Efficient propagation of systematic uncertainties from calibration to analysis with the SnowStorm method in IceCube

Efficient treatment of systematic uncertainties that depend on a large number of nuisance parameters is a persistent difficulty in particle physics and astrophysics experiments. Where low-level effects are not amenable to simple parameterization or re-weighting, analyses often rely on discrete simul...

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Published in:Journal of Cosmology and Astroparticle Physics
Main Authors: Aartsen, M. G., Ackermann, M., Adams, J., Aguilar, J. A., Ahlers, M., Alispach, C., Al Atoum, B., Andeen, K., Anderson, T., Ansseau, I, Anton, G., Arguelles, C., Auenberg, J., Axani, S., Backes, P., Bagherpour, H., Bai, X., Balagopal, A., V, Barbano, A., Barwick, S. W., Bastian, B., Baum, V, Baur, S., Bay, R., Beatty, J. J., Becker, K-H, Tjus, J. Becker, BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Binder, G., Bindig, D., Blaufuss, E., Blot, S., Bohm, C., Boerner, M., Boeser, S., Botner, O., Boettcher, J., Bourbeau, E., Bourbeau, J., Bradascio, F., Braun, J., Bron, S., Brostean-Kaiser, J., Burgman, A., Buscher, J., Busse, R. S., Carver, T., Chen, C., Cheung, E., Chirkin, D., Choi, S., Clark, K., Classen, L., Coleman, A., Collin, G. H., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Cross, R., Dave, P., De Clercq, C., DeLaunay, J. J., Dembinski, H., Deoskar, K., De Ridder, Sam, Desiati, P., de Vries, K. D., de Wasseige, G., de With, M., DeYoung, T., Diaz, A., Diaz-Velez, J. C., Dujmovic, H., Dunkman, M., Dvorak, E., Eberhardt, B., Ehrhardt, T., Eller, P., Engel, R., Evenson, P. A., Fahey, S., Fazely, A. R., Felde, J., Filimonov, K., Finley, C., Franckowiak, A., Friedman, E., Fritz, A., Gaisser, T. K., Gallagher, J., Ganster, E., Garrappa, S., Gerhardt, L., Ghorbani, K., Glauch, T., Gluesenkamp, T., Goldschmidt, A., Gonzalez, J. G., Grant, D., Griffith, Z., Griswold, S., Guender, M., Guenduez, M., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hanson, K., Haungs, A., Hebecker, D., Heereman, D., Heix, P., Helbing, K., Hellauer, R., Henningsen, F., Hickford, S., Hignight, J., Hill, G. C., Hoffman, K. D., Hoffmann, R., Hoinka, T., Hokanson-Fasig, B., Hoshina, K., Huang, F., Huber, M., Huber, T., Hultqvist, K., Huennefeld, M., Hussain, R., In, S., Iovine, N., Ishihara, A., Japaridze, G. S., Jeong, M., Jero, K., Jones, B. J. P., Jonske, F., Joppe, R., Kang, D., Kang, W., Kappes, A., Kappesser, D., Karg, T., Karl, M., Karle, A., Katz, U., Kauer, M., Kelley, J. L., Kheirandish, A., Kim, J., Kintscher, T., Kiryluk, J., Kittler, T., Klein, S. R., Koirala, R., Kolanoski, H., Kopke, L., Kopper, C., Kopper, S., Koskinen, D. J., Kowalski, M., Krings, K., Krueckl, G., Kulacz, N., Kurahashi, N., Kyriacou, A., Labare, Mathieu, Lanfranchi, J. L., Larson, M. J., Lauber, F., Lazar, J. P., Leonard, K., Leszczynska, A., Leuermann, M., Liu, Q. R., Lohfink, E., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Lunemann, J., Luszczak, W., Lyu, Y., Madsen, J., Maggi, G., Mahn, K. B. M., Makino, Y., Mallik, P., Mallot, K., Mancina, S., Maris, I. C., Maruyama, R., Mase, K., Maunu, R., McNally, F., Meagher, K., Medici, M., Medina, A., Meier, M., Meighen-Berger, S., Menne, T., Merino, G., Meures, T., Micallef, J., Mockler, D., Momente, G., Montaruli, T., Moore, R. W., Morse, R., Moulai, M., Muth, P., Nagai, R., Naumann, U., Neer, G., Niederhausen, H., Nowicki, S. C., Nygren, D. R., Pollmann, A. Obertacke, Oehler, M., Olivas, A., O'Murchadha, A., O'Sullivan, E., Palczewski, T., Pandya, H., Pankova, D., V, Park, N., Peiffer, P., de los Heros, C. Perez, Philippen, S., Pieloth, D., Pinat, E., Pizzuto, A., Plum, M., Porcelli, Alessio, Price, P. B., Przybylski, G. T., Raab, C., Raissi, A., Rameez, M., Rauch, L., Rawlins, K., Rea, I. C., Reimann, R., Relethford, B., Renschler, M., Renzi, G., Resconi, E., Rhode, W., Richman, M., Robertson, S., Rongen, M., Rott, C., Ruhe, T., Ryckbosch, Dirk, Rysewyk, D., Safa, I, Herrera, S. E. Sanchez, Sandrock, A., Sandroos, J., Santander, M., Sarkar, S., Satalecka, K., Schaufel, M., Schieler, H., Schlunder, P., Schmidt, T., Schneider, A., Schneider, J., Schroeder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seunarine, S., Shefali, S., Silva, M., Snihur, R., Soedingrekso, J., Soldin, D., Song, M., Spiczak, G. M., Spiering, C., Stachurska, J., Stamatikos, M., Stanev, T., Stein, R., Steinmuller, P., Stettner, J., Steuer, A., Stezelberger, T., Stokstad, R. G., Stossl, A., Strotjohann, N. L., Stuerwald, T., Stuttard, T., Sullivan, G. W., Taboada, I, Tenholt, F., Ter-Antonyan, S., Terliuk, A., Tilav, S., Tollefson, K., Tomankova, L., Tonnis, C., Toscano, S., Tosi, D., Trettin, A., Tselengidou, M., Tung, C. F., Turcati, A., Turcotte, R., Turley, C. F., Ty, B., Unger, E., Elorrieta, M. A. Unland, Usner, M., Vandenbroucke, J., Van Driessche, Ward, van Eijk, D., van Eijndhoven, N., Vanheule, Sander, van Santen, J., Vraeghe, Matthias, Walck, C., Wallace, A., Wallra, M., Wandkowsky, N., Watson, T. B., Weaver, C., Weindl, A., Weiss, M. J., Weldert, J., Wendt, C., Werthebach, J., Whelan, B. J., Whitehorn, N., Wiebe, K., Wiebusch, C. H., Wille, L., Williams, D. R., Wills, L., Wolf, M., Wood, J., Wood, T. R., Woschnagg, K., Wrede, G., Xu, D. L., Xu, X. W., Xu, Y., Yanez, J. P., Yodh, G., Yoshida, S., Yuan, T., Zoecklein, M.
Format: Article in Journal/Newspaper
Language:English
Published: 2019
Subjects:
Online Access:https://biblio.ugent.be/publication/8668166
http://hdl.handle.net/1854/LU-8668166
https://doi.org/10.1088/1475-7516/2019/10/048
https://biblio.ugent.be/publication/8668166/file/8668212
Description
Summary:Efficient treatment of systematic uncertainties that depend on a large number of nuisance parameters is a persistent difficulty in particle physics and astrophysics experiments. Where low-level effects are not amenable to simple parameterization or re-weighting, analyses often rely on discrete simulation sets to quantify the effects of nuisance parameters on key analysis observables. Such methods may become computationally untenable for analyses requiring high statistics Monte Carlo with a large number of nuisance degrees of freedom, especially in cases where these degrees of freedom parameterize the shape of a continuous distribution. In this paper we present a method for treating systematic uncertainties in a computationally efficient and comprehensive manner using a single simulation set with multiple and continuously varied nuisance parameters. This method is demonstrated for the case of the depth-dependent effective dust distribution within the IceCube Neutrino Telescope.