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Dynamics of Transmon Ionization

2022· article· en· W4226401025 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysical Review Applied · 2022
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsCanadian Institute for Advanced ResearchUniversité de Sherbrooke
FundersArmy Research OfficeNatural Sciences and Engineering Research Council of CanadaOffice of ScienceCanada First Research Excellence FundOntario Ministry of Research, Innovation and ScienceGovernment of CanadaInstitut de Ciències FotòniquesInstitut Périmètre de physique théoriqueInnovation, Science and Economic Development CanadaU.S. Department of Energy
KeywordsTransmonQubitPhysicsSpurious relationshipFidelitySemiclassical physicsQuantumQuantum computerCircuit quantum electrodynamicsResonatorPhase qubitIonizationQuantum mechanicsComputer scienceOptoelectronicsIonTelecommunications

Abstract

fetched live from OpenAlex

Qubit measurement is an essential step in any quantum computation. In circuit quantum electrodynamics, a leading quantum computer architecture, qubit readout is commonly one of the longest and lowest-fidelity processes. The authors numerically explore the dynamics of a driven transmon-resonator system under strong, nearly resonant measurement drives to better understand this issue. They find clear signs of transmon ``ionization'', in which the qubit escapes its confining potential under the influence of the drive, and semiclassical methods then reveal the mechanism. This approach can be used to optimize circuit parameters, suppress these spurious effects, and increase readout fidelity.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.246
Teacher spread0.238 · 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