Events at Physics |
Events on Thursday, August 27th, 2026
- Graduate Program Event
- Qualifying Exam - Classical Mechanics
- Time: 9:00 am - 10:30 am
- Place: 2241 Chamberlin
- Host: Sharon Kahn
- Preliminary Exam
- Using physics methodologies to study machine learning and using machine learning to help advance physics
- Time: 9:30 am - 11:30 am
- Place: 5280 Chamberlin
- Speaker: Raheem Hashmani, Physics PhD Graduate Student
- Host: Kyle Cranmer
- Graduate Program Event
- Qualifying Exam - Statistical Mechanics
- Time: 11:30 am - 1:00 pm
- Place: 2241 Chamberlin
- Host: Sharon Kahn
- Preliminary Exam
- Energy level measurement and analysis in Si/SiGe quantum dot devices
- Time: 2:00 pm - 4:00 pm
- Place: B343 Sterling
- Speaker: Alysa Huffman, Physics PhD Graduate Student
- Abstract: The characterization of excited-state structure in semiconductor quantum dot (QD) devices is an important component of tuning them for spin-qubit operation. I will discuss two projects that focus on the characterization of excited states in QDs. First, I will present valley splitting measurements in a device with a quantum well containing an average of 5% Ge. We extract valley splitting and orbital splitting across two samples and four barrier-gate tuning configurations, and observe a positive correlation between the valley and orbital splittings. Random Ge-alloy disorder simulations reproduce the measured energy scale and are consistent with the interpretation that experimental tuning paths change how the dot samples the random alloy landscape. Next, I will present Spectroscopy With Intelligent Feature Tracking (SWIFT), a framework that combines machine-learning (ML)-assisted feature identification with physics-informed geometric processing to extract energy-level splittings from pulsed-gate spectroscopy data. Using Si/SiGe QD devices, we demonstrate SWIFT both offline and in real time, including automated tracking of QD excited states and lead resonances. These results provide a path toward incorporating confidence-guided excited-state spectroscopy into autonomous QD characterization, tuning, and optimization.
- Host: Mark Eriksson