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Record W4393234843 · doi:10.1038/s41586-024-07160-2

High-fidelity spin qubit operation and algorithmic initialization above 1 K

2024· article· en· W4393234843 on OpenAlexaff
Jonathan Y. Huang, Rocky Y. Su, Wee Han Lim, MengKe Feng, Barnaby van Straaten, Brandon Severin, Will Gilbert, Nard Dumoulin Stuyck, Tuomo Tanttu, Santiago Serrano, Jesús D. Cifuentes, Ingvild Hansen, Amanda E. Seedhouse, Ensar Vahapoglu, Ross C. C. Leon, N. V. Abrosimov, Hans-Joachim Pohl, M. L. W. Thewalt, Fay E. Hudson, Christopher C. Escott, Natalia Ares, Stephen D. Bartlett, Andrea Morello, André Saraiva, Arne Laucht, Andrew S. Dzurak, Chih Hwan Yang

Bibliographic record

VenueNature · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsSimon Fraser University
FundersArmy Research OfficeU.S. Air ForceAir Force Office of Scientific ResearchUniversity of New South WalesAustralian National Fabrication Facility
KeywordsQubitQuantum computerInitializationComputer sciencePhysicsSpin (aerodynamics)Topology (electrical circuits)Quantum mechanicsQuantumElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract The encoding of qubits in semiconductor spin carriers has been recognized as a promising approach to a commercial quantum computer that can be lithographically produced and integrated at scale 1–10 . However, the operation of the large number of qubits required for advantageous quantum applications 11–13 will produce a thermal load exceeding the available cooling power of cryostats at millikelvin temperatures. As the scale-up accelerates, it becomes imperative to establish fault-tolerant operation above 1 K, at which the cooling power is orders of magnitude higher 14–18 . Here we tune up and operate spin qubits in silicon above 1 K, with fidelities in the range required for fault-tolerant operations at these temperatures 19–21 . We design an algorithmic initialization protocol to prepare a pure two-qubit state even when the thermal energy is substantially above the qubit energies and incorporate radiofrequency readout to achieve fidelities up to 99.34% for both readout and initialization. We also demonstrate single-qubit Clifford gate fidelities up to 99.85% and a two-qubit gate fidelity of 98.92%. These advances overcome the fundamental limitation that the thermal energy must be well below the qubit energies for the high-fidelity operation to be possible, surmounting a main obstacle in the pathway to scalable and fault-tolerant quantum computation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.251
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations92
Published2024
Admission routes1
Has abstractyes

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