Scalable Quantum Computing Architecture with Mixed Species Ion Chains

TL;DR

This paper advances scalable quantum computing using mixed species ion chains, demonstrating effective cooling, ion-photon entanglement, and plans for surface trap integration to improve control and scalability.

Contribution

It presents progress in implementing mixed species ion chains for scalable quantum computing, including cooling techniques, entanglement generation, and surface trap integration.

Findings

Cooling of mixed ion chains is effective at low ion numbers.

Ion-photon entanglement fidelity exceeds 0.84.

Progress towards surface trap implementation for better control.

Abstract

We report on progress towards implementing mixed ion species quantum information processing for a scalable ion trap architecture. Mixed species chains may help solve several problems with scaling ion trap quantum computation to large numbers of qubits. Initial temperature measurements of linear Coulomb crystals containing barium and ytterbium ions indicate that the mass difference does not significantly impede cooling at low ion numbers. Average motional occupation numbers are estimated to be $\bar{n} \approx 130$ quanta per mode for chains with small numbers of ions, which is within a factor of three of the Doppler limit for barium ions in our trap. We also discuss generation of ion-photon entanglement with barium ions with a fidelity of $F \ge 0.84$, which is an initial step towards remote ion-ion coupling in a more scalable quantum information architecture. Further, we are working to implement these techniques in surface traps in order to exercise greater control over ion chain ordering and positioning.