!!Ofer Lahav - Selected Publications
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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]\\
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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]\\
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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]\\
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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]\\
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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]\\
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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]\\
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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]\\
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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]\\
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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.]\\
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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.]