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SUMMARY:From $\\pi$ Production to Proton Decay: Confronting Nuclear Effect
 s in Next-Generation Neutrino Experiments
DTSTART;VALUE=DATE-TIME:20260507T070000Z
DTEND;VALUE=DATE-TIME:20260507T083000Z
DTSTAMP;VALUE=DATE-TIME:20260501T173800Z
UID:indico-event-4988@indico-tdli.sjtu.edu.cn
DESCRIPTION:Speakers: QiyuYan （严启宇） (University of Chinese Acade
 my of Sciences （UCAS))\n\nAbstract: Neutrino physics has entered the pr
 ecision era\, where theoretical uncertainties in neutrino-nucleus interact
 ions have become a dominant systematic limitation for flagship measurement
 s—the neutrino mass ordering\, the CP-violating phase\, and nucleon deca
 y searches. This talk presents a coherent study of nuclear effects spannin
 g bottom-up model development to top-level experimental sensitivity projec
 tions. I will first discuss the implementation of the Ghent Hybrid single-
 pion production model into the NuWro event generator\, which is rigorously
  validated against MINERvA and T2K transverse kinematic imbalance data. Fo
 llowing this\, I will present a systematic assessment of nuclear medium ef
 fects using the GiBUU transport framework\, revealing intriguing tensions 
 among current experimental datasets in their preference for different medi
 um-effect strengths. Building on these foundational models\, I will then d
 emonstrate how nuclear effects propagate into proton decay searches ($p \\
 to e^+ \\pi^0$) in next-generation water Cherenkov detectors (Super-Kamiok
 ande and Hyper-Kamiokande)\, where initial-state Fermi motion\, final-stat
 e interactions\, and atmospheric-neutrino backgrounds are self-consistentl
 y quantified. Finally\, turning to the JUNO liquid-scintillator detector\,
  I will present a Bayesian atmospheric neutrino oscillation analysis that 
 clarifies the origin of mass-ordering sensitivity and the critical role of
  flavor identification. To address the computational challenges in these l
 arge-scale fits\, I will introduce a novel systematic-error propagation fr
 amework based on the Professor 2 method\, designed to efficiently handle t
 he high-dimensional nuclear-uncertainty space and enable robust sensitivit
 y projections for JUNO's atmospheric neutrino program.Introduction: Qiyu 
 Yan is a Ph.D. candidate in experimental high-energy physics at the Univer
 sity of Chinese Academy of Sciences (UCAS)\, advised by Prof. Yangheng Zhe
 ng. He is also a visiting student at the University of Warwick\, working w
 ith Dr. Xianguo Lu. His research focuses on neutrino-nucleus interactions\
 , cross-section modeling\, and systematic uncertainty evaluations for next
 -generation neutrino experiments.Within the JUNO collaboration\, Qiyu serv
 es as a task lead for the GENIE and NuWro event generator efforts in the a
 tmospheric neutrino group. His key contributions include implementing the 
 Ghent Hybrid pion production model into the NuWro generator and developing
  systematic uncertainty propagation frameworks based on the Professor 2 me
 thod. Additionally\, he actively explores modern computational techniques 
 in physics\, such as Markov Chain Monte Carlo (MCMC) methods and GPU-accel
 erated fitting and inference. Having recently and successfully defended hi
 s dissertation\, he is expected to receive his Ph.D. in June 2026.Alternat
 ive online link: https://meeting.tencent.com/dm/ZwZge46bbpeVID:875707306\
 n\nhttps://indico-tdli.sjtu.edu.cn/event/4988/
LOCATION:Tsung-Dao Lee Institute/N6F-N600 - Lecture Room (Tsung-Dao Lee In
 stitute)
URL:https://indico-tdli.sjtu.edu.cn/event/4988/
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