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REVIEW 3 major objections 4 minor 70 references

Revisiting Thermal Scalability for Large-Scale Superconducting Quantum Systems

T0 review · 3 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read Readout-amplifier heat—dissipation plus bias-wire conduction—is the dominant thermal bottleneck in modern superconducting quantum systems, and omitting it overestimates qubit capacity by up to about a factor of two.

desk verdict Careful model that adds a real missing term, but the flashy result (144→80 qubits) depends on AWG30 copper wire and 4× multiplexing; still worth refereeing. read the letter →

arxiv 2608.00990 v1 pith:SNBV5RDN submitted 2026-08-02 quant-ph

Shaswot Shresthamali , Ilkwon Byun , Teruo Tanimoto , Yoshinori Uzawa , Kunihiro Inomata , Tsuyoshi Yamamoto , Koji Inoue This is my paper
classification quant-ph PACS 03.67.Lx07.20.Mc85.25.-j
keywords thermalscalabilitysuperconductingqubitscryogenicreadoutamplifierspassiveheatloaddilutionrefrigeratorbottleneckmigrationfault-tolerantquantumcomputingamplifierbiaswiring
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper sets out to correct the system-level heat accounting used to decide how many superconducting qubits a dilution refrigerator can support. Its central claim is that the readout amplification chain—the active power dissipated by 4 K amplifiers, the passive heat conducted down their bias wires, and Joule heating in those wires—is now the dominant thermal bottleneck in modern cryogenic systems, a term earlier scalability models omit or only partially include. Under the paper's accounting, that omission is not benign: in the high-density-wiring system previously estimated to hold about 144 qubits, the corrected model supports about 80; in an optical-architecture claim of roughly 3,000 qubits, the corrected model yields about 170. The paper then maps which amplifier-and-wiring combinations reduce the amplifier load and shows that lowering amplifier power alone often does not help because bias-wire conduction or ohmic heat takes over. A sympathetic reader would care because the paper redirects engineering priorities: improving refrigeration and cable heat loads only exposes amplifier heat as the next wall, so single-fridge 10k-qubit systems require solving the readout chain's thermal footprint first.

What carries the argument

The carrying device is a stage-by-stage ledger of normalised heat load (NHL): each contribution—passive conduction, active dissipation, ohmic (Joule) heating—is divided by the cooling power of the stage that absorbs it, and the first stage whose cumulative NHL reaches unity sets the physical-qubit capacity. The new term inserted into that ledger is the amplifier module's full three-part load, and the argument's engine is bottleneck migration: improving wiring and refrigeration moves the limiting stage from the cold plate toward 4 K, where the amplifier terms dominate.

What would settle it

Measure the actual residual cooling power of a KIDE-class platform at 4 K and CP under load, and calorimetrically measure the steady heat conducted into 4 K by one AWG30 copper amplifier-bias wire over the 50 K–4 K span. If the per-wire conduction is well below the model's roughly 6.8 mW, or if the real 4 K capacity is much larger than 6 W, the claim that amplifier bias wires dominate the modern 4 K budget and cap capacity at about 80 qubits in the HDW case would fail, and the bottleneck would sit elsewhere.

Watch

Extended reading notes

Core claim

The paper's central discovery is that amplifier-associated heat—three mechanisms bundled in one module: the always-on dissipation of the cryogenic readout amplifier, passive conduction through its DC bias wires, and Joule heating in those same wires—emerges as the dominant normalised heat load at the 4 K stage once modern low-PHL wiring and higher-capacity refrigerators relieve the millikelvin stages. Where prior models placed the bottleneck at the cold plate (as in the stainless-steel, XLD400 system that supports 144 qubits), the modernised configuration (Cri/oFlex wiring in a KIDE fridge) shifts the bottleneck to 4 K and makes amplifier heat the first constraint; when bias-wire passive con

Load-bearing premise

The modern-system numbers rest on an unverified input: the cooling powers assumed for the KIDE refrigerator (90 W at 50 K, 6 W at 4 K, 90 mW at Still, 3 mW at CP, 90 µW at MXC) are estimates obtained by treating KIDE as three independent XLD1000sl-class units, because measured values are not public; if the real 4 K or CP cooling profile differs materially, the point at which amplifier heat becomes the dominant bottleneck, and the headline capacity figures, would shift.

Editorial extensions

If this is right

  • Systems designed with older models will underestimate the 4 K stage's stress; adding amplifier bias-line passive conduction alone cuts the HDW/XLD1000sl capacity from about 144 to about 80 physical qubits.
  • Reducing amplifier active power is not sufficient: with copper bias wires every amplifier option is dominated by bias-wire passive conduction, so the lowest-active-power amplifier (ULP-HEMT) carries the largest total load when paired with copper.
  • Amplifier-heat reductions saturate: once the per-amplifier 4 K budget drops below about 2 mW, the bottleneck migrates to MXC at roughly 4,688 qubits, so further amplifier improvements add no capacity.
  • With today's components in a KIDE-class fridge the system reaches only about 700–800 physical qubits; reaching 10k requires optical interconnects with the photodetector at 4 K, YBCO-based superconducting microwave striplines, or a Colossus-class fridge with dilution units redistributed toward the cold plate.
  • Even if lower-gain amplifier chains degrade measurement error by up to 4x, the larger physical-qubit budget still yields more logical qubits than the current HEMT-copper baseline (about 4 versus 2 at a target logical error rate of 0.001).

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the paper's accounting is right, an immediate test is available from operating hardware: calorimetric measurement of the 4 K heat floor of one tiled readout chain (amplifier plus its bias wires) in a production dilution refrigerator would either confirm or contradict the roughly 7 mW per wire of passive conduction that drives the headline result.
  • The same three-term ledger should apply to any other always-on component with room-temperature-to-4 K wiring—bias-T networks, DC blocks, cryogenic CMOS control electronics—so the framework is a template for auditing those subsystems as they scale.
  • The results imply readout multiplexing is a thermal lever as much as a wiring one: doubling multiplexing from 4x to 8x halves the number of amplifier modules and, with copper wiring, nearly halves the dominant 4 K load—a tradeoff the paper flags but does not quantify.
  • A testable engineering corollary: because bias-wire material alone moves the per-amplifier load by nearly two orders of magnitude, swapping copper bias wires for Manganin or YBCO in an existing machine should measurably extend the 4 K margin before any amplifier or fridge upgrade.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. The paper develops a steady-state thermal scalability model for large-scale superconducting quantum systems, adding previously omitted readout-amplifier heat terms: active dissipation, passive conduction through bias wires, and ohmic (Joule) heating in those wires. The model is validated against the 100-qubit-scale system of [8], reproducing its 144-qubit capacity with CP as the bottleneck. The authors then apply the model to modern configurations with lower-PHL wiring (HDW, Cri/oFlex) and higher-capacity fridges (KIDE), concluding that amplifier-associated heat at 4 K becomes the dominant bottleneck and that prior system-level models that omit amplifier bias-wire loads misidentify the bottleneck and overestimate physical-qubit capacity. The paper also explores mitigation options (Manganin or YBCO bias wires, ULP-HEMT and SIS amplifiers, current splitting), integrates surface-code logical-error simulations to estimate logical-qubit yield, and assesses forward-looking 10k-qubit pathways with optical interconnects and the Colossus platform.

Significance. If the central claim survives scrutiny, this is a useful and timely correction to system-level cryogenic scalability models: it identifies a concrete, currently omitted heat term that changes the location of the thermal bottleneck and the estimated qubit capacity of modern systems. The framework is flexible and transparent, with the full implementation publicly available, validation against a real system (Section IV-A), and a conservative treatment of several secondary heat sources. The T-pad attenuator analysis (Appendix A-E) and the optimal current-splitting expression (Eq. 8) are clean and transferable. However, the main quantitative conclusions are conditional on a few unvaried architectural assumptions, so the strength of the abstract currently runs ahead of the demonstrated robustness.

major comments (3)
  1. [Section IV-C / Table 3 / Appendix B-G] The HDW comparison that yields the headline 'roughly half' capacity reduction (144 to ~80 qubits) is driven by the choice of AWG30 copper bias wires, whose PHL into 4 K is 6.81 mW/wire, versus 1.23 mW/wire for the AWG35 wires used in [8]. Using AWG35, the per-amplifier 4 K load in Table 10 would be about 7.8 mW + 3×1.23 mW ≈ 11.5 mW instead of 28.07 mW, which could largely or entirely close the gap with [11]'s 144-qubit estimate. The paper does not report this sensitivity, even though AWG35 is a plausible installed-wire choice. The claim that omitting bias-line PHL causes a ~2× overestimation therefore needs to be quantified as a function of wire gauge.
  2. [Section V / Section IV-A] All system-level results assume 4× readout multiplexing, which fixes one amplifier per four qubits. Section V acknowledges that 8× multiplexing halves the number of amplifiers and their associated heat, but no system-level sweep over the multiplexing factor is presented. Since the central claim is that amplifier heat is the dominant 4 K bottleneck, halving that load could shift the bottleneck to CP or MXC under otherwise identical assumptions. The abstract and the Section IV-A conclusion should either be conditioned on the multiplexing factor or accompanied by a sensitivity analysis showing that the bottleneck identification is robust.
  3. [Appendix A-A / Table 1] The modern-system scenarios in Section IV-A and Section V rely on KIDE cooling powers (90 W at 50 K, 6 W at 4 K, 90 mW at Still, 3 mW at CP, 90 µW at MXC) estimated by treating KIDE as three independent XLD1000sl-class dilution units. These values are not measured, as the paper states. The claim that the bottleneck 'has shifted to 4 K' and is dominated by amplifier heat depends on these assumed powers. The authors should provide a sensitivity analysis varying the KIDE cooling profile, or explicitly restrict the conclusion to 'under the assumed KIDE cooling budget.'
minor comments (4)
  1. [Eq. (3) and Eq. (4)] The notation 'L / A(TH-TL) ∫' is ambiguous: it should be written as (L/(A(TH-TL))) ∫ or with explicit parentheses, since it could be read as L/(A(TH-TL)) or L/A × (TH-TL).
  2. [Table 3] The resistance entries for AWG35 copper are listed as '-' even though the OHL for the [8] reconstruction depends on it. If AWG35 resistance is unavailable, the text should state the impact of this missing parameter on the relevant heat budgets.
  3. [Section VI-1] The PHL of the hypothetical shielded YBCO stripline is set to 5× the PHL of a single YBCO bias wire by assumption. This multiplier directly affects the 12k/16k qubit estimates. It is flagged in the text as an estimate, but the basis for the factor of five should be stated more explicitly.
  4. [Abstract / Section VII] Section VII appropriately states that the model identifies trends rather than exact operating points, but the abstract states the bottleneck shift as an unconditional result. The abstract should be softened to reflect the parametric dependence noted above.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the bottleneck analysis follows from external component data and disclosed assumptions; no prediction is equivalent to an input by construction.

full rationale

The paper builds a steady-state thermal model from independently reported component data (cable PHL, amplifier AHL, fridge cooling powers) and then computes stage-level normalized heat loads. The central claim that amplifier-associated heat becomes the dominant bottleneck in modern configurations is a calculated output, not a restatement of an input. Section III-B2 explicitly discloses that AWG30 copper bias wires are assumed for all configurations other than the [8] system, and Section V discloses the uniform 4x readout multiplexing assumption. These are legitimate parameter choices, and the paper itself notes in Section V that increasing multiplexing to 8x would halve amplifier heat. Section VII further limits the model to identifying trends rather than exact operating points, which is an honest scope statement rather than a hidden circular move. The reconstruction of the [8] system in Section IV-A reproduces the published 144-qubit CP-bottleneck result, providing an external validation check. The only self-citation ([10], grouped with prior scalability models) is not load-bearing, since the omission claim is corroborated by the external references [8], [9], and [11]. No equation is defined in terms of its own conclusion, no fitted parameter is renamed as a prediction, and no uniqueness claim is imported from the authors' prior work. The derivation chain is therefore self-contained and not circular.

Assumptions & free parameters 7 free parameters · 10 assumptions · 2 invented entities

The quantitative conclusions rest on the estimated fridge cooling powers, the chosen wire and amplifier parameters, and the stated steady-state and linear-scaling assumptions. The largest uncertainties are KIDE and Colossus cooling-power profiles and the bias-wire material inputs. The central qualitative claim, that amplifier-related heat matters and can move the bottleneck to 4 K, is less sensitive to workload details because amplifier and bias-wire heat are essentially always-on.

free parameters (7)
  • KIDE cooling powers = 50K: 90 W, 4K: 6 W, Still: 90 mW, CP: 3 mW, MXC: 90 uW
    Estimated as 3x XLD1000sl residual powers because measured KIDE values are not public. All modern-system bottleneck and capacity results depend on these values (Table 1, Appendix A-A).
  • Colossus cooling powers = 50K: 9 kW, 4K: 200 W, 2K: 10 W, Still: 100 mW, CP: 3 mW, MXC: 300 uW
    Projected residual powers from refs [15], [16], used for the forward-looking 10k-qubit scenarios. The values are not measured platform specifications.
  • Bias wire material and geometry = AWG30 copper PHL 6.81 mW per wire at 4 K; Manganin 25.47 uW; YBCO 3.84 uW
    The conclusion that bias-wire PHL dominates the 4 K budget depends on these material-model values, the chosen AWG30 gauge, and the RRR=50 assumption (Table 3, Appendix A-B).
  • Readout multiplexing factor = 4x
    Sets the number of amplifier chains per qubit; a 10k-qubit system uses 2500 amplifiers. An 8x multiplexing factor would halve amplifier heat. The authors fix 4x for consistency (Section V).
  • Physical error probabilities = 1Q 6.2e-4, 2Q 2.8e-3, measurement 8e-3, reset 1.5e-3, idle 9e-3
    Borrowed from the [3] platform and applied to both CX and CZ architectures. These values determine code distance and logical-qubit yield, though not the thermal bottleneck itself (Table 9).
  • Optical link constants and Optical-LP drive power reduction = R = 1 A/W, Z = 10 kOhm; drive powers reduced by 15 dB in Optical-LP
    Optimistic assumptions for photonic-link scenarios. The 15 dB reduction is explicitly labeled a sensitivity study and hypothetical operating regime (Section III-D4, VI-2).
  • YBCO microwave stripline PHL multiplier = 5x the PHL of a single YBCO bias wire
    Ad hoc scaling used to estimate the PHL of a hypothetical shielded YBCO stripline between 50 K and 4 K (Section VI-1, Appendix B-L).
assumptions (10)
  • domain assumption Each fridge stage maintains its specified operating temperature whenever the total heat load is below the stage cooling power, with no inter-stage thermodynamic coupling or temperature rise.
    Section III-A and VII. This steady-state assumption is load-bearing because the model computes capacities by comparing summed heat loads against fixed cooling powers.
  • domain assumption An 8-qubit unit cell scales linearly to N qubits, ignoring boundary effects, geometric crowding, routing congestion, crosstalk, and chip-layout constraints.
    Section III-G and VII. Used to convert per-unit-cell heat loads into system capacities for 10k-qubit estimates.
  • domain assumption Attenuators dissipate all incident signal power as heat at the stage where they are anchored.
    Section III-D3. This is a worst-case estimate for attenuator active heat loads.
  • domain assumption Passive heat conduction into a stage comes only from the immediately warmer flange; radiation and conduction through insulation are omitted.
    Section III-B and Appendix A-B. Consistent with prior models but excludes radiative and non-adjacent-stage paths.
  • ad hoc to paper KIDE behaves as three independent XLD1000sl-class dilution units with functionally separated cryocoolers.
    Appendix A-A. The paper states this is a modeling assumption, not a manufacturer-specified configuration, and it sets all KIDE cooling powers.
  • ad hoc to paper Colossus-CP can reassign two dilution units from MXC to CP without thermodynamic coupling penalties.
    Section VI-3 and Appendix B-R. The authors call this an idealized redistribution and note that real dilution-unit reassignment may introduce stability and efficiency problems.
  • ad hoc to paper A shielded YBCO microwave stripline has PHL equal to 5x the PHL of a single YBCO bias wire and is usable from 50 K to 4 K at large scale.
    Section VI-1 and Appendix B-L. Only laboratory-scale YBCO microwave interconnects have been demonstrated; the 5x scaling is a paper-specific estimate.
  • domain assumption Optical photonic links operate with responsivity 1 A/W and 10 kOhm control-line impedance, and the relocated 4 K termination has at least 35 dB isolation.
    Section III-D4, Appendix B-E and A-D. These are optimistic but stated assumptions; the 35 dB isolation gives a first-order noise estimate, not a demonstrated qubit-compatible configuration.
  • domain assumption All qubits are continuously engaged in repeated ESM cycles with high activity.
    Section III-G. This conservative upper bound on active heat is used to produce lower bounds on qubit capacity.
  • domain assumption Skin-effect and microwave-frequency conductor loss in control and readout lines are negligible relative to the modeled heat loads.
    Section III-C2. The authors omit frequency-dependent AC resistance, which is reasonable at the low powers and duty cycles considered but is still an omission.
invented entities (2)
  • Ag-YBCO-NbTi microwave stripline
    purpose: Hypothetical RF interconnect with reduced PHL between 50 K and 4 K, used in a configuration that reaches above 10k estimated physical qubits.
    YBCO microwave interconnects have only been demonstrated as laboratory-scale prototypes; the 5x bias-wire PHL scaling and the shielded geometry are assumed (Section VI-1, Appendix B-L).
  • Colossus-CP fridge configuration
    purpose: Hypothetical redistribution of dilution units within the Colossus platform to increase CP cooling power from 3 mW to 6 mW, enabling 10k-plus-qubit scenarios.
    The authors describe it as an idealized thermodynamic upper bound and note that reassigning dilution units may not be straightforward (Section VI-3).

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Cite this review

Pith. "Pith review of Revisiting Thermal Scalability for Large-Scale Superconducting Quantum Systems." pith.science (2026). https://pith.science/paper/SNBV5RDN

@misc{pith2026260800990,
  author       = {Pith},
  title        = {Pith review of: Revisiting Thermal Scalability for Large-Scale Superconducting Quantum Systems},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/SNBV5RDN}},
  note         = {Machine review of arXiv:2608.00990}
}
read the original abstract

The readout amplification chain imposes a critical thermal scalability bottleneck in large-scale superconducting quantum systems. This happens through three mechanisms: amplifier dissipation, passive conduction through bias wiring and Joule heating within that same wiring. These terms are absent or only partially represented in several prior system-level thermal-scalability models, leading to bottleneck misidentification and scalability overestimation. In this work, we improve upon previous system-level heat estimation models by fully accounting for the major heat sources in modern cryogenic quantum systems including the active dissipation, passive conduction, and Joule heating in the readout amplifier module. Our analysis demonstrates that amplifier-associated heat emerges as the dominant thermal bottleneck that fundamentally alters the thermal landscape of modern large-scale cryogenic systems. We explore various technology options and their tradeoffs to identify configurations that reduce this critical heat load and improve scalability. Finally, we evaluate forward-looking system configurations, including larger refrigeration platforms and optical approaches, and analyze forward-looking pathways toward single-fridge 10k-qubit cryogenic systems.

Figures

Figures reproduced from arXiv: 2608.00990 by the authors.

Figure 1
Figure 1. FIGURE 1 [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
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Figure 2. FIGURE 2 [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
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Figure 3. FIGURE 3 [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figures from the paper (44 more)
Figure 5
Figure 5. Figure 5: During fault-tolerant operation, the dominant recurring ac￾tivity is repeated error-syndrome measurement (ESM), also referred to as the surface-code cycle. This cycle repeatedly triggers control and readout operations across the system and therefore directly determines…
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Figure 4. Figure 4: FIGURE 4 [PITH_FULL_IMAGE:figures/full_fig_p012_4.png]
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Figure 5. Figure 5: FIGURE 5 [PITH_FULL_IMAGE:figures/full_fig_p012_5.png]
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Figure 6. Figure 6: FIGURE 6 [PITH_FULL_IMAGE:figures/full_fig_p013_6.png]
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Figure 7. Figure 7: FIGURE 7 [PITH_FULL_IMAGE:figures/full_fig_p013_7.png]
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Figure 8. Figure 8: FIGURE 8 [PITH_FULL_IMAGE:figures/full_fig_p014_8.png]
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Figure 9. Figure 9: (a) shows the thermal profile of the original system using our modeling methodology. Each stacked bar corre￾sponds to a temperature stage, with the heights representing normalized total heat load. The stacked segments indicate contributions from individual sources. The…
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Figure 10. Figure 10: FIGURE 10 [PITH_FULL_IMAGE:figures/full_fig_p018_10.png]
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Figure 11. Figure 11: FIGURE 11 [PITH_FULL_IMAGE:figures/full_fig_p018_11.png]
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Figure 25. Figure 25: The modeled trend is consistent with reports in [PITH_FULL_IMAGE:figures/full_fig_p030_25.png]
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Works this paper leans on

70 extracted references · 63 canonical work pages

  1. [8]

    Engineering cryogenic setups for 100-qubit scale superconduct- ing circuit systems

    Sebastian Krinner, Simon Storz, Philipp Kurpiers, Paul Magnard, Johannes Heinsoo, Raphael Keller, Janis Luetolf, Christopher Eichler, and Andreas Wallraff. Engineering cryogenic setups for 100-qubit scale superconduct- ing circuit systems. EPJ Quantum Technology, 6(1):2, 2019

    work page 2019

  2. [11]

    Cryogenic thermal modeling of microwave high density signaling

    Naomi Raicu, Tom Hogan, Xian Wu, Mehrnoosh Vahidpour, David Snow, Matthew Hollister, and Mark Field. Cryogenic thermal modeling of microwave high density signaling. EPJ Quantum Technology, 12(1):124, 2025

    work page 2025

  3. [9]

    Scaling up superconducting quantum computers with cryogenic rf-photonics

    Sanskriti Joshi and Sajjad Moazeni. Scaling up superconducting quantum computers with cryogenic rf-photonics. Journal of Lightwave Technology, 42(1):166–175, 2023

    work page 2023

  4. [1]

    How to build a quantum supercomputer: Scaling from hundreds to millions of qubits

    Masoud Mohseni, Artur Scherer, K Grace Johnson, Oded Wertheim, Matthew Otten, Navid Anjum Aadit, Yuri Alexeev, Kirk M Bresniker, Kerem Y Camsari, Barbara Chapman, et al. How to build a quantum supercomputer: Scaling from hundreds to millions of qubits. arXiv preprint arXiv:2411.10406, 2024

    arXiv 2024

  5. [2]

    Enabling technolo- gies for scalable superconducting quantum computing

    Xanthe Croot, Kasra Nowrouzi, Christopher Spitzer, Carmen G Al- mudever, Alexandre Blais, Malcolm Carroll, Jerry Chow, Daniel Fried- man, Masao Tokunari, Edoardo Charbon, et al. Enabling technolo- gies for scalable superconducting quantum computing. arXiv preprint arXiv:2512.15001, 2025

    arXiv 2025

  6. [3]

    Abanin, Laleh Aghababaie-Beni, Igor Aleiner, Trond I

    Rajeev Acharya, Dmitry A. Abanin, Laleh Aghababaie-Beni, Igor Aleiner, Trond I. Andersen, Markus Ansmann, Frank Arute, Kunal Arya, Abraham Asfaw, Nikita Astrakhantsev, Juan Atalaya, Ryan Babbush, Dave Bacon, Brian Ballard, Joseph C. Bardin, Johannes Bausch, Andreas Bengtsson, Alexander Bilmes, Sam Blackwell, Sergio Boixo, Gina Bortoli, Alexan- dre Bourass...

    work page 2025

  7. [4]

    Ibm technology roadmap

    IBM. Ibm technology roadmap. https://www.ibm.com/roadmaps/ quantum/2025/, 2025. [Accessed 04-11-2025]

    work page 2025

  8. [5]

    Roadmap | Google Quantum AI — quantumai.google

    Google. Roadmap | Google Quantum AI — quantumai.google. https: //quantumai.google/roadmap, 2025. [Accessed 04-11-2025]

    work page 2025

Show all 70 references
  1. [6]

    Fujitsu starts official development of plus-10,000 qubit su- perconducting quantum computer targeting completion in 2030

    Fujitsu. Fujitsu starts official development of plus-10,000 qubit su- perconducting quantum computer targeting completion in 2030. https: //global.fujitsu/en-global/pr/news/2025/08/01-01-en, 2025. [Accessed 04- 11-2025]

  2. [7]

    QuantWare announces scaling breakthrough with VIO- 40K™, delivering 10,000 qubit Quantum Processors for the first time | Quantware — quantware.com

    QuantWare. QuantWare announces scaling breakthrough with VIO- 40K™, delivering 10,000 qubit Quantum Processors for the first time | Quantware — quantware.com. https://quantware.com/news/ quantware-announces-scaling-breakthrough-with-vio-40k, 08-12-2025. [Accessed 29-01-2026]

    2025

  3. [10]

    Qisim: Architecting 10+ k qubit qc interfaces toward quantum supremacy

    Dongmoon Min, Junpyo Kim, Junhyuk Choi, Ilkwon Byun, Masamitsu Tanaka, Koji Inoue, and Jangwoo Kim. Qisim: Architecting 10+ k qubit qc interfaces toward quantum supremacy. In Proceedings of the 50th Annual International Symposium on Computer Architecture, pages 1–16, 2023

    2023

  4. [12]

    Flexible cryogenic i/o

    Delft Circuits. Flexible cryogenic i/o. https://photonteck.com/uploads/ 20241109/b3531c2c55a53a8e034ba1e998f3f7ee.pdf, 22-02-2024. [Ac- cessed 19-12-2025]

    2024

  5. [13]

    High-Density Wiring — bluefors.com

    BlueFors. High-Density Wiring — bluefors.com. https://bluefors.com/ products/measurement-infrastructure/high-density-wiring/, 2025. [Ac- cessed 11-12-2025]

    2025

  6. [14]

    KIDE Cryogenic Platform — bluefors.com

    BlueFors. KIDE Cryogenic Platform — bluefors.com. https://bluefors. com/products/kide-cryogenic-platform/, 2025. [Accessed 07-11-2025]

    2025

  7. [15]

    A large millikelvin platform at fermilab for quantum computing applications

    Matthew I Hollister, Ram C Dhuley, and Grzegorz L Tatkowski. A large millikelvin platform at fermilab for quantum computing applications. In IOP Conference Series: Materials Science and Engineering, volume 1241, page 012045. IOP Publishing, 2022

    2022

  8. [16]

    An update on the colossus mk platform at fermilab

    Matthew I Hollister, Ram C Dhuley, Christopher James, and Grzegorz L Tatkowski. An update on the colossus mk platform at fermilab. In IOP Conference Series: Materials Science and Engineering, volume 1302, page 012030. IOP Publishing, 2024

    2024

  9. [17]

    Thermal capacity mapping of cryogenic platforms for quantum computers

    Scott A Manifold, George B Long, and Jonathan J Burnett. Thermal capacity mapping of cryogenic platforms for quantum computers. arXiv preprint arXiv:2503.10775, 2025

    2025 arXiv

  10. [18]

    Cryogenic Catalogue 2022

    coax.co.jp. Cryogenic Catalogue 2022. https://www.coax.co.jp/wcaxp/ wp-content/uploads/2022/10/Cryogenic_catalogue_2022.pdf, 2022. [Ac- cessed 15-07-2026]

    2022

  11. [19]

    Effect of neutron irradiation on the density of low-energy excitations in vitreous silica

    Terry Lee Smith, PJ Anthony, and AC Anderson. Effect of neutron irradiation on the density of low-energy excitations in vitreous silica. Physical Review B, 17(12):4997, 1978

    1978

  12. [20]

    Equivalence of flexible stripline and coaxial cables for superconducting qubit control and readout pulses

    VY Monarkha, Slawomir Simbierowicz, M Borrelli, R van Gulik, N Drobotun, D Kuitenbrouwer, D Bouman, Debom Datta, Patrik Eske- linen, Elsa Mannila, et al. Equivalence of flexible stripline and coaxial cables for superconducting qubit control and readout pulses. Applied Physics ...

    2024

  13. [21]

    Thermalization of a flexible microwave stripline measured by a superconducting qubit

    Patrick Paluch, Martin Spiecker, Nicolas Gosling, Viktor Adam, Jakob Kammhuber, Kiefer Vermeulen, Daniël Bouman, Wolfgang Wernsdorfer, and Ioan M Pop. Thermalization of a flexible microwave stripline measured by a superconducting qubit. Applied Physics Letters, 126(3), 2025. 5...

    2025

  14. [22]

    Control and readout of a superconducting qubit using a photonic link

    Florent Lecocq, Franklyn Quinlan, Katarina Cicak, Jose Aumentado, SA Diddams, and JD Teufel. Control and readout of a superconducting qubit using a photonic link. Nature, 591(7851):575–579, 2021

    2021

  15. [23]

    LNF-NANO9M - Low Noise Factory — lownoisefac- tory.com

    Low Noise Factory. LNF-NANO9M - Low Noise Factory — lownoisefac- tory.com. https://lownoisefactory.com/product/lnf-nano9m/, 2025. [Ac- cessed 18-12-2025]

    2025

  16. [24]

    Development of a cryogenic system for the characterization of advanced cmos technologies down to 350 mk

    Martínez-R Ismael, Omar López-L, Daniel Ferrusca, Miguel Velázquez, EA Gutiérrez-D, D Durini, et al. Development of a cryogenic system for the characterization of advanced cmos technologies down to 350 mk. In 2021 IEEE International Instrumentation and Measurement Technology C...

    2021

  17. [25]

    Ybco-on-kapton: Material for high-density quantum computer interconnects with ultra-low thermal loss

    Vyacheslav Solovyov, Olli-Pentti Saira, Zachary Mendleson, and Ilya Drozdov. Ybco-on-kapton: Material for high-density quantum computer interconnects with ultra-low thermal loss. IEEE Transactions on Applied Superconductivity, 31(5):1–5, 2021

    2021

  18. [26]

    Cryogenic material properties OFHC Copper — trc.nist.gov

    NIST. Cryogenic material properties OFHC Copper — trc.nist.gov. https://trc.nist.gov/cryogenics/materials/OFHC%20Copper/OFHC_ Copper_rev1.htm, 2010. [Accessed 18-12-2025]

    2010

  19. [27]

    Cryogenic Properties of Copper — copper.org

    Copper Development Association Inc. Cryogenic Properties of Copper — copper.org. https://www.copper.org/resources/properties/cryogenic/,

  20. [28]

    twire.co.jp

    Tokyo Wire Works. twire.co.jp. https://www.twire.co.jp/english/ {A}lloy2-en.html, 2026. [Accessed 10-02-2026]

    2026

  21. [29]

    Characterization of the pressure coefficient of manganin and temperature evolution of pressure in piston-cylinder cells

    Li Xiang, Elena Gati, Sergey L Bud’ko, Raquel A Ribeiro, Arif Ata, Ulrich Tutsch, Michael Lang, and Paul C Canfield. Characterization of the pressure coefficient of manganin and temperature evolution of pressure in piston-cylinder cells. Review of Scientific Instruments, 91(9), 2020

    2020

  22. [30]

    Cryogenic wire — lakeshore.com

    Lakeshore Cryotronics. Cryogenic wire — lakeshore.com. https://www.lakeshore.com/products/categories/specification/ temperature-products/cryogenic-accessories/cryogenic-wire, 2025. [Accessed 18-12-2025]

    2025

  23. [31]

    Microwaves in quantum computing

    Joseph C Bardin, Daniel H Slichter, and David J Reilly. Microwaves in quantum computing. IEEE journal of microwaves, 1(1):403–427, 2021

    2021

  24. [32]

    Calibration of a cross-resonance two-qubit gate between directly coupled transmons

    AD Patterson, J Rahamim, T Tsunoda, PA Spring, S Jebari, K Ratter, M Mergenthaler, G Tancredi, B Vlastakis, M Esposito, et al. Calibration of a cross-resonance two-qubit gate between directly coupled transmons. Physical Review Applied, 12(6):064013, 2019

    2019

  25. [33]

    First- principles analysis of cross-resonance gate operation

    Moein Malekakhlagh, Easwar Magesan, and David C McKay. First- principles analysis of cross-resonance gate operation. arXiv preprint arXiv:2005.00133, 2020

    2005 arXiv

  26. [34]

    Quantum supremacy using a programmable super- conducting processor

    Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C Bardin, Rami Barends, Rupak Biswas, Sergio Boixo, Fernando GSL Brandao, David A Buell, et al. Quantum supremacy using a programmable super- conducting processor. Nature, 574(7779):505–510, 2019

    2019

  27. [35]

    LNF-LNC4_8G - Low Noise Factory — lownoise- factory.com

    Low Noise Factory. LNF-LNC4_8G - Low Noise Factory — lownoise- factory.com. https://lownoisefactory.com/wp-content/uploads/2022/03/ lnf-lnc4_8c.pdf, 2022-03-28. [Accessed 23-02-2026]

    2022

  28. [36]

    LNF-LNC4_8G - Low Noise Factory — lownoisefac- tory.com

    Low Noise Factory. LNF-LNC4_8G - Low Noise Factory — lownoisefac- tory.com. https://lownoisefactory.com/product/lnf-lnc4_8g/, 2025. [Ac- cessed 04-12-2025]

    2025

  29. [37]

    A 300-µw cryogenic hemt lna for quantum computing

    Eunjung Cha, Niklas Wadefalk, Giuseppe Moschetti, Arsalan Pourk- abirian, Jörgen Stenarson, and Jan Grahn. A 300-µw cryogenic hemt lna for quantum computing. In 2020 IEEE/MTT-S International Microwave Symposium (IMS), pages 1299–1302. IEEE, 2020

    2020

  30. [38]

    Sub-mw cryogenic inp hemt lna for qubit readout

    Yin Zeng, Jörgen Stenarson, Peter Sobis, Niklas Wadefalk, and Jan Grahn. Sub-mw cryogenic inp hemt lna for qubit readout. IEEE Transactions on Microwave Theory and Techniques, 72(3):1606–1617, 2023

    2023

  31. [39]

    Characterization of a low- noise superconductor–insulator–superconductor-based microwave ampli- fier with local oscillator phase-adjusting architecture

    T Kojima, S Masui, W Shan, and Y Uzawa. Characterization of a low- noise superconductor–insulator–superconductor-based microwave ampli- fier with local oscillator phase-adjusting architecture. Applied Physics Letters, 122(7), 2023

    2023

  32. [40]

    Fabrication and evaluation of waveguide josephson array oscillators at millimeter- wave lengths for sis mixer-based amplifiers

    Yosuke Murayama, Akira Kawakami, Wenlei Shan, Shohei Ezaki, Akihira Miyachi, Sho Masui, Takafumi Kojima, and Yoshinori Uzawa. Fabrication and evaluation of waveguide josephson array oscillators at millimeter- wave lengths for sis mixer-based amplifiers. IEEE Transactions on Ap...

    2024

  33. [41]

    A near–quantum-limited josephson traveling-wave parametric amplifier

    Chris Macklin, K O’brien, D Hover, ME Schwartz, V Bolkhovsky, X Zhang, WD Oliver, and I Siddiqi. A near–quantum-limited josephson traveling-wave parametric amplifier. Science, 350(6258):307–310, 2015

    2015

  34. [42]

    rf- squid-based traveling-wave parametric amplifier with input saturation power of- 84 dbm across more than one octave in bandwidth

    Victor Gaydamachenko, Christoph Kissling, and Lukas Grünhaupt. rf- squid-based traveling-wave parametric amplifier with input saturation power of- 84 dbm across more than one octave in bandwidth. Physical Review Applied, 23(6):064053, 2025

    2025

  35. [43]

    Product Leaflet: SHFQA 8.5 GHz Quantum An- alyzer

    Zurich Instruments. Product Leaflet: SHFQA 8.5 GHz Quantum An- alyzer. https://www.zhinst.com/sites/default/files/documents/2023-02/zi_ shfqa_leaflet.pdf, 2023-02. [Accessed 09-02-2026]

    2023

  36. [44]

    Fault-tolerant quantum computation by anyons

    A Yu Kitaev. Fault-tolerant quantum computation by anyons. Annals of physics, 303(1):2–30, 2003

    2003

  37. [45]

    Quantum codes on a lattice with boundary

    Sergey B Bravyi and A Yu Kitaev. Quantum codes on a lattice with boundary. arXiv preprint quant-ph/9811052, 1998

    1998 arXiv

  38. [46]

    Fault-tolerant quantum com- putation with high threshold in two dimensions

    Robert Raussendorf and Jim Harrington. Fault-tolerant quantum com- putation with high threshold in two dimensions. Physical review letters, 98(19):190504, 2007

    2007

  39. [47]

    Surface codes: Towards practical large-scale quantum compu- tation

    Austin G Fowler, Matteo Mariantoni, John M Martinis, and Andrew N Cleland. Surface codes: Towards practical large-scale quantum compu- tation. Physical Review A—Atomic, Molecular, and Optical Physics, 86(3):032324, 2012

    2012

  40. [48]

    Scalable quantum circuit and control for a supercon- ducting surface code

    Richard Versluis, Stefano Poletto, Nader Khammassi, Brian Tarasinski, Nadia Haider, David J Michalak, Alessandro Bruno, Koen Bertels, and Leonardo DiCarlo. Scalable quantum circuit and control for a supercon- ducting surface code. Physical Review Applied, 8(3):034021, 2017

    2017

  41. [49]

    Demonstration of a high-fidelity cnot gate for fixed-frequency transmons with engineered zz suppression

    Abhinav Kandala, Ken X Wei, Srikanth Srinivasan, Easwar Magesan, S Carnevale, GA Keefe, D Klaus, O Dial, and DC McKay. Demonstration of a high-fidelity cnot gate for fixed-frequency transmons with engineered zz suppression. Physical Review Letters, 127(13):130501, 2021

    2021

  42. [50]

    Fast multiplexed superconducting-qubit readout with intrinsic purcell filtering using a mul- ticonductor transmission line

    Peter A Spring, Luka Milanovic, Yoshiki Sunada, Shiyu Wang, Arjan F Van Loo, Shuhei Tamate, and Yasunobu Nakamura. Fast multiplexed superconducting-qubit readout with intrinsic purcell filtering using a mul- ticonductor transmission line. PRX Quantum, 6(2):020345, 2025

    2025

  43. [51]

    Realization of high-fidelity cz and zz- free iswap gates with a tunable coupler

    Youngkyu Sung, Leon Ding, Jochen Braumüller, Antti Vepsäläinen, Bharath Kannan, Morten Kjaergaard, Ami Greene, Gabriel O Samach, Chris McNally, David Kim, et al. Realization of high-fidelity cz and zz- free iswap gates with a tunable coupler. Physical Review X, 11(2):021058, 2021

    2021

  44. [52]

    Benchmarking coherent er- rors in controlled-phase gates due to spectator qubits

    Sebastian Krinner, Stefania Lazar, Ants Remm, Christian K Andersen, Nathan Lacroix, Graham J Norris, Christoph Hellings, Mihai Gabureac, Christopher Eichler, and Andreas Wallraff. Benchmarking coherent er- rors in controlled-phase gates due to spectator qubits. Physical Review...

    2020

  45. [53]

    Using cryogenic cmos control electronics to enable a two-qubit cross-resonance gate

    Devin Underwood, Joseph A Glick, Ken Inoue, David J Frank, John Timmerwilke, Emily Pritchett, Sudipto Chakraborty, Kevin Tien, Mark Yeck, John F Bulzacchelli, et al. Using cryogenic cmos control electronics to enable a two-qubit cross-resonance gate. PRX Quantum, 5(1):010326, 2024

    2024

  46. [54]

    Stim: a fast stabilizer circuit simulator

    Craig Gidney. Stim: a fast stabilizer circuit simulator. Quantum, 5:497, July 2021

    2021

  47. [55]

    Sparse Blossom: correcting a million errors per core second with minimum-weight matching

    Oscar Higgott and Craig Gidney. Sparse Blossom: correcting a million errors per core second with minimum-weight matching. Quantum, 9:1600, January 2025

    2025

  48. [56]

    Machine learning assisted superconducting qubit readout

    Benjamin Lienhard. Machine learning assisted superconducting qubit readout. PhD thesis, Massachusetts Institute of Technology, 2021

    2021

  49. [57]

    Andersen, Markus Ansmann, Frank Arute, Kunal Arya, Abraham Asfaw, Juan Atalaya, Ryan Babbush, Dave Bacon, Joseph C

    Rajeev Acharya, Igor Aleiner, Richard Allen, Trond I. Andersen, Markus Ansmann, Frank Arute, Kunal Arya, Abraham Asfaw, Juan Atalaya, Ryan Babbush, Dave Bacon, Joseph C. Bardin, Joao Basso, Andreas Bengtsson, Sergio Boixo, Gina Bortoli, Alexandre Bourassa, Jenna Bovaird, Leon ...

    2023

  50. [58]

    Dispersive qubit readout with intrinsic resonator reset

    M Jerger, F Motzoi, Y Gao, C Dickel, L Buchmann, A Bengtsson, G Tancredi, CW Warren, J Bylander, D DiVincenzo, et al. Dispersive qubit readout with intrinsic resonator reset. arXiv preprint arXiv:2406.04891, 2024

    2024 arXiv

  51. [59]

    Removing leakage-induced correlated errors in superconducting quantum error correction

    Matt McEwen, Dvir Kafri, Z Chen, Juan Atalaya, KJ Satzinger, Chris Quintana, Paul Victor Klimov, Daniel Sank, C Gidney, AG Fowler, et al. Removing leakage-induced correlated errors in superconducting quantum error correction. Nature communications, 12(1):1761, 2021

    2021

  52. [60]

    Fast readout and reset of a superconducting qubit coupled to a resonator with an intrinsic purcell filter

    Yoshiki Sunada, Shingo Kono, Jesper Ilves, Shuhei Tamate, Takanori Sugiyama, Yutaka Tabuchi, and Yasunobu Nakamura. Fast readout and reset of a superconducting qubit coupled to a resonator with an intrinsic purcell filter. Physical Review Applied, 17(4):044016, 2022

    2022

  53. [61]

    Fast reset and suppressing spontaneous emission of a superconducting qubit

    Matthew D Reed, Blake R Johnson, Andrew A Houck, Leonardo DiCarlo, Jerry M Chow, David I Schuster, Luigi Frunzio, and Robert J Schoelkopf. Fast reset and suppressing spontaneous emission of a superconducting qubit. Applied Physics Letters, 96(20), 2010

    2010

  54. [62]

    Fast unconditional reset and leakage reduc- tion in fixed-frequency transmon qubits

    Liangyu Chen, Simon Pettersson Fors, Zixian Yan, Anaida Ali, Tahereh Abad, Amr Osman, Eleftherios Moschandreou, Benjamin Lienhard, San- doko Kosen, Hang-Xi Li, et al. Fast unconditional reset and leakage reduc- tion in fixed-frequency transmon qubits. arXiv preprint arXiv:2409...

    2024 arXiv

  55. [63]

    New Products: Enhanced Cooling, High-Density Flex Wiring, and LD400sl — bluefors.com

    Bluefors. New Products: Enhanced Cooling, High-Density Flex Wiring, and LD400sl — bluefors.com. https://bluefors.com/news/ new-products-enhanced-cooling-high-density-flex-wiring-and-ld400sl/, 17-March-2025. [Accessed 15-02-2026]

    2025

  56. [64]

    Delft circuits product roadmap

    Delft Circuits. Delft circuits product roadmap. https://delft-circuits.com/ wp-content/uploads/2025/09/Roadmap_2025.pdf, 2025. [Accessed 04- 11-2025]

    2025

  57. [65]

    The connection of refrigeration to a superconducting magnet with a minimum amount of cryogen

    Michael A Green and Heng Pan. The connection of refrigeration to a superconducting magnet with a minimum amount of cryogen. In IOP Conference Series: Materials Science and Engineering, volume 278, page 012180. IOP Publishing, 2017

    2017

  58. [66]

    National Bureau of Standards and RW Powell

    United States. National Bureau of Standards and RW Powell. Thermal conductivity of selected materials, volume 8. US Government Printing Office, 1966

    1966

  59. [67]

    Kerr reversal in josephson meta-material and traveling wave parametric amplification

    Arpit Ranadive, Martina Esposito, Luca Planat, Edgar Bonet, Cécile Naud, Olivier Buisson, Wiebke Guichard, and Nicolas Roch. Kerr reversal in josephson meta-material and traveling wave parametric amplification. Nature communications, 13(1):1737, 2022

    2022

  60. [68]

    Qmc-cryocoupler-20nm

    Quantum Microwave. Qmc-cryocoupler-20nm. https: //quantummicrowave.com/wp-content/uploads/2023/01/ {Q}{M}{C}-{C}{R}{Y}{O}{C}{O}{U}{P}{L}{E}{R}-20{N}{M}-2. pdf, 2026. [Accessed 21-07-2026]. SHASWOT SHRESTHAMALIreceived his B.E. in Electronics and Communication Engineering from ...

    2023

  61. [2015]

    His research interests include quantum computer system architecture, edge computing systems, and secure computer architecture. YOSHINORI UZAWAis the Director of Ad- vanced Technology Center of National Astronom- ical Observatory of Japan (NAOJ) and a professor in The Graduate ...

    1991

  62. [2025]

    [Accessed 08-01-2026]

    2026

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.