About me

Linda Blot portraitI am a PostDoc researcher at the Institute of Space Sciences, in the Cosmology & Fundamental Physics Department.

My research work focuses on cosmological simulations in the context of data analysis for large galaxy surveys. In particular, I work on modelling galaxy clustering and weak lensing observables and their statistical properties using simulations.

I am member of the « Euclid Consortium », for which I produce large galaxy mock catalogues for testing the performances of the Euclid satellite, in collaboration with the Spanish Euclid data center at PIC.

I am part of the « Exploring Dark Energy through Cosmic Structures » (EDECS) project, for which I develop numerical methods to perform cosmological simulations of clustering dark energy scenarios.

Research

Cosmology with large scale structure surveys

Credit: M. Blanton and the Sloan Digital Sky Survey

The distribution of galaxies and other cosmic structures like clusters, voids and gas clouds, contains information about the cosmology of our Universe. To infer the values of cosmological parameter from the statistic of the large scale structure we need to define estimators and to model their statistical properties for a wide range of cosmological scenarios. Making theoretical predictions for such observables is a challenging task, especially at small scales, where the matter distribution is shaped by the non-linear regime of gravitational collapse. N-body simulations are a useful tool in this context, since they allow to follow the evolution of large volumes of the universe down to galactic scales from very high redshifts to today. My work focuses on the production of simulations for the analysis of large galaxy surveys.

Flagship mock galaxy catalogue

Credit: J. Carretero/P. Tallada/S. Serrano for ICE/PIC/U.Zurich and the Euclid Consortium Cosmological Simulations SWG

The Flagship mock galaxy catalogue is the largest simulated galaxy catalogue ever produced, which consistently model galaxy clustering and weak lensing observables for the surveys that will be carried out with the Euclid satellite. The catalog contains 2.6 billion galaxies over 1/8th of the sky and extends up to redshift 2.3. We were able to speed-up the production of mock catalogues in a scalable way by using a Big Data platform in the calibration, generation and distribution phases. To make this possible I contributed to the development of a modular python library used in the pipeline to produce the Flagship mock. Our team won the Euclid Star Prize 2018 for this work.

DEUS-PUR

deus_pur_illustration
Credit: Deus Consortium

The Dark Energy Universe Simulations – Parallel Universe Runs (DEUS-PUR) are a series of simulation sets with WMAP-7 ΛCDM cosmology, that I have contributed running in the context of a Grand Challenge project at the IDRIS super-computing centre. The main set contains 12288 simulations, the largest so far, and has been used in my works on the covariance matrix of the power spectrum and bispectrum statistics. The other simulation sets are complementary ones designed with the purpose of studying numerical systematics, such as the mass resolution and the volume of the simulations used to make the predictions.

Dark Energy

Since the discovery of the acceleration of the expansion of the universe in 1998, we know that the universe must be filled by a material with negative pressure with an abundance of 70%. In the concordance ΛCDM model this role is played by the cosmological constant Λ, but a variety of other Dark Energy models have been proposed, together with modifications of General Relativity. As a part of the EDECS project, I am interested in studying the phenomenology of a class of Dark Energy models in which this component can be represented as a fluid by the means of numerical simulations. In particular, I develop numerical methods to be implemented in existing codes for cosmological hydrodynamics simulations.

CV and Publications

Click here to see my CV.

Peer-reviewed publications

Chan K.C., Blot L., An Assessment of the Information Content of the Power Spectrum and Bispectrum, 2017, PRD, 96, 023528

Blot L., Corasaniti P.S., Amendola, L., Kitching T., Non-Linear Matter Power Spectrum Covariance Matrix Errors and Cosmological Parameter Uncertainties, 2016, MNRAS, 458, 4462

Blot L., Corasaniti P.S., Alimi J.-M., Reverdy V., Rasera Y., Matter Power Spectrum Covariance Matrix from the DEUS-PUR ΛCDM simulations: Mass Resolution and non-Gaussian Errors, 2015, MNRAS, 446, 1756

Proceedings

Carretero J., Tallada P., Casals J., Caubet M., Castander F., Blot L., Alarcón A., Serrano S., Fosalba P., Acosta-Silva C., Tonello N., Torradeflot F., Eriksen M., Neissner C., Delfino M., CosmoHub and SciPIC: Massive cosmological data analysis, distribution and generation using a Big Data platform, 2017, Proceedings of the European Physical Society Conference on High Energy Physics, 488

Pre-prints

Arnold C., Fosalba P., Springel V., Puchwein E., Blot L., The modified gravity lightcone simulation project I: Statistics of matter and halo distributions, arXiv: 1805.09824

Lippich M., Sánchez A.G., Colavincenzo M., Sefusatti E., Monaco P., Blot L., Crocce M., Alvarez M.A., Agrawal A., Avila S., Balaguera-Antolínez A., Bond R., Codis S., Dalla Vecchia C., Dorta A., Fosalba P., Izard A., Kitaura F.S., Pellejero-Ibanez M., Stein G, Vakili M., Yepes G., Comparing approximate methods for mock catalogues and covariance matrices I: correlation function, arXiv:1806.09477

Blot L., Crocce M., Sefusatti E., Lippich M., Sánchez A.G., Colavincenzo M., Monaco P., Alvarez M.A., Agrawal A., Avila S., Balaguera-Antolínez A., Bond R., Codis S., Dalla Vecchia C., Dorta A., Fosalba P., Izard A., Kitaura F.S., Pellejero-Ibanez M., Stein G, Vakili M., Yepes G., Comparing approximate methods for mock catalogues and covariance matrices II: power spectrum multipoles, arXiv:1806.09497

Colavincenzo M., Sefusatti E., Monaco P., Blot L., Crocce M., Lippich M., Sánchez A.G., Alvarez M.A., Agrawal A., Avila S., Balaguera-Antolínez A., Bond R., Codis S., Dalla Vecchia C., Dorta A., Fosalba P., Izard A., Kitaura F.S., Pellejero-Ibanez M., Stein G, Vakili M., Yepes G., Comparing approximate methods for mock catalogues and covariance matrices III: bispectrum, arXiv:1806.09499

Works in progress

Knabenhans M., Stadel J., Potter D., Teyssier R., Legrand L., Marelli S., Schneider A., Sudret B., Blot L., The EuclidEmulator: A Tool to Compute the Cosmology Dependence of the Non- linear Matter Power Spectrum, in prep.

Blot L., Carretero J., Castander F.J., Crocce M., Fosalba P., Tallada P., The Flagship mock galaxy catalogue, in prep.

Blot L., Crocce M., Angulo R., Sanchez A., Dalla Vecchia C., Halo Clustering in paired and fixed simulations, in prep.

Blot L., Corasaniti P.S., Rasera Y., Cosmology dependence of the matter power spectrum covariance matrix, in prep.

Corasaniti P.S., Blot L., Non-linear Eulerian Hydrodynamics of Cosmic Dark Fluids: Riemann problem and Upwind Schemes (I), in prep.

Blot L., Corasaniti P.S., Non-linear Eulerian Hydrodynamics of Cosmic Dark Fluids: Spherical Collapse (II), in prep.

Blot L., Corasaniti P.S., Non-linear Eulerian Hydrodynamics of Cosmic Dark Fluids: Cosmological simulations of clustering Dark Energy scenarios (III), in prep.

Theses

Non-linear regime of cosmic structure formation: Imprints on the covariance of the power spectrum and dynamics of Dark Energy inhomogeneities – PhD thesis

The alignment profile of satellite galaxies in simulated clusters – Master thesis

Codes and Data

Python libraries for the analysis of DEUS-PUR simulations: github

Covariance matrices from the DEUS-PUR main sample of simulations corrected for the mass resolution effect: cov_all_256_mcorrected.tar.gz

Further data can be found here.

If you use these data please refer to:

L. Blot, P.S. Corasaniti, J.-M. Alimi, V. Reverdy, Y. Rasera, “Matter Power Spectrum Covariance Matrix from the DEUS-PUR ΛCDM simulations: Mass Resolution and non-Gaussian Errors”, Mont. Not. Roy. Astron. Soc. 446, 1756 (2015) (arXiv:1406.2713)

Contacts

Institute of Space Sciences
Campus UAB
c/ Can Magrans s/n
08193 Cerdanyola del Vallès
Barcelona, Spain

+34 937379788 (933049)
blot[at]ice.cat