Speaker
Description
Feebly coupled long-lived mediators that will decay back to visible particles and missing energy are one of the smoking-gun signatures for DM at colliders. The Belle II experiment in Japan is ideally suited to search for such events. We plan to develop real time algorithms using AI to identify non-pointing vertices in the presence of very high beam-induced backgrounds.
We plan to develop resource-efficient algorithms for high background scenarios aimed at online data taking. Our focus will be on establishing a methodology towards efficient, scalable, and optimized translation of AI-based models for popular hardware platforms used in this field such as FPGAs. By combining modern AI SW libraries (e.g. PyTorch) and modern hardware development flows such as High-Level Synthesis we aim to abstract from hardware details while keeping key figures of merit such as resource efficiency, latency and algorithm performance comparable to manual implementations. This will enable key advances towards easier maintenance, adaptability, faster exploration for algorithms to be used, and validation before and after integration. Based on the distinct characteristics present at modern trigger and detector data flows, such as at Belle II, we will develop a reference processing system showcasing the viability of our approach. Derived from this, guidelines and methods for technology transfer towards similar applications from physics and industry will be developed.
Please describe your expertise/areas in which you would like to contribute / advise.
Offline algorithm development, trigger monitoring and detector calibration
My current most burning research question, I like to find partners for, is:
Simplifying AI workflows beyond HLS synthesis to find DM with existing experiments
Please describe areas in which you would like to improve your knowledge / skills.
Automatized implementation of algorithms beyond proof of concept papers in state of the art hardware
Please describe areas in which you can contribute to “data handling” teaching.
Offline reconstruction algorithms
What is your field and role?
Experimental particle physics, leading calorimeter reconstruction and physics performance coordinator in Belle II
What is your expertise in computing and / or software development?
Belle II calorimeter software convenor
In ErUM-Data, what kind of data are you dealing with?
Large simulated and real datasets from the Belle II experiment
| Your ErUM - Committee is | KET - Komitee für Elementarteilchenphysik |
|---|---|
| Do you consent to the data usage and public abstract data posting in the ErUM-Data Community Information Exchange? | Yes |
