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Record W3084854368 · doi:10.1364/josab.405098

Dynamics of two coupled qubits interacting with two-photon transitions via a nondegenerate parametric amplifier: nonlocal correlations under intrinsic decoherence

2020· article· lv· W3084854368 on OpenAlexaff
Abdel‐Baset A. Mohamed, Ahmed Farouk, Mansour F. Yassen, Hichem Eleuch

Bibliographic record

VenueJournal of the Optical Society of America B · 2020
Typearticle
Languagelv
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsWilfrid Laurier University
FundersPrince Sattam bin Abdulaziz University
KeywordsPhysicsSuperposition principleQubitAlgorithmQuantum mechanicsQuantumComputer science

Abstract

fetched live from OpenAlex

In this study, an analytical solution for a novel intrinsic noise model represented by two coupled qubits inside a cavity, the S u ( 1 , 1 ) and S u ( 2 ) Lie group, is investigated. Each qubit interacts with a two-mode parametric amplifier through a nondegenerate two-photon process when the two-mode system is initially in a superposition of a generalized Barut–Girardello coherent state. The nonlinearity of the interaction and the initial two-mode fields lead to the generation of different quantum correlations (QCs), which are measured by log-negativity, uncertainty-induced nonlocality, and local quantum uncertainty (LQU). The generated QC of the interaction depends not only on the two-qubit coupling but also on the intrinsic noise and the initial coherent intensity. Our results show that the ability of the two-qubit coupling to protect and enhance the robustness and generation of the QCs depends on the superposition and the coherent intensity of the initial S u ( 1 , 1 ) state. Furthermore, the sudden birth and death of the log-negativity and the sudden variations of the LQU depend on the intrinsic noise and the two-qubit coupling.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0010.003
Open science0.0010.002
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 head0.017
GPT teacher head0.257
Teacher spread0.240 · 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 designSimulation or modeling
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

Citations4
Published2020
Admission routes1
Has abstractyes

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