English

Optimal operating temperature for industry-compatible silicon spin quantum computing: colder is not necessarily better

Quantum Physics 2026-07-13 v1 Mesoscale and Nanoscale Physics

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.

Cite

@article{arxiv.2607.11846,
  title  = {Optimal operating temperature for industry-compatible silicon spin quantum computing: colder is not necessarily better},
  author = {Paul Steinacker and Amanda E. Seedhouse and Nard Dumoulin Stuyck and Tuomo Tanttu and MengKe Feng and Santiago Serrano and Ensar Vahapoglu and Samuel K. Bartee and Philip Y. Mai and Alexis Shaw and Andreas Nickl and Sebastian Pauka and Brendan Harlech-Jones and Juan P. Dehollain and Fay E. Hudson and Kok Wai Chan and Thomas A. Ohki and David Reilly and Christopher C. Escott and Chih Hwan Yang and Wee Han Lim and Arne Laucht and Andre Saraiva and Andrew S. Dzurak and Jared H. Cole},
  journal= {arXiv preprint arXiv:2607.11846},
  year   = {2026}
}

Comments

16 pages, 6 figures, 4 extended data figures