Regularization of P-P and P-S converted waves data through the FO-CRS traveltime approximation

Santos, Raphael Di Carlo Silva dos; Cruz, João Carlos Ribeiro; Fernandes, Alexandre

doi:10.22564/8simbgf2018.087

Cited by 12 publications

(27 citation statements)

References 9 publications

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“…In the lower panels of Figure 2 we show how the bimodality disappears at z > 0.2, while the cool-core clusters become dominant in the range z > 0.35. Given the coarse redshift binning, this is not in contradiction with previous claims on the dearth of cool-core clusters at z > 0.7 (see Santos et al 2008), considering that we have only 7 clusters at z > 0.7. In addition, we note that the requirement on the S/N slightly favors CC clusters as the redshift increases.…”

Section: Imaging and Spectral Analysissupporting

confidence: 68%

“…However, since this is not the main focus of this paper, we will not make further analysis on the cool-core properties of the clusters, but merely investigate the global fraction of cool cores in our sample. Using c SB < 0.075 and c SB > 0.155 as the thresholds between non-cool-core/weak cool-core, and weak/strong cool-core clusters, respectively (see Santos et al 2008), we find that 72 clusters in our sample are non-cool-core clusters, while 46 and 68 are weak-and strongcool-core clusters. These numbers correspond to a percentage of 38.7%, 24.7% and 36.6% of non-cool-core, weak-cool-core and strong-cool-core clusters, respectively.…”

Section: Imaging and Spectral Analysismentioning

confidence: 84%

“…Major mergers are observed to affect mostly the inner regions, while at large radii often shows a rather flat abundance distribution, similar to relaxed clusters (Urdampilleta et al 2019). There are many morphological parameters that can be used to determine whether a cluster is regular or not, such as the X-ray surface brightness concentration (Santos et al 2008;Cassano et al 2010), the power ratio (Buote & Tsai 1995, 1996, and the centroid shift (O'Hara et al 2006;Cassano et al 2010;Lovisari et al 2017). In this work we adopt the centroid shift parameter, which measures the variance of the separations between the X-ray peak and the centroids of emission obtained within a number of apertures of different radii:…”

Section: Sample Selectionmentioning

confidence: 99%

“…Since cool-core and non-cool-core clusters are significantly different in both the abundance and spatial distribution of iron in the ICM, we estimate the fraction of cool-core clusters in our sample with the surface brightness concentration c SB (Santos et al 2008(Santos et al , 2010, defined as the ratio of the fluxes observed within 40 kpc and 400 kpc:…”

Section: Imaging and Spectral Analysismentioning

confidence: 99%

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The chemical evolution of galaxy clusters: Dissecting the iron mass budget of the intracluster medium

Liu

Tozzi

Ettori

et al. 2020

A&A

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Aims. We study the chemical evolution of galaxy clusters by measuring the iron mass in the ICM after dissecting the abundance profiles into different components. Methods. We use Chandra archival observations of 186 morphologically regular clusters in the redshift range [0.04, 1.07]. For each cluster we compute the azimuthally-averaged iron abundance and gas density profiles. In particular, we aim at identifying a central peak in the iron distribution, associated with the central galaxy, and an approximately constant plateau reaching the largest observed radii, possibly associated with early enrichment occurred before and/or shortly after the virialization of the cluster. We are able to firmly identify the two components in the iron distribution in a significant fraction of the sample, simply relying on the fit of the iron abundance profile. From the abundance and ICM density profiles we compute the iron mass included in the iron peak and iron plateau, and the gas mass-weighted iron abundance of the ICM, out to an extraction radius of 0.4 r 500 and, extending the abundance profile as a constant, to r 500 . Results. We find that the iron plateau shows no evolution with redshift. On the other hand, we find marginal (< 2σ c.l.) decrease with redshift in the iron mass included in the iron peak rescaled by the gas mass. We measure that the fraction of iron peak mass is typically a few percent (∼ 1%) of the total iron mass within r 500 . Therefore, since the total iron mass budget is dominated by the plateau, we find consistently that the global gas mass-weighted iron abundance does not evolve significantly across our sample. We are also able to reproduce past claims of evolution in the global iron abundance, which turn out to be due to the use of cluster samples with different selection methods combined to the use of emission-weighted instead of gas mass-weighted abundance values. Finally, while the intrinsic scatter in the iron plateau mass is consistent with zero, the iron peak mass exhibits a large scatter, in line with the fact that the peak is produced after the virialization of the halo and depends on the formation history of the hosting cool core and the strength of the associated feedback processes. Conclusions. We conclude that only a spatially-resolved approach can resolve the issue of the iron abundance evolution in the ICM, reconciling the contradictory results obtained in the last ten years. Evolutionary effects below z ∼ 1 are marginally measurable with present-day data, while at z > 1 the constraints are severely limited by the poor knowledge of the high-z cluster population. The path towards a full and comprehensive chemical history of the ICM necessarily requires the use of high-angular resolution X-ray bolometers and a dramatic increase in the statistics of faint, extended X-ray sources.

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Section: Imaging and Spectral Analysissupporting

confidence: 68%

Section: Imaging and Spectral Analysismentioning

confidence: 84%

Section: Sample Selectionmentioning

confidence: 99%

Section: Imaging and Spectral Analysismentioning

confidence: 99%

See 2 more Smart Citations

The chemical evolution of galaxy clusters: Dissecting the iron mass budget of the intracluster medium

Liu

Tozzi

Ettori

et al. 2020

A&A

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show abstract

“…Even in the low-signal regime, there are subtle observable signals that can offer key insights for improving cluster mass estimates. Measures of cluster morphology, including surface brightness concentration (e.g., Santos et al 2008), centroid shift (e.g., Mohr et al 1993), and morphological composite parameters (e.g., , provide additional information about a cluster's dynamical state (Mantz et al 2015a), which has been shown to influence the scatter in the mass-T X relationship of simulated clusters (Ventimiglia et al 2008), the correlated scatter in the relationship between weak lensing mass and integrated SZ Compton parameter Y sph (e.g., Angulo et al 2012;Marrone et al 2012;Shirasaki et al 2016), and the probability that a cluster is observed (Eckert et al 2011;Planck Collaboration et al 2011;Lovisari et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Using X-Ray Morphological Parameters to Strengthen Galaxy Cluster Mass Estimates via Machine Learning

Green

Ntampaka

Nagai

et al. 2019

ApJ

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We present a machine-learning approach for estimating galaxy cluster masses, trained using both Chandra and eROSITA mock X-ray observations of 2041 clusters from the Magneticum simulations. We train a random forest (RF) regressor, an ensemble learning method based on decision tree regression, to predict cluster masses using an input feature set. The feature set uses core-excised X-ray luminosity and a variety of morphological parameters, including surface brightness concentration, smoothness, asymmetry, power ratios, and ellipticity. The regressor is cross-validated and calibrated on a training sample of 1615 clusters (80% of sample), and then results are reported as applied to a test sample of 426 clusters (20% of sample). This procedure is performed for two different mock observation series in an effort to bracket the potential enhancement in mass predictions that can be made possible by including dynamical state information. The first series is computed from idealized Chandra-like mock cluster observations, with high spatial resolution, long exposure time (1 Ms), and the absence of background. The second series is computed from realistic-condition eROSITA mocks with lower spatial resolution, short exposures (2 ks), instrument effects, and background photons modeled. We report a 20% reduction in the mass estimation scatter when either series is used in our RF model compared to a standard regression model that only employs core-excised luminosity. The morphological parameters that hold the highest feature importance are smoothness, asymmetry, and surface brightness concentration. Hence these parameters, which encode the dynamical state of the cluster, can be used to make more accurate predictions of cluster masses in upcoming surveys, offering a crucial step forward for cosmological analyses.

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A LOFAR study of non-merging massive galaxy clusters

Savini

Bonafede

Brüggen

et al. 2019

A&A

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Centrally located diffuse radio emission has been observed in both merging and non-merging galaxy clusters. Depending on their morphology and size, we distinguish between giant radio haloes, which occur predominantly in merging clusters, and mini haloes, which are found in non-merging, cool-core clusters. In recent years, cluster-scale radio emission has also been observed in clusters with no sign of major mergers, showing that our knowledge of the mechanisms that lead to particle acceleration in the intra-cluster medium (ICM) is still incomplete. Low-frequency sensitive observations are required to assess whether the emission discovered in these few cases is common in galaxy clusters or not. With this aim, we carried out a campaign of observations with the LOw Frequency ARay (LOFAR) in the frequency range 120 -168 MHz of nine massive clusters selected from the Planck SZ catalogue, which had no sign of major mergers. In this paper, we discuss the results of the observations that have led to the largest cluster sample studied within the LOFAR Two-metre Sky Survey, and we present Chandra X-ray data used to investigate the dynamical state of the clusters, verifying that the clusters are currently not undergoing major mergers, and to search for traces of minor or off-axis mergers. We discover large-scale steep-spectrum emission around mini haloes in the cool-core clusters PSZ1G139.61+24 and RXJ1720.1+2638, which is not observed around the mini halo in the non-cool-core cluster A1413. We also discover a new 570 kpc-halo in the noncool-core cluster RXCJ0142.0+2131. We derived new upper limits to the radio power for clusters in which no diffuse radio emission was found, and we discuss the implication of our results to constrain the cosmic-ray energy budget in the ICM. We conclude that radio emission in non-merging massive clusters is not common at the sensitivity level reached by our observations and that no clear connection with the cluster dynamical state is observed. Our results might indicate that the sloshing of a dense cool core could trigger particle acceleration on larger scales and generate steep-spectrum radio emission.

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Regularization of P-P and P-S converted waves data through the FO-CRS traveltime approximation

Cited by 12 publications

References 9 publications

The chemical evolution of galaxy clusters: Dissecting the iron mass budget of the intracluster medium

The chemical evolution of galaxy clusters: Dissecting the iron mass budget of the intracluster medium

Using X-Ray Morphological Parameters to Strengthen Galaxy Cluster Mass Estimates via Machine Learning

A LOFAR study of non-merging massive galaxy clusters

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