scholarly journals Constraints on the Matter Fluctuation Spectrum from X-Ray Cluster Number Counts

1998 ◽  
Vol 188 ◽  
pp. 314-314
Author(s):  
Tetsu Kitayama ◽  
Yasushi Suto
Keyword(s):  
Cold Dark Matter ◽  
Theoretical Modelling ◽  
Density Parameter ◽  
Cluster Number ◽  
New Approach ◽  
X Ray ◽  
Fluctuation Amplitude ◽  
Number Counts ◽  
Cosmological Constants ◽  
Best Fit

We find that the observed logN-logS relation of X-ray clusters (Ebeling et al. 1997; Rosati et al. 1997) can be reproduced remarkably well with a certain range of values for the fluctuation amplitude σ8 and the cosmological density parameter Ω0 in cold dark matter (CDM) universes (Kitayama & Suto 1997). The 1σ confidence limits on σ8 in the CDM models with n = 1 and h = 0.7 are expressed as (0.54 ± 0.02)Ω−0.35-0.82Ω0+0.55Ω200 (λ0 = 1 - Ω0) and (0.54 ± 0.02) Ω−0.28-0.91Ω0+0.68Ω200 (λ0 = 0), where n is the primordial spectral index, and h and λ0 are the dimensionless Hubble and cosmological constants. The errors quoted above indicate the statistical ones from the observed logN-logS only, and the systematic uncertainty from our theoretical modelling of X-ray flux in the best-fit value of σ8 is about 15%. In the case of n = 1, we find that the CDM models with (Ω0, λ0, h, σ8) ≃ (0.3, 0.7, 0.7, 1) and (0.45, 0, 0.7, 0.8) simultaneously account for the cluster logN-logS, X-ray temperature functions, and the normalization from the COBE 4 year data. The derived values assume the observations are without systematic errors, and we discuss in details other theoretical uncertainties which may change the limits on Ω0 and σ8 from the logN-logS relation. We have shown the power of this new approach which will become a strong tool as the observations attain more precision.

scholarly journals A Monte Carlo study of cosmological parameter estimators from galaxy cluster number counts

2014 ◽  
Vol 10 (S306) ◽  
pp. 262-265
Author(s):  
Mariana Penna-Lima ◽  
Martín Makler ◽  
Carlos A. Wuensche
Keyword(s):  
Monte Carlo ◽  
Dark Energy ◽  
Cold Dark Matter ◽  
High Redshift ◽  
Cosmological Parameters ◽  
State Parameter ◽  
Monte Carlo Study ◽  
Density Parameter ◽  
Cluster Number ◽  
Number Counts

AbstractModels for galaxy clusters abundance and their spatial distribution are sensitive to cosmological parameters. Present and future surveys will provide high-redshift sample of clusters, such as Dark Energy Survey (z ⩽ 1.3), making cluster number counts one of the most promising cosmological probes. In the literature, some cosmological analyses are carried out using small cluster catalogs (tens to hundreds), like in Sunyaev-Zel'dovich (SZ) surveys. However, it is not guaranteed that maximum likelihood estimators of cosmological parameters are unbiased in this scenario. In this work we study different estimators of the cold dark matter density parameter Ωc, σ8 and the dark energy equation of state parameter w0 obtained from cluster abundance. Using an unbinned likelihood for cluster number counts and the Monte Carlo approach, we determine the presence of bias and how it varies with the size of the sample. Our fiducial models are based on the South Pole Telescope (SPT). We show that the biases from SZ estimators do not go away with increasing sample sizes and they may become the dominant source of error for an all sky survey at the SPT sensitivity.

scholarly journals Number Counts of Clusters of Galaxies in X-ray and Submm Bands

1999 ◽  
Vol 183 ◽  
pp. 255-255 ◽  
Author(s):  
Tetsu Kitayama ◽  
Shin Sasaki ◽  
Yasushi Suto
Keyword(s):  
Theoretical Models ◽  
Model Parameters ◽  
Clusters Of Galaxies ◽  
Cluster Number ◽  
Parameter Region ◽  
X Ray ◽  
Background Radiations ◽  
The Press ◽  
Number Counts ◽  
Acceptable Parameter

We compute the number counts of clusters of galaxies, the logN-logS relation, in several X-ray and submm bands on the basis of the Press—Schechter theory (Kitayama et al. 1998). We pay particular attention to a set of theoretical models which well reproduce the ROSAT 0.5–2 keV band logN-logS (Ebeling et al. 1997; Rosati et al. 1997), and explore possibilities to further constrain the models from future observations with ASCA and/or at submm bands. The latter is closely related to the European PLANCK mission and the Japanese LMSA project. We exhibit that one can break the degeneracy in an acceptable parameter region on the Ω0–σ8 plane by combining the ROSAT logN-logS and the submm number counts. Models which reproduce the ROSAT band logN-logS will have N(> S) ∼ (150–300)(S/10−12 erg cm−2 s−) −1.3 str−1 at S ≳ 10−12 erg cm−2 s−1 in the ASCA 2–10 keV band, and N(> Sv) ∼ (102–104)(Sv/100 mJy)−1.5 str−1 at Sv ≳ 100m J y in the submm (0.85mm) band. The amplitude of the logN-logS is very sensitive to the model parameters in the submm band. We also compute the redshift evolution of the cluster number counts and compare with that of the X-ray brightest Abell-type clusters (Ebeling et al. 1996). The results, although still preliminary, point to low density (Ω0 ∼ 0.3) universes. The contribution of clusters to the X-ray and submm background radiations is shown to be insignificant in any model compatible with the ROSAT logN-logS.

scholarly journals The XXL Survey

2018 ◽  
Vol 620 ◽  
pp. A1 ◽  
Author(s):  
F. Marulli ◽  
A. Veropalumbo ◽  
M. Sereno ◽  
L. Moscardini ◽  
F. Pacaud ◽  
...  
Keyword(s):  
Correlation Function ◽  
Galaxy Clusters ◽  
Cluster Number ◽  
X Ray ◽  
Mass Scaling ◽  
Cosmological Constraints ◽  
Density Peaks ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Number Counts

Context.Galaxy clusters trace the highest density peaks in the large-scale structure of the Universe. Their clustering provides a powerful probe that can be exploited in combination with cluster mass measurements to strengthen the cosmological constraints provided by cluster number counts.Aims.We investigate the spatial properties of a homogeneous sample of X-ray selected galaxy clusters from the XXL survey, the largest programme carried out by theXMM-Newtonsatellite. The measurements are compared to Λ-cold dark matter predictions, and used in combination with self-calibrated mass scaling relations to constrain the effective bias of the sample,beff, and the matter density contrast, ΩM.Methods.We measured the angle-averaged two-point correlation function of the XXL cluster sample. The analysed catalogue consists of 182 X-ray selected clusters from the XXL second data release, with median redshift ⟨z⟩ = 0.317 and median mass ⟨M500⟩≃ 1.3 × 1014M⊙. A Markov chain Monte Carlo analysis is performed to extract cosmological constraints using a likelihood function constructed to be independent of the cluster selection function.Results.Modelling the redshift-space clustering in the scale range 10 <r[h−1Mpc] < 40, we obtain ΩM= 0.27−0.04+0.06andbeff= 2.73−0.20+0.18.This is the first time the two-point correlation function of an X-ray selected cluster catalogue at such relatively high redshifts and low masses has been measured. The XXL cluster clustering appears fully consistent with standard cosmological predictions. The analysis presented in this work demonstrates the feasibility of a cosmological exploitation of the XXL cluster clustering, paving the way for a combined analysis of XXL cluster number counts and clustering.

scholarly journals Dark Matter Sterile Neutrino from Scalar Decays

Universe ◽  
2021 ◽  
Vol 7 (8) ◽  
pp. 309
Author(s):  
Lucia Aurelia Popa
Keyword(s):  
Dark Matter ◽  
Gravitational Potential ◽  
Cold Dark Matter ◽  
Sterile Neutrino ◽  
Sterile Neutrinos ◽  
X Ray ◽  
Linear Effects ◽  
Best Fit ◽  
Neutrino Decay ◽  
Matter Energy

We place constraints on DM sterile neutrino scalar decay production (SDP) assuming that sterile neutrinos representa fraction from the total Cold Dark Matter energy density. For the cosmological analysis we complement the CMB anisotropy measurements with CMB lensing gravitational potential measurements, that are sensitive to the DM distribution to high redshifts and with the cosmic shear data that constrain the gravitational potential at lower redshifts than CMB. We also use the most recent low-redshift BAO measurements that are insensitive to the non-linear effects, providing robust geometrical tests. We show that our datasets have enough sensitivity to constrain the sterile neutrino mass mνs and the mass fraction fS inside the co-moving free-streaming horizon. We find that the best fit value mνs=7.88±0.73 keV (68% CL) is in the parameter space of interest for DM sterile neutrino decay interpretation of the 3.5 keV X-ray line and that fS=0.86±0.07 (68% CL) is in agreement with the upper limit constraint on fS from the X-ray non-detection and Ly-α forest measurements that rejects fS=1 at 3σ. However, we expect that the future BAO and weak lensing surveys, such as EUCLID, will provide much more robust constraints.

scholarly journals Cosmic expansion and structure formation in running vacuum cosmologies

2015 ◽  
Vol 30 (22) ◽  
pp. 1540031 ◽  
Author(s):  
Spyros Basilakos
Keyword(s):  
Large Scale ◽  
Cold Dark Matter ◽  
Vacuum Energy ◽  
Dynamical Evolution ◽  
Quantum Field ◽  
Cluster Number ◽  
Energy Behavior ◽  
Collapse Model ◽  
Number Counts ◽  
Structure Properties

We investigate the dynamics of the Friedmann–Lemaître–Robertson–Walker (FLRW) flat cosmological models in which the vacuum energy varies with redshift. A particularly well-motivated model of this type is the so-called quantum field vacuum, in which both kind of terms [Formula: see text] and constant appear in the effective dark energy (DE) density affecting the evolution of the main cosmological functions at the background and perturbation levels. Specifically, it turns out that the functional form of the quantum vacuum endows the vacuum energy of a mild dynamical evolution which could be observed nowadays and appears as dynamical DE. Interestingly, the low-energy behavior is very close to the usual Lambda cold dark matter (ΛCDM) model, but it is by no means identical. Finally, within the framework of the quantum field vacuum we generalize the large scale structure properties, namely growth of matter perturbations, cluster number counts and spherical collapse model.

Some Problems in Understanding the Solar Corona

1994 ◽  
Vol 144 ◽  
pp. 1-9
Author(s):  
A. H. Gabriel
Keyword(s):  
Solar Corona ◽  
Solar Atmosphere ◽  
Theoretical Modelling ◽  
Total System ◽  
Major Advance ◽  
X Ray ◽  
Proper Perspective ◽  
Space Observations

The development of the physics of the solar atmosphere during the last 50 years has been greatly influenced by the increasing capability of observations made from space. Access to images and spectra of the hotter plasma in the UV, XUV and X-ray regions provided a major advance over the few coronal forbidden lines seen in the visible and enabled the cooler chromospheric and photospheric plasma to be seen in its proper perspective, as part of a total system. In this way space observations have stimulated new and important advances, not only in space but also in ground-based observations and theoretical modelling, so that today we find a well-balanced harmony between the three techniques.

scholarly journals Methodology and Models for Individuals’ Creditworthiness Management Using Digital Footprint Data and Machine Learning Methods

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1820
Author(s):  
Ekaterina V. Orlova
Keyword(s):  
Interest Rates ◽  
Additional Data ◽  
Risk Level ◽  
Gradient Boosting ◽  
Cluster Number ◽  
New Approach ◽  
Credit Risks ◽  
Stochastic Gradient Boosting ◽  
The Stability ◽  
Digital Footprints

This research deals with the challenge of reducing banks’ credit risks associated with the insolvency of borrowing individuals. To solve this challenge, we propose a new approach, methodology and models for assessing individual creditworthiness, with additional data about borrowers’ digital footprints to implement comprehensive analysis and prediction of a borrower’s credit profile. We suggest a model for borrowers’ clustering based on the method of hierarchical clustering and the k-means method, which groups actual borrowers having similar creditworthiness and similar credit risks into homogeneous clusters. We also design the model for borrowers’ classification based on the stochastic gradient boosting (SGB) method, which reliably determines the cluster number and therefore the risk level for a new borrower. The developed models are the basis for decision making regarding the decision about lending value, interest rates and lending terms for each risk-homogeneous borrower’s group. The modified version of the methodology for assessing individual creditworthiness is presented, which is to reduce the credit risks and to increase the stability and profitability of financial organizations.

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