Cryogenic Time-Division-Multiplexed Voltage Control for Scalable Trapped-Ion Quantum Processors

TL;DR

This paper demonstrates cryogenic time-division multiplexed voltage control systems for static and dynamic electrodes in trapped-ion quantum computers, addressing system scaling challenges.

Contribution

It develops and experimentally validates TDM-based voltage control schemes operating at cryogenic temperatures for both static and dynamic electrodes.

Findings

Achieved 37.5 kHz voltage update rate for static electrodes at ~27 K.

Achieved 1 MHz voltage update rate for dynamic electrodes at ~14 K.

Established TDM voltage control as practical for scalable trapped-ion quantum processors.

Abstract

Trapped-ion quantum computers based on the quantum charge-coupled device architecture require on the order of ten trap electrodes per qubit, making the number of vacuum feedthroughs a bottleneck at the system scale. Time-division multiplexed (TDM)-based voltage control for trap electrodes provides a natural route to alleviate this constraint. However, previous studies have been limited to architectural proposals for static trap-potential compensation and room-temperature demonstrations of dynamic-electrode control, leaving cryogenic operation of TDM-based voltage control for static and dynamic electrodes experimentally unexplored. In this study, we develop and cryogenically validate TDM-based voltage control schemes for two distinct electrode classes. For static electrodes used in trap-potential compensation, we implement a 32-channel demultiplexed system operating at approximately 27~K, achieving an effective voltage update rate of 37.5~kHz with an output range of $\pm10~\mathrm{V}$ per channel. For dynamic electrodes used in ion operations, such as shuttling, we implement a four-channel demultiplexed system operating at approximately 14~K, achieving an effective voltage update rate of 1~MHz with a comparable output range. These results establish TDM-based voltage control as a practical approach for both electrode classes, providing a path for mitigating the vacuum feedthrough bottleneck in scalable trapped-ion quantum processors.