Andy Taylor

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Personal profile

Research Interests

My research interests are in Theoretical and Observational Cosmology, in particular the nature of Dark Energy and Dark Matter, the very Early Universe and theories of Modified Gravity. To study these I have developed and led the analysis of Gravitational Lensing Surveys, the Cosmic Microwave Background, Galaxy Redshift Surveys, and Gravitational Wave Astronomy. My theoretical work has been on the Early Universe and theories of Dark Energy and Modified Gravity.

I currently lead the Weak Lensing Cosmic Shear Team for the European Space Agency's Euclid Satellite Dark Energy Mission, and the UK's Science Ground Segment leading the UK development of the science analysis and the UK's Euclid Science Data Centre. Previously I led the Eucid Weak Lensing Science Working Group.

Teaching

I am the Astrophysics Degree Programme Coordinator,  and a supervisor for both Senior Honours and and Mphys Projects. I have taught many courses from 1st Year to Masters at the University, including

  • Stellar Structure,
  • Astronomical Statistics (Level 10),
  • Astrophysical Cosmology (Level 10),
  • Advanced Cosmology (Level 11),
  • General Relativity (Level 11)
  • Radiation and Matter (Level 11).  

I have supervised over 21 PhD students, with the majority remaining in research. 

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Collaborations and top research areas from the last five years

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  • Euclid: Modelling massive neutrinos in cosmology -- a code comparison

    EUCLID Consortium, 16 Jun 2023, In: Journal of Cosmology and Astroparticle Physics (JCAP). 2023, 6, p. 1-43 43 p., 035.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    File
  • Future prospects on testing extensions to ΛcDM through the weak lensing of gravitational waves

    Mpetha, C. T., Congedo, G. & Taylor, A., 15 May 2023, In: Physical Review D. 107, 10, p. 1-20 20 p., 103518.

    Research output: Contribution to journalArticlepeer-review

    Open Access
  • Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images

    Euclid Collaboration, Bisigello, L., Conselice, C. J., Baes, M., Bolzonella, M., Brescia, M., Cavuoti, S., Cucciati, O., Humphrey, A., Hunt, L. K., Maraston, C., Pozzetti, L., Tortora, C., van Mierlo, S. E., Aghanim, N., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., & 180 othersBranchini, E., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castander, F. J., Castellano, M., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kohley, R., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Rix, H. W., Romelli, E., Roncarelli, M., Rosset, C., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Scodeggio, M., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zacchei, A., Zamorani, G., Zoubian, J., Andreon, S., Bardelli, S., Boucaud, A., Colodro-Conde, C., Di Ferdinando, D., Graciá-Carpio, J., Lindholm, V., Maino, D., Mei, S., Scottez, V., Sureau, F., Tenti, M., Zucca, E., Borlaff, A. S., Ballardini, M., Biviano, A., Bozzo, E., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Cooray, A., Coupon, J., Courtois, H. M., Cuby, J., Davini, S., De Lucia, G., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Farina, M., Fotopoulou, S., Ganga, K., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Hook, I., Huertas-Company, M., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macías-Pérez, J. F., Magliocchetti, M., Mainetti, G., Marcin, S., Martinelli, M., Martinet, N., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Peel, A., Potter, D., Pourtsidou, A., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Schirmer, M., Sefusatti, E., Sereno, M., Stadel, J., Teyssier, R., Valieri, C., Valiviita, J. & Viel, M., 1 Apr 2023, In: Monthly Notices of the Royal Astronomical Society. 520, 3, p. 3529-3548 20 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access
  • Testing Quadratic Maximum Likelihood estimators for forthcoming Stage-IV weak lensing surveys

    Maraio, A., Hall, A. & Taylor, A., 1 Apr 2023, In: Monthly Notices of the Royal Astronomical Society . 520, 4, p. 4836-4852 17 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    File
  • The PAU Survey and Euclid: Improving broadband photometric redshifts with multi-task learning

    EUCLID Consortium, Cabayol, L., Eriksen, M., Carretero, J., Casas, R., Castander, F. J., Fernández, E., Garcia-Bellido, J., Gaztanaga, E., Hildebrandt, H., Hoekstra, H., Joachimi, B., Miquel, R., Padilla, C., Pocino, A., Sanchez, E., Serrano, S., Sevilla, I., Siudek, M., Tallada-Crespí, P., & 107 othersAghanim, N., Amara, A., Auricchio, N., Baldi, M., Bender, R., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Fosalba, P., Frailis, M., Franceschi, E., Franzetti, P., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kohley, R., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Mei, S., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. M., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L., Pozzetti, L., Raison, F., Rebolo, R., Rhodes, J., Riccio, G., Rosset, C., Rossetti, E., Saglia, R., Sartoris, B., Schneider, P., Secroun, A., Seidel, G., Sirignano, C., Sirri, G., Stanco, L., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E., Valenziano, L., Wang, Y., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Scottez, V. & Tramacere, A., 21 Mar 2023, In: Astronomy and Astrophysics. 671, p. 1-23 23 p., A153.

    Research output: Contribution to journalArticlepeer-review

    Open Access