David Richard Harvey
david.harvey@epfl.ch +41 21 693 37 87 https://www.epfl.ch/research/domains/astrophysics/home/research-groups/david-harvey/
EPFL SB IPHYS LASTRO
Observatoire de Sauverny
1290 Versoix
+41 21 693 37 87
Office: BSP 314
EPFL › SB › IPHYS › LASTRO
Site web: https://lastro.epfl.ch/
EPFL SB IPHYS LASTRO
SAUV 344 (Sauverny)
Ch. Pegasi 51
1290 Versoix
+41 21 693 37 87
Office: SAUV 344
EPFL › VPA › VPA-AVP-DLE › AVP-DLE-EDOC › EDPY-ENS
Publications représentatives
On the cross-section of dark matter using substructure infall into galaxy clusters
Harvey, David; Tittley, Eric; Massey, Richard; Kitching, Thomas D.; Taylor, Andy; Pike, Simon R.; Kay, Scott T.; Lau, Erwin T.; Nagai, Daisuke
Published in MNRAS, Volume 441, Issue 1, p.404-416 in
Origins of weak lensing systematics, and requirements on future instrumentation (or knowledge of instrumentation)
Massey, Richard; Hoekstra, Henk; Kitching, Thomas; Rhodes, Jason; Cropper, Mark; Amiaux, Jérôme; Harvey, David; Mellier, Yannick; Meneghetti, Massimo; Miller, Lance; Paulin-Henriksson, Stéphane; Pires, Sandrine; Scaramella, Roberto; Schrabback, Tim
Published in MNRAS, Volume 429, Issue 1, p.661-678 in
Dark matter astrometry: accuracy of subhalo positions for the measurement of self-interaction cross-sections
Harvey, David; Massey, Richard; Kitching, Thomas; Taylor, Andy; Jullo, Eric; Kneib, Jean-Paul; Tittley, Eric; Marshall, Philip J.
Published in MNRAS, Volume 433, Issue 2, p.1517-1528 in
Observing Dark Worlds: A crowdsourcing experiment for dark matter mapping
Harvey, D.; Kitching, T. D.; Noah-Vanhoucke, J.; Hamner, B.; Salimans, T.; Pires, A. M.
Published in Astronomy and Computing, Volume 5, p. 35-44. in
The Galaxy Activity, Torus, and Outflow Survey (GATOS) VI. Black hole mass estimation using machine learning
ASTRONOMY & ASTROPHYSICS. 2025. DOI : 10.1051/0004-6361/202347566.Search for a massless dark photon in c → uγ' decays
PHYSICAL REVIEW D. 2025. DOI : 10.1103/PhysRevD.111.L011103.Sleptonic SUSY: from UV framework to IR phenomenology
Journal of High Energy Physics. 2022. DOI : 10.1007/JHEP09(2022)142.Search for dark matter produced in association with a Higgs boson decaying to a pair of bottom quarks in proton–proton collisions at $\sqrt{s}=13\,\text {Te}\text {V} $
The European Physical Journal C. 2019. DOI : 10.1140/epjc/s10052-019-6730-7.Search for new physics in events with a leptonically decaying Z boson and a large transverse momentum imbalance in proton–proton collisions at $\sqrt{s} $ = 13 $\,\text {TeV}$
The European Physical Journal C. 2018. DOI : 10.1140/epjc/s10052-018-5740-1.Search for dark matter and unparticles in events with a Z boson and missing transverse momentum in proton-proton collisions at $ \sqrt{s}=13 $ TeV
Journal of High Energy Physics. 2017. DOI : 10.1007/JHEP03(2017)061.Looking for dark matter trails in colliding galaxy clusters
Monthly Notices Of The Royal Astronomical Society. 2017. DOI : 10.1093/mnras/stw2671.The behaviour of dark matter associated with four bright cluster galaxies in the 10 kpc core of Abell 3827
Monthly Notices Of The Royal Astronomical Society. 2015. DOI : 10.1093/mnras/stv467.The nongravitational interactions of dark matter in colliding galaxy clusters
Science. 2015. DOI : 10.1126/science.1261381.Weyssenhoff fluid dynamics in general relativity using a 1 + 3 covariant approach
Classical and Quantum Gravity. 2007. DOI : 10.1088/0264-9381/24/24/011.The fate of the zero mode of the five-dimensional kink in the presence of gravity
JHEP. 2005. DOI : 10.1088/1126-6708/2005/09/062.Cosmic microwave background constraints on the strong equivalence principle
Physical Review D [1970-2015]. 2004. DOI : 10.1103/PhysRevD.70.103528.Primordial constraint on the spatial dependence of the Newton constant
2004The behaviour of dark matter associated with four bright cluster galaxies in the 10 kpc core of Abell 3827
Monthly Notices Of The Royal Astronomical Society. 2015. DOI : 10.1093/mnras/stv467.Systematic or signal? How dark matter misalignments can bias strong lensing models of galaxy clusters
Monthly Notices Of The Royal Astronomical Society. 2016. DOI : 10.1093/mnras/stw295.Hubble Frontier Fields: the geometry and dynamics of the massive galaxy cluster merger MACSJ0416.1-2403
Monthly Notices Of The Royal Astronomical Society. 2015. DOI : 10.1093/mnras/stu2425.A weak lensing comparability study of galaxy mergers that host AGNs
Monthly Notices Of The Royal Astronomical Society. 2015. DOI : 10.1093/mnrasl/slv073.Enseignement et PhD
Doctorant·es actuel·les
Ethan Daniel Tregidga, Felix Francisco Vecchi
Cours
Lecture series on scientific machine learning
PHYS-754
Ce cours présente des travaux sur la façon dont les questions scientifiques peuvent être abordées à l'aide de l'apprentissage automatique. L'apprentissage automatique permet d'extraire des connaissances à partir de données de manière automatisée. Nous apprendrons à partir d'exemples concrets.