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Andy Mounce


Andy Mounce has research experience in condensed matter physics, semiconductor qubits, nitrogen vacancy magnetometry, and defects in wide band gap semiconductors. His expertise includes utilizing quantum information science techniques for understanding basic properties of quantum materials and quantum information relevant materials, such as superconductors, strongly correlated electronic materials, magnetic materials, and topological phases in materials. These techniques include cryogenic amplification, optically detected magnetic resonance, nitrogen vacancy detected magnetometry, photoluminescence, and bulk spin-resonance. Additionally, he is using machine learning in image analysis techniques, such as compressive sensing and neural networks, to both optimize experimental implementations and analysis.