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Near-term quantum algorithms

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If you have a question about this talk, please contact Dr Vivien Gruar.

Can be both open-ended or well-defined (depending on student interest).

Open-ended version: you will read and understand recent papers on near-term quantum algorithms (choice according to your interest), implement a simulation into code and hopefully suggest improvements to the algorithm.

Well-defined version: you will focus on active machine learning variational quantum algorithms to solve chemistry problems (i.e. finding ground state energies of compounds like H2O , O2 etc.).

An even more well-defined version: you will optimise existing company code of standard quantum algorithms (such as Shor’s, Grover’s, eigensolver) or a particular algorithm recently invented by the company.

This talk is part of the Cambridge Mathematics Placements Seminars series.

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