Advanced Quantum Testbed (AQT)

Built High-Throughput Materials Characterization Pipeline in Python: “Statistical Observation of Quantum Decoherence” (StOQD)

• Optimized experimental data collection using Gaussian Process Regression

• Automated XPS analysis and low temperature quantum device characterization

• Data/Results stored in centralized repository in HDF5

• Custom sample representation syntax for statistical comparison/machine learning on samples

Using StOQD, improved Quality Factor of superconducting quantum resonators by factor of 5 through interface engineering and cross-correlation analysis of materials/electrical properties

• Performed X-Ray Photoelectron Spectroscopy on superconducting quantum devices

• Interpreted experimental results through mathematical modelling of superconducting quantum device behavior as well as error estimation using Bayesian error estimation and Monte Carlo Methods.

• Worked collaboratively with theorists and experimentalists to improve experimental design.

Developed XPS python package

• Deconvolution of spectral peaks and cross-correlation of atomic compounds across multiple spectra

• Various machine learning tools implemented: LDA, QDA, PCA, Non-Negative Matrix factorization and Nerural Network for parameter initialization

• High quality visualization capabilities using matplotlib

• PyQt GUI Application

Coordinated presentation of results from all aspects of the AQT

Mathematical Modeling

• Modeled the energy transfer between electron, spin & lattice subsystems after femtosecond laser excitation

• Simulated the rapid thermal expansion & subsequent vibrational dynamics of nanostructures

• Visualized the spatial character of spin waves in nanomagnets excited by surface acoustic waves

• Modeled energy transfer and lattice dynamics of ferrimagnetic systems subject to femtosecond laser excitation using mean-field theory

• Derived 2nd principal equation describing magnon-phonon dynamics in nanostructures

Experimental Data Analysis

• Used techniques such as background subtraction, digital filtering, FFT, least-squares regression, & Monte Carlo methods to analyze of magnetic & acoustic dynamics

• Fit spin-wave dispersion using the LLG equation to estimate magnetic parameters

• Fit and analyzed magnon-phonon coupling within individual nanostructures

Experimental Data Acquisition

• Performed time-domain measurements of the picosecond spin dynamics & vibrational modes in isolated nanostructures, arrays, & thin films via ultrafast magneto-optic spectroscopy

• Maintained 1.6 Watt Ti:Sapphire laser oscillator system & second harmonic generation cavity

• Measured dynamic μrad polarization rotations using lock-in modulation & differential detection

• Built autonomous experimental setup using LabVIEW, MATLAB, & instrument-specific software to record/analyze data & interface with equipment such as mechanical delay lines, lock-in detectors, digital multimeters, cameras, sensors, electromagnets, & piezoelectric actuators

• Designed & characterized kinetic optical systems with sub-micron precision & femtosecond resolution

• Built an ultrafast laser setup to optically control the magnetization of thin films with micron precision via helicity-dependent switching - included a wide-field magneto-optic microscope to image magnetic domains

• Designed & fabricated phononic & magnetic nanostructures to implement novel characterization techniques

• Built free-space optical setup using a Nd:YAG laser to measure optical power limiting of various hyper-branched polymers.

• Fabricated and characterized organic-nano particles of TCNQ-Perylene for potential use as LEDs and Photovoltaics