From the earliest days of the field of quantum information, trapped atomic ions have had great potential as qubits. Trapped-ion experiments have demonstrated the individual ingredients believed necessary for scalable quantum information processing, and, for small numbers of ions, many of these ingredients have been combined within the same experimental system. Scaling the capabilities of such test-bed systems to larger numbers of qubits will require a higher level of integration between traps, electronics, optics, and control systems than has been achieved to date. Moreover, calibrating and controlling such a complex system with the necessary speed and accuracy will demand a far greater degree of automation than could be achieved through human intervention.

To explore these challenges, the Quantum Information Systems Group at GTRI has microfabricated several ion traps incorporating 40+ control electrodes, including a long linear trap, a trap with a curved mirror microfabricated onto its surface, an X-junction trap, and a trap with integrated microwave lines. In the linear traps we have loaded long chains with more than 20 resolved ions, while the mirror trap enhanced the collection of ion fluorescence by a factor of 1.8. The junction and microwave traps, when fully tested, should allow us to reorder ions into an arbitrary linear configuration and to perform fast qubit rotations, respectively. Successful operation of these traps necessitates accurate and precise modeling of their electromagnetic properties, so we have developed an in-house method-of-moments simulation package, capable of handling millions of elements, which we use to derive an accurate basis set of micromotion compensation potentials. We are planning an experiment to incorporate in-vacuum DAC electronics alongside a trap chip, all mounted on a single compact circuit board within the vacuum chamber. Finally, we have developed a machine language, known as “OPCODEs”, that translates high-level schedules directly into experimental operations for our ion traps. The success of OPCODEs relies on automated calibration and control of trap parameters, accurate modeling of the potentials required for compensation, and automated detection of ion positions. I will present our most recent experimental results in these areas.