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Quantum Systems Analysis

There is increasing interest in quantum-enabled simulation and computation using small-scale quantum devices. We are working on the development of new theoretical and computational algorithms and techniques that can utilize such devices, which we are developing in parallel with the other efforts described here.

Lincoln Laboratory Staff

Andrew (Jamie) Kerman, Michael O’Keeffe, Kevin Obenland

Campus Faculty

Alan Aspuru-Guzik (Harvard, Chemistry), Isaac Chuang (MIT, Physics and EECS)

  • Provide machine-learning-based methods for quantum logic gate and circuit optimization that could lead to more efficient quantum code

Project Goals
  • Develop classical and quantum machine-learning techniques to improve error-correction protocols in gate-model quantum computing
  • Generate guidance for hardware designers of medium-scale quantum processors on what gates, codes, and architectures to build toward

Project Goals
  • Determine how errors endemic to a particular physical implementation for quantum information processing affect thresholds for different fault-tolerant methods and then optimize small quantum demo algorithms or quantum error-correcting codes for that implementation
Project Goals
  • Design an optical and microwave resonator to enhance the capability of NV magnetic field sensors
  • Develop laser threshold magnetometry using a whispering gallery mode resonator
  • Develop power-budget-optimized quantum sensors in a compact form factor


This diamond optical micro-resonator may enable resonant interaction with the NV’s within and allow for enhanced sensors.