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VERSION:2.0
CALSCALE:GREGORIAN
PRODID:UW-Madison-Physics-Events
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SEQUENCE:0
UID:UW-Physics-Event-9809
DTSTART:20260827T190000Z
DTEND:20260827T210000Z
DTSTAMP:20260822T184743Z
LAST-MODIFIED:20260821T212434Z
LOCATION:B343 Sterling
SUMMARY:Energy level measurement and analysis in Si/SiGe quantum dot d
 evices\, Preliminary Exam\, Alysa Huffman\, Physics PhD Graduate Stude
 nt
DESCRIPTION:The characterization of excited-state structure in semicon
 ductor quantum dot (QD) devices is an important component of tuning th
 em 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 contain
 ing an average of 5% Ge. We extract valley splitting and orbital split
 ting across two samples and four barrier-gate tuning configurations\, 
 and observe a positive correlation between the valley and orbital spli
 ttings. Random Ge-alloy disorder simulations reproduce the measured en
 ergy scale and are consistent with the interpretation that experimenta
 l 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 feat
 ure identification with physics-informed geometric processing to extra
 ct energy-level splittings from pulsed-gate spectroscopy data. Using S
 i/SiGe QD devices\, we demonstrate SWIFT both offline and in real time
 \, including automated tracking of QD excited states and lead resonanc
 es. These results provide a path toward incorporating confidence-guide
 d excited-state spectroscopy into autonomous QD characterization\, tun
 ing\, and optimization.
URL:https://www.physics.wisc.edu/events/?id=9809
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