Quantum Software for Simulation of molecular systems on NISQ devices

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Near-term Intermediate Scale Quantum (NISQ) devices describe quantum devices which are available today, or within the next few years. Quantum hardware is not yet fully fault tolerant and error corrected, meaning that any algorithms running on current devices are subject to noise. This project aims to develop and test algorithms for simulation of molecular systems on NISQ devices. An example of a scheme which can be simulated is the Hubbard model. There will be a strong focus upon validation throughout this project, where the goal is to develop the most accurate quantum algorithms possible.Included in the PhD work is a continuation of a project developing a hybrid quantum - classical machine learning scheme for quantum state discrimination in the presence of noise. This is a scheme where the output of a quantum device is minimised by a classical machine learning algorithm. The work is an extension of previous work examining the case where the quantum device is subject to noise. This work will then be used later in the PhD to develop hybrid machine learning algorithms for molecular simulation.