Ofer Lahav - Selected Publications#


Gualdi, D., Gil-Marin, H., Schummann, R., Manera, M., Joachimi, B., and Lahav, O., 2019. "Enhancing BOSS bispectrum cosmological constraints with maximal compression" MNARAS, 484, 3713
[5 citations, led by OL’s PhD student]

The DES collaboration (in alphabetical order, incl Lahav O. ), 2018, "Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing" , Phys Rev D, 98, 043526
[260 citations, the culmination of DES work over a decade]

Palmese, A., Hartley, W., Tarsitano, F., Conselice, C., Lahav, O. & DES collaboration, 2017, “Evidence for Dynamically Driven Formation of the GW170817 Neutron Star Binary in NGC 4994”, The Astrophysical Journal Letters, 849, L34 (2017), arXiv:1710.06748
[10 citations, led by my PhD student and Post-doc]

Clerkin L., Kirk, D., Manera, M, Lahav, O. et al., 2017, "Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps", MNRAS, 466, 1444
[18 citations, led by OL’s PhD student and ERC Postdoc]

McLeod, M., Libeskind, N., Lahav, O., & Hoffman, Y., 2017, "Estimating the mass of the Local Group using machine learning applied to numerical simulations", JCAP, 12 03
[5 citations, led by OL’s PhD student]

The DES Collaboration (authors in alphabetical order, incl Lahav O. ), 2016, The Dark Energy Survey: more than Dark Energy – an overview, MNRAS, 460, 1270
[258 citations, OL initiated and coordinated this overview article on DES]

Sadeh, I., Abdalla, F.B., Lahav, O., 2016, ANNZ2: Photometric redshifts and probability distribution functions using Machine Learning, PASP, 128, 4502
[57 citations, led by OL’s ERC Post-doc]

Lochner, M., McEwen, J.D., Periris, H.V., Lahav, O., Winter, M.K., 2016. ApJS, 225, 31
[37 citations, led by OL’s ERC Post-doc]

Thomas, S.A., Abdalla, F.B., Lahav, O., 2010, Upper Bound of 0.28eV on the Neutrino Masses from the Largest Photometric Redshift Survey, PRL, 115, 031301.
[141 citations; paper led by OL’s Post-doc.]

Collister, A. & Lahav, O. & 2004, “ANNz: estimating photometric redshifts using artificial neural networks” PASP, 116, 345.
[298 citations; first author was OL’s PhD student.]

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