Elettra Preosti
Status: Current Trainee
- Software Engineering for Scientific Computing, FPGA training module
Biography and Interests
I am a second-year PhD student in the CMS group at Princeton advised by Professor Jim Olsen. My research interests lie at the intersection of machine learning and data analysis for high energy physics, with a focus on developing algorithms and computational tools to make large-scale simulation and experimental data more tractable and useful.
Prior to starting my PhD, I completed my BA at the University of California, Berkeley. There, I primarily worked on applying machine learning methods, including PCA, to develop algorithms that improve energy resolution in data from the CUORE experiment, which searches for neutrinoless double beta decay.
Project
Simulating beamlines is critically important for the study and optimization of ongoing and future accelerator projects, such as the Mu2e experiment and the Muon Ionization Cooling Demonstrator. To optimize these systems, researchers must run beam simulation tools (e.g., G4BeamLine, ICOOL) to generate very high statistics. This is possible only on large computing facilities, however, many of these simulation tools were developed years ago and are not currently optimized for efficient execution on modern large-scale computing infrastructures.
This work therefore focuses on two main phases. (1) First, large language models (LLMs) will be used to help update and modernize existing beam simulation tools and their interfaces, enabling efficient and scalable operation on modern computing facilities such as FermiGrid and NERSC. (2) Second, we will develop a framework for agentic AI–based beamline optimization, which can be applied to the Mu2e experiment and the Muon Ionization Cooling Demonstrator, with potential extensions to other beamlines and accelerator facilities.
This work will help to enable scalable, high-statistics beamline simulations and automated optimization workflows on modern computing facilities. The resulting framework will accelerate the design and optimization of beamlines for Mu2e and muon cooling R&D while providing a reusable platform for future accelerator and particle physics experiments.
Recent Accomplishments
- (In progress)
Mentors
- Jim Olsen (Princeton)
- Isobel Ojalvo (Princeton)
- Diktys Stratakis (FNAL)
- Sergo Jindariani (FNAL)
Traineeship Dates
- Start: 25-07-31
- Expected End: ongoing