MétaCan
Menu
Back to cohort
Record W3081774815 · doi:10.1103/physrevb.102.115401

Pump power control of photon statistics in a nanowire quantum dot

2020· article· en· W3081774815 on OpenAlexafffund
Dan Dalacu, David B. Northeast, Philip J. Poole, G. C. Aers, Robin L. Williams, Kim A. Owen, Daniel Oblak

Bibliographic record

VenuePhysical review. B./Physical review. B · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsNational Research Council Canada
FundersCanadian Space Agency
KeywordsQuantum dotExcitationBiexcitonPhysicsDegenerate energy levelsNanowireExcitonAtomic physicsPhotonEnergy (signal processing)Range (aeronautics)Condensed matter physicsQuantum mechanicsMaterials science

Abstract

fetched live from OpenAlex

Through fluctuations in the local composition, InAsP quantum dots embedded within site-selected InP nanowires are observed to display biexciton binding energies spanning a range between $\ensuremath{-}0.3\phantom{\rule{0.16em}{0ex}}\mathrm{meV}$ and $+2.9\phantom{\rule{0.16em}{0ex}}\mathrm{meV}$. From this range we select dots having energy-degenerate exciton and biexciton emission and observe an excitation rate-mediated transition from sub- to super-Poissonian second-order correlation statistics. Under pulsed excitation, ${g}^{(2)}(\ensuremath{\tau}=0)$ is found to increase from 0.5 at high excitation levels, rising to 28 as the excitation is reduced by two orders of magnitude. The observed second-order correlation statistics are interpreted using both a stochastic model and a rate equation model of the competition between the various excitonic emission processes. Our results demonstrate that nanowire quantum dots represent a promising approach to the efficient generation of twin-photon states.

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 categoriesMeta-epidemiology (narrow)
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 score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.338
Teacher spread0.322 · 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.

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

Citations8
Published2020
Admission routes2
Has abstractyes

Explore more

Same venuePhysical review. B./Physical review. BSame topicSemiconductor Quantum Structures and DevicesFrench-language works237,207