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Curtin, D. et al, & Hirsch, M. (2019). Long-lived particles at the energy frontier: the MATHUSLA physics case. Rep. Prog. Phys., 82(11), 116201–133pp.
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Das, C. R., Mena, O., Palomares-Ruiz, S., & Pascoli, S. (2013). Determining the dark matter mass with DeepCore. Phys. Lett. B, 725(4-5), 297–301.
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de Adelhart Toorop, R., Bazzocchi, F., & Morisi, S. (2012). Quark mixing in the discrete dark matter model. Nucl. Phys. B, 856(3), 670–681.
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de los Rios, M., Petac, M., Zaldivar, B., Bonaventura, N. R., Calore, F., & Iocco, F. (2023). Determining the dark matter distribution in simulated galaxies with deep learning. Mon. Not. Roy. Astron. Soc., 525(4), 6015–6035.
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de Putter, R., Wagner, C., Mena, O., Verde, L., & Percival, W. J. (2012). Thinking outside the box: effects of modes larger than the survey on matter power spectrum covariance. J. Cosmol. Astropart. Phys., 04(4), 019–31pp.
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