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Quantum computers can potentially solve problems that are intractable for classical computers. However, despite the development of a theory on the processing of quantum information over the years, the computers we use every day still outperform their quantum counterparts, if we exclude some as interesting as specific tasks. In fact, quantum states that are manipulated in place of bits are extremely sensitive to noise and thus make the quantum computation error-prone.
Quantum error correction is thus crucial in this context. While in classical information theory, redundancy can be used to detect and correct the error, in the quantum domain we usually encode the information typically stored in one quantum bits in many bits entangled among them. The error correction protocol is especially efficient when the overall states used to encode the information are non-Gaussian. However, non-Gaussian states are much more difficult to generate than Gaussian ones, and improving success probability of conditional sources is key to make them fast and reliable. The goal of the project is to evaluate the strengths and weaknesses of these conditional sources, based, for example, on Gaussian boson sampling devices, and determine which modifications can enhance their success probability or reduce the required resources.
Khabat Heshami
Imperial College London
Physics
Education
University of Ottawa
Globalink Research Award
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