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Quantum Algorithms
Optimal operating temperature for industry-compatible silicon spin quantum computing: colder is not necessarily better
arXiv
Authors: Paul Steinacker, Amanda E. Seedhouse, Nard Dumoulin Stuyck, Tuomo Tanttu, MengKe Feng, Santiago Serrano, Ensar Vahapoglu, Samuel K. Bartee, Philip Y. Mai, Alexis Shaw, Andreas Nickl, Sebastian Pauka, Brendan Harlech-Jones, Juan P. Dehollain, Fay E. Hudson, Kok Wai Chan, Thomas A. Ohki, David Reilly, Christopher C. Escott, Chih Hwan Yang, Wee Han Lim, Arne Laucht, Andre Saraiva, Andrew S. Dzurak, Jared H. Cole
Year
2026
Paper ID
72857
Status
Preprint
Abstract Read
~2 min
Abstract Words
178
Citations
N/A
Abstract
Silicon spin qubits are a leading candidate for large-scale quantum computing owing to their compatibility with semiconductor manufacturing. However, scaling to useful fault-tolerant processors will likely generate thermal loads that exceed the cooling power available at millikelvin temperatures. Raising the operating temperature eases cooling requirements but reduces gate fidelity, increasing the overhead of quantum error correction. Identifying the operating temperature that minimizes total power consumption is therefore a key challenge for commercially viable quantum computers. Here, we use gate set tomography to benchmark two-qubit silicon chips fabricated in both industrial and academic environments over a range of temperatures. Elevated temperatures substantially shorten coherence times and increase gate and state-preparation-and-measurement infidelities. Based on these measurements, we develop a general power model for silicon quantum computers that combines cryogenic cooling requirements with error-correction overheads. We show that a finite optimal operating temperature exists and is strongly influenced by a crossover temperature near 1 K in current devices, above which gate fidelity degrades rapidly. These results connect device-level fidelity limitations to system-level power requirements, providing design guidelines for large-scale silicon quantum computers.
Why This Paper Matters
- It adds a 2026 reference point for readers tracking recent quantum research.
- Silicon spin qubits are a leading candidate for large-scale quantum computing owing to their compatibility with semiconductor manufacturing.
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