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Let me introduce you to CLOThIlde, my project awarded with a Marie Curie IF Fellowship from the H2020 Framework.

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CLOThIlde stands for The Cluster Observations and Theory Intersection: Providing selection functions and scaling relations to set constraints on the physics of the accelerating universe. 

 

GOAL: The main goal of CLOThIlde is the to characterise the observational relations used to obtain cosmological constraints using clusters.

 

To obtain cosmological constraints, we basically need to compare the observed number of clusters as a function of redshift and mass with the expected ones. The expected number of clusters can be modeled as:

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And this relation depends on two main observable relations: (1) the observable-mass relation and (2) the survey selection function. These are the main relations that we are going to characterise.

 

DATA: In order to have high precission results, we need large amount of data. We choose to work with the expected data coming from the next-generation surveys in the IR (Euclid) and the optical (J-PAS). We have eventually added LSST as a concurrent survey. To have update information about these surveys, just check the above links.

 

METHODOLOGY: The first step of the project consists on the creation of realistic cosmological simulations that mimic well the observed properties of galaxy clusters. In order to do this, we used PhotReal (Ascaso et al. 2015) and applied it to the Merson et al. 2003 publicly available EUCLID catalogues to create mock catalogues for Euclid, LSST and J-PAS.

 

The second step runs the Bayesian Cluster Finder (Ascaso et al. 2012) on these cosmological simulations to obtain a list of detections from which we can work.

CLOThIlde

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The third step uses the previous results to compute completeness and purity rates, from which we will estimate the selection function by imposing both quantities >80% (Ascaso et al. 2016, 2017, see also Figure). These results were confirmed using available datasets with reliable X-rays, WL or SZ measurements.

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The fourth step is focus on designing the best halo mass proxy in the optical from which we can estimate a low-scatter mass-observable relation. We have used three different measures, obtaining similar scatter level, comparable to previous works in wider redshift and mass ranges (Ascaso et al. 2016, 2017).

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The final step finally, puts together the results obtained in the third and fourth step to compute the cluster counts. It builds a likelihood model dependent on cosmological parameters that we fit using a Fisher Matrix approach and a MCMC approach. For some results, check Sartoris et al. 2016 or Benítez et al. 2014.

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Figure: Selection function of Euclid, LSST and J-PAS

(Ascaso et al. 2016, 2017) compared to

eROSITA, ACTpol and SPTpol selection functions.

RESULTS: Some of the results of the project can be found in the following papers:

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To know more about the project you can read the cited papers or ask me directly. 

 

ADDITIONAL RESOURCES: Here you will find a general presentation on the overall project. 

 

ACKNOWLEDGEMENTS: This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 656354

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