Available student project - Machine learning for optics and controls

Research fields

  • Photonics, Lasers and Nonlinear Optics
A suspended steerable mirror, complete with drive electronics. The mirror will form one part of the optical cavity to be controlled by a machine learning system.

Project details

Modern gravitational wave detectors such as Advanced LIGO, which recently detected gravitational waves, are the most sensitive measurement devices ever constructed.  They are based around multiple nested optical cavities, with each mirror in the system suspended to limit the impact of local seismic motion.  This leaves the mirrors free to move, but for the detectors to function, the mirrors positions and orientations must be precisely sensed and delicately controlled.  This yields a rich controls problem with many relevant degrees-of-freedom.  

We want to apply the methods of machine learning and artificial intelligence to this controls problem, to find optimal solutions that cannot be obtained by humans in a reasonable time.  This project will develop a machine learning system for alignment control of a single optical cavity.  The machine learning system will be trained and tested with a numerical simulation of a cavity system, and then demonstrated in a table-top optical experiment.  

Required background

Some knowledge of python or another imperative programming language, image processing experience would be useful.  

Project suitability

This research project can be tailored to suit students of the following type(s)
  • PhB (1st year)
  • PhB (2nd or 3rd year)
  • Honours project
  • Phd or Masters

Contact supervisor

Ward, Robert profile

Other supervisor(s)

Slagmolen, Bram profile
Research Fellow

Updated:  4 September 2019/ Responsible Officer:  Director, RSPhys/ Page Contact:  Physics Webmaster