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Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference

A Cryo-CMOS Low-Power Semi-Autonomous Qubit State Controller in 14nm FinFET Technology

David J. Frank, Sudipto Chakraborty, Kevin Tien, Pat Rosno, Thomas Fox, Mark Yeck, Joseph Glick, R. P. Robertazzi, Ray Richetta, John F. Bulzacchelli, Daniel Ramirez, Dereje Yilma, Andrew Davies, Rajiv Joshi, Shawn D. Chambers, Scott Lekuch, Ken Inoue, Devin Underwood, Dorothy Wisnieff, Christian W. Baks, Donald S. Bethune, John Timmerwilke, Blake R. Johnson, B. Gaucher, Daniel J. Friedman

Published Feb 20, 2022• 54 citations
Publisher

Abstract

Error-corrected quantum computing is expected to require at least 105to 106physical qubits. Superconducting transmons, which are promising qubit candidates for scaled quantum computing systems, typically require individually tailored RF pulses in the 4-to-6 GHz range to manipulate their states, so scaling to 106qubits presents an enormous challenge. Providing a control line for every qubit from room temperature (RT) to the 10mK environment does not appear to be viable for a 106qubit system due to multiple factors, including RF loss, mechanical congestion, heat load, and connector unreliability. TDM cannot be used to reduce the number of control lines since all of the qubits may need to be activated at once (e.g., during quantum error correction (QEC) cycles). FDM has been proposed but is undesirable because extra tones can give rise to unwanted qubit excitations.

DOI
10.1109/isscc42614.2022.9731538

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Advanced Intelligent Systems•May 26, 2022•12 citations
Error-corrected quantum computing is expected to require at least 105to 106physical qubits. Superconducting transmons, which are promising qubit candidates for scaled quantum computing systems, typically require individually tailored RF pulses in the 4-to-6 GHz range to manipulate their states, so scaling to 106qubits presents an enormous challenge. Providing a control line for every qubit from room temperature (RT) to the 10mK environment does not appear to be viable for a 106qubit system due to multiple factors, including RF loss, mechanical congestion, heat load, and connector unreliability. TDM cannot be used to reduce the number of control lines since all of the qubits may need to be activated at once (e.g., during quantum error correction (QEC) cycles). FDM has been proposed but is undesirable because extra tones can give rise to unwanted qubit excitations.
A scalable, non-multiplexed cryogenic 14-nm FinFET quantum bit (qubit) state controller (QSC) for use in the semi-autonomous control of superconducting transmon qubits is reported. The QSC includes an augmented general-purpose digital processor that supports waveform generation and phase rotation operations combined with a low-power current-mode single sideband upconversionI/Q{I}/{Q}I/Qmixer-based RF arbitrary waveform generator (AWG). Implemented in the 14-nm CMOS FinFET technology, the QSC generates control signals in its target 4.5–5.5-GHz-frequency range, achieving an spurious free dynamic range (SFDR) > 50 dB for a signal bandwidth of 500 MHz. With the controller operating in the 4 K stage of a cryostat and connected to a transmon qubit in the cryostat’s millikelvin stage, measured transmonT1T_{1}T1​andT2T_{2}T2​coherence times were 75.7 and 73μs\mu \text{s}μs, respectively, in each case comparable to results achieved using conventional room temperature (RT) controls. In further tests with transmons, a qubit-limited error rate of 7.76 × 10−4 per Clifford gate is achieved, again comparable to the results achieved using RT controls. The QSC’s maximum RF output power is −18 dBm, and power dissipation per qubit under active control is 23 mW.
This chapter will cover practical challenges for cryogenic CMOS designs for next generation quantum computing. Starting from system level, it will detail the design considerations for a non-multiplexed, semi-autonomous, transmon qubit state controller (QSC) implemented in 14nm CMOS FinFET technology. The QSC includes an augmented general-purpose digital processor that supports waveform generation and phase rotation operations combined with a low power current-mode single sideband upconversion I/Q mixer-based RF arbitrary waveform generator (AWG). Implemented in 14nm CMOS FinFET technology, the QSC generates control signals in its target 4.5GHz to 5.5 GHz frequency range, achieving an SFDR > 50dB for a signal bandwidth of 500MHz. With the controller operating in the 4K stage of a cryostat and connected to a transmon qubit in the cryostat’s millikelvin stage, measured transmon T1 and T2 coherence times were 75.7μs and 73μs, respectively, in each case comparable to results achieved using conventional room temperature controls. In further tests with transmons, a qubit-limited error rate of 7.76×10-4 per Clifford gate is achieved, again comparable to results achieved using room temperature controls. The QSC’s maximum RF output power is -18 dBm, and power dissipation per qubit under active control is 23mW.
Quantum computing promises exponential speed-up in solving certain complex problems that would be intractable by classical computers. However, thousands or millions of qubits might be required to solve useful problems. High-precision and low-noise electrical signals are required to manipulate and read the state of a qubit and to control qubit-to-qubit interactions. Current systems use room temperature electronics with many coax cables routed to the qubit chip inside a dilution refrigerator. This approach does not scale to large number of qubits, due to form factor, cost, power consumption and thermal load to the fridge. To address this challenge, a cryogenic qubit controller has been proposed [1]. The first integrated implementation of a cryogenic pulse modulator has been presented in [2], demonstrating the capability of manipulating (drive) the state of superconducting qubits. The work in [3] extends the capability of the controller with 3 main features: frequency-multiplexing to reduce the number of RF cables per qubit, an arbitrary I/Q pulse generation for improved control fidelity and a digitally-intensive architecture with integrated instruction set to enable integration in existing quantum control stacks. This work further advances the prior art by integrating the capability of reading the qubit state and generating the voltage pulses required for drive, readout, 2-qubit operations and qubit characterization. The SoC can drive up to 16 spin qubits by frequency multiplexing over a single RF line, read the state of up to 6 qubits simultaneously and control up to 22 gate potentials. The SoC also integrates a μ\muμ-controller for increased flexibility in implementing the control instruction set. The proposed cryogenic controller can replace all the high-speed control electronics used in conventional solutions today, paving the way towards scalable quantum computers.
In today's mainstream superconducting quantum computing platforms in a dilution refrigerator, the qubits work at a cryogenic temperature (CT) of a few tens of mK, while the qubit controller hardware works on plates with temperature ranging from a few K to room temperature (RT). The highly-integrated cryo-CMOS qubit controller ASIC that can fully work at 3-4K has been proven to be the most feasible way to scale down the quantum computing system [1–5]. In [1], a pulse modulator is implemented with a limited qubit driving capability, which can only generate fixed length symmetric driving pulse. The controllers in [2], [3] generated the RF driving pulse with a frequency division multiplexing (FDM) mode, with the power dissipation of 192mW/qubit and 46.5mW/qubit, respectively. In [4], a local oscillator (LO) was included to improve the controller integration level, and the chip power consumption was 24.1mW/qubit. An arbitrary waveform generation (AWG) functionality digital design was presented in [5] with a power consumption of 23.1mW/qubit. Nevertheless, with continuously increasing number of qubits to integrate, it remains as one of the major tasks to further reduce the power consumption and size of controller.
Extensive research on quantum mechanics in past decades has successfully paved the way towards the disruptive technology of quantum computing. A further step to the realization of a fault-tolerant scalable quantum computer is presenting challenges in the field of engineering. It necessitates a microsystem operating at 4K in a dilution refrigerator, which would be inevitable to control thousands or millions of qubits sitting at 10mK. There have been IC implementations of pulse modulators generating qubit-controlling microwave signals [1– 4]. The pulse modulation based on direct synthesis demonstrated feasibility of driving multiple qubits with frequency-division multiplexing (FDM) through one RF cable [1 – 3]. The first implementation of a full controller [1], which includes both read and write chains for spin qubits, demonstrated the highest level of integration. However, the previous work used external local oscillator (LO) sources for frequency synthesis. External feeding of LO requires precise matching; otherwise, a failure would cause leakage to the qubit driving output through PCB traces, resulting in AC-Stark shift of qubit state by unwanted tones at near-resonance. It becomes more problematic in FDM-based multi-qubit driving. Since the fidelity of qubit operations strongly relies on the quality of driving frequency, a low-noise LO generation by a phase-locked loop (PLL) is one of the most important factors [5]. The internal generation of LO gives additional benefits in superconducting qubit interface. It necessitates multiple LOs since the superconducting qubit uses microwave pulse driving for both read and write. To detect the state of a qubit through dispersive readout, the phase reflected from the readout resonator should be measured. Therefore, the driving pulses for the read and the write should be synchronized to a single reference timing. Using built-in PLLs sharing a single reference clock naturally solves this problem.
Quantum computing promises an exponentially higher computational power than classical computers; although all the building blocks have become available, certain constraints still prevent quantum advantage. The fundamental challenge in building a practical quantum computer is integrating thousands of highly coherent qubits with the control and readout electronics. The need for a high‐coherence qubit drives the effort for quantum error correction algorithms to create fault‐tolerant quantum systems. Error correction becomes tangible in a quantum processor only in large numbers of qubits. Thus, the other challenge is reducing the number of physical interconnects (coaxial lines) between the quantum–classical interface and bulky room‐temperature electronics. To interface thousands of qubits, interconnects can be reduced by bringing the control and readout electronics near the quantum processor. Cryogenic complementary metal–oxide–semiconductor (CMOS) technology has been an ideal candidate for this purpose. Integrated control and readout at cryogenic temperatures require low power dissipation circuit designs and techniques such as frequency‐division multiplexing (FDM) due to the finite cooling power of a dilution refrigerator. Herein, an overview of each building block in a superconducting quantum computer is provided, focusing on scalability. Furthermore, this article is concluded with an outlook discussing current challenges and future directions for the scalable superconducting control and readout.