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

量子计算(QC)的最新重大突破是首次展示了具有50多个超导量子比特的量子系统，从而实现了量子至上。其他非常有前景的量子比特技术包括基于Si、SiGe或III-V量子点(QD)的自旋量子比特。它们利用非常成熟的CMOS技术和制造工艺，在芯片级别提供低成本和高度可扩展的量子系统。主要的研究中心和行业，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是用位于低温恒温器外部的笨重的经典电子设备来执行的。由于没有完全集成的低温电子学，自旋量子比特和控制电子学之间存在着布线瓶颈，因此不可能建立大规模的量子系统。此外，量子点容易受到制造缺陷和环境干扰所固有的器件之间的变异性。因此，质量控制领域的下一个重大突破是使用集成的原位低温电子来自动化控制基于量子点的非常大量的自旋量子位。3IT和1QBit的合作旨在(I)展示基于低功耗机器学习和内存计算范式的固态量子点的实时自动调谐，该范例基于CMOS电路和新兴的基于TiOx的电阻存储器(OxRAM)的共集成；以及(Ii)设计和制造专门设计用于在低温下运行的超低功耗人工智能硬件以进行原位调谐。这一独特的概念验证将为快速、节能的人工智能解决方案与低温恒温器内的量子电路共存实现大规模量子系统铺平道路。

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.