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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchShort answer: Silicon spin qubits offer an unusually compact device and a plausible path to dense, wafer-scale fabrication, while superconducting qubits remain the more mature platform for building and operating larger coupled systems. Silicon still has difficult problems in device variation, yield, wiring, calibration and readout. Superconducting systems have demonstrated larger arrays, but their microwave wiring, refrigerator heat load and electromagnetic sensitivity become increasingly severe as systems grow. The evidence supports a technology trade-off—not a universal winner.
The fairest comparison is between specific device generations and operating conditions. A small silicon dot, a wafer-probing experiment and a superconducting processor with more than one hundred coupled qubits answer different engineering questions. The sections below separate demonstrated results from projections about million-qubit machines.
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What the two qubit platforms are
Silicon spin qubits
A silicon spin qubit stores information in the spin state of an electron or, in some designs, a nucleus confined in a semiconductor structure. Electrostatic gates form and tune quantum dots. Microwave or electrically driven spin resonance rotates the spin, while exchange interactions between neighboring dots provide an important mechanism for two-qubit operations.
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Spin is comparatively insensitive to some electric-field fluctuations, which can support long coherence under suitable conditions. The trade-off is that the spin must be coupled to electric control structures to initialize, manipulate and measure it. Those structures are tiny, closely spaced and sensitive to process variation.
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Superconducting qubits
Superconducting qubits are circuits made from superconducting materials and Josephson junctions. Microwave pulses carry control signals, and resonators and measurement chains extract the state. Couplers can connect neighboring circuits, with the exact connectivity depending on the processor generation.
The platform has a substantial experimental and engineering lead in integrated arrays. Its physical circuits are much larger than semiconductor spin devices, but fabrication, packaging, calibration methods and control software are comparatively developed.
Demonstrated scale and platform maturity
Published figures come from different years and experimental contexts, so they should not be read as a single head-to-head benchmark. The following table keeps each result attached to its source and scope.
| Metric | Silicon spin qubits | Superconducting qubits | How to interpret it |
|---|---|---|---|
| Device scale | About 100 nm for silicon quantum-dot spin qubits in the 2024 wafer-probing study | Not stated as a comparable linear dimension in the cited comparison | Spin devices are physically much smaller, but system size is set by wiring, control and yield as well as by the qubit itself. |
| Array scope reported in the cited sources | Integrated arrays had reached six quantum dots in the systems discussed by the 2024 Nature paper; larger one- and two-dimensional demonstrations were also reported | More than one hundred coupled qubits, according to imec’s 2023 comparison | These are dated source statements, not a current inventory of every processor. |
| Coherence | Depends strongly on device, isotopic material, noise and operating point; no single matched value is supplied by the comparison sources | Up to several hundred microseconds in laboratory environments in imec’s 2023 account | The superconducting value is a dated laboratory statement, not a universal 2026 benchmark. |
| Manufacturing evidence | A cryogenic 300-mm wafer prober tested hundreds of industry-manufactured devices at 1.6 K in a 2024 Nature study | Industrial fabrication is established, but the cited sources do not provide a directly comparable wafer-yield study for a complete processor | Testing many devices on a wafer is an important scale-up step, not proof of a high-yield, million-qubit processor. |
Imeс’s 2023 comparison described superconducting circuits as arguably the most developed quantum platform at that time. That maturity reflects the ability to fabricate, package, calibrate and operate comparatively large coupled systems; it does not remove the platform’s wiring and cryogenic constraints.
Why silicon’s footprint is attractive—and what it does not prove
Sub-micrometre devices create geometric headroom
A 2025 review in the European Physical Journal A describes silicon spin-qubit device footprints below 1 µm² and discusses possible compatibility with CMOS and VLSI manufacturing. A smaller qubit can, in principle, allow more devices in a given die area, shorter local connections and denser control structures.
This is a manufacturing opportunity rather than a demonstrated processor specification. The same review cautions that adopting silicon technology alone does not solve quantum scale-up. Materials, dimensions, low-temperature single-charge operation, process customization, yield and integration with control electronics all have to work together.
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What the 300-mm wafer experiment demonstrated
The Nature study “Probing single electrons across 300-mm spin qubit wafers,” published in 2024, used a cryogenic wafer-probing process to collect high-volume data from hundreds of industry-manufactured spin-qubit devices at 1.6 K. Process optimization produced low disorder in the reported measurements.
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That result matters because process variation and yield have historically made spin-qubit results difficult to reproduce across a wafer. It shows that cryogenic characterization can be performed at industrial wafer diameter and that device distributions can be measured rather than inferred from a few hand-selected samples.
It does not establish the yield of a complete processor containing control wiring, couplers, readout, packaging and calibration infrastructure. A wafer with many acceptable test devices can still lose most of its usable qubits when assembled into a large fault-tolerant system.
Where the manufacturing work remains
- Uniformity: Quantum dots must load the intended number of electrons and maintain predictable energy levels across a die.
- Low-temperature behavior: Transistors and tunnel barriers must work in the single-charge regime at cryogenic temperatures, not merely at room-temperature test conditions.
- Customization: Standard CMOS layers may need changes for materials, interfaces, gate dimensions and microwave structures.
- Yield definition: A useful metric must include qubits, couplers, resonators, control lines, package connections and calibration time—not only functioning transistors.
- Variation-aware control: Automated tuning must compensate for device-to-device differences without consuming impractical amounts of measurement time.
Control and two-qubit operations
Silicon control stack
Electrostatic gates define and tune each quantum dot. Spin resonance or electrically driven spin resonance performs single-spin rotations. Exchange coupling between neighboring electrons supplies a fast and local route to two-qubit interactions. The 2023 Reviews of Modern Physics review of semiconductor spin qubits identifies exchange interactions as central to single- and two-qubit control and surveys noise sources and alternative spin implementations.
The small physical footprint does not make control simple. Each dot needs gate voltages, sensors and calibration procedures, and neighboring dots must be coupled without introducing unwanted charge noise or leakage. Connecting many dots to classical electronics can consume more area and routing capacity than the dots themselves.
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Superconducting circuits use microwave-frequency pulses delivered through coaxial and on-chip wiring. Readout usually sends a microwave probe through a resonator and analyzes the returning signal. Couplers and tunable elements add further control channels.
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Imeс’s 2023 account notes that early processors used at least one control line per qubit from room temperature to the refrigerator’s cold stage. That approach is workable for modest arrays but becomes a major input/output problem as qubit count rises. Cryogenic CMOS multiplexing can reduce the number of lines routed from room temperature, although it introduces its own power dissipation, noise and calibration requirements.
Readout, wiring and heat load
Why interconnects become the system bottleneck
Quantum processors are operated inside dilution refrigerators or other cryogenic systems, while most control electronics remain warmer. Every cable, attenuator, amplifier and filter that crosses temperature stages occupies space and carries thermal load. More channels also create more opportunities for crosstalk, calibration drift and electromagnetic interference.
For silicon, the challenge is the density of local connections: many quantum dots must be linked to each other and to sensors or cryogenic control electronics. For superconducting circuits, the challenge is often the number of high-bandwidth microwave paths and the heat they conduct into the cold stages. The physical origin differs, but both platforms face a control-stack limit before the qubit material itself necessarily fails.
Silicon approaches to integration
Imec’s comparison describes demonstrations of cryogenic electronics for spin systems and discusses operation at elevated temperatures as one possible way to ease integration. A Nature experiment published in 2024 demonstrated high-fidelity spin-qubit operation and algorithmic initialization above 1 K. The result indicates that some control functions might eventually be placed closer to the qubits, where shorter interconnects are possible.
The experiment is not evidence that commercial spin processors now operate above 1 K. Its authors also identify control and state-preparation/readout errors as issues that must improve, and they describe fault-tolerant engineering at the million-qubit level as formidable.
A separate Nature paper, “Spin-qubit control with a milli-kelvin CMOS chip,” reached version of record in June 2025. It reported control of MOS-style silicon spin qubits with a heterogeneously integrated cryo-CMOS chip operating at millikelvin temperatures. This is a concrete demonstration that control electronics can be integrated at the cold stage; it is not proof that wiring has ceased to be a system-level bottleneck.
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Superconducting approaches to integration
Superconducting systems can use multiplexing, cryogenic amplifiers and more compact packaging to reduce room-temperature wiring. Those measures trade cable count against local power, noise and circuit complexity. The platform is also sensitive to electromagnetic noise and heat, so adding electronics near the qubits must be done without degrading coherence or introducing excess thermal load.
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Temperature and cryogenic requirements
| Question | Silicon spin qubits | Superconducting qubits |
|---|---|---|
| Typical operating regime represented here | Many experiments operate at millikelvin temperatures; one 2024 experiment demonstrated operation above 1 K | Operated in dilution-refrigerator environments; the cited comparison emphasizes cryogenic I/O and heat load |
| Potential integration benefit | Some control and initialization functions may be moved closer to the qubits, including cryo-CMOS demonstrations | Cryogenic multiplexing and amplifiers can reduce room-temperature cable count |
| Principal risk | Higher-temperature operation still requires better control and readout accuracy, while dense local wiring remains difficult | Microwave lines, thermal conduction and electromagnetic noise constrain further scaling |
“Higher temperature” should therefore be read as a system-integration result, not as permission to remove refrigeration. The demonstrated regime above 1 K is a particular experiment, and scalable fault-tolerant operation requires an error budget that includes every control and measurement step.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Gate fidelity, readout and speed: how to compare fairly
The supplied comparisons do not provide a matched dataset of single-qubit fidelity, two-qubit fidelity, readout fidelity, readout latency or gate duration measured under identical conditions. It would be misleading to rank the platforms with one number.
Use the following distinctions when reading a device claim:
- Single-qubit versus two-qubit fidelity: Two-qubit operations generally expose more leakage, calibration error and crosstalk. A high single-qubit result does not predict a processor’s algorithmic performance.
- Readout fidelity versus readout speed: A slow measurement can be accurate but limit error-correction cycle time; a fast measurement can increase back-action or assignment error.
- Coherence versus usable circuit depth: A long measured relaxation or dephasing time is useful only if gates, measurement and reset complete reliably within it.
- Laboratory peak versus distribution: A best device can demonstrate physics, while a scalable processor needs a large fraction of devices to meet specifications without hand tuning.
- Connectivity: More connections can shorten algorithms but add couplers, wiring and calibration parameters. Sparse connectivity may require routing operations that consume fidelity and time.
Connectivity and layout trade-offs
Silicon
Quantum dots are naturally local: exchange interactions are strongest between neighboring dots, so a two-dimensional array must manage both nearest-neighbor control and longer-range communication. The approximately 100-nm device scale helps fit many sites into an area, but routing gates and sensors to those sites is difficult. Larger one- and two-dimensional demonstrations show that arrays can be extended beyond a single pair, yet the cited 2024 study’s six-dot integrated arrays should not be mistaken for a complete large-scale processor.
Superconducting circuits
Superconducting chips can implement engineered coupling graphs and tune interaction strengths, but each added coupler and resonator occupies area and introduces another microwave element to calibrate. The platform’s demonstrated coupled-qubit count is therefore an achievement in coordinated control as much as in lithography.
Error correction and the path to useful machines
Fault tolerance depends on repeated cycles of entangling gates, measurement, reset and classical decoding. The relevant figure is not the largest isolated qubit count; it is the number of qubits that maintain sufficiently low, correlated error over many cycles while the control system keeps up.
Superconducting technology is further along in demonstrating large, coordinated processors and the experimental infrastructure needed for error-correction research, according to the dated 2023 imec comparison. That does not mean a commercially useful, fault-tolerant machine has been established.
Silicon spin qubits have attractive ingredients—small devices, potentially long coherence and compatibility with semiconductor manufacturing—but still need repeatable arrays, high-yield interconnects, fast and accurate readout, automated tuning and an economical cryogenic control architecture. The above-1-K and cryo-CMOS results address parts of that stack, not the complete error-correction problem.
A decision framework for engineers
| If your priority is… | Platform currently favored by the evidence | Reason and qualification |
|---|---|---|
| Largest demonstrated coupled arrays in the cited comparison | Superconducting | Imeс reported more than one hundred coupled qubits in 2023, with a comparatively mature platform; this is a dated source statement. |
| Smallest physical qubit footprint | Silicon spin | The 2025 manufacturing review describes footprints below 1 µm² and the 2024 Nature study describes dots of about 100 nm. |
| Use of established semiconductor manufacturing infrastructure | Silicon spin, as an opportunity | 300-mm wafer probing and CMOS/VLSI compatibility are encouraging, but full-processor yield and customization remain unresolved. |
| Existing control and calibration ecosystem for larger arrays | Superconducting | Longer operating experience and larger coupled systems are advantages, offset by wiring and refrigerator constraints. |
| Reducing room-temperature interconnects | Neither has a free solution | Silicon has cryo-CMOS and elevated-temperature demonstrations; superconducting systems use multiplexing. Both approaches add power, noise and calibration trade-offs. |
| Proof of operation above 1 K | Silicon spin, in a specific experiment | The 2024 Nature result demonstrates a regime, not a commercial processor or a solved fault-tolerant architecture. |
What to watch in the next generation
- Array-level yield: Reports that include the distribution of qubit, coupler and readout performance across an entire wafer or processor.
- Calibration automation: The time, measurement volume and stability required to tune thousands of devices without manual intervention.
- Integrated control power: Cryogenic electronics that reduce cable count while staying within the refrigerator’s cooling budget.
- Repeated error-correction cycles: Demonstrations that combine gate fidelity, measurement, reset and decoding over many cycles rather than reporting isolated gate records.
- Comparable benchmarks: Results that state temperature, device generation, connectivity, measurement bandwidth and whether values are best-device or median statistics.
Bottom line
Silicon spin qubits are compelling because each device is tiny and could draw on high-volume semiconductor manufacturing. The 300-mm wafer-probing result, cryo-CMOS integration and operation above 1 K show meaningful progress on manufacturability and control. None demonstrates a million-qubit processor, and process variation, yield, wiring and readout remain central risks.
Superconducting qubits have the stronger record for coordinated, larger coupled systems and a more mature development ecosystem. Their scaling problem is equally concrete: microwave I/O, heat conducted into the refrigerator, electromagnetic noise and the growing control burden. Choose between them by the system metric that matters—array yield, two-qubit error, measurement cycle, connectivity, control power or correction-cycle stability—not by qubit count or device size alone.
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