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arXiv:2601.03922 · IEICE Transactions on Electronics

Integration and Resource Estimation of Cryoelectronics for Superconducting Fault-Tolerant Quantum Computers

Shiro Kawabata

quant-phcond-mat.mes-hallcond-mat.supr-conphysics.app-phSubmitted Jan 7, 2026• Announced Jan 8, 2026• 1 citation
v1 · Jan 7, 2026v2 · May 3, 2026
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Abstract

Scaling superconducting quantum computers to the fault-tolerant regime calls for a commensurate scaling of the classical control and readout stack. Today's systems largely rely on room-temperature, rack-based instrumentation connected to dilution-refrigerator cryostats through many coaxial cables. Looking ahead, superconducting fault-tolerant quantum computers (FTQCs) will likely adopt a heterogeneous quantum-classical architecture that places selected electronics at cryogenic stages -- for example, cryo-CMOS at 4~K and superconducting digital logic at 4~K and/or mK stages -- to curb wiring and thermal-load overheads. This review distills key requirements, surveys representative room-temperature and cryogenic approaches, and provides a transparent first-order accounting framework for cryoelectronics. Using an RSA-2048-scale benchmark as a concrete reference point, we illustrate how scaling targets motivate constraints on multiplexing and stage-wise cryogenic power, and discuss implications for functional partitioning across room-temperature electronics, cryo-CMOS, and superconducting logic.

Journal reference
IEICE TRANSACTIONS on Electronics E109-C (2026) 512-520
DOI
10.1587/transele.2025SEI0001
Comments
8 pages, 3 figures

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Scaling superconducting quantum computers to the fault-tolerant regime calls for a commensurate scaling of the classical control and readout stack. Today's systems largely rely on room-temperature, rack-based instrumentation connected to dilution-refrigerator cryostats through many coaxial cables. Looking ahead, superconducting fault-tolerant quantum computers (FTQCs) will likely adopt a heterogeneous quantum-classical architecture that places selected electronics at cryogenic stages -- for example, cryo-CMOS at 4K and superconducting digital logic at 4K and/or mK stages -- to curb wiring and thermal-load overheads. This review distills key requirements, surveys representative room-temperature and cryogenic approaches, and provides a transparent first-order accounting framework for cryoelectronics. Using an RSA-2048-scale benchmark as a concrete reference point, we illustrate how scaling targets motivate constraints on multiplexing and stage-wise cryogenic power, and discuss implications for functional partitioning across room-temperature electronics, cryo-CMOS, and superconducting logic.
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Current superconducting quantum computers (QC) rely on a brute-force scaling approach where quantum chips operating at the millikelvin stage inside dilution refrigerators are connected to room-temperature electronics via an ever-increasing number of signal wires. In order to drastically scale up such systems without facing refrigeration challenges, these quantum interface electronics need to be integrated at cryogenic temperatures, ideally at the same stage as qubits. In this paper, we show that, by employing energy-efficient digital superconducting microchips based on single flux quantum (SFQ) technology, all essential functions to operate a full stack quantum computer can be integrated at 10 mK. They include digital qubit charge control and magnetic flux control for single- and two-qubit gates, as well as digital qubit readout.
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.
Abstract Realizing a practically useful superconducting quantum computer will require a dramatic scale-up of quantum control electronics to meet the growth in required qubit counts. Conventional rack-based room-temperature control electronics impose severe constraints on wiring density, cost, and system footprint, creating a barrier to large-scale and fault-tolerant quantum computing. Here we demonstrate a hybrid quantum control architecture that combines cryogenic complementary metal-oxide semiconductor (cryo‑CMOS) application-specific integrated circuits (ASICs) for two‑qubit flux control with room‑temperature radio‑frequency electronics for single‑qubit control and readout. The resulting system achieves high density and scalable quantum control without compromising two‑qubit gate fidelity. Deployed on a 156‑qubit quantum processor, the cryo-CMOS subsystem achieves two‑qubit gate errors at the {10}^{-3} level, with a best randomized benchmarking error per gate of 8.4\times{10}^{-4}, stable operation over multi‑day timescales, and no measurable performance degradation as we increase the temperature of the cryo-CMOS ASICs from 7 to 20 K. Thermal analysis identifies cryo-CMOS chip operation near 20 K as a favorable regime, enabling efficient cooling of a large number of channels per cryostat. Compared against rack‑based flux-control, the cryo-CMOS subsystem achieves statistically indistinguishable two-qubit gate fidelities under matched gate settings and enables a tenfold improvement in system spatial footprint. These results establish cryo‑CMOS flux control as a practical and scalable foundation for large‑scale and fault-tolerant superconducting quantum systems.
Quantum computers hold the promise to solve some of the most complex problems of today. The core of a quantum computer is a quantum processor, which is composed of quantum bits (qubits). Qubits are fragile and their state needs to be corrected in real time by a classical controller. Today, the control of qubits is done at room temperature by racks of instruments, while qubits operate at several tens of milli-Kelvin. To ensure compactness, and eventually scalability, we have proposed the use of controllers operating at a few Kelvin, so as to reduce the length of control cables, while potentially enabling superconductive interconnects, which enable virtually zero resistance and low thermal conductivity. We have chosen CMOS to achieve this functionality due to its scalable nature and overall miniaturization opportunities. Cryogenic CMOS, or cryo-CMOS, circuits and systems need to be carefully designed, so as to ensure low noise and high bandwidth, while operating at strict power budgets of a few milliwatts per qubit. In this paper, we outline the requirements of a classical controller and we show examples of such circuits and systems. Results and perspectives are presented discussing a roadmap for the future.
Scaling fault-tolerant quantum computing (FTQC) requires orchestrating millions of operations continuously across a tightly coupled classical-quantum control stack. A critical challenge in this orchestration is determining the optimal hardware-software boundary, i.e., the Quantum Instruction Set Architecture (QISA). We focus on cryogenic, fixed-connectivity qubit platforms, such as superconducting and topological Majorana qubits. For these, existing QISA choices either operate at too low a level, violating cryogenic thermal budgets at scale, or at too high a level, imposing unrealizable complexity on the control engine. To reason about these tradeoffs, we introduce the ARIES instruction set hierarchy, which categorizes QISAs into distinct abstraction levels. To systematically evaluate these levels, we develop an end-to-end evaluation toolflow featuring a cycle-accurate classical driver and hardware engine simulator. Using eight quantum applications across superconducting and topological qubit platforms, we measure instruction bandwidth, transceiver power dissipation, and measurement processing overheads. We demonstrate that while physical-level abstractions exceed the thermal limits of dilution refrigerators by orders of magnitude, canonical-level abstractions significantly underestimate hardware routing congestion and execution runtimes. Our Level 4 QISA (local logical operations) offers an optimal architectural balance. As quantum hardware platforms scale toward FTQC in the coming years, our findings provide concrete architectural guidance for the design of their classical control stacks and instruction interfaces.