This paper presents an extensive characterization and modeling of a commercial 28-nm FDSOI CMOS process operating down to cryogenic temperatures. The important cryogenic phenomena influencing this technology are discussed. The low-temperature transfer characteristics including body-biasing are modeled over a wide temperature range (room temperature down to 4.2\,K) using the design-oriented simplified-EKV model. The trends of the free-carrier mobilities versus temperature in long and short-narrow devices are extracted from dc measurements down to 1.4\,K and 4.2\,K respectively, using a recently-proposed method based on the output conductance. A cryogenic-temperature-induced mobility degradation is observed on long pMOS, leading to a maximum hole mobility around 77\,K. This work sets the stage for preparing industrial design kits with physics-based cryogenic compact models, a prerequisite for the successful co-integration of FDSOI CMOS circuits with silicon qubits operating at deep-cryogenic temperatures.
In the strive for scalable quantum processors, significant effort is being devoted to the development of cryogenic classical hardware for the control and readout of a growing number of qubits. Here we report on a cryogenic circuit incorporating a CMOS-based active inductor enabling fast impedance measurements with a sensitivity of 10 aF and an input-referred noise of 3.7 aF/sqrt(Hz). This type of circuit is especially conceived for the readout of semiconductor spin qubits. As opposed to commonly used schemes based on dispersive rf reflectometry, which require mm-scale passive inductors, it all…
Solid-state quantum computers require classical electronics to control and readout individual qubits and to enable fast classical data processing [1-3]. Integrating both subsystems at deep cryogenic temperatures [4], where solid-state quantum processors operate best, may solve some major scaling challenges, such as system size and input/output (I/O) data management [5]. Spin qubits in silicon quantum dots (QDs) could be monolithically integrated with complementary metal-oxide-semiconductor (CMOS) electronics using very-large-scale integration (VLSI) and thus leveraging over wide manufacturing …
The most promising quantum algorithms require quantum processors hosting millions of quantum bits when targeting practical applications. A major challenge towards large-scale quantum computation is the interconnect complexity. In current solid-state qubit implementations, a major bottleneck appears between the quantum chip in a dilution refrigerator and the room temperature electronics. Advanced lithography supports the fabrication of both CMOS control electronics and qubits in silicon. When the electronics are designed to operate at cryogenic temperatures, it can ultimately be integrated with…