Quantum technologies offer unprecedented capabilities in computation and secure information transfer. Their implementation requires qubits to operate at cryogenic temperatures (CT) while control and readout electronics typically still remains at room temperature (RT). As systems scale to millions of qubits, the electronics should also operate at CT to avoid a wiring bottleneck. However, wired power transfer from RT for such electronics introduces severe challenges, including thermal load between cooling stages, Joule heating, noise coupling, and wiring scalability. This paper addresses those challenges by evaluating several candidate architectures for scalable power transfer in the dilution frige: high-voltage (HV) wired power transfer, radiative wireless transfer, non-radiative wireless transfer, and a hybrid HV and non-radiative transfer. These architectures are analyzed in terms of thermal load, power loss, heating, coupling noise, power density, scalability, reliability, and complexity. Comparative analysis demonstrates the trade-offs among these architectures, while highlighting HV non-radiative transfer as a promising candidate for scalable quantum systems.

This paper presents extensive guidelines for the design of an integrated DC-readout interface for semiconductor spin qubits. Since the focus is on the readout via a single electron transistor (SET), the SET behavior and performance are first described and modeled, showing that the signal-to-noise ratio (SNR) theoretically achievable by a SET-based DC-readout is significantly beyond the state-of-the-art. Practical circuit architectures for implementing a DC-readout, such as the voltage amplifier, the transimpedance amplifier, the charge sampling, and the current pre-amplifier, are then analyzed by deriving their design equations and trade-offs. As a result, the practical performances of those different solutions are evaluated and compared, thus presenting clear selection criteria for the readout architecture and its design equations given the specific parameters of the SET sensor.

Design, simulation, analysis and verification methodologies are crucial for developing electronic circuits and systems at large. Whereas long-standing EDA software is used in the semiconductor technology, there is no counterpart for quantum computing systems yet. Although the quantum computing community started utilizing and adapting some of the already existing EDA tools, for instance, to design quantum processors and control electronics for driving the qubits, or even to solve some quantum computing design tasks, they do not fully use the expertise gained over the last decades in the field of design automation. Current intermediate-scale quantum computers have been designed in an ‘adhoc’ manner with heterogeneous methods and tools. As we are entering the large-scale era, it is timely and key to further adopt EDA methodologies and software for quantum computing. In this paper, we provide an overview on how full-stack quantum computing systems are being implemented nowadays and discuss which the main challenges are for transitioning from this current scenario to a comprehensive framework encompassing full automated system-wide architecting, design, simulation, verification, and test.

This paper presents a floating inverter amplifier (FIA) that performs high-linearity amplification and sampling while driving a 2$\times$time-interleaved (TI) SAR ADC, operating from room temperature (RT) down to 4.2 K. The power-efficient FIA samples the continuous-time input signal by windowed integration, thus avoiding the traditional sample-and-hold. Cascode switching, a floating supply and accurate pulse-width timing calibration enable high-speed operation and interleaving. In addition, by exploiting the behavior of CMOS devices at cryogenic temperatures, forward-body-biasing (FBB) is pushed well beyond what is possible at RT to ensure performance down to 4.2 K, and its impact on the performance of cryogenic circuits is analyzed. The resulting ADC, implemented in 40-nm bulk CMOS and including the FIA driver, achieves SNDR$=$38.7 dB (38.2 dB), SFDR$>$50 dB ($>$50 dB), and FOMW$=$25.4 fJ/conv-step (31.3 fJ/conv-step) with Nyquist-rate input at 1.0 GS/s (0.9 GS/s) at 4.2 K (RT), respectively.

Despite Noisy Intermediate-Scale Quantum devices being severely constrained, hardware- and algorithm-aware quantum circuit mapping techniques have been developed to enable successful algorithm executions. Not so much attention has been paid to mapping and compilation implementations for spin-qubit quantum processors due to the scarce availability of experimental devices and their small sizes. However, based on their high scalability potential and their rapid progress it is timely to start exploring solutions on such devices. In this work, we discuss the unique mapping challenges of a scalable crossbar architecture with shared control and introduce SpinQ , the first native compilation framework for scalable spin-qubit architectures. At the core of SpinQ is the Integrated Strategy that addresses the unique operational constraints of the crossbar while considering compilation scalability and obtaining a O(n) computational complexity. To evaluate the performance of SpinQ on this novel architecture, we compiled a broad set of well-defined quantum circuits and performed an in-depth analysis based on multiple metrics such as gate overhead, depth overhead, and estimated success probability, which in turn allowed us to create unique mapping and architectural insights. Finally, we propose novel mapping techniques that could increase algorithm success rates on this architecture and potentially inspire further research on quantum circuit mapping for other scalable spin-qubit architectures.

The grand challenge of scaling up quantum computers requires a full-stack architectural standpoint. In this position paper, we will present the vision of a new generation of scalable quantum computing architectures featuring distributed quantum cores (Qcores) interconnected via quantum-coherent qubit state transfer links and orchestrated via an integrated wireless interconnect.

This article presents a 4-to-5GHz LC oscillator operating at 4.2K for quantum computing applications. The phase noise (PN) specification of the oscillator is derived based on the control fidelity for a single-qubit operation. To reveal the substantial gap between the theoretical predictions and measurement results at cryogenic temperatures, a new PN expression for an oscillator is derived by considering the shot-noise effect. To reach the optimum performance of an LC oscillator, a common-mode (CM) resonance technique is implemented. Additionally, this work presents a digital calibration loop to adjust the CM frequency automatically at 4.2K, reducing the oscillator’s PN and thus improving the control fidelity. The calibration technique reduces the flicker corner of the oscillator over a wide temperature range (10$\times $and 8$\times $reduction at 300K and 4.2K, respectively). At 4.2K, our 0.15-mm2 oscillator consumes a 5-mW power and achieves a PN of −153.8dBc/Hz at a 10MHz offset, corresponding to a 200-dB FOM. The calibration circuits consume only a 0.4-mW power and 0.01-mm2 area.

Abstract Image analysis is a branch of signal analysis that focuses on the extraction of meaningful information from images through digital image processing techniques. Convolution is a technique used to enhance specific characteristics of an image, while deconvolution is its inverse process. In this work, we focus on the deconvolution process, defining a new approach to retrieve filters applied in the convolution phase. Given an imageIand a filtered image $$I' = f(I)$$ I′=f(I) , we propose three mathematical formulations that, starting fromIand $$I'$$ I′ , are able to identify the filter $$f'$$ f′ that minimizes the mean absolute error between $$I'$$ I′ and $$f'(I)$$ f′(I) . Several tests were performed to investigate the applicability of our approaches in different scenarios. The results highlight that the proposed algorithms are able to identify the filter used in the convolution phase in several cases. Alternatively, the developed approaches can be used to verify whether a specific input imageIcan be transformed into a sample image $$I'$$ I′ through a convolution filter while returning the desired filter as output.

Accurate and low-noise generation and amplification of microwave signals are required for the manipulation and readout of quantum bits (qubits). A fault-tolerant quantum computer operates at deep cryogenic temperatures (i.e., <; 100mK) and requires thousands of qubits for running practical quantum algorithms. Consequently, CMOS radio-frequency (RF) integrated circuits operating at cryogenic temperatures down to 4 K (Cryo-CMOS) offer a higher level of system integration and scalability for future quantum computers. In this paper, we extensively discuss the role, benefits, and constraints of Cryo-CMOS for qubits control and readout. The main characteristics of the CMOS transistors and their impacts on RF circuit designs are described. Furthermore, opportunities and challenges of low noise RF signal generation and amplification are investigated.

I. VLSI Systems: A Glance Into The Last Decades Since their inception in 1970s, VLSI systems have enabled several new technological capabilities and made them accessible to an unceasingly wider range of users, reaching a scale that has been exponentially increasing over the decades[1](seeFig. 1). Relentless integration of more complex systems has driven such remarkable evolution, as made possible by the inexorable miniaturization. As shown inFig. 1, more functionality has been crammed in a consistently smaller form factor, as exemplified by the physical volume shrinking of computers by 100 X/decade[2],[3]. At the same time, the energy per task has been decreasing at 10–100 X/decade, as shown inFig. 2, for several systems and system-on-chip subsystems[4]. This allowed packing more capabilities into the same power envelope, as generally observed in the electronic systems, even before the advent of the integrated circuit[5].

A quantum computer fundamentally comprises a quantum processor and a classical controller. The classical electronic controller is used to correct and manipulate the qubits, the core components of a quantum processor. To enable quantum computers scalable to millions of qubits, as required in practical applications, the simultaneous optimization of both the classical electronic and quantum systems is needed. In this paper, a co-design methodology is proposed for obtaining an optimized qubit performance while considering practical trade-offs in the control circuits, such as power consumption, complexity, and cost. The SPINE (SPIN Emulator) toolset is introduced for the co-design and co-optimization of electronic/quantum systems. It comprises a circuit simulator enhanced with a Verilog-A model emulating the quantum behavior of single-electron spin qubits. Design examples show the effectiveness of the proposed methodology in the optimization, design and verification of a whole electronic/quantum system.

Quantum computers1 could revolutionize computing in a profound way due to the massive speedup they promise. A quantum computer comprises a cryogenic quantum processor and a classical electronic controller. When scaling up the cryogenic quantum processor to at least a few thousands, and possibly millions, of qubits required for any practical quantum algorithm, cryogenic CMOS (cryo-CMOS) electronics is required to allow feasible and compact interconnections between the controller and the quantum processor. Cryo-CMOS leverages the CMOS fabrication infrastructure while exploiting the continuous improvement of performance and miniaturization guaranteed by Moore's law, in order to enable the fabrication of a cost-effective practical quantum computer. However, designing cryo-CMOS integrated circuits requires a new set of CMOS device models, their embedding in design and verification tools, and the possibility to co-simulate the cryo-CMOS/quantum-processor architecture for full-system optimization. In this paper, we address these challenges by focusing on their impact on the design of complex cryo-CMOS systems.

A smart CMOS thermal wind sensor has been optimized for commercial use. Optimizing the sensor chip's thermal design resulted in better area efficiency and improved thermal dynamics with respect to prior work. The latter simplifies the off-chip decimation of the sensor's bitstream outputs. Moreover, by realizing more logic on-chip, the number of bond wires has been reduced by 33%, to 8, thus reducing manufacturing costs. Fabricated in a standard 0.7μm CMOS process, the sensor chip occupies 4×4mm2and consumes 25mW of heating power, while achieving an inaccuracy of ±6% (speed) and ±2° (direction), for wind speeds between 4 and 25m/s.

This work describes a method of implementing a fully-integrated ultra-low power (ULP) radio for wireless sensor networks (WSN). This is achieved using a specific medium access control (MAC) protocol, employing a duty- cycled wake-up radio and a crystal-less clock generator, and an ad-hoc modulation scheme (Impulse Radio) with a bandwidth of 17.7 MHz in the 2.4 GHz - ISM band. The total average power consumption is expected to be less than 100 muW.