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Demonstration of an All-Microwave Controlled-Phase Gate between Far-Detuned Qubits

2020· article· en· W3036937150 on OpenAlexafffund
Sebastian Krinner, Philipp Kurpiers, Baptiste Royer, Paul Magnard, Ivan Tsitsilin, Jean-Claude Besse, Ants Remm, Alexandre Blais, Andreas Wallraff

Bibliographic record

VenuePhysical Review Applied · 2020
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsCanadian Institute for Advanced ResearchInstitut quantiqueUniversité de Sherbrooke
FundersArmy Research OfficeNational Center of Competence in Research Quantum Science and TechnologyNatural Sciences and Engineering Research Council of CanadaNational University of Science and TechnologyH2020 European Research CouncilCanada First Research Excellence FundSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungMinistry of Education and Science of the Russian FederationIntelligence Advanced Research Projects ActivityEidgenössische Technische Hochschule ZürichOffice of the Director of National Intelligence
KeywordsTransmonQubitPhysicsQuantum decoherenceQuantum mechanicsMicrowaveQuantum computerPhase qubitTopology (electrical circuits)Coupling (piping)Coherence (philosophical gambling strategy)QuantumElectrical engineering

Abstract

fetched live from OpenAlex

One of the major challenges in building fully functional quantum computers based on superconducting circuits is a scalable, high-fidelity two-qubit gate. Microwave-induced gates are appealing, but so far have been restricted to small qubit detunings, leading to frequency crowding and reduced gate speed and qubit addressability, due to crosstalk. The authors present a high-fidelity all-microwave gate based on a Raman transition, which allows for detunings that are large compared to the anharmonicity of the qubits, setting the stage for scalable, resource-efficient quantum processors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.323
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations50
Published2020
Admission routes2
Has abstractyes

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