Ion traps fabricated in a CMOS foundry

We demonstrate trapping in a surface-electrode ion trap fabricated in a 90-nm CMOS (complementary metal-oxide-semiconductor) foundry process utilizing the top metal layer of the process for the trap electrodes. The process includes doped active regions and metal interconnect layers, allowing for co-fabrication of standard CMOS circuitry as well as devices for optical control and measurement. With one of the interconnect layers defining a ground plane between the trap electrode layer and the p-type doped silicon substrate, ion loading is robust and trapping is stable. We measure a motional heating rate comparable to those seen in surface-electrode traps of similar size. This is the first demonstration of scalable quantum computing hardware, in any modality, utilizing a commercial CMOS process, and it opens the door to integration and co-fabrication of electronics and photonics for large-scale quantum processing in trapped-ion arrays.Comment: 4 pages, 3 figure

Ablation loading of barium ions into a surface electrode trap

Trapped-ion quantum information processing may benefit from qubits encoded in isotopes that are practically available in only small quantities, e.g. due to low natural abundance or radioactivity. Laser ablation provides a method of controllably liberating neutral atoms or ions from low-volume targets, but energetic ablation products can be difficult to confine in the small ion-electrode distance, micron-scale, microfabricated traps amenable to high-speed, high-fidelity manipulation of ion arrays. Here we investigate ablation-based ion loading into surface-electrode traps of different sizes to test a model describing ion loading probability as a function of effective trap volume and other trap parameters. We demonstrate loading of ablated and photoionized barium in two cryogenic surface-electrode traps with 730 $\mu$m and 50 $\mu$m ion-electrode distances. Our loading success probability agrees with a predictive analytical model, providing insight for the confinement of limited-quantity species of interest for quantum computing, simulation, and sensing