Heather Gray, Professor

Closed (1) A new method to probe the coupling of the Higgs boson to charm quarks

Applications for fall 2021 are now closed for this project.

One of the key topics being studied by the ATLAS experiment at the Large Hadron Collider are the properties of the Higgs boson. This project focuses on developing a new method to probe the coupling of the Higgs boson to charm quarks.

Some funding may be available for students who are eligible for work study. Please indicate if you are eligible and if you would like to be considered for such funding. Please note that students cannot both be paid and receive course credit for the same work. Eligibility for work study will NOT be used as a criterion for selecting candidates

Tasks
- Follow ROOT tutorials to become familiar with the program
- Analyse data to produce plots of the discriminant between charm and bottom quarks
- Fit the distribution to determine the fraction of charm and bottom quarks
- Calculate the cross-section and the expected uncertainty

Learning outcomes
- Become familiar with experimental particle physics
- Become confident with analysing data and producing plots using the particle physicist's toolkit, ROOT
- Learn techniques for searching for the coupling of the Higgs boson to charm quarks
- Learn and develop techniques to identify jets containing charm
- Become confident with fitting tools

Day-to-day supervisor for this project: Miha Muskinja, Post-Doc

Qualifications: Required: Programming experience in either C++ or python Desirable: Physics 129 Desirable: Knowledge of particle physics

Weekly Hours: 9-11 hrs

Off-Campus Research Site: LBNL, 1 Cyclotron Road

Closed (2) Developing new computing algorithms to find charged particles.

Applications for fall 2021 are now closed for this project.

ACTS is international, open source project developing an experiment-independent set of track reconstruction tools. The main philosophy is to provide high-level track reconstruction modules that can be used for any tracking detector. The description of the tracking detector’s geometry is optimized for efficient navigation and quick extrapolation of tracks. Converters for several common geometry description languages exist. Having a highly performant, yet largely customizable implementation of track reconstruction algorithms was a primary objective for the design of this toolset. Additionally, the applicability to real-life HEP experiments plays major role in the development process. Apart from algorithmic code, this project also provides an event data model for the description of track parameters and measurements.

Some funding may be available for students who are eligible for work study. Please indicate if you are eligible and if you would like to be considered for such funding. Please note that students cannot both be paid and receive course credit for the same work. Eligibility for work study will NOT be used as a criterion for selecting candidates

Day-to-day supervisor for this project: Tomohiro Yamazaki, Post-Doc

Qualifications: Tasks Develop and debug algorithms to reconstruct tracks as part of the ACTS project. This can include profiling of algorithms and the development of parallel versions or the development of software to use the tracks to precisely determine the position of the detector elements. Qualifications Required: Significant programming experience in modern languages ideally in C++ Optional: Experience with scientific computing Optional: Experience in high-energy physics

Weekly Hours: 9-11 hrs

Off-Campus Research Site: LBNL, 1 Cyclotron Road

Related website: https://gitlab.cern.ch/acts

Closed (3) Charm production measurements

Applications for fall 2021 are now closed for this project.

Although the charm quarks was discovered almost half a century ago, there remain many puzzles about how it is produced. This project would focus on performing measurements of charm production, either alone or when produced together with vector bosons. Such measurements would provide important insight on the structure of the proton and provide tests of the theory of quantum chromodynamics.

Some funding may be available for students who are eligible for work study. Please indicate if you are eligible and if you would like to be considered for such funding. Please note that students cannot both be paid and receive course credit for the same work. Eligibility for work study will NOT be used as a criterion for selecting candidates

Tasks
- Follow ROOT/pyROOT tutorials to become familiar with the program
- Analyse data to produce plots
- Study backgrounds and uncertainties
- Perform the statistical analysis

Learning outcomes
- Become familiar with experimental particle physics
- Become confident with analysing data and producing plots using the particle physicist's toolkit, ROOT
- Learn techniques for data analysis
- Become confident with statistical tools

Day-to-day supervisor for this project: Louis-Guillaume Gagnon

Qualifications: Required: Programming experience in either C++ or python Desirable: Physics 129 Desirable: Knowledge of particle physics

Weekly Hours: 9-11 hrs

Off-Campus Research Site: LBNL

Closed (4) Explainable charm tagging for Higgs boson physics

Closed. This professor is continuing with Spring 2021 apprentices on this project; no new apprentices needed for Fall 2021.

Decay of the Higgs boson to pairs of charm quarks is one of the most
important Higgs decay mode that has yet to be observed in laboratory.
Current plans for searches for this process make use of machine
learning classifiers such as neural networks to recognize charm jets
in proton-proton collisions at the LHC, and while their expected
performance is very good, there is some uneasiness about the the
black-box nature of such algorithms. This project aims to leverage
techniques from the field of machine learning interpretability
research to gain insight about the inner working of these classifiers.

Some funding may be available for students who are eligible for work study. Please indicate if you are eligible and if you would like to be considered for such funding. Please note that students cannot both be paid and receive course credit for the same work. Eligibility for work study will NOT be used as a criterion for selecting candidates

Tasks:
+ Generate explanations for a charm-tagging neural network using
gradient-based techniques such as "Activation Maximisation"
+ Assess the faithfulness of these explanations
+ Present the results for understanding by a physicist audience
Learning outcomes:
+ Gain experience working with the tensorflow python library in a realistic big data usage scenario
+ Gain experience working with machine learning explanation techniques
+ Gain intuition about the inner working of neural networks
+ Learn about Charm & Higgs physics
+ Acquire scientific communication skills, Post-Doc

Qualifications: Qualifications: + Required: Programming experience in python + Required: Physics 77 or 88, or equivalent experience + Desirable: Physics 129

Weekly Hours: 9-11 hrs

Off-Campus Research Site: LBNL, 1 Cyclotron Road