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Realization of Harmonic Oscillator Arrays with Graded Semiconductor Quantum Wells

2020· article· en· W3082738380 on OpenAlexafffund
Chris Deimert, Paul Goulain, Jean‐Michel Manceau, Wojciech Julian Pasek, Taehyun Yoon, Adel Bousseksou, Na Young Kim, R. Colombelli, Z. R. Wasilewski

Bibliographic record

VenuePhysical Review Letters · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundAgence Nationale de la RechercheEuropean Commission
KeywordsRealization (probability)Harmonic oscillatorPhysicsQuantum wellSemiconductorHarmonicQuantumQuantum mechanicsMathematics

Abstract

fetched live from OpenAlex

The harmonic oscillator is a foundational concept in both theoretical and experimental quantum mechanics. Here, we demonstrate harmonic oscillators in a semiconductor platform by faithfully implementing continuously graded alloy semiconductor quantum wells. Unlike current technology, this technique avoids interfaces that can hamper the system and allows for the production of multiwell stacks several micrometers thick. The experimentally measured system oscillations are at 3 THz for two structures containing 18 and 54 parabolic quantum wells. Absorption at room temperature is achieved: this is as expected from a parabolic potential and is unlike square quantum wells that require cryogenic operation. Linewidths below 11% of the central frequency are obtained up to 150 K, with a 5.6% linewidth obtained at 10 K. Furthermore, we show that the system correctly displays an absence of nonlinearity despite electron-electron interactions-analogous to the Kohn theorem. These high-quality structures already open up several new experimental vistas.

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 score0.001
Threshold uncertainty score0.003

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.269
Teacher spread0.245 · 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

Citations24
Published2020
Admission routes2
Has abstractyes

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