Emergent Mind

Abstract

Quantum simulation holds the promise of improving the atomic simulations used at EDF to anticipate the ageing of materials of interest. One simulator in particular seems well suited to modeling interacting electrons: the Rydberg atoms quantum processor. The first task of this thesis is to design a variational algorithm that can be implemented on a Rydberg atom simulator for chemistry. This algorithm is specially designed for this platform and optimized by recent theoretical tools. We compare our numerical results, obtained with an emulation of a real experiment, with other approaches and show that our method is more efficient. Finally, we show that by limiting the number of measurements to make the experiment feasible on a real architecture, we can reach the fundamental energy of H2, LiH and BeH2 molecules with 5% error.For a second algorithm, we used the "slave" spin method to implement the physics of the Fermi-Hubbard 2D model on a Rydberg atom simulator. The idea is to decouple the degrees of freedom of charges and "slave" spins using a mean field to obtain two self-consistent Hamiltonians: a classically solvable one and an Ising Hamiltonian that can be reproduced on a real machine. We show numerically that we can recover a Mott transition from the initial model with this method even when emulating the noise of a real experiment, and we show that we can also recover the dynamics of non-equilibrium electrons in this same paradigm with good results. Both algorithms can possibly be improved theoretically until they reach materials of interest, but they can also be implemented on today's existing architectures, to achieve a potential quantum advantage

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