PhD position in Robust Tensor Networks Algorithms for Quantum Computing at Lille University

Quantum computing is at the cutting edge of technological innovation,
offering the potential to solve complex problems that classical “binary”
computers cannot address. Tensor algebra, with its comprehensive
mathematical framework, offers crucial tools for modeling and
approximating large multidimensional datasets. This thesis seeks to
investigate the interplay between tensor networks and quantum computing
by proposing original, robust (to decoherence of qubits) quantum
algorithms that utilize tensor structures to improve computational
efficiency and capabilities. This research requires a multidisciplinary
understanding of quantum physics and linear algebra. This thesis topic
will benefit from the complementary expertises of Remy Boyer
(CRISTAL/SIGMA) for the multilinear algebra aspect and Giuseppe Patera
(PhLAM, Quantum Information team) for the quantum physics aspect.