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Record W2251836938

Hybrid Qubit gates in circuit QED: A scheme for quantum bit encoding and information processing

2011· preprint· en· W2251836938 on OpenAlexaboutno aff
M. C. de Oliveira

Bibliographic record

VenuearXiv (Cornell University) · 2011
Typepreprint
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsnot available
Fundersnot available
KeywordsQubitQuantum computerPhase qubitPhysicsFlux qubitCharge qubitQuantumSuperconducting quantum computingQuantum informationQuantum mechanicsTopology (electrical circuits)Electrical engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

Institute for Quantum Information Science, University of Calgary, Alberta T2N 1N4, Canada(Dated: October 7, 2011)Solid state superconducting devices coupled to coplanar transmission lines offer an exquisite architecturefor quantum optical phenomena probing as well as for quantum computation implementation, being the objectof intense theoretical and experimental investigation lately. In appropriate conditions the transmission lineradiation modes can get strongly coupled to a superconducting device with only two levels -for that reason calledartificial atom or qubit. Employing this system we propose a hybrid two-quantum bit gate encoding involvingquantum electromagnetic field qubit states prepared in a coplanar transmission line capacitively coupled to asingle charge qubit. Since dissipative effects are more drastic in the solid state qubit than in the field one, itcan be employed for storage of information, whose efficiency against the action of an ohmic bath show that thisencoding can be readily implemented with present day technology. We extend the investigation to generateentanglement between several solid state qubits and the field qubit through the action of external classicalmagnetic pulses.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.013

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 communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.070
GPT teacher head0.186
Teacher spread0.116 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations3
Published2011
Admission routes1
Has abstractyes

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