations and analytical recipes that closely reproduce the source selection process. An extensive spectroscopic follow-up provided redshifts for 97 of the 100 clusters. We derived accurate X-ray parameters for all the sources. Scaling relations were self-consistently derived from the same sample in other publications of the series. On this basis, we study the number density, luminosity function, and spatial distribution of the sample. Results. The bright cluster sample consists of systems with masses between $M_{500}=7\times 10^{13}$ and $3\times 10^{14} M_\odot$, mostly located between $z=0.1$ and 0.5. The observed sky density of clusters is slightly below the predictions from the WMAP9 model, and significantly below the predictions from the Planck 2015 cosmology. In general, within the current uncertainties of the cluster mass calibration, models with higher values of $σ_8$ and/or $Ω_m$ appear more difficult to accommodate. We provide tight constraints on the cluster differential luminosity function and find no hint of evolution out to $z\sim1$. We also find strong evidence for the presence of large-scale structures in the XXL bright cluster sample and identify five new superclusters.

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The XXL Survey III. Luminosity-temperature relation of the Bright Cluster Sample

The XXL Survey is the largest homogeneous survey carried out with XMM-Newton. Covering an area of 50 deg$^{2}$, the survey contains several hundred galaxy clusters out to a redshift of $\approx$2 above an X-ray flux limit of $\sim$5$\times10^{-15}$ erg cm$^{-2}$ s$^{-1}$. This paper belongs to the first series of XXL papers focusing on the bright cluster sample. We investigate the luminosity-temperature (LT) relation for the brightest clusters detected in the XXL Survey, taking fully into account the selection biases. We investigate the form of the LT relation, placing constraints on its evolution. We have classified the 100 brightest clusters in the XXL Survey based on their measured X-ray flux. These 100 clusters have been analysed to determine their luminosity and temperature to evaluate the LT relation. We used three methods to fit the LT relation, with two of these methods providing a prescription to fully take into account the selection effects of the survey. We measure the evolution of the LT relation internally using the broad redshift range of the sample. Taking into account selection effects, we find a slope of the bolometric LT relation of B$_{\rm LT}=3.08\pm$0.15, steeper than the self-similar expectation (B$_{\rm LT}$=2). Our best-fit result for the evolution factor is $E(z)^{1.64\pm0.77}$, consistent with "strong self-similar" evolution where clusters scale self-similarly with both mass and redshift. However, this result is marginally stronger than "weak self-similar" evolution, where clusters scale with redshift alone. We investigate the sensitivity of our results to the assumptions made in our model, finding that using an external LT relation as a low-z baseline can have a profound effect on the measured evolution. However, more clusters are needed to break the degeneracy between the choice of likelihood model and mass-temperature relation on the derived evolution.

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The XXL Survey. XIII. Baryon content of the bright cluster sample

Traditionally, galaxy clusters have been expected to retain all the material accreted since their formation epoch. For this reason, their matter content should be representative of the Universe as a whole, and thus their baryon fraction should be close to the Universal baryon fraction. We make use of the sample of the 100 brightest galaxy clusters discovered in the XXL Survey to investigate the fraction of baryons in the form of hot gas and stars in the cluster population. We measure the gas masses of the detected halos and use a mass--temperature relation directly calibrated using weak-lensing measurements for a subset of XXL clusters to estimate the halo mass. We find that the weak-lensing calibrated gas fraction of XXL-100-GC clusters is substantially lower than was found in previous studies using hydrostatic masses. Our best-fit relation between gas fraction and mass reads $f_{\rm gas,500}=0.055_{-0.006}^{+0.007}\left(M_{\rm 500}/10^{14}M_\odot\right)^{0.21_{-0.10}^{+0.11}}$. The baryon budget of galaxy clusters therefore falls short of the Universal baryon fraction by about a factor of two at $r_{\rm 500}$. Our measurements require a hydrostatic bias $1-b=M_X/M_{\rm WL}=0.72_{-0.07}^{+0.08}$ to match the gas fraction obtained using lensing and hydrostatic equilibrium. Comparing our gas fraction measurements with the expectations from numerical simulations, our results favour an extreme feedback scheme in which a significant fraction of the baryons are expelled from the cores of halos. This model is, however, in contrast with the thermodynamical properties of observed halos, which might suggest that weak-lensing masses are overestimated. We note that a mass bias $1-b=0.58$ as required to reconcile Planck CMB and cluster counts should translate into an even lower baryon fraction, which poses a major challenge to our current understanding of galaxy clusters. [Abridged]

astro-ph.CO

LoCuSS: Testing hydrostatic equilibrium in galaxy clusters

We test the assumption of hydrostatic equilibrium in an X-ray luminosity selected sample of 50 galaxy clusters at $0.15<z<0.3$ from the Local Cluster Substructure Survey (LoCuSS). Our weak-lensing measurements of $M_{500}$ control systematic biases to sub-4 per cent, and our hydrostatic measurements of the same achieve excellent agreement between XMM-Newton and Chandra. The mean ratio of X-ray to lensing mass for these 50 clusters is $β_{\rm X}=0.95\pm0.05$, and for the 44 clusters also detected by Planck, the mean ratio of Planck mass estimate to LoCuSS lensing mass is $β_{\rm P}=0.95\pm0.04$. Based on a careful like-for-like analysis, we find that LoCuSS, the Canadian Cluster Comparison Project (CCCP), and Weighing the Giants (WtG) agree on $β_{\rm P}\simeq0.9-0.95$ at $0.15<z<0.3$. This small level of hydrostatic bias disagrees at $\sim5σ$ with the level required to reconcile Planck cosmology results from the cosmic microwave background and galaxy cluster counts.

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The XMM-LSS survey: the Class 1 cluster sample over the extended 11 deg$^2$ and its spatial distribution

This paper presents 52 X-ray bright galaxy clusters selected within the 11 deg$^2$ XMM-LSS survey. 51 of them have spectroscopic redshifts ($0.05 3 σ$) constraints on the presence of a large void in the cluster distribution. We work out alternative hypotheses and demonstrate that a negative redshift evolution in the normalization of the $L_{X}-T_X$ relation (with respect to a self-similar evolution) is a plausible explanation for the observed deficit. We confirm this evolutionary trend by directly studying how C1 clusters populate the $L_{X}-T_X-z$ space, properly accounting for selection biases. We point out that a systematically evolving, unresolved, central component in clusters and groups (AGN contamination or cool core) can impact the classification as extended sources and be partly responsible for the observed redshift distribution.[abridged]

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