Towards scalable cryogenic quantum dot biasing using memristor-based DC sources

TL;DR

This paper demonstrates the potential of memristor-based DC sources for cryogenic quantum dot biasing, showing experimental validation at 1.2K and proposing scalable CMOS-integrated solutions for large-scale quantum computing.

Contribution

It presents experimental validation of memristor-based DC sources at cryogenic temperatures and proposes a scalable CMOS-integrated approach for large-scale quantum dot biasing.

Findings

Successful operation of a cryogenic memristor-based DC source at 1.2K

Demonstrated tunability and low drift of the DC source prototype

Simulations indicate potential for monolithic integration of up to one million sources

Abstract

Cryogenic memristor-based DC sources offer a promising avenue for in situ biasing of quantum dot arrays. In this study, we present experimental results and discuss the scaling potential for such DC sources. We first demonstrate the operation of a commercial discrete operational amplifier down to 1.2K which is used on the DC source prototype. Then, the tunability of the memristor-based DC source is validated by performing several 250mV-DC sweeps with a resolution of 10mV at room temperature and at 1.2K. Additionally, the DC source prototype exhibits a limited output drift of $\approx1\mathrm{\mu Vs^{-1}}$ at 1.2K. This showcases the potential of memristor-based DC sources for quantum dot biasing. Limitations in power consumption and voltage resolution using discrete components highlight the need for a fully integrated and scalable complementary metal-oxide-semiconductor-based (CMOS-based) approach. To address this, we propose to monolithically co-integrate emerging non-volatile memories (eNVMs) and 65nm CMOS circuitry. Simulations reveal a reduction in power consumption, down to $\mathrm{10\mu W}$ per DC source and in footprint. This allows for the integration of up to one million eNVM-based DC sources at the 4.2K stage of a dilution fridge, paving the way for near term large-scale quantum computing applications.