| EPSRC Reference: |
GR/S47649/01 |
| Title: |
Novel Machine Learning Approaches to Molecular Coherent Control |
| Principal Investigator: |
Whitaker, Professor JBC |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Sch of Chemistry |
| Organisation: |
University of Leeds |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 February 2004 |
Ends: |
31 July 2007 |
Value (£): |
442,363
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Gas & Solution Phase Reactions |
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| EPSRC Industrial Sector Classifications: |
| Aerospace, Defence and Marine |
Chemicals |
| Electronics |
Information Technologies |
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| Related Grants: |
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| Panel History: |
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Summary on Grant Application Form |
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To apply machine learning techniques to develop new, robust and efficient, optimisation algorithms for coherent control and to apply these to quantum control problems. The initial aim is to demonstrate control over chemical processes, such as the branching ratio of a photochemically driven reaction, by means of tailored optical pulses whose profile is learned through an empirically driven feedback loop based on a genetic algorithm. We will then develop a more intelligent adaptive approach in which the search for the optimum pulse shape is also informed by chemical knowledge in addition to the empirical feedback from the controlled reaction. To achieve this we will perform experiments (in the gas phase and in solution) on a statistically significant number of chemically related compounds, and so assess how best to represent chemical knowledge in machine learning applications. The project will also develop technology to specify the temporal modulation of a laser pulse that could be used for a new generation of spectroscopic instrumentation and even to implement a quantum computer, and these possibilities will also be explored.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.leeds.ac.uk |