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Dr Marika Asgari

Dr Marika Asgari

Lecturer in data science and artificial intelligence

Faculty and Department

  • Faculty of Science and Engineering
  • School of Natural Sciences

Qualifications

  • PhD (University of Edinburgh)

Recent outputs

View more outputs

Journal Article

KiDS-1000 Cosmology: Constraints from density split statistics

Burger, P. A., Friedrich, O., Harnois-Dèraps, J., Schneider, P., Marika, A., & et al. (in press). KiDS-1000 Cosmology: Constraints from density split statistics. Astronomy and Astrophysics, https://doi.org/10.1051/0004-6361/202244673

Consistent lensing and clustering in a low-S8 Universe with BOSS, DES Year 3, HSC Year 1, and KiDS-1000

Amon, A., Robertson, N. C., Miyatake, †. H., Heymans, C., White, M., Derose, J., …Zhang, Y. (2023). Consistent lensing and clustering in a low-S8 Universe with BOSS, DES Year 3, HSC Year 1, and KiDS-1000. Monthly notices of the Royal Astronomical Society, 518(1), 477-503. https://doi.org/10.1093/mnras/stac2938

The halo model with beyond-linear halo bias: unbiasing cosmological constraints from galaxy-galaxy lensing and clustering

Mahony, C., Dvornik, A., Mead, A., Heymans, C., Asgari, M., Hildebrandt, H., …Reischke, R. (2022). The halo model with beyond-linear halo bias: unbiasing cosmological constraints from galaxy-galaxy lensing and clustering. Monthly notices of the Royal Astronomical Society, 515(2), 2612–2623. https://doi.org/10.1093/mnras/stac1858

KiDS-1000: cosmic shear with enhanced redshift calibration

Van Den Busch, J. L., Wright, A. H., Hildebrandt, H., Bilicki, M., Asgari, M., Joudaki, S., …Tröster, T. (in press). KiDS-1000: cosmic shear with enhanced redshift calibration. Astronomy and Astrophysics, https://doi.org/10.1051/0004-6361/202142083

Pure-mode correlation functions for cosmic shear and application to KiDS-1000

Schneider, P., Asgari, M., Jozani, Y. N., Dvornik, A., Giblin, B., Harnois-Déraps, J., …Wright, A. H. (in press). Pure-mode correlation functions for cosmic shear and application to KiDS-1000. Astronomy and Astrophysics, https://doi.org/10.1051/0004-6361/202142479

Research interests

Cosmology

Dark Matter

Dark energy

Data analysis

Lead investigator

Project

Funder

Grant

Started

Status

Project

Rapid Cosmology: machine learning emulators and likelihood analysis

Funder

Royal Society

Grant

£19,995.00

Started

17 October 2022

Status

Ongoing

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