CMOS-OxRAM integrated circuits for low-power AI and cryogenic quantum dot auto-tuning

量子计算（QC）的最新重大突破是展示了具有50多个超导量子比特的量子系统，首次实现了量子霸权。其他非常有前途的量子位技术包括基于Si、SiGe或III-V族量子点（QD）的自旋量子位。它们利用CMOS技术和制造工艺的高度成熟，在芯片级提供低成本和高度可扩展的量子系统。主要的研究中心和工业公司，如CEA和英特尔，已经开始报告基于半导体技术的高质量自旋量子比特。然而，自旋量子比特的校准和控制仍然主要由位于低温恒温器外部的笨重的经典电子设备手动执行。由于自旋量子比特和控制电子设备之间的“布线瓶颈”，完全集成的低温电子设备的缺乏使得不可能构建大规模的量子系统。此外，QD易于因制造缺陷和环境扰动而固有的设备间差异。因此，QC的下一个重大突破之一是使用集成的原位低温电子器件自动控制基于量子点的大量自旋量子位。3 IT和1 QBit之间的合作伙伴关系旨在（i）使用低功耗机器学习和基于CMOS电路和新兴的基于TiOx的电阻存储器（OxRAM）的共集成的内存计算范例来展示固态量子点的真实的实时自动调谐以及（ii）设计和制造超低功率人工智能硬件，该硬件专门设计为在低温下操作以用于原位调谐。这种独特的概念验证将为大规模量子系统铺平道路，这些系统由快速且节能的AI解决方案与低温恒温器内的量子电路共同定位。

The latest major breakthrough in quantum computing (QC) has been the demonstration of quantum systems with more than 50 superconducting qubits allowing quantum supremacy for the first time. Other very promising qubit technologies include spin qubits based on Si, SiGe or III-V quantum dots (QDs). They leverage the great maturity of CMOS technologies and fabrication processes to offer low cost and highly scalable quantum systems at the chip level. Major research centers and industrials like CEA and Intel have started to report high quality spin qubits based on semiconductor technologies. However, the calibration and control of spin qubits are still performed mostly by hand with bulky classical electronics located outside the cryostat. The absence of fully integrated cryogenic electronics makes it impossible to build a large-scale quantum system due to the "wiring bottleneck" between the spin qubits and the control electronics. Additionally, QDs are prone to device-to-device variability inherent to manufacturing imperfections and environment perturbations. One of the next major breakthroughs in QC is thus to automate the control of very large numbers of spin qubits based on QDs using integrated in-situ cryogenic electronics.The partnership between 3IT and 1QBit aims to (i) demonstrate real time auto-tuning of solid-state QDs using low-power machine learning and In-Memory Computing paradigm based on the co-integration of CMOS circuits and emerging TiOx-based resistive memories (OxRAM) and (ii) design and fabricate ultra-low power artificial intelligence hardware specifically designed to operate at cryogenic temperature for in-situ tuning. This unique proof-of-concept will pave the way for large-scale quantum systems enabled by fast and energy efficient AI solutions co-located with quantum circuits inside a cryostat.