The International School for Advanced Studies (SISSA) was founded in 1978 and was the first institution in Italy to promote post-graduate courses leading to a Doctor Philosophiae (or PhD) degree. A centre of excellence among Italian and international universities, the school has around 65 teachers, 100 post docs and 245 PhD students, and is located in Trieste, in a campus of more than 10 hectares with wonderful views over the Gulf of Trieste.
SISSA hosts a very high-ranking, large and multidisciplinary scientific research output. The scientific papers produced by its researchers are published in high impact factor, well-known international journals, and in many cases in the world's most prestigious scientific journals such as Nature and Science. Over 900 students have so far started their careers in the field of mathematics, physics and neuroscience research at SISSA.
Efficient propagation of systematic uncertainties from calibration to analysis with the SnowStorm method in IceCube
M.G. Aartsen16, M. Ackermann54, J. Adams16, J.A. Aguilar12, M. Ahlers20, C. Alispach26, B. Al Atoum4, K. Andeen37, T. Anderson51, I. Ansseau12, G. Anton24, C. Argüelles14, J. Auffenberg1, S. Axani14, P. Backes1, H. Bagherpour16, X. Bai43, A. Balagopal V.29, A. Barbano26, S.W. Barwick28, B. Bastian54, V. Baum36, S. Baur12, R. Bay8, J.J. Beatty18,19, K.-H. Becker53, J. Becker Tjus11, S. BenZvi45, D. Berley17, E. Bernardini54, D.Z. Besson30, G. Binder8,9, D. Bindig53, E. Blaufuss17, S. Blot54, C. Bohm46, M. Börner21, S. Böser36, O. Botner52, J. Böttcher1, E. Bourbeau20, J. Bourbeau35, F. Bradascio54, J. Braun35, S. Bron26, J. Brostean-Kaiser54, A. Burgman52, J. Buscher1, R.S. Busse38, T. Carver26, C. Chen6, E. Cheung17, D. Chirkin35, S. Choi48, K. Clark31, L. Classen38, A. Coleman39, G.H. Collin14, J.M. Conrad14, P. Coppin13, P. Correa13, D.F. Cowen50,51, R. Cross45, P. Dave6, C. De Clercq13, J.J. DeLaunay51, H. Dembinski39, K. Deoskar46, S. De Ridder27, P. Desiati35, K.D. de Vries13, G. de Wasseige13, M. de With10, T. DeYoung22, A. Diaz14, J.C. Díaz-Vélez35, H. Dujmovic48, M. Dunkman51, E. Dvorak43, B. Eberhardt35, T. Ehrhardt36, P. Eller51, R. Engel29, P.A. Evenson39, S. Fahey35, A.R. Fazely7, J. Felde17, K. Filimonov8, C. Finley46, A. Franckowiak54, E. Friedman17, A. Fritz36, T.K. Gaisser39, J. Gallagher34, E. Ganster1, S. Garrappa54, L. Gerhardt9, K. Ghorbani35, T. Glauch25, T. Glüsenkamp24, A. Goldschmidt9, J.G. Gonzalez39, D. Grant22, Z. Griffith35, S. Griswold45, M. Günder1, M. Gündüz11, C. Haack1, A. Hallgren52, L. Halve1, F. Halzen35, K. Hanson35, A. Haungs29, D. Hebecker10, D. Heereman12, P. Heix1, K. Helbing53, R. Hellauer17, F. Henningsen25, S. Hickford53, J. Hignight23, G.C. Hill2, K.D. Hoffman17, R. Hoffmann53, T. Hoinka21, B. Hokanson-Fasig35, K. Hoshina35, F. Huang51, M. Huber25, T. Huber29,54, K. Hultqvist46, M. Hünnefeld21, R. Hussain35, S. In48, N. Iovine12, A. Ishihara15, G.S. Japaridze5, M. Jeong48, K. Jero35, B.J. P. Jones4, F. Jonske1, R. Joppe1, D. Kang29, W. Kang48, A. Kappes38, D. Kappesser36, T. Karg54, M. Karl25, A. Karle35, U. Katz24, M. Kauer35, J.L. Kelley35, A. Kheirandish35, J. Kim48, T. Kintscher54, J. Kiryluk47, T. Kittler24, S.R. Klein8,9, R. Koirala39, H. Kolanoski10, L. Köpke36, C. Kopper22, S. Kopper49, D.J. Koskinen20, M. Kowalski10,54, K. Krings25, G. Krückl36, N. Kulacz23, N. Kurahashi42, A. Kyriacou2, M. Labare27, J.L. Lanfranchi51, M.J. Larson17, F. Lauber53, J.P. Lazar35, K. Leonard35, A. Leszczyńska29, M. Leuermann1, Q.R. Liu35, E. Lohfink36, C.J. Lozano Mariscal38, L. Lu15, F. Lucarelli26, J. Lünemann13, W. Luszczak35, Y. Lyu8,9, W.Y. Ma54, J. Madsen44, G. Maggi13, K.B. M. Mahn22, Y. Makino15, P. Mallik1, K. Mallot35, S. Mancina35, I.C. Mariş12, R. Maruyama40, K. Mase15, R. Maunu17, F. McNally33, K. Meagher35, M. Medici20, A. Medina19, M. Meier21, S. Meighen-Berger25, T. Menne21, G. Merino35, T. Meures12, J. Micallef22, D. Mockler12, G. Momenté36, T. Montaruli26, R.W. Moore23, R. Morse35, M. Moulai14, P. Muth1, R. Nagai15, U. Naumann53, G. Neer22, H. Niederhausen25, S.C. Nowicki22, D.R. Nygren9, A. Obertacke Pollmann53, M. Oehler29, A. Olivas17, A. O'Murchadha12, E. O'Sullivan46, T. Palczewski8,9, H. Pandya39, D.V. Pankova51, N. Park35, P. Peiffer36, C. Pérez de los Heros52, S. Philippen1, D. Pieloth21, E. Pinat12, A. Pizzuto35, M. Plum37, A. Porcelli27, P.B. Price8, G.T. Przybylski9, C. Raab12, A. Raissi16, M. Rameez20, L. Rauch54, K. Rawlins3, I.C. Rea25, R. Reimann1, B. Relethford42, M. Renschler29, G. Renzi12, E. Resconi25, W. Rhode21, M. Richman42, S. Robertson9, M. Rongen1, C. Rott48, T. Ruhe21, D. Ryckbosch27, D. Rysewyk22, I. Safa35, S.E. Sanchez Herrera22, A. Sandrock21, J. Sandroos36, M. Santander49, S. Sarkar41, S. Sarkar23, K. Satalecka54, M. Schaufel1, H. Schieler29, P. Schlunder21, T. Schmidt17, A. Schneider35, J. Schneider24, F.G. Schröder29,39, L. Schumacher1, S. Sclafani42, D. Seckel39, S. Seunarine44, S. Shefali1, M. Silva35, R. Snihur35, J. Soedingrekso21, D. Soldin39, M. Song17, G.M. Spiczak44, C. Spiering54, J. Stachurska54, M. Stamatikos19, T. Stanev39, R. Stein54, P. Steinmüller29, J. Stettner1, A. Steuer36, T. Stezelberger9, R.G. Stokstad9, A. Stößl15, N.L. Strotjohann54, T. Stürwald1, T. Stuttard20, G.W. Sullivan17, I. Taboada6, F. Tenholt11, S. Ter-Antonyan7, A. Terliuk54, S. Tilav39, K. Tollefson22, L. Tomankova11, C. Tönnis48, S. Toscano12, D. Tosi35, A. Trettin54, M. Tselengidou24, C.F. Tung6, A. Turcati25, R. Turcotte29, C.F. Turley51, B. Ty35, E. Unger52, M.A. Unland Elorrieta38, M. Usner54, J. Vandenbroucke35, W. Van Driessche27, D. van Eijk35, N. van Eijndhoven13, S. Vanheule27, J. van Santen54, M. Vraeghe27, C. Walck46, A. Wallace2, M. Wallraff1, N. Wandkowsky35, T.B. Watson4, C. Weaver23, A. Weindl29, M.J. Weiss51, J. Weldert36, C. Wendt35, J. Werthebach35, B.J. Whelan2, N. Whitehorn32, K. Wiebe36, C.H. Wiebusch1, L. Wille35, D.R. Williams49, L. Wills42, M. Wolf25, J. Wood35, T.R. Wood23, K. Woschnagg8, G. Wrede24, D.L. Xu35, X.W. Xu7, Y. Xu47, J.P. Yanez23, G. Yodh28, S. Yoshida15, T. Yuan35 and M. Zöcklein1
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.